Abas, AEP & Mahlia, TMI 2018, 'Development of energy labels based on consumer perspective: Room air conditioners as a case study in Brunei Darussalam', Energy Reports, vol. 4, pp. 671-681.
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© 2018 The Authors For the past years, Brunei Darussalam has seen an increase in its electricity consumption with an average annual rate of increase of 3% per annum from the year 2011 to 2015. Like other developing countries with tropical climates, electricity consumption from air conditioning systems contributes a big part to this electricity consumption. The Energy Department of the Prime Minister's Office is considering the implementation of energy label for air-conditioning system; to provide guideline for consumers to compare efficiencies of their systems, encourage manufacturers to improve the energy efficiency of their systems and ultimately, to reduce the overall energy consumption of the country. This paper proposes a suitable energy label for air conditioning system in this country based on an online survey. Data from the survey shall be analysed to come up with consumers’ preferred energy label with suggestions used for its improvement. This label is also suitable for other electrical systems without major modification.
Abbas, SM, Desai, SC, Esselle, KP, Volakis, JL & Hashmi, RM 2018, 'Design and Characterization of a Flexible Wideband Antenna Using Polydimethylsiloxane Composite Substrate', International Journal of Antennas and Propagation, vol. 2018, pp. 1-6.
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The design and characterization of a simple, flexible wideband antenna using polydimethylsiloxane (PDMS) composite are presented. Conductive fibers are used to construct the metallic parts on a PDMS composite. To characterize the performance, two identical antennas are designed, one using the PDMS composite while the other on conventional dielectric materials. It was observed that both antennas behave well in terms of the matched bandwidth; however, the radiation towards the broadside direction is reduced when using the PDMS composite as substrate, particularly at higher frequencies. The antenna exhibits a matched bandwidth of 59.9%, ranging from 3.43 to 11.1 GHz. Moreover, the bending analysis carried out for different scenarios show that the wideband behavior of the antenna is well preserved and the variation reaches a maximum of 1% variation.
Abbasi, M & Tousi, B 2018, 'Performance evaluation of switched-diode symmetric, asymmetric and cascade multilevel converter topologies: A case study', Journal of Engineering Science and Technology, vol. 13, no. 5, pp. 1165-1180.
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In this paper, a precise study is presented on switched-diode symmetric, asymmetric and cascade multilevel converter topologies, which have been introduced and published recently. According to the published papers, these topologies have many advantages over other topologies in the same class. However, it is proved here that the mentioned switched-diode topologies suffer from main problems, which make them completely impractical. First, a brief study is presented on a typical sub-multilevel converter that consists of a basic unit and an H-bridge converter. Then, extended inverter topologies based on the switched-diode basic unit and their problems are studied. It is revealed in this section that the main problem is because of the basic unit. Finally, comprehensive experimental and simulation results are presented to validate the analysis. The simulations have been performed in MATLAB/SIMULINK environment.
Abbasi, M, Khazaee, S & Tousi, B 2018, 'Application of an online controller for statcom to mitigate the SSR oscillations', Journal of Engineering Science and Technology, vol. 13, no. 9, pp. 2945-2963.
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This paper presents an on-line controller for a Static Synchronous Shunt Compensator (STATCOM) to damp subsynchronous frequency oscillations. Series capacitors in transmission lines can increase stability margin and power transfer capability but also result in shaft failure or fatigue in a thermal production unit. Flexible AC Transmission System (FACTS) devices are widely employed to control several features of the power system. Recent surveys demonstrated that FACTS devices, equipped with well-designed controllers, can be effective in damping Subsynchronous Resonance (SSR) oscillations. To achieve this goal, PI controllers are mostly used that are simple controllers. However, they need exact and accurate information about the power system, which is hard to get. Therefore, they lose their desired performance by changing the operating conditions. The proposed on-line controller is based on an identifier and a pole-shifting controller. This controller estimates system parameters on-line and shifts the location of system poles radially with a factor (α) to guarantee the system stability. The considered structure for the system is Autoregressive Moving Average Exogenous (ARMAX) model and the used identifier is Recursive Least Squares (RLS) method. Simulations have been performed by MATLAB/SIMULINK. The eigenvalue analysis has been obtained to study the SSR characteristics of the power system and the studied system is IEEE first benchmark model on SSR.
Abbasi, M, Khazaee, S & Tousi, B 2018, 'Application of an online controller for statcom to mitigate the SSR oscillations', Journal of Engineering Science and Technology, vol. 13, pp. 2945-2963.
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This paper presents an on-line controller for a Static Synchronous Shunt Compensator (STATCOM) to damp subsynchronous frequency oscillations. Series capacitors in transmission lines can increase stability margin and power transfer capability but also result in shaft failure or fatigue in a thermal production unit. Flexible AC Transmission System (FACTS) devices are widely employed to control several features of the power system. Recent surveys demonstrated that FACTS devices, equipped with well-designed controllers, can be effective in damping Subsynchronous Resonance (SSR) oscillations. To achieve this goal, PI controllers are mostly used that are simple controllers. However, they need exact and accurate information about the power system, which is hard to get. Therefore, they lose their desired performance by changing the operating conditions. The proposed on-line controller is based on an identifier and a pole-shifting controller. This controller estimates system parameters on-line and shifts the location of system poles radially with a factor (α) to guarantee the system stability. The considered structure for the system is Autoregressive Moving Average Exogenous (ARMAX) model and the used identifier is Recursive Least Squares (RLS) method. Simulations have been performed by MATLAB/SIMULINK. The eigenvalue analysis has been obtained to study the SSR characteristics of the power system and the studied system is IEEE first benchmark model on SSR.
Abbasi, M, Tousi, B & Abbasi, M 2018, 'A Novel Controller Based on Single-Phase Instantaneous p-q Power Theory for a Cascaded PWM Transformerless STATCOM for Voltage Regulation', Journal of Operation and Automation in Power Engineering, vol. 6, no. 1, pp. 80-88.
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In this paper, dynamic performance of a transformerless cascaded PWM static synchronous shunt compensator (STATCOM) based on a novel control scheme is investigated for bus voltage regulation in a 6.6kV distribution system. The transformerless STATCOM consists of a thirteen-level cascaded H-bridge inverter, in which each voltage source H-bridge inverter should be equipped with a floating and isolated capacitor without any power source. The proposed control algorithm uses instantaneous p-q power theory in an innovative way that devotes itself not only to meet the reactive power demand but also to balance the dc link voltages at the same time. DC link voltage balancing control consists of two main parts: cluster and individual balancing. The control algorithm based on a phase shifted carrier modulation strategy has no restriction on the number of cascaded voltage source H-bridge inverters. Comprehensive simulations are presented in MATLAB/ SIMULINK environment for validating the performance of proposed transformerless STATCOM.
Abbasnejad, B, Thorby, W, Razmjou, A, Jin, D, Asadnia, M & Ebrahimi Warkiani, M 2018, 'MEMS piezoresistive flow sensors for sleep apnea therapy', Sensors and Actuators A: Physical, vol. 279, pp. 577-585.
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© 2018 Elsevier B.V. A MEMS liquid crystal polymer (LCP), used in the membrane-based pressure sensor, has been found highly useful as a flow sensor. Here we conducted a set of elaborate experiments using an air flow generator to investigate the potential of our LCP flow sensor for sleep apnea therapy. Critical properties of the LCP flow sensor, including flow range, resolution (sensitivity), accuracy, and response time, have been systematically characterized. As a result, LCP flow sensor achieves a limit of detection of 8 LPM to measure flow rate, better than the commercial flow sensor (>10 LPM). Our LCP flow sensor shows a favourable response in a large flow range (8–160 LPM) with a sensitivity of detecting a linear voltage response of 0.004 V per 1 LPM flow rate. With minimum detectable flow, high sensitivity and resolution, we further demonstrated our LCP flow sensor for detecting human respiration. Moreover, using a two- dimensional simulation in COMSOL Multiphysics, we demonstrated the deformation of LCP membrane in response to different flow velocities which leads to resistance change in sensor's strain gauge.
abbondanza, G & bailo, F 2018, 'the electoral payoff of immigration flows for anti-immigration parties: the case of Italy’s Lega Nord', European Political Science, vol. 17, no. 3, pp. 378-403.
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© 2017, European Consortium for Political Research. The aim of this article is to examine and quantify the relationship between regular immigration and voting for anti-immigration parties in Italy’s eight Northern regions – from 1992 to 2015 – and in Italy’s forty-five Northern provinces from 2004 to 2015. Firstly, we identified the Lega Nord as Italy’s main xenophobic party, then we used a fixed effects regression model for panel data to test our hypothesis, while controlling for a series of social, political and economic variables. Our results suggest that there is a positive and significant effect: an increase of 1 per cent in the number of new regular immigrants is associated with an increase of more than 2 per cent in the votes given to the Lega Nord; voter-turnout is significantly and negatively associated with Lega Nord’s vote-share, and a high perception of crime – but not actual crime – is positively associated with anti-immigration votes. At the provincial level, we also found a positive association between Muslim foreign population and Lega Nord’s vote-share. These results ought to be considered along with the fact that Northern Italy is highly representative of the wealthiest and most densely populated regions of Europe, suggesting the possibility that similar phenomena could be witnessed in other comparable contexts.
Abdulkareem, JH, Pradhan, B, Sulaiman, WNA & Jamil, NR 2018, 'Quantification of Runoff as Influenced by Morphometric Characteristics in a Rural Complex Catchment', Earth Systems and Environment, vol. 2, no. 1, pp. 145-162.
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This study addresses the critical scientific question of assessing the relationship between morphometric features and the hydrological factors that increase the risk of flooding in Kelantan River basin, Malaysia. Two hypotheses were developed to achieve this aim, namely: the alternate hypothesis (runoff, is influenced by morphometric characteristics in the study watershed) and the null hypothesis (runoff is not influenced by morphometric characteristics). First, the watershed was delineated into four major catchments, namely: Galas, Pergau, Lebir, and Nenggiri. Next, quantitative morphometric characters such as linear aspects, areal aspects, and relief aspects were determined on each of these catchments. Furthermore, HEC–HMS and flood response analyses were employed to simulate the hydrological response of the catchments. From the results of morphometric analysis, profound spatial changes were observed between runoff features of Kelantan River and the morphometric characteristics. The length of overflow that was related to drainage density and constant channel maintenance was found to be 0.12 in Pergau, 0.04 in both Nenggiri and Lebir, and 0.03 in Galas. Drainage density as influenced by geology and vegetation density was found to be low in all the catchments (0.07–0.24). Results of hydrological response indicated that Lebir, Nenggiri, Galas, and Pergau recorded a flood response factor of 0.75, 0.63, 0.40, and 0.05, respectively. Therefore, Lebir and Nenggiri are more likely to be flooded during a rainstorm. There was no clear indication with regard to the catchment that emerged as the most prevailing in all the morphological features. Hence, the alternate hypothesis was affirmed. This study can be replicated in other catchments with different hydrologic setup.
Abdulkareem, JH, Pradhan, B, Sulaiman, WNA & Jamil, NR 2018, 'Review of studies on hydrological modelling in Malaysia', Modeling Earth Systems and Environment, vol. 4, no. 4, pp. 1577-1605.
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Hydrological models are vital component and essential tools for water resources and environmental planning and management. In recent times, several studies have been conducted with a view of examining the compatibility of model results with streamflow measurements. Some modelers are of the view that even the use of complex modeling techniques does not give better assessment due to soil heterogeneity and climatic changes that plays vital roles in the behavior of streamflow. In Malaysia, several public domain hydrologic models that range from physically-based models, empirical models and conceptual models are in use. These include hydrologic modeling system (HEC-HMS), soil water assessment tool (SWAT), MIKE-SHE, artificial neural network (ANN). In view of this, a study was conducted to evaluate the hydrological models used in Malaysia, determine the coverage of the hydrological models in major river basins and to identify the methodologies used (specifically model performance and evaluation). The results of the review showed that 65% of the studies conducted used physical-based models, 37% used empirical models while 6% used conceptual models. Of the 65% of physical-based modelling studies, 60% utilized HEC-HMS an open source models, 20% used SWAT (public domain model), 9% used MIKE-SHE, MIKE 11 and MIKE 22, Infoworks RS occupied 7% while TREX and IFAS occupy 2% each. Thus, indicating preference for open access models in Malaysia. In the case of empirical models, 46% from the total of empirical researches in Malaysia used ANN, 13% used Logistic Regression (LR), while Fuzzy logic, Unit Hydrograph, Auto-regressive integrated moving average (ARIMA) model and support vector machine (SVM) contributed 8% each. Whereas the remaining proportion is occupied by Numerical weather prediction (NWP), land surface model (LSM), frequency ratio (FR), decision tree (DT) and weight of evidence (WoE). Majority of the hydrological modelling studies utilized one or more statis...
Abdulkareem, JH, Sulaiman, WNA, Pradhan, B & Jamil, NR 2018, 'Long-Term Hydrologic Impact Assessment of Non-point Source Pollution Measured Through Land Use/Land Cover (LULC) Changes in a Tropical Complex Catchment', Earth Systems and Environment, vol. 2, no. 1, pp. 67-84.
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The contribution of non-point source pollution (NPS) to the contamination of surface water is an issue of growing concern. Non-point source (NPS) pollutants are of various types and altered by several site-specific factors making them difficult to control due to complex uncertainties involve in their behavior. Kelantan River basin, Malaysia is a tropical catchment receiving heavy monsoon rainfall coupled with intense land use/land cover (LULC) changes making the area consistently flood prone thereby deteriorating the surface water quality in the area. This study was conducted to determine the spatio-temporal variation of NPS pollutant loads among different LULC changes and to establish a NPS pollutant loads relationships among LULC conditions and sub-basins in each catchment. Four pollutants parameters such as total suspended solids (TSS), total phosphorus (TP), total nitrogen (TN) and ammonia nitrogen (AN) were chosen with their corresponding event mean concentration values (EMC). Soil map and LULC change maps corresponding to 1984, 2002 and 2013 were used for the calculation of runoff and NPS pollutant loads using numeric integration in a GIS environment. Analysis of Variance (ANOVA) was conducted for the comparison of NPS pollutant loads among the three LULC conditions used and the sub-basins in each catchment. The results showed that the spatio-temporal variation of pollutant loads in almost all the catchments increased with changes in LULC condition as one moves from 1984 to 2013, with 2013 LULC condition found as the dominant in almost all cases. NPS pollutant loads among different LULC changes also increased with changes in LULC condition from 1984 to 2013. While urbanization was found to be the dominant LULC change with the highest pollutant load in all the catchments. Results from ANOVA reveals that statistically most significant (p < 0.05) pollutant loads were obtained from 2013 LULC conditions, while statistically least significant (p < 0.05) pollutant...
Abdulkareem, JH, Sulaiman, WNA, Pradhan, B & Jamil, NR 2018, 'Relationship between design floods and land use land cover (LULC) changes in a tropical complex catchment', Arabian Journal of Geosciences, vol. 11, no. 14.
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© 2018, Saudi Society for Geosciences. Rainfall characteristics are directly related to the climate of a basin, but this can only be noticed after a long period. Human activities, such as deforestation, tend to play a major role in transforming the land use land cover (LULC). Knowledge of the relationship between design floods and LULC is important in modeling and designing watershed management strategies. A study was conducted in the Kelantan River basin, Malaysia, to determine the impact of past and present LULC changes on peak discharge and runoff volumes. To achieve this, the basin was delineated into four catchments (Galas, Pergau, Nenggiri, and Lebir) due to its size and increased precision. Hydrologic Engineering Center-Hydrologic Modeling System (HEC-HMS) model was calibrated based on December 20–30th, 2014, flood in Kelantan. Flood hydrographs corresponding to 1984, 2002, and 2013 LULC conditions were simulated, and relative changes in peak discharge and runoff volume were determined for different return periods (2, 5, 10, 20, 50, 100 years). Results of LULC analysis showed that Galas recorded highest deforestation (54.35%). When the four catchments were compared with respect to highest contribution of outlet peak discharge, Lebir under 2013 LULC condition was the highest with 2847.70 m3/s. This was followed by Nenggiri (2196.90 m3/s), Galas (1252.7 m3/s), and Pergau (328.7 m3/s), all under the 2013 LULC condition. Results of unit response approach applied based on 50-year return period to the catchments for ranking their sub-basins revealed that the novel fa index developed in this study provides a better way of ranking sub-basins with respect to their contribution to the outlet and therefore is recommended for use. Methodologies developed in this study may be useful to land use planners from around the world which when applied can provide alternatives that will minimize the adverse effects of floods.
Abdullahi, S & Pradhan, B 2018, 'Land use change modeling and the effect of compact city paradigms: integration of GIS-based cellular automata and weights-of-evidence techniques', Environmental Earth Sciences, vol. 77, no. 6.
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© 2018, Springer-Verlag GmbH Germany, part of Springer Nature. In recent decades, attaining urban sustainability is the primary goal for urban planners and decision makers. Among various aspects of urban sustainability, environmental protection such as agricultural and forest conservations is very important in tropical countries like Malaysia. In this regard, compact urban development due to high density, rural development containment is known as the most sustainable urban forms. This paper attempts to propose an integrated modeling approach to predict the future land use changes by considering city compactness paradigms. First, the cellular automata (CA) were applied for calculating land use conversion. Next, weights-of-evidence (WoE) which is based on Bayes theory was utilized to calibrate CA model and to support the transitional rule assessment. Several urban-related parameters as well as compact city indicators were utilized to estimate the future land use maps. The results showed how compact development parameters and site characteristics can be combined using the WoE model to predict the probability of land use changes. The modeling approach supports the essential logic of probabilistic methods and indicates that spatial autocorrelation of various land use types and accessibility is the main drivers of urban land use changes.
Abdullahi, S, Pradhan, B & Mojaddadi, H 2018, 'City Compactness: Assessing the Influence of the Growth of Residential Land Use', Journal of Urban Technology, vol. 25, no. 1, pp. 21-46.
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© 2017 The Society of Urban Technology. In the urban sprawl paradigm, residential land use exhibits a more significant growth than other categories. Consequently, large proportions of the natural environment are converted to residential areas, particularly in tropical countries. Compact urban development is one of the most sustainable urban forms with environmental perspectives, such as rural development containment and natural environment preservation. However, no proper investigation of the relationship and influence of residential growth and city compactness is available. This study evaluated and forecasted the residential development of Kajang City in Malaysia based on compact development. First, the relationship between residential land use change and city compactness was evaluated. Second, residential growth was projected by utilizing the land transformation model (LTM) and the statistical-based weight of evidence (WoE) using various spatial parameters. Both models were evaluated with respect to observed land use and compactness maps. Results indicated that most of the newly developed residential areas were in zones where the degrees of compactness increase during certain periods. In addition, LTM performed better and provided a more accurate modeling of residential growth than the WoE. However, WoE provided clearer and more informative results than LTM in terms of functional relationships between dependent and independent variables related to city compactness.
Abeywickrama, HV, Jayawickrama, BA, He, Y & Dutkiewicz, E 2018, 'Comprehensive Energy Consumption Model for Unmanned Aerial Vehicles, Based on Empirical Studies of Battery Performance', IEEE Access, vol. 6, pp. 58383-58394.
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© 2018 IEEE. Unmanned aerial vehicles (UAVs) are fast gaining popularity in a wide variety of areas and are already being used for a range of tasks. Despite their many desirable features, a number of drawbacks hinder the potential of UAV applications. As typical UAVs are powered by on-board batteries, limited battery lifetime is identified as a key limitation in UAV applications. Thus, in order to preserve the available energy, planning UAV missions in an energy efficient manner is of utmost importance. For energy efficient UAV mission planning, it is necessary to predict the energy consumption of specific UAV manoeuvring actions. Accurate energy prediction requires a reliable and realistic energy consumption model. In this paper, we present a consistent and complete energy consumption model for UAVs based on empirical studies of battery usage for various UAV activities. We considered the impact of different flight scenarios and conditions on UAV energy consumption when developing the proposed model. The energy consumption model presented in this paper can be readily used for energy efficient UAV mission planning.
Abolbashari, MH, Chang, E, Hussain, OK & Saberi, M 2018, 'Smart Buyer: A Bayesian Network modelling approach for measuring and improving procurement performance in organisations', Knowledge-Based Systems, vol. 142, pp. 127-148.
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© 2017 Elsevier B.V. Procurement, the act of buying goods or services from an external supplier, plays an important role in any organisation. To measure how well an organisation undertakes this activity, it needs to measure all associated Key Performance Indicators (KPIs). The current literature's major drawback in performing such a measurement is how to integrate the different KPIs, each of which captures a specific aspect of the organisation's performance. In this paper, we highlight this drawback and present our proposed Smart Buyer framework that is based on a Bayesian Network (BN) model capable of capturing and integrating the different KPIs. The measured procurement performance value can then be used by organisations to identify the areas in which they need to improve and develop plans to achieve this. Four scenarios are presented to show how the proposed BN model can be further used for analysis and decision making within organisations. Finally, a recent real-world procurement example is studied to demonstrate the applicability of the proposed Smart Buyer framework.
Abolhasan, M, Abdollahi, M, Ni, W, Jamalipour, A, Shariati, N & Lipman, J 2018, 'A Routing Framework for Offloading Traffic From Cellular Networks to SDN-Based Multi-Hop Device-to-Device Networks', IEEE Transactions on Network and Service Management, vol. 15, no. 4, pp. 1516-1531.
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© 2004-2012 IEEE. Device-to-device (D2D) communications are set to form an integral part of future 5G wireless networks. D2D communications have a number of benefits such as improving energy efficiency and spectrum utilization. Until now much of the D2D research in LTE and 5G-type network scenarios have focused on direct (one-hop) communications between two adjacent mobile devices. In this paper, we propose a new routing framework called virtual ad hoc routing protocol (VARP). This framework introduces significant advantages such as better security, lower routing overheads, and higher scalability, when compared to conventional ad hoc routing protocols. It also reduces traffic overhead in LTE networks using multi-hop D2D communications under management of a software defined networking (SDN)-controller. Further, it enables the development of various types of routing protocols for different networking scenarios. To this end, a source-routing based protocol was developed on top of VARP, referred to as VARP-S. We present a detailed analytical study of routing overhead in the VARP-S protocol, as compared to overhead analysis of our previous proposed hybrid SDN architecture for wireless distributed networks (HSAW) Our results show that VARP-S, compared to HSAW, achieves higher network scalability and lower power consumption for mobile nodes.
Aboulkheyr Es, H, Montazeri, L, Aref, AR, Vosough, M & Baharvand, H 2018, 'Personalized Cancer Medicine: An Organoid Approach', Trends in Biotechnology, vol. 36, no. 4, pp. 358-371.
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Personalized cancer therapy applies specific treatments to each patient. Using personalized tumor models with similar characteristics to the original tumors may result in more accurate predictions of drug responses in patients. Tumor organoid models have several advantages over pre-existing models, including conserving the molecular and cellular composition of the original tumor. These advantages highlight the tremendous potential of tumor organoids in personalized cancer therapy, particularly preclinical drug screening and predicting patient responses to selected treatment regimens. Here, we highlight the advantages, challenges, and translational potential of tumor organoids in personalized cancer therapy and focus on gene–drug associations, drug response prediction, and treatment selection. Finally, we discuss how microfluidic technology can contribute to immunotherapy drug screening in tumor organoids.
Aboutorab, H, Saberi, M, Asadabadi, MR, Hussain, O & Chang, E 2018, 'ZBWM: The Z-number extension of Best Worst Method and its application for supplier development', Expert Systems with Applications, vol. 107, pp. 115-125.
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© 2018 Elsevier Ltd Best Worst Method (BWM) has recently been proposed as a method for Multi Criteria Decision Making (MCDM). Studies show that BWM compared with other methods such as Analytic Hierarchy Process (AHP), leads to lower inconsistency of the results while reducing the number of required pairwise comparisons. MCDM methods such as BWM require accurate information. However, it often happens in practice that a level of uncertainty accompanies the information. The main aim of this paper is to address this problem and provide an integration of BWM and Z-numbers, namely ZBWM. Providing BWM with Z-numbers enables the BWM method to handle the uncertainty of information of a multi-criteria decision. Additionally, the capabilities of the proposed method in the process of utilizing the linguistic information dealing with big data are highlighted. The proposed method is examined to address a supplier development problem. By experimental results, we show that ZBWM results lower inconsistency when compared with BWM. A Z-number contains subjectivity in its fuzzy part, which can be addressed in future applications of ZBWM.
Acosta, E, Wight, NM, Smirnov, V, Buckman, J & Bennett, NS 2018, 'Hydrogenated Nano-/Micro-Crystalline Silicon Thin-Films for Thermoelectrics', Journal of Electronic Materials, vol. 47, no. 6, pp. 3077-3084.
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© 2017, The Minerals, Metals & Materials Society. Thermoelectric technology has not yet been able to reach full-scale market penetration partly because most commercial materials employed are scarce/costly, environmentally unfriendly and in addition provide low conversion efficiency. The necessity to tackle some of these hurdles leads us to investigate the suitability of n-type hydrogenated microcrystalline silicon (μc-Si: H) in the fabrication of thermoelectric devices, produced by plasma enhanced chemical vapour deposition (PECVD), which is a mature process of proven scalability. This study reports an approach to optimise the thermoelectric power factor (PF) by varying the dopant concentration by means of post-annealing without impacting film morphology, at least for temperatures below 550°C. Results show an improvement in PF of more than 80%, which is driven by a noticeable increase of carrier mobility and Seebeck coefficient in spite of a reduction in carrier concentration. A PF of 2.08 × 10−4 W/mK2 at room temperature is reported for n-type films of 1 μm thickness, which is in line with the best values reported in recent literature for similar structures.
Adnan, R, Sabri Adlan, Z, Munir, FA, Indra, TM & Masjuki, HH 2018, 'Effects of equivalence ratio on performance and emissions of diesel engine with hydrogen and water injection system at variable injection timing', International Journal of Mechanical and Mechatronics Engineering, vol. 18, no. 1, pp. 106-111.
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This paper aims to develop a comprehensive development and research for performance and emissions of diesel engine fueled with hydrogen and water at variable injection timing. Experiments have been conducted to compare the performance and emissions between diesel alone, diesel with hydrogen and hydrogen-diesel and water injection pressure. addition of hydrogen into diesel engine resulted in higher pressure which lead to huge indicated work. Furthermore, injecting water into diesel engine with hydrogen mixture indicated a desirable outcome. Existence of water in combustion slightly decreased the amount of emissions but opposite in term of performance. The fact is water injection exist in combustion will absorb a portion of heat release which will result low in combustion process thus lead to low in performance production otherwise production of NOx emission is low. In conclusion, humidification in combustion engine is a great idea toward a high performance and low in emissions production compared to diesel alone operation which leads to a green technology production.
Aerts, D, Geriente, S, Moreira, C & Sozzo, S 2018, 'Testing ambiguity and Machina preferences within a quantum-theoretic framework for decision-making', Journal of Mathematical Economics, vol. 78, pp. 176-185.
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Afzal, MU, Esselle, KP & Lalbakhsh, A 2018, 'A Methodology to Design a Low-Profile Composite-Dielectric Phase-Correcting Structure', IEEE Antennas and Wireless Propagation Letters, vol. 17, no. 7, pp. 1223-1227.
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© 2002-2011 IEEE. A methodology to synthesize a low-profile composite-dielectric phase-correcting structure (CD PCS) is presented. The CD PCS, in function, is similar to an all-dielectric varying-height PCS and transforms a nonuniform aperture phase distribution of a low-gain antenna to a nearly uniform phase distribution. The methodology is aimed at reducing the maximum height of all-dielectric PCSs by using a combination of commercially available transmissive dielectric materials. The principle of operation has been demonstrated by designing a CD PCS using two dielectric materials. A higher permittivity dielectric material is used in the central region of the CD PCS, which requires a larger phase delay, while a lower permittivity dielectric material is used in the outer region, which requires a smaller phase delay. The height of the CD PCS is 43\% less and its weight is 25\% less than the single-dielectric PCS, but both have similar radiation performance.
Afzal, MU, Lalbakhsh, A & Esselle, KP 2018, 'Electromagnetic-wave beam-scanning antenna using near-field rotatable graded-dielectric plates', Journal of Applied Physics, vol. 124, no. 23, pp. 234901-234901.
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The paper proposes an electromagnetic-wave beam-scanning antenna system using a simple rotation of a pair of near-field graded-dielectric plates (GDPs). The antenna system requires an electromagnetic (EM) illuminator, with nearly symmetric aperture field distribution, as the base antenna and two types of GDPs: one radially graded dielectric (RGD) and two linearly graded dielectric (LGD) plates. The RGD first focuses the beam of the base antenna in the broadside direction, and the LGD then tilts the focused beam at an offset angle. For some types of base antennas, having fairly uniform aperture phase distributions, an RGD may not be required and only a pair of LGDs are sufficient. Irrespective of the antenna configuration, using a simple rotation of the two LGDs, the beam can be scanned to any position within a large conical region. The antenna system presented as a proof of concept has a resonant-cavity antenna as the base antenna and three graded-dielectric plates. The aperture length of the antenna system is 6λ0 and its height is 2.2λ0. The results predicted by numerical simulations indicate that the antenna system has highest peak directivity of 21 dBi. The beam can be scanned to any direction within a cone having an apex angle of 20°.
Agrawal, DP, Gupta, BB, Wang, H, Chang, X, Yamaguchi, S & Perez, GM 2018, 'Guest Editorial Deep Learning Models for Industry Informatics', IEEE Transactions on Industrial Informatics, vol. 14, no. 7, pp. 3166-3169.
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Ahmadirouhani, R, Karimpour, M-H, Rahimi, B, Malekzadeh-Shafaroudi, A, Pour, AB & Pradhan, B 2018, 'Integration of SPOT-5 and ASTER satellite data for structural tracing and hydrothermal alteration mineral mapping: implications for Cu–Au prospecting', International Journal of Image and Data Fusion, vol. 9, no. 3, pp. 237-262.
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© 2018, © 2018 Informa UK Limited, trading as Taylor & Francis Group. The integration of information extracted from the Syste`m Pour l’Observation de la Terre (SPOT) and the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data, comprehensive field and mineralogy studies demonstrates that phyllic alteration zone associated with northwestern (NW)–southeastern (SE) structural fractures is a high potential zone for Cu–Fe–Au vein-type mineralisation in the Bajestan region, the Lut block, east Iran. The fractal pattern was calculated for fractures map using the Box-Counting algorithm to the SPOT-5 data. Statistical parameters of fractures, such as density, intensity and fractures’ intersection were also determined. Band composition, specialised band ratio and Spectral Angle Mapper (SAM) classification methods were implemented to the ASTER dataset for detecting hydrothermal alteration zones, such as propylitic, phyllic, argillic and gossan. Results indicate that the maximum value of the fractal dimension, intensity, density and the intersection of the fractures are concentrated in the NW and SE parts of SPOT image maps. In the other hand, phyllic alteration zone containing sericite, alunite, kaolinite and jarosite mineral assemblages was also identified in several zones of the NW and SE parts of the ASTER image maps. Integration of the results indicates the high potential zones for the occurrence of Cu–Fe–Au mineralisation in the Bajestan region.
Ahmed, A, Abu Bakar, MS, Azad, AK, Sukri, RS & Mahlia, TMI 2018, 'Potential thermochemical conversion of bioenergy from Acacia species in Brunei Darussalam: A review', Renewable and Sustainable Energy Reviews, vol. 82, pp. 3060-3076.
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© 2017 Elsevier Ltd As the demand for energy increases and fossil fuel resources are depleted, the search for clean sources of energy has intensified worldwide. This is coupled with a strong global desire to reduce CO2 emissions to curb global warming. Brunei Darussalam is committed to reduce its CO2 emissions but currently utilizes fossil fuels to meet almost all of its energy requirements. This situation provides good incentives to search for renewable and sustainable resources to produce energy in the country. Acacia species are exotic species that have invaded and spread to natural habitats in Brunei Darussalam. Acacia species are a sustainable source of high quality biomass feedstock to produce bioenergy in the country. Hot tropical weather of the country is highly suitable for the rapid growth of Acacias without requiring any major agricultural input. This study reviews the thermochemical conversion of Acacia species especially; Acacia mangium and Acacia auriculiformis to produce biofuels and bio-products. The prospective of using Acacia biomass as feedstock in pyrolysis, gasification, liquefaction and combustion is also discussed. Acacia biomass is a sustainable and renewable energy resource for Brunei Darussalam to be exploited for energy requirements and can be beneficial for the economy of the country by providing new investment and employment opportunities.
Ahmed, AA, Pradhan, B, Sameen, MI & Makky, AM 2018, 'An optimized object-based analysis for vegetation mapping using integration of Quickbird and Sentinel-1 data', Arabian Journal of Geosciences, vol. 11, no. 11.
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© 2018, Saudi Society for Geosciences. This study proposed a workflow for an optimized object-based analysis for vegetation mapping using integration of Quickbird and Sentinel-1 data. The method is validated on a set of data captured over a part of Selangor located in the Peninsular Malaysia. The method comprised four components including image segmentation, Taguchi optimization, attribute selection using random forest, and rule-based feature extraction. Results indicated the robustness of the proposed approach as the area under curve of forest; grassland, old oil palm, rubber, urban tree, and young oil palm were calculated as 0.90, 0.89, 0.87, 0.87, 0.80, and 0.77, respectively. In addition, results showed that SAR data is very useful for extracting rubber and young oil palm trees (given by random forest importance values). Finally, further research is suggested to improve segmentation results and extract more features from the scene.
Ahmed, JB & Pradhan, B 2018, 'Termite mounds as bio-indicators of groundwater: Prospects and constraints', Pertanika Journal of Science and Technology, vol. 26, no. 2, pp. 479-498.
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Reliance on modern sophisticated equipment for making ‘discoveries’ has limited the human power of observing subtle clues in the environment that are capable of saving cost and labour that come with researching new resources and methods to improve life for all. Due to the growing scarcity of potable water, especially in African and Asian countries, newer, cheaper and reliable methods of investigating groundwater resources are becoming critical. One such potentially promising method is mapping the distribution of termite mounds in the environment. Termite mounds are conspicuous landscape features in tropical and sub-tropical regions of the world. Built from surrounding soils by several species of termite, the properties of mound soil are relatively different from the surrounding soil in most cases, indicating improved hydraulic properties. In this paper, the aim is to review the possibility of employing termite mounds as prospecting tools for groundwater search from three spatial scales of observation. From assessing the smallest to the highest scale of observation, it can be concluded that termite mounds’ prospect as surface indicators of groundwater is apparent. Review findings indicate increased surface water infiltration, presence of riparian tree vegetation and other trees with tap-root system around termite mounds, linear assemblage of termite mounds along aquiferous dykes and seep-lines as well as the dependence of termites on water but avoidance of places with risk of inundation. Whether they indicate permanent groundwater reserves in all cases or whether all species depend largely on water for their metabolism is a subject for further research.
Ahmed, MB, Johir, MAH, Khourshed, C, Zhou, JL, Ngo, HH, Nghiem, DL, Moni, M & Sun, L 2018, 'Sorptive removal of dissolved organic matter in biologically-treated effluent by functionalized biochar and carbon nanotubes: Importance of sorbent functionality', Bioresource Technology, vol. 269, pp. 9-17.
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© 2018 Elsevier Ltd The sorptive removal of dissolved organic matter (DOM) in biologically-treated effluent was studied by using multi-walled carbon nanotube (MWCNT), carboxylic functionalised MWCNT (MWCNT-COOH), hydroxyl functionalized MWCNT (MWCNT-OH) and functionalized biochar (fBC). DOM was dominated by hydrophilic fraction (79.6%) with a significantly lower hydrophobic fraction (20.4%). The sorption of hydrophobic DOM was not significantly affected by the sorbent functionality (∼10.4% variation) and sorption capacity followed the order of MWCNT > MWCNT-COOH > MWCNT-OH > fBC. In comparison, the sorption of hydrophilic fraction of DOM changed significantly (∼37.35% variation) with the change of sorbent functionality with adsorption capacity decreasing as MWCNT-OH > MWCNT-COOH > MWCNT > fBC. Furthermore, the affinity of adsorbents toward a hydrophilic compound (dinitrobenzene), a hydrophobic compound (pyrene) and humic acid was also evaluated to validate the proposed mechanisms. The results provided important insights on the type of sorbents which are most effective to remove different DOM fractions.
Ahmed, MB, Zhou, JL, Ngo, HH, Johir, MAH & Sornalingam, K 2018, 'Sorptive removal of phenolic endocrine disruptors by functionalized biochar: Competitive interaction mechanism, removal efficacy and application in wastewater', Chemical Engineering Journal, vol. 335, pp. 801-811.
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© 2017 Elsevier B.V. Sorptive removal of six phenolic endocrine disrupting chemicals (EDCs) estrone (E1), 17β-estradiol (E2), estriol (E3), 17α-ethynylestradiol (EE2), bisphenol A (BPA) and 4-tert-butylphenol (4tBP) by functionalized biochar (fBC) through competitive interactions was investigated. EDC sorption was pH dependent with the maximum sorption at pH 3.0–3.5 due to hydrogen bonds and π-π interactions as the principal sorptive mechanism. Sorption isotherm of the EDCs was fitted to the Langmuir model. Sorption capacities and distribution coefficient values followed the order E1 > E2 ≥ EE2 > BPA > 4tBP > E3. The findings suggested that EDC sorption occurred mainly through pseudo-second order and external mass transfer diffusion processes, by forming H-bonds along with π-π electron-donor–acceptor (EDA) interactions at different pH. The complete removal of ∼500 μg L−1 of each EDC from different water decreased in the order: deionised water > membrane bioreactor (MBR) sewage effluent > synthetic wastewater. The presence of sodium lauryl sulphonate and acacia gum in synthetic wastewater significantly suppressed sorption affinity of EDCs by 38–50%, hence requiring more fBC to maintain removal efficacy.
Ahmed, MB, Zhou, JL, Ngo, HH, Johir, MAH, Sun, L, Asadullah, M & Belhaj, D 2018, 'Sorption of hydrophobic organic contaminants on functionalized biochar: Protagonist role of π-π electron-donor-acceptor interactions and hydrogen bonds', Journal of Hazardous Materials, vol. 360, pp. 270-278.
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© 2018 Elsevier B.V. The sorption of five potent endocrine disruptors as representative hydrophobic organic contaminants (HOCs) namely estrone (E1), 17β-estradiol (E2), estriol (E3), 17α-ethynylestradiol (EE2) and bisphenol A (BPA) on functionalized biochar (fBC) was systematically examined, with a particular focus on the importance of π-electron-donor (phenanthrene: PHEN) and π-electron-acceptors (1,3-dinitrobenzene: DNB, p-amino benzoic acid: PABA) on sorption. Experimental results suggested that hydrogen-bond formation and π-π-electron-donor-acceptor (EDA) interactions were the dominant sorption mechanisms. The sorption of HOCs decreased as E1 > E2 > EE2 > E3 > BPA based on the Freundlich and Polanyi-Mane-models. The comparison of adsorption coefficient (Kd) normalized against hexadecane-water partition coefficient (KHW) between HOCs and PHEN indicated strong π-π-EDA interactions. π-π interactions among DNB, PHEN and HOCs were verified by the observed upfield frequency (Hz) shifts using proton nuclear magnetic resonance (1H NMR) which identified the specific direction of π-π interactions. UV–vis spectra showed charge-transfer bands for π-donors (PHEN and HOCs) with the model π-acceptor (DNB) also demonstrating the role of π-π EDA interactions. The role of π-electron-donor and π-electron-acceptor domains in fBC was identified at different solution pH.
Ahmmad, MS, Haji Hassan, MB & Kalam, MA 2018, 'Comparative corrosion characteristics of automotive materials in Jatropha biodiesel', International Journal of Green Energy, vol. 15, no. 6, pp. 393-399.
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Ait Lamqadem, A, Pradhan, B, Saber, H & Rahimi, A 2018, 'Desertification Sensitivity Analysis Using MEDALUS Model and GIS: A Case Study of the Oases of Middle Draa Valley, Morocco', Sensors, vol. 18, no. 7, pp. 2230-2230.
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Oases can play a significant role in the sustainable economic development of arid and Saharan regions. The aim of this study was to map the desertification-sensitive areas in the Middle Draa Valley (MDV), which is in the southeast of Morocco. A total of 13 indices that affect desertification processes were identified and analyzed using a geographic information system. The Mediterranean desertification and land use approach; which has been widely used in the Mediterranean regions due to its simplicity; flexibility and rapid implementation strategy; was applied. All the indices were grouped into four main quality indices; i.e., soil quality; climate quality; vegetation quality and management quality indices. Each quality index was constructed by the combination of several sub-indicators. In turn; the geometric mean of the four quality index maps was used to construct a map of desertification-sensitive areas; which were classified into four classes (i.e., low; moderate; high and very high sensitivity). Results indicated that only 16.63% of the sites in the study were classified as least sensitive to desertification; and 50.34% were classified as highly and very highly sensitive areas. Findings also showed that climate and human pressure factors are the most important indicators affecting desertification sensitivity in the MDV. The framework used in this research provides suitable results and can be easily implemented in similar oasis arid areas.
Akbari, MA, Aghaei, J, Barani, M, Niknam, T, Ghavidel, S, Farahmand, H, Korpas, M & Li, L 2018, 'Convex Models for Optimal Utility-Based Distributed Generation Allocation in Radial Distribution Systems', IEEE Systems Journal, vol. 12, no. 4, pp. 3497-3508.
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© 2007-2012 IEEE. This paper introduces various models for optimal and maximal utility-based distributed generation penetration in the radial distribution systems. Several problems with different probabilistic indices as objective functions constrained by power flow equations, distributed generation penetration, voltage, and thermal limits are proposed to obtain the optimal penetration of distributed generations on rural distribution networks. There are tradeoffs between interests and risks that the distribution network operators or distribution companies may be willing to take on. Thus, to have an effective method for maximal allocation of distributed generations, new indices are proposed, and the problems are formulated as a risk-constrained optimization model. The obtained problems have mixed-integer nonlinear programming and nonconvex forms because of nonlinearity and nonconvexity of the optimal power flow (OPF) equations and indices, leading to computationally nondeterministic polynomial-time-hard problems. Accordingly, in this paper, convex relaxations of OPF are introduced instead of the conventional nonlinear equations. Efficient linear equivalents of the objective function and constraints are introduced to reduce the computational burden. Test results of the proposed models on a radial distribution system are presented and discussed.
Akther, N, Daer, S & Hasan, SW 2018, 'Effect of flow rate, draw solution concentration and temperature on the performance of TFC FO membrane, and the potential use of RO reject brine as a draw solution in FO–RO hybrid systems', Desalination and Water Treatment, vol. 136, pp. 65-71.
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Al Muderis, MM, Lu, WY, Li, JJ, Kaufman, K, Orendurff, M, Highsmith, MJ, Lunseth, PA & Kahle, JT 2018, 'Clinically Relevant Outcome Measures Following Limb Osseointegration; Systematic Review of the Literature', Journal of Orthopaedic Trauma, vol. 32, no. 2, pp. e64-e75.
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Objectives: The current standard of care for an amputee is a socket-based prostheses. An osseointegrated implant (OI) is an alternative for prosthetic attachment. Osseointegration addresses reported problems related to wearing a socket interface, such as skin issues, discomfort, diminished function, quality of life, prosthetic use, and abandonment. The purpose of this report is to systematically review current literature regarding OI to identify and categorize the reported clinically relevant outcome measures, rate the quality of available evidence, and synthesize the findings. Data sources: A multidisciplinary team used PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) methods. Search methodology was based on identifying clinically relevant articles. Three databases were searched: PubMed, CINAHL, and Web of Science. Study Selection: Clinical studies with aggregated data reporting at least 1 clinically relevant outcome measure were included. Data Extraction: The Grading of Recommendations Assessment, Development, and Evaluation (GRADE) criterion was used for critical appraisal and recommendations. Conclusions: This review identified 21 clinically relevant observational studies. Outcome measures were categorized into the following 9 categories: vibratory stimulation, complications, biomechanics, economics, patient-reported outcome measures, electromyography, x-ray, physical functional performance, and energy consumption. This systemat...
Alabd, R, Safavi-Naeini, M, Wilson, KJ, Rosenfeld, AB & Franklin, DR 2018, 'A simulation study of BrachyShade, a shadow-based internal source tracking system for HDR prostate brachytherapy', Physics in Medicine & Biology, vol. 63, no. 20, pp. 205019-205019.
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This paper presents a simulation study of BrachyShade, a proposed internal source-tracking system for real time quality assurance in high dose rate prostate brachytherapy. BrachyShade consists of a set of spherical tungsten occluders located above a pixellated silicon photodetector. The source location is estimated by minimising the mean squared error between a parametric model of the shadow image and acquired images of the shadows projected on the detector plane. A novel algorithm is finally employed to correct the systemic error resulting from Compton scattering in the medium. The worst-case error obtained with BrachyShade for a 13.5 ms image acquisition is less than 1.3 mm in the most distant part of the treatment volume, while for 75% of source locations an error of less than 0.42 mm was achieved.
Alajlouni, D, Bliuc, D, Tran, T, Pocock, N, Nguyen, TV, Eisman, JA & Center, JR 2018, 'Nonstandard Lumbar Region in Predicting Fracture Risk', Journal of Clinical Densitometry, vol. 21, no. 2, pp. 220-226.
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© 2017 The International Society for Clinical Densitometry Femoral neck (FN) bone mineral density (BMD) is the most commonly used skeletal site to estimate fracture risk. The role of lumbar spine (LS) BMD in fracture risk prediction is less clear due to osteophytes that spuriously increase LS BMD, particularly at lower levels. The aim of this study was to compare fracture predictive ability of upper L1–L2 BMD with standard L2–L4 BMD and assess whether the addition of either LS site could improve fracture prediction over FN BMD. This study comprised a prospective cohort of 3016 women and men over 60 yr from the Dubbo Osteoporosis Epidemiology Study followed up for occurrence of minimal trauma fractures from 1989 to 2014. Dual-energy X-ray absorptiometry was used to measure BMD at L1–L2, L2–L4, and FN at baseline. Fracture risks were estimated using Cox proportional hazards models separately for each site. Predictive performances were compared using receiver operating characteristic curve analyses. There were 565 women and 179 men with a minimal trauma fracture during a mean of 11 ± 7 yr. L1–L2 BMD T-score was significantly lower than L2–L4 T-score in both genders (p < 0.0001). L1–L2 and L2–L4 BMD models had a similar fracture predictive ability. LS BMD was better than FN BMD in predicting vertebral fracture risk in women [area under the curve 0.73 (95% confidence interval, 0.68–0.79) vs 0.68 (95% confidence interval, 0.62–0.74), but FN was superior for hip fractures prediction in both women and men. The addition of L1–L2 or L2–L4 to FN BMD in women increased overall and vertebral predictive power compared with FN BMD alone by 1% and 4%, respectively (p < 0.05). In an elderly population, L1–L2 is as good as but not better than L2–L4 site in predicting fracture risk. The addition of LS BMD to FN BMD provided a modest additional benefit in overall fracture risk. Further studies in individuals with spinal degenerative disease are needed.
Alavi, AH, Cui, Z, Gandomi, AH, Gao, X-Z, Wang, G-G & Lim, M-H 2018, 'Editorial', Memetic Computing, vol. 10, no. 2, pp. 121-122.
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Alazigha, DP, Indraratna, B, Vinod, JS & Heitor, A 2018, 'Mechanisms of stabilization of expansive soil with lignosulfonate admixture', Transportation Geotechnics, vol. 14, pp. 81-92.
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Aldebei, K, He, X, Jia, W & Yeh, W 2018, 'SUDMAD: Sequential and unsupervised decomposition of a multi‐author document based on a hidden markov model', Journal of the Association for Information Science and Technology, vol. 69, no. 2, pp. 201-214.
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Decomposing a document written by more than one author into sentences based on authorship is of great significance due to the increasing demand for plagiarism detection, forensic analysis, civil law (i.e., disputed copyright issues), and intelligence issues that involve disputed anonymous documents. Among existing studies for document decomposition, some were limited by specific languages, according to topics or restricted to a document of two authors, and their accuracies have big room for improvement. In this paper, we consider the contextual correlation hidden among sentences and propose an algorithm for Sequential and Unsupervised Decomposition of a Multi‐Author Document (SUDMAD) written in any language, disregarding topics, through the construction of a Hidden Markov Model (HMM) reflecting the authors' writing styles. To build and learn such a model, an unsupervised, statistical approach is first proposed to estimate the initial values of HMM parameters of a preliminary model, which does not require the availability of any information of author's or document's context other than how many authors contributed to writing the document. To further boost the performance of this approach, a boosted HMM learning procedure is proposed next, where the initial classification results are used to create labeled training data to learn a more accurate HMM. Moreover, the contextual relationship among sentences is further utilized to refine the classification results. Our proposed approach is empirically evaluated on three benchmark datasets that are widely used for authorship analysis of documents. Comparisons with recent state‐of‐the‐art approaches are also presented to demonstrate the significance of our new ideas and the superior performance of our approach.
Alderighi, T, Malomo, L, Giorgi, D, Pietroni, N, Bickel, B & Cignoni, P 2018, 'Metamolds: computational design of silicone molds.', ACM Trans. Graph., vol. 37, no. 4, pp. 136-136.
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Alexander, TB, Gu, Z, Iacobucci, I, Dickerson, K, Choi, JK, Xu, B, Payne-Turner, D, Yoshihara, H, Loh, ML, Horan, J, Buldini, B, Basso, G, Elitzur, S, de Haas, V, Zwaan, CM, Yeoh, A, Reinhardt, D, Tomizawa, D, Kiyokawa, N, Lammens, T, De Moerloose, B, Catchpoole, D, Hori, H, Moorman, A, Moore, AS, Hrusak, O, Meshinchi, S, Orgel, E, Devidas, M, Borowitz, M, Wood, B, Heerema, NA, Carrol, A, Yang, Y-L, Smith, MA, Davidsen, TM, Hermida, LC, Gesuwan, P, Marra, MA, Ma, Y, Mungall, AJ, Moore, RA, Jones, SJM, Valentine, M, Janke, LJ, Rubnitz, JE, Pui, C-H, Ding, L, Liu, Y, Zhang, J, Nichols, KE, Downing, JR, Cao, X, Shi, L, Pounds, S, Newman, S, Pei, D, Guidry Auvil, JM, Gerhard, DS, Hunger, SP, Inaba, H & Mullighan, CG 2018, 'The genetic basis and cell of origin of mixed phenotype acute leukaemia', Nature, vol. 562, no. 7727, pp. 373-379.
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Mixed phenotype acute leukaemia (MPAL) is a high-risk subtype of leukaemia with myeloid and lymphoid features, limited genetic characterization, and a lack of consensus regarding appropriate therapy. Here we show that the two principal subtypes of MPAL, T/myeloid (T/M) and B/myeloid (B/M), are genetically distinct. Rearrangement of ZNF384 is common in B/M MPAL, and biallelic WT1 alterations are common in T/M MPAL, which shares genomic features with early T-cell precursor acute lymphoblastic leukaemia. We show that the intratumoral immunophenotypic heterogeneity characteristic of MPAL is independent of somatic genetic variation, that founding lesions arise in primitive haematopoietic progenitors, and that individual phenotypic subpopulations can reconstitute the immunophenotypic diversity in vivo. These findings indicate that the cell of origin and founding lesions, rather than an accumulation of distinct genomic alterations, prime tumour cells for lineage promiscuity. Moreover, these findings position MPAL in the spectrum of immature leukaemias and provide a genetically informed framework for future clinical trials of potential treatments for MPAL.
Alfaro-García, VG, Merigó, JM, Gil-Lafuente, AM & Kacprzyk, J 2018, 'Logarithmic aggregation operators and distance measures', International Journal of Intelligent Systems, vol. 33, no. 7, pp. 1488-1506.
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© 2018 Wiley Periodicals, Inc. The Hamming distance is a well-known measure that is designed to provide insights into the similarity between two strings of information. In this study, we use the Hamming distance, the optimal deviation model, and the generalized ordered weighted logarithmic averaging (GOWLA) operator to develop the ordered weighted logarithmic averaging distance (OWLAD) operator and the generalized ordered weighted logarithmic averaging distance (GOWLAD) operator. The main advantage of these operators is the possibility of modeling a wider range of complex representations of problems under the assumption of an ideal possibility. We study the main properties, alternative formulations, and families of the proposed operators. We analyze multiple classical measures to characterize the weighting vector and propose alternatives to deal with the logarithmic properties of the operators. Furthermore, we present generalizations of the operators, which are obtained by studying their weighting vectors and the lambda parameter. Finally, an illustrative example regarding innovation project management measurement is proposed, in which a multi-expert analysis and several of the newly introduced operators are utilized.
Ali, A & Lee, JE-Y 2018, 'Piezoelectric-on-Silicon Square Wine-Glass Mode Resonator for Enhanced Electrical Characterization in Water', IEEE Transactions on Electron Devices, vol. 65, no. 5, pp. 1925-1931.
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Ali, AR, Gabrys, B & Budka, M 2018, 'Cross-domain Meta-learning for Time-series Forecasting', Procedia Computer Science, vol. 126, pp. 9-18.
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© 2018 The Author(s). There are many algorithms that can be used for the time-series forecasting problem, ranging from simple (e.g. Moving Average) to sophisticated Machine Learning approaches (e.g. Neural Networks). Most of these algorithms require a number of user-defined parameters to be specified, leading to exponential explosion of the space of potential solutionS. since the trial-and-error approach to finding a good algorithm for solving a given problem is typically intractable, reSearchers and practitioners need to resort to a more intelligent Search strategy, with one option being to constraint the Search space using past experience - an approach known as Meta-learning. Although potentially attractive, Meta-learning comes with its own challengeS. Gathering a sufficient number of Meta-examples, which in turn requires collecting and processing multiple datasets from each problem domain under consideration is perhaps the most prominent issue. In this paper, we are investigating the situations in which the use of additional data can improve performance of a Meta-learning System, with focus on cross-domain transfer of Meta-knowledge. A similarity-based cluster analysis of Meta-features has also been performed in an attempt to discover homogeneous groups of time-series with respect to Meta-learning performance. Although the experiments revealed limited room for improvement over the overall best base-learner, the Meta-learning approach turned out to be a safe choice, minimizing the risk of selecting the least appropriate base-learner.
Ali, SM, Kim, JE, Phuntsho, S, Jang, A, Choi, JY & Shon, HK 2018, 'Forward osmosis system analysis for optimum design and operating conditions', Water Research, vol. 145, pp. 429-441.
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© 2018 Elsevier Ltd Low energy consumption and less fouling propensity of forward osmosis (FO) processes have been attractive as a promising water filtration technology. The performance of this process is however significantly influenced by its operating conditions. Moreover, these operating parameters have both favourable and adverse effects on its performance. Therefore, it is very important to optimize its performance for efficient and economic operation. This study aims to develop a software to analyze a full-scale FO system for optimum performance. A comprehensive theoretical framework was developed to estimate the performance of FO system. Analysis results were compared with the experimental results to validate the models. About 5% deviation of simulation results and the experimental findings shows a very good agreement between them. A novel optimization algorithm was then developed to estimate the minimum required draw solution (DS) inlet flowrate and the number of elements in a pressure vessel to attain the design objectives (i.e. desired final DS concentration and recovery rate at a specific feed solution (FS) flowrate). A detailed parametric study was also conducted to determine the optimum operating conditions for different objectives. It showed that for a specific design objective, higher recovery rate can be achieved by increasing the DS flowrate and number of elements in a pressure vessel. In contrast, lower final concentration can be obtained by lowering the DS flowrate and increasing the number of elements. Finally, a MATLAB based software with graphical user interface was developed to make the analysis process easier and efficient.
Alidadi, H, Dolatabadi, M, Davoudi, M, Barjasteh-Askari, F, Jamali-Behnam, F & Hosseinzadeh, A 2018, 'Enhanced removal of tetracycline using modified sawdust: Optimization, isotherm, kinetics, and regeneration studies', Process Safety and Environmental Protection, vol. 117, pp. 51-60.
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Alizadeh, M, Hashim, M, Alizadeh, E, Shahabi, H, Karami, MR, Beiranvand Pour, A, Pradhan, B & Zabihi, H 2018, 'Multi-Criteria Decision Making (MCDM) Model for Seismic Vulnerability Assessment (SVA) of Urban Residential Buildings', ISPRS International Journal of Geo-Information, vol. 7, no. 11, pp. 444-444.
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Earthquakes are among the most catastrophic natural geo-hazards worldwide and endanger numerous lives annually. Therefore, it is vital to evaluate seismic vulnerability beforehand to decrease future fatalities. The aim of this research is to assess the seismic vulnerability of residential houses in an urban region on the basis of the Multi-Criteria Decision Making (MCDM) model, including the analytic hierarchy process (AHP) and geographical information system (GIS). Tabriz city located adjacent to the North Tabriz Fault (NTF) in North-West Iran was selected as a case study. The NTF is one of the major seismogenic faults in the north-western part of Iran. First, several parameters such as distance to fault, percent of slope, and geology layers were used to develop a geotechnical map. In addition, the structural construction materials, building materials, size of building blocks, quality of buildings and buildings-floors were used as key factors impacting on the building’s structural vulnerability in residential areas. Subsequently, the AHP technique was adopted to measure the priority ranking, criteria weight (layers), and alternatives (classes) of every criterion through pair-wise comparison at all levels. Lastly, the layers of geotechnical and spatial structures were superimposed to design the seismic vulnerability map of buildings in the residential area of Tabriz city. The results showed that South and Southeast areas of Tabriz city exhibit low to moderate vulnerability, while some regions of the north-eastern area are under severe vulnerability conditions. In conclusion, the suggested approach offers a practical and effective evaluation of Seismic Vulnerability Assessment (SVA) and provides valuable information that could assist urban planners during mitigation and preparatory phases of less examined areas in many other regions around the world.
Alizadeh, M, Ngah, I, Hashim, M, Pradhan, B & Pour, AB 2018, 'A Hybrid Analytic Network Process and Artificial Neural Network (ANP-ANN) Model for Urban Earthquake Vulnerability Assessment', Remote Sensing, vol. 10, no. 6, pp. 975-975.
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Vulnerability assessment is one of the prerequisites for risk analysis in disaster management. Vulnerability to earthquakes, especially in urban areas, has increased over the years due to the presence of complex urban structures and rapid development. Urban vulnerability is a result of human behavior which describes the extent of susceptibility or resilience of social, economic, and physical assets to natural disasters. The main aim of this paper is to develop a new hybrid framework using Analytic Network Process (ANP) and Artificial Neural Network (ANN) models for constructing a composite social, economic, environmental, and physical vulnerability index. This index was then applied to Tabriz City, which is a seismic-prone province in the northwestern part of Iran with recurring devastating earthquakes and consequent heavy casualties and damages. A Geographical Information Systems (GIS) analysis was used to identify and evaluate quantitative vulnerability indicators for generating an earthquake vulnerability map. The classified and standardized indicators were subsequently weighed and ranked using an ANP model to construct the training database. Then, standardized maps coupled with the training site maps were presented as input to a Multilayer Perceptron (MLP) neural network for producing an Earthquake Vulnerability Map (EVM). Finally, an EVM was produced for Tabriz City and the level of vulnerability in various zones was obtained. South and southeast regions of Tabriz City indicate low to moderate vulnerability, while some zones of the northeastern tract are under critical vulnerability conditions. Furthermore, the impact of the vulnerability of Tabriz City on population during an earthquake was included in this analysis for risk estimation. A comparison of the result produced by EVM and the Population Vulnerability (PV) of Tabriz City corroborated the validity of the results obtained by ANP-ANN. The findings of this paper are useful for decisi...
Allioux, F-M, David, O, Merenda, A, Maina, JW, Benavides, ME, Tanaka, AP & Dumée, LF 2018, 'Catalytic nickel and nickel–copper alloy hollow-fiber membranes for the remediation of organic pollutants by electrocatalysis', Journal of Materials Chemistry A, vol. 6, no. 16, pp. 6904-6915.
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Electrocatalytic membrane reactors are becoming a viable solution for the treatment of wastewater contaminated with persistent organic pollutants and compounds.
Alsahafi, YA & Gay, V 2018, 'An overview of electronic personal health records', Health Policy and Technology, vol. 7, no. 4, pp. 427-432.
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© 2018 Electronic Personal Health Record systems are providing health consumers with greater access and control to their health records by shifting these records from being a health provider-centred Electronic Health Record, to a patient-centred, Electronic Personal Health Record (ePHR). Based on the delivery system, ePHR systems are classified into standalone, tethered, and integrated or unified ePHRs. While national approaches of implementing integrated ePHR vary, the middle out method has been recognised as the ideal approach. It is worth considering the adoption of ePHRs has been slow due to several factors, including technical, individual, environmental, social, and legal factors. This paper provides a representative overview of an ePHR system, outlining its definition, types, architectures, and nationwide approaches of its implementation. Additionally, the drivers and hindrances to health consumer adoption are discussed.
Alshehri, MD, Hussain, FK & Hussain, OK 2018, 'Clustering-Driven Intelligent Trust Management Methodology for the Internet of Things (CITM-IoT)', Mobile Networks and Applications, vol. 23, no. 3, pp. 419-431.
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© 2018, Springer Science+Business Media, LLC, part of Springer Nature. The growth and adoption of the Internet of Things (IoT) is increasing day by day. The large number of IoT devices increases the risk of security threats such as (but not limited to) viruses or cyber-attacks. One possible approach to achieve IoT security is to enable a trustworthy IoT environment in IoT wherein the interactions are based on the trust value of the communicating nodes. Trust management and trust assessment has been extensively studied in distributed networks in general and the IoT in particular, but there are still outstanding pressing issues such as bad-mouthing of trust values which prevent them from being used in practical IoT applications. Furthermore, there is no research in ensuring that the developed IoT trust solutions are scalable across billions of IoT nodes. To address the above-mentioned issues, we propose a methodology for scalable trust management solution in the IoT. The methodology addresses practical and pressing issues related to IoT trust management such as trust-based IoT clustering, intelligent methods for countering bad-mouthing attacks on trust systems, issues of memory-efficient trust computation and trust-based migration of IoT nodes from one cluster to another. Experimental results demonstrate the effectiveness of the proposed approaches.
Altaee, A 2018, 'Osmotic Power Plant: Process Innovation and Future Potential', Recent Advances in Petrochemical Science, vol. 4, no. 3, pp. 1-1.
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Osmotic power plant operating by Pressure Retarded Osmosis (PRO) is a promising technology for power generation from renewable resources. A wealth of literature has been published in PRO feasibility to replace conventional fossil fuel power plants. In this paper the PRO and the new innovative Dual Stage PRO process are briefly reviewed with the authors’ insight on the future development and application of the PRO power plants.
Altaee, A, Zaragoza, G, Millar, GJ, Sharif, AO & Alanezi, AA 2018, 'Limitations of osmotic gradient resource and hydraulic pressure on the efficiency of dual stage PRO process', Desalination and Water Treatment, vol. 105, pp. 11-22.
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© 2018 Desalination Publications. All rights reserved. A dual stage PRO process has been proposed for power generation from a salinity gradient across a semi-permeable membrane. Both closed-loop and open-loop dual stage PRO system were evaluated using 2 M NaCl and Dead Sea as draw solutions, whereas the feed solution was either fresh water or seawater. The impact of feed salinity gradient resource and feed pressure on the net power generation and water flux were evaluated. The results showed that power density in stage one reached a maximum amount at ΔP = p/2, but the maximum net power generation occurred at ΔP = p/2. This result was mainly attributed to the variation of net driving pressure in stage one and two of the PRO process. The dual stage PRO process was found to perform better at high osmotic pressure gradient across the PRO membrane, for example when Dead Sea brine or highly concentrated NaCl was the draw solution. Total power generation in the dual stage PRO process was up to 40% higher than that in the conventional PRO process. This outcome was achieved through harvesting the rest of the energy remaining in the diluted draw solution. Therefore, a dual stage PRO process has the potential of maximizing power generation from a salinity gradient resource.
Alzoubi, YI, Gill, AQ & Moulton, B 2018, 'A measurement model to analyze the effect of agile enterprise architecture on geographically distributed agile development.', J. Softw. Eng. Res. Dev., vol. 6, no. 4, pp. 4-4.
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Al-Zubaydi, AYT & Hong, G 2018, 'Experimental investigation of counter flow heat exchangers for energy recovery ventilation in cooling mode', International Journal of Refrigeration, vol. 93, pp. 132-143.
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© 2018 Elsevier Ltd and IIR Ventilation heat recovery is a system that requires low power to operate and has a high capacity to reduce the energy consumption and increase the overall efficiency for air conditioning. This paper reports the experimental investigation of air-to-air heat exchangers employed for heat recovery ventilation in cooling mode. The two main objective of this research are to design, fabricate and testing two polymers heat exchangers of different plate geometries and to evaluate and compare the thermal performance two quasi-counter flow plate heat exchangers. The key aims were to evaluate the effect of the surface geometry of the plates heat exchanger on the performance parameters specified in ANSI/ASHRAE Standard 84 and ANSI/AHRI Standard 1060 and narrow the gap of the limited experimental comparison of polymers sensible heat exchanger in cooling mode. The experiments were conducted on two polymer heat exchangers, one with a flat plate and the other with a dimpled surface plate. The experimental results showed that the cooling capacity of the dimpled surface heat exchanger as ventilation heat recovery system in cooling mode was 50–60% better than that of the flat surface plate heat exchanger. In addition, the sensible efficiency of the dimpled surface heat exchanger was higher than that of the flat surface plates heat exchanger at lower air velocities and higher air initial temperatures. The highest COP was 6.6 achieved with dimpled surface heat exchanger under primary air operating temperature of 32.6 °C.
Amjadipour, M, Tadich, A, Boeckl, JJ, Lipton-Duffin, J, MacLeod, J, Iacopi, F & Motta, N 2018, 'Quasi free-standing epitaxial graphene fabrication on 3C–SiC/Si(111)', Nanotechnology, vol. 29, no. 14, pp. 145601-145601.
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Growing graphene on SiC thin films on Si is a cheaper alternative to the growth on bulk SiC, and for this reason it has been recently intensively investigated. Here we study the effect of hydrogen intercalation on epitaxial graphene obtained by high temperature annealing on 3C-SiC/Si(111) in ultra-high vacuum. By using a combination of core-level photoelectron spectroscopy, low energy electron diffraction, and near-edge x-ray absorption fine structure (NEXAFS) we find that hydrogen saturates the Si atoms at the topmost layer of the substrate, leading to free-standing graphene on 3C-SiC/Si(111). The intercalated hydrogen fully desorbs after heating the sample at 850 °C and the buffer layer appears again, similar to what has been reported for bulk SiC. However, the NEXAFS analysis sheds new light on the effect of hydrogen intercalation, showing an improvement of graphene's flatness after annealing in atomic H at 600 °C. These results provide new insight into free-standing graphene fabrication on SiC/Si thin films.
Anaissi, A, Khoa, NLD & Wang, Y 2018, 'Automated parameter tuning in one-class support vector machine: an application for damage detection', International Journal of Data Science and Analytics, vol. 6, no. 4, pp. 311-325.
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Anaissi, A, Khoa, NLD, Rakotoarivelo, T, Alamdari, MM & Wang, Y 2018, 'Adaptive Online One-Class Support Vector Machines with Applications in Structural Health Monitoring', ACM Transactions on Intelligent Systems and Technology, vol. 9, no. 6, pp. 1-20.
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One-class support vector machine (OCSVM) has been widely used in the area of structural health monitoring, where only data from one class (i.e., healthy) are available. Incremental learning of OCSVM is critical for online applications in which huge data streams continuously arrive and the healthy data distribution may vary over time. This article proposes a novel adaptive self-advised online OCSVM that incrementally tunes the kernel parameter and decides whether a model update is required or not. As opposed to existing methods, this novel online algorithm does not rely on any fixed threshold, but it uses the slack variables in the OCSVM to determine which new data points should be included in the training set and trigger a model update. The algorithm also incrementally tunes the kernel parameter of OCSVM automatically based on the spatial locations of the edge and interior samples in the training data with respect to the constructed hyperplane of OCSVM. This new online OCSVM algorithm was extensively evaluated using synthetic data and real data from case studies in structural health monitoring. The results showed that the proposed method significantly improved the classification error rates, was able to assimilate the changes in the positive data distribution over time, and maintained a high damage detection accuracy in all case studies.
Andrade-Valbuena, NA & Merigo, JM 2018, 'Outlining new product development research through bibliometrics', Journal of Strategy and Management, vol. 11, no. 3, pp. 328-350.
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PurposeNew product development (NPD) is a noteworthy field that has attracted the attention of scholars for its relevance for firm success. Based on bibliometric indicators and spatial distance network analysis, the authors outline the general structure overview of NPD research through the last 40 years of scientific production; identify and categorize key articles, authors, journals, institutions, and countries related to NPD research; identify and map the research subareas that have mostly contributed to the construction of NPD intellectual structure. The paper aims to discuss these issues.Design/methodology/approachThe work uses the Web of Science Core Collection and the visualization of similarities viewer software. The analysis searches for all the documents connected to NPD available in the database. The graphical visualization maps the bibliographic data in terms of bibliographic coupling and co-citation.FindingsThe general NPD citation pattern evidences a construction of knowledge and learning, as evidenced in different subjects, such as biology or physics. Relevant contributions and contributors are highlighted as journals, articles, researchers, countries and institutions in overall NPD research and in its constituent subfields. Five subareas related to the NPD field based on journals and authors network are identified: marketing; operations and production; strategy; industrial engineering and operations; and management.Originality/valueThis paper contributes to the NPD literature by offering a global perspective on the field by using bibliometric data graphical networks, provid...
Ansari, AJ, Hai, FI, He, T, Price, WE & Nghiem, LD 2018, 'Physical cleaning techniques to control fouling during the pre-concentration of high suspended-solid content solutions for resource recovery by forward osmosis', Desalination, vol. 429, pp. 134-141.
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Ansari, AJ, Hai, FI, Price, WE, Ngo, HH, Guo, W & Nghiem, LD 2018, 'Assessing the integration of forward osmosis and anaerobic digestion for simultaneous wastewater treatment and resource recovery', Bioresource Technology, vol. 260, pp. 221-226.
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© 2018 This study assessed the performance and key challenges associated with the integration of forward osmosis (FO) and anaerobic digestion for wastewater treatment and resource recovery. Using a thin film composite polyamide FO membrane, maximising the pre-concentration factor (i.e. system water recovery) resulted in the enrichment of organics and salinity in wastewater. Biomethane potential evaluation indicated that methane production increased correspondingly with the FO pre-concentration factor due to the organic retention in the feed solution. At 90% water recovery, about 10% more methane was produced when using NaOAc compared with NaCl because of the contribution of biodegradable reverse NaOAc flux. No negative impact on anaerobic digestion was observed when wastewater was pre-concentrated ten-fold (90% water recovery) for both draw solutes. Interestingly, the unit cost of methane production using NaOAc was slightly lower than NaCl due to the lower reverse solute flux of NaOAc, although NaCl is a much cheaper chemical.
Anshu, A, Berta, M, Jain, R & Tomamichel, M 2018, 'Partially smoothed information measures', IEEE Trans. Inf. Theory, vol. 66, pp. 5022-5036.
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Smooth entropies are a tool for quantifying resource trade-offs in (quantum)information theory and cryptography. In typical bi- and multi-partite problems,however, some of the sub-systems are often left unchanged and this is notreflected by the standard smoothing of information measures over a ball ofclose states. We propose to smooth instead only over a ball of close stateswhich also have some of the reduced states on the relevant sub-systems fixed.This partial smoothing of information measures naturally allows to give morerefined characterizations of various information-theoretic problems in theone-shot setting. In particular, we immediately get asymptotic second-ordercharacterizations for tasks such as privacy amplification against classicalside information or classical state splitting. For quantum problems like statemerging the general resource trade-off is tightly characterized by partiallysmoothed information measures as well.
Anshu, A, Hsieh, M-H & Jain, R 2018, 'Noisy quantum state redistribution with promise and the Alpha-bit', IEEE Transactions on Information Theory (IEEE-TIT), Volume: 66, Issue: 12, 2020, vol. 66, no. 12, pp. 7772-7786.
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We consider a variation of the well-studied quantum state redistributiontask, in which the starting state is known only to the receiver Bob and not tothe sender Alice. We refer to this as quantum state redistribution with aone-sided promise. In addition, we consider communication from Alice to Bobover a noisy channel $\mathcal{N}$, instead of the noiseless channel, as isusually considered in state redistribution. We take a natural approach towardsthe solution of this problem where we 'embed' the promise as part of the stateand then invoke known protocols for quantum state redistribution composed withknown protocols for transfer of quantum information over noisy channels. Usingour approach, we are able to reproduce the Alpha-bit capacities with or withoutentanglement assistance in Ref. [ArXiv:1706.09434], using known protocols forquantum state redistribution and quantum communication over noisy channels.Furthermore, we generalize the entanglement assisted classical Alpha-bitcapacity, showing that any quantum state redistribution protocol can be used asa black box to simulate classical communication.
Anshu, A, Hsieh, M-H & Jain, R 2018, 'Quantifying Resources in General Resource Theory with Catalysts', Physical Review Letters, vol. 121, no. 19.
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© 2018 American Physical Society. A question that is commonly asked in all areas of physics is how a certain property of a physical system can be used to achieve useful tasks and how to quantify the amount of such a property in a meaningful way. We answer this question by showing that, in a general resource-theoretic framework that allows the use of free states as catalysts, the amount of 'resources' contained in a given state, in the asymptotic scenario, is equal to the regularized relative entropy of a resource of that state. While we need to place a few assumptions on our resource-theoretical framework, it is still sufficiently general, and its special cases include quantum resource theories of entanglement, coherence, asymmetry, athermality, nonuniformity, and purity. As a by-product, our result also implies that the amount of noise one has to inject locally to erase all the entanglement contained in an entangled state is equal to the regularized relative entropy of entanglement.
Anwar, M, Rasul, MG, Ashwath, N & Rahman, MM 2018, 'Optimisation of Second-Generation Biodiesel Production from Australian Native Stone Fruit Oil Using Response Surface Method', Energies, vol. 11, no. 10, pp. 2566-2566.
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In this study, the production process of second-generation biodiesel from Australian native stone fruit have been optimised using response surface methodology via an alkali catalysed transesterification process. This process optimisation was performed varying three factors, each at three different levels. Methanol: oil molar ratio, catalyst concentration (wt %) and reaction temperature were the input factors in the optimisation process, while biodiesel yield was the key model output. Both 3D surface plots and 2D contour plots were developed using MINITAB 18 to predict optimum biodiesel yield. Gas chromatography (GC) and Fourier transform infrared (FTIR) analysis of the resulting biodiesel was also done for biodiesel characterisation. To predict biodiesel yield a quadratic model was created and it showed an R2 of 0.98 indicating the satisfactory performance of the model. Maximum biodiesel yield of 95.8% was obtained at a methanol: oil molar ratio of 6:1, KOH catalyst concentration of 0.5 wt % and a reaction temperature of 55 °C. At these reaction conditions, the predicted biodiesel yield was 95.9%. These results demonstrate reliable prediction of the transesterification process by Response surface methodology (RSM). The results also show that the properties of the synthesised Australian native stone fruit biodiesel satisfactorily meet the ASTM D6751 and EN14214 standards. In addition, the fuel properties of Australian native stone fruit biodiesel were found to be similar to those of conventional diesel fuel. Thus, it can be said that Australian native stone fruit seed oil could be used as a potential second-generation biodiesel source as well as an alternative fuel in diesel engines.
Apkon, SD, Alman, B, Birnkrant, DJ, Fitch, R, Lark, R, Mackenzie, W, Weidner, N & Sussman, M 2018, 'Orthopedic and Surgical Management of the Patient With Duchenne Muscular Dystrophy', Pediatrics, vol. 142, no. Supplement_2, pp. S82-S89.
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Orthopedic care is an important aspect of the overall management of patients with Duchenne muscular dystrophy (DMD). In addition to progressive muscle weakness and loss of function, patients may develop joint contractures, scoliosis, and osteoporosis, causing fractures; all of these necessitate intervention by a multidisciplinary team including an orthopedic surgeon as well as rehabilitation specialists such as physio- and occupational therapists. The causes of these musculoskeletal complications are multifactorial and are related to primary effects on the muscles from the disease itself, secondary effects from weak muscles, and the related side effects of treatments, such as glucocorticoid use that affect bone strength. The musculoskeletal manifestations of DMD change over time as the disease progresses, and therefore, musculoskeletal management needs change throughout the life span of an individual with DMD. In this review, we target pediatricians, neurologists, orthopedic surgeons, rehabilitation physicians, anesthesiologists, and other individuals involved in the management of patients with DMD by providing specific recommendations to guide clinical practice related to orthopedic issues and surgical management in this setting.
Arabameri, A, Pradhan, B, Pourghasemi, HR & Rezaei, K 2018, 'Identification of erosion-prone areas using different multi-criteria decision-making techniques and GIS', Geomatics, Natural Hazards and Risk, vol. 9, no. 1, pp. 1129-1155.
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Arabameri, A, Pradhan, B, Pourghasemi, HR, Rezaei, K & Kerle, N 2018, 'Spatial Modelling of Gully Erosion Using GIS and R Programing: A Comparison among Three Data Mining Algorithms', Applied Sciences, vol. 8, no. 8, pp. 1369-1369.
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Gully erosion triggers land degradation and restricts the use of land. This study assesses the spatial relationship between gully erosion (GE) and geo-environmental variables (GEVs) using Weights-of-Evidence (WoE) Bayes theory, and then applies three data mining methods—Random Forest (RF), boosted regression tree (BRT), and multivariate adaptive regression spline (MARS)—for gully erosion susceptibility mapping (GESM) in the Shahroud watershed, Iran. Gully locations were identified by extensive field surveys, and a total of 172 GE locations were mapped. Twelve gully-related GEVs: Elevation, slope degree, slope aspect, plan curvature, convergence index, topographic wetness index (TWI), lithology, land use/land cover (LU/LC), distance from rivers, distance from roads, drainage density, and NDVI were selected to model GE. The results of variables importance by RF and BRT models indicated that distance from road, elevation, and lithology had the highest effect on GE occurrence. The area under the curve (AUC) and seed cell area index (SCAI) methods were used to validate the three GE maps. The results showed that AUC for the three models varies from 0.911 to 0.927, whereas the RF model had a prediction accuracy of 0.927 as per SCAI values, when compared to the other models. The findings will be of help for planning and developing the studied region.
Arabameri, A, Pradhan, B, Rezaei, K, Yamani, M, Pourghasemi, HR & Lombardo, L 2018, 'Spatial modelling of gully erosion using evidential belief function, logistic regression, and a new ensemble of evidential belief function–logistic regression algorithm', Land Degradation & Development, vol. 29, no. 11, pp. 4035-4049.
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AbstractThis study aims to assess gully erosion susceptibility and delineate gully erosion‐prone areas in Toroud Watershed, Semnan Province, Iran. Two different methods, namely, logistic regression (LR) and evidential belief function (EBF), were evaluated, and a new ensemble method was proposed using the combination of both methods. We initially created a gully erosion inventory map using different resources, including early reports, Google Earth images, and Global Positioning System‐aided field surveys. We subsequently split this information randomly and selected 70% (90) of the gullies for calibration and 30% (38) for validation. The method was constructed using a combination of morphometric and thematic predictors that include 16 conditioning parameters. We also assessed the following: (a) potential multicollinearity issues using tolerance and variance inflation factor indices and (b) covariate effects using LR coefficients and EBF class weights. Results show that land use/land cover, lithology, and distance to roads dominate the method with the greatest effect on gully occurrences. We produced three susceptibility maps and evaluated their predictive power through area under the curve (AUC) and seed cell area index analyses. AUC results revealed that the ensemble method presented a considerably higher performance (AUC = 0.909) than did the individual LR (0.802) and EBF (0.821) methods. Similarly, seed cell area index displayed a constant decrease from the ensemble to single methods. The resulted gully erosion‐susceptibility map could be used by decision makers and local managers for soil conservation, and for minimising damages in development activities including construction of infrastructures such as roads and the route of gas and electricity transmission lines.
Arandiyan, H, Wang, Y, Scott, J, Mesgari, S, Dai, H & Amal, R 2018, 'In Situ Exsolution of Bimetallic Rh–Ni Nanoalloys: a Highly Efficient Catalyst for CO2 Methanation', ACS Applied Materials & Interfaces, vol. 10, no. 19, pp. 16352-16357.
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© 2018 American Chemical Society. Unique CO2 methanation catalysts comprising bimetallic Ni-Rh nanoalloy/3DOM LaAlO3 have been successfully prepared via a poly(methyl methacrylate) microsphere colloidal crystal-templating route, followed by the in situ growth of Ni nanoparticles (NPs). Here, we show that unlike traditional Ni particles deposited on a perovskite support, the exsolution of Ni occurs on both the external and internal surface of the porous perovskite substrate, leading to a strong metal-support interaction. Owing to the exsolution of Ni and the formation of Ni-Rh nanoalloys, a 52% enhancement in the methanation turnover frequency was obtained over the Ni-Rh/3DOM LaAlO3 [13.9 mol/(mol h)] compared to Rh/3DOM LaNi0.08Al0.92O3 [9.16 mol/(mol h)] before reduction treatment. The results show that the low-temperature reducibility, rich surface adsorbed oxygen species, and basic sites of the catalyst greatly improve its activity toward CO2 methanation. The hierarchically porous structure of the perovskite support provides a high dispersion of bimetallic Ni-Rh NPs.
Argha, A, Li, L & Su, SW 2018, '‐based optimal sparse sliding mode control for networked control systems', International Journal of Robust and Nonlinear Control, vol. 28, no. 1, pp. 16-30.
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SummaryThis paper is devoted to the problem of designing a sparsely distributed sliding mode control for networked systems. Indeed, this note uses a distributed sliding mode control framework by exploiting (some of) other subsystems' information to improve the performance of each local controller so that it can widen the applicability region of the given scheme. To do so, different from the traditional schemes in the literature, a novel approach is proposed to design the sliding surface, in which the level of required control effort is taken into account during the sliding surface design based on the control. We then use this novel scheme to provide an innovative less‐complex procedure that explores sparse control networks to satisfy the underlying control objective. Besides, the proposed scheme to design the sliding surface makes it possible to avoid unbounded growth of control effort during the sparsification of the control network structure. Illustrative examples are presented to show the effectiveness of the proposed approach.
Argha, A, Li, L, Su, SW & Nguyen, H 2018, 'Sparsely distributed sliding mode control for interconnected systems', Journal of the Franklin Institute, vol. 355, no. 14, pp. 6191-6214.
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© 2018 The Franklin Institute This paper proposes a framework for the design of sparsely distributed output feedback discrete-time sliding mode control (ODSMC) for interconnected systems. The major target here is to develop an observer based discrete-time sliding mode controller employing a sparsely distributed control network structure in which local controllers exploit some other sub-systems’ information as well as its own local information. As the local controllers/observers have access to some other sub-systems’ states, the control performance will be improved and the applicability region will be widened compared to the decentralised structure. As the first step, a stability condition is derived for the overall closed-loop system obtained from applying ODSMC to the underlying interconnected system, by assuming a priori known structure for the control/observer network. The developed LMI based controller design scheme provides the possibility to employ different information patterns such as fully distributed, sparsely distributed and decentralised patterns. In the second step, we propose a methodology to identify a sparse control/observer network structure with the least possible number of communication links that satisfies the stability condition given in the first step. The boundedness of the obtained overall closed-loop system is analysed and a bound is derived for the augmented system state which includes the closed-loop system state and the switching function.
Argha, A, Su, SW, Savkin, A & Celler, BG 2018, 'Mixed H2/H∞-based actuator selection for uncertain polytopic systems with regional pole placement', International Journal of Control, vol. 91, no. 2, pp. 320-336.
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© 2017 Informa UK Limited, trading as Taylor & Francis GroupThis paper is devoted to the problem of designing an (Formula presented.) and/or (Formula presented.) row-sparse static output feedback controller for continuous linear time-invariant systems with polytopic uncertainty. The immediate application of the proposed approach lies within the problem of the optimal selection of a subset of available actuators during the fault accommodation stage of a fault-tolerant control scheme. Incorporating an extra term for penalising the number of actuators into the optimisation objective function, we propose an explicit scheme and two iterative procedures according to the reweighted ℓ1 (REL1) and reweighted iterative support detection (RISD) algorithms for the purposes of identifying the favourable row-sparse feedback gains. Furthermore, this problem formulation allows us to incorporate additional constraints into the designing problem such as regional pole placement constraints which provide more control over the satisfactory transient behaviour and closed-loop pole locations. In this paper, we present two examples which demonstrate the remarkable performance and broad applicability of the proposed approaches.
Argha, A, Su, SW, Savkin, A & Celler, BG 2018, 'Novel frameworks for the design of fault‐tolerant control using optimal sliding‐mode control', International Journal of Robust and Nonlinear Control, vol. 28, no. 8, pp. 3015-3032.
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SummaryThis paper describes 2 schemes for a fault‐tolerant control using a novel optimal sliding‐mode control, which can also be employed as actuator redundancy management for overactuated uncertain linear systems. By using the effectiveness level of the actuators in the performance indexes, 2 schemes for redistributing the control effort among the remaining (redundant or nonfaulty) set of actuators are constructed based on an ‐based optimal sliding‐mode control. In contrast to the current sliding‐mode fault‐tolerant control design methods, in these new schemes, the level of control effort required to maintain sliding is penalised. The proposed optimal sliding‐mode fault‐tolerant control design schemes are implemented in 2 stages. In the first stage, a state feedback gain is derived using an LMI‐based scheme that can assign a number of the closed‐loop eigenvalues to a known value whilst satisfying performance specifications. The sliding function matrix related to the particular state feedback derived in the first stage is obtained in the second stage. The difference between the 2 schemes proposed for the sliding‐mode fault‐tolerant control is that the second one includes a separate control allocation module, which makes it easier to apply actuator constraints to the problem. Moreover, it will be shown that, with the second scheme, we can deal with actuator faults or even failures without controller reconfiguration. We further discuss the advantages and disadvantages of the 2 schemes in more details. The effectiveness of the proposed schemes are illustrated with numerical examples.
Asadabadi, MR, Saberi, M & Chang, E 2018, 'Targets of Unequal Importance Using the Concept of Stratification in a Big Data Environment', International Journal of Fuzzy Systems, vol. 20, no. 4, pp. 1373-1384.
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© 2017, Taiwan Fuzzy Systems Association and Springer-Verlag GmbH Germany, part of Springer Nature. The concept of stratification (CST) has recently been proposed as an innovative approach in problem solving. CST takes a recursive approach to solve problems. It considers a system which has to transition through states until it arrives to a state which belongs to a desired set of states, namely a target set. The states can be stratified by enlarging the target (absorbing adjacent states). Incremental enlargement is a means to identify possible paths to achieve the target. Such an enlargement can also be used to degrade the target when the original target is not reachable. Although the characteristics of the concept, such as incremental enlargement, enhance its potential application in robotics, artificial intelligence, and planning and monitoring, there is a major shortcoming in the approach, namely its inability to consider targets of unequal importance. This study considers two targets of unequal importance for the system in CST, labelled Bi-Objective CST model (BOCST). In comparison with the original proposed CST model in this research, a version of CST with finite states which is much easier to apply than the original CST is proposed, labelled fuzzy CST. Following that, a combination of Fuzzy CST and BOCST (FBO-CST) is proposed. The model is then employed to address a restaurant selection problem using data from Google. The example illustrates how the model should be applied in a big data environment. By defining finite state CST and considering targets of unequal importance, this study is expected to facilitate future applications of CST.
Asif, MB, Hai, FI, Dhar, BR, Ngo, HH, Guo, W, Jegatheesan, V, Price, WE, Nghiem, LD & Yamamoto, K 2018, 'Impact of simultaneous retention of micropollutants and laccase on micropollutant degradation in enzymatic membrane bioreactor', Bioresource Technology, vol. 267, pp. 473-480.
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Asif, MB, Hai, FI, Kang, J, van de Merwe, JP, Leusch, FDL, Price, WE & Nghiem, LD 2018, 'Biocatalytic degradation of pharmaceuticals, personal care products, industrial chemicals, steroid hormones and pesticides in a membrane distillation-enzymatic bioreactor', Bioresource Technology, vol. 247, pp. 528-536.
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© 2017 Elsevier Ltd Laccase-catalyzed degradation of a broad spectrum of trace organic contaminants (TrOCs) by a membrane distillation (MD)-enzymatic membrane bioreactor (EMBR) was investigated. The MD component effectively retained TrOCs (94–99%) in the EMBR, facilitating their continuous biocatalytic degradation. Notably, the extent of TrOC degradation was strongly influenced by their molecular properties. A significant degradation (above 90%) of TrOCs containing strong electron donating functional groups (e.g., hydroxyl and amine groups) was achieved, while a moderate removal was observed for TrOCs containing electron withdrawing functional groups (e.g., amide and halogen groups). Separate addition of two redox-mediators, namely syringaldehyde and violuric acid, further improved TrOC degradation by laccase. However, a mixture of both showed a reduced performance for a few pharmaceuticals such as primidone, carbamazepine and ibuprofen. Mediator addition increased the toxicity of the media in the enzymatic bioreactor, but the membrane permeate (i.e., final effluent) was non-toxic, suggesting an added advantage of coupling MD with EMBR.
Asikin-Mijan, N, Lee, HV, Juan, JC, Noorsaadah, AR, Ong, HC, Razali, SM & Taufiq-Yap, YH 2018, 'Promoting deoxygenation of triglycerides via Co-Ca loaded SiO 2 -Al 2 O 3 catalyst', Applied Catalysis A: General, vol. 552, pp. 38-48.
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Askari, G, Pour, AB, Pradhan, B, Sarfi, M & Nazemnejad, F 2018, 'Band Ratios Matrix Transformation (BRMT): A Sedimentary Lithology Mapping Approach Using ASTER Satellite Sensor', Sensors, vol. 18, no. 10, pp. 3213-3213.
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Remote sensing imagery has become an operative and applicable tool for the preparation of geological maps by reducing the costs and increasing the precision. In this study, ASTER satellite remote sensing data were used to extract lithological information of Deh-Molla sedimentary succession, which is located in the southwest of Shahrood city, Semnan Province, North Iran. A robust and effective approach named Band Ratio Matrix Transformation (BRMT) was developed to characterize and discriminate the boundary of sedimentary rock formations in Deh-Molla region. The analysis was based on the forward and continuous division of the visible-near infrared (VNIR) and the shortwave infrared (SWIR) spectral bands of ASTER with subsequent application of principal component analysis (PCA) for producing new transform datasets. The approach was implemented to ASTER spectral band ratios for mapping dominated mineral assemblages in the study area. Quartz, carbonate, and Al, Fe, Mg –OH bearing-altered minerals such as kaolinite, alunite, chlorite and mica were appropriately mapped using the BRMT approach. The results match well with geology map of the study area, fieldwork data and laboratory analysis. Accuracy assessment of the mapping result represents a reasonable kappa coefficient (0.70%) and appropriate overall accuracy (74.64%), which verified the robustness of the BRMT approach. This approach has great potential and capability for mapping sedimentary succession with diverse local–geological–physical characteristics around the world.
Aslani, M, Ghasemi, P & Gandomi, AH 2018, 'Constrained mean‐variance mapping optimization for truss optimization problems', The Structural Design of Tall and Special Buildings, vol. 27, no. 6, pp. e1449-e1449.
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SummaryTruss optimization is a complex structural problem that involves geometric and mechanical constraints. In the present study, constrained mean‐variance mapping optimization (MVMO) algorithms have been introduced for solving truss optimization problems. Single‐solution and population‐based variants of MVMO are coupled with an adaptive exterior penalty scheme to handle geometric and mechanical constraints. These tools are explained and tuned for weight minimization of trusses with 10 to 200 members and up to 1,200 nonlinear constraints. The results are compared with those obtained from the literature and classical genetic algorithm. The results show that a MVMO algorithm has a rapid rate of convergence and its final solution can obviously outperform those of other algorithms described in the literature. The observed results suggest that a constrained MVMO is an attractive tool for engineering‐based optimization, particularly for computationally expensive problems in which the rate of convergence and global convergence are important.
Atiquzzaman, M & Kandasamy, J 2018, 'Robustness of Extreme Learning Machine in the prediction of hydrological flow series', Computers & Geosciences, vol. 120, pp. 105-114.
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Avilés-Ochoa, E, León-Castro, E, Perez-Arellano, LA & Merigó, JM 2018, 'Government transparency measurement through prioritized distance operators', Journal of Intelligent & Fuzzy Systems, vol. 34, no. 4, pp. 2783-2794.
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© 2018 - IOS Press and the authors. All rights reserved. The prioritized induced probabilistic ordered weighted average distance (PIPOWAD) has been developed. This new operator is an extension of the ordered weighted average (OWA) operator that can be used in cases where we have two sets of data that want to be compared. Some of the main characteristics of this new operator are: 1) Not all the decision makers are equally important, so the information needs to be prioritized, 2) The information has a probability to occur and 3) The decision makers can change the importance of the information based in an induced variable. Additionally, characteristics and families of the PIPOWAD operator are presented. Finally, an application of the PIPOWAD operator in order to measure government transparency in Mexico is presented.
Awadallah, M, Tawadros, P, Walker, P & Zhang, N 2018, 'Comparative fuel economy, cost and emissions analysis of a novel mild hybrid and conventional vehicles', Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering, vol. 232, no. 13, pp. 1846-1862.
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Mild hybrid vehicles have been explored as a potential pathway to reduce vehicle emissions cost-effectively. The use of manual transmissions to develop novel hybrid vehicles provides an alternate route to producing low cost electrified powertrains. In this paper, a comparative analysis examining a conventional vehicle and a mild hybrid electric vehicle is presented. The analysis considers fuel economy, capital and ongoing costs and environmental emissions, and includes developmental analysis and simulation using mathematical models. Vehicle emissions (nitrogen oxides, carbon monoxide and hydrocarbons) and fuel economy are computed, analysed and compared using a number of alternative driving cycles and their weighted combination. Different driver styles are also evaluated. Studying the relationship between the fuel economy and driveability, where driveability is addressed using fuel-economical gear shift strategies. Our simulation suggests the hybrid concept presented can deliver fuel economy gains of between 5 and 10%, as compared to the conventional powertrain.
Ayachit, A, Siwakoti, YP, Galigekere, VPN, Kazimierczuk, MK & Blaabjerg, F 2018, 'Steady-State and Small-Signal Analysis of A-Source Converter', IEEE Transactions on Power Electronics, vol. 33, no. 8, pp. 7118-7131.
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© 1986-2012 IEEE. This paper presents a detailed steady-state analysis and ac small-signal modeling of the power stage of pulse-width modulated A-source converter. The voltage and current waveforms along with their corresponding expressions describing the converter operation are presented in detail. The input-to-output and input-to-capacitor dc voltage transfer functions are determined. The minimum inductance required to ensure continuous conduction mode is derived. The expressions for the semiconductor devices stresses are also presented. The dc, averaged equivalent circuit is derived using the circuit averaging technique. A complete derivation of the small-signal model including the converter parasitic resistances are presented followed by the power stage transfer functions relevant to the capacitor voltage loop, such as: 1) duty cycle-to-capacitor voltage; and 2) input-to-capacitor voltage. In addition, the expressions for the network input impedance and output impedance are derived. Finally, experimental validations of the derived small-signal models are performed, both in frequency and time domain for a laboratory prototype of an A-source converter. The theoretical predictions were in good agreement with the experimental results over a wide range of frequencies.
Azeez, OS, Pradhan, B & Shafri, HZM 2018, 'Vehicular CO Emission Prediction Using Support Vector Regression Model and GIS', Sustainability, vol. 10, no. 10, pp. 3434-3434.
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Transportation infrastructures play a significant role in the economy as they provide accessibility services to people. Infrastructures such as highways, road networks, and toll plazas are rapidly growing based on changes in transportation modes, which consequently create congestions near toll plaza areas and intersections. These congestions exert negative impacts on human health and the environment because vehicular emissions are considered as the main source of air pollution in urban areas and can cause respiratory and cardiovascular diseases and cancer. In this study, we developed a hybrid model based on the integration of three models, correlation-based feature selection (CFS), support vector regression (SVR), and GIS, to predict vehicular emissions at specific times and locations on roads at microscale levels in an urban areas of Kuala Lumpur, Malaysia. The proposed model comprises three simulation steps: first, the selection of the best predictors based on CFS; second, the prediction of vehicular carbon monoxide (CO) emissions using SVR; and third, the spatial simulation based on maps by using GIS. The proposed model was developed with seven road traffic CO predictors selected via CFS (sum of vehicles, sum of heavy vehicles, heavy vehicle ratio, sum of motorbikes, temperature, wind speed, and elevation). Spatial prediction was conducted based on GIS modelling. The vehicular CO emissions were measured continuously at 15 min intervals (recording 15 min averages) during weekends and weekdays twice per day (daytime, evening-time). The model’s results achieved a validation accuracy of 80.6%, correlation coefficient of 0.9734, mean absolute error of 1.3172 ppm and root mean square error of 2.156 ppm. In addition, the most appropriate parameters of the prediction model were selected based on the CFS model. Overall, the proposed model is a promising tool for traffic CO assessment on roads.
Aziz, N, Rasekh, H, Mirzaghorbanali, A, Yang, G, Khaleghparast, S & Nemcik, J 2018, 'An Experimental Study on the Shear Performance of Fully Encapsulated Cable Bolts in Single Shear Test', Rock Mechanics and Rock Engineering, vol. 51, no. 7, pp. 2207-2221.
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A set of single shear tests on fully encapsulated cable bolts was carried out using a newly developed and integrated Megabolt single shear apparatus. The instrument is designed to determine the pure shear strength of cable bolts where there is no contact between the host body faces during the shearing process. Eight different types of cable bolt were encapsulated in 40 MPa concrete cylinders, using Stratabinder HS grout. Prior to encapsulation, cable bolts were pretensioned at the desired value using a manual pretensioner. Effects of surface profile, pretension value and debonding on shear strength of cable bolts were investigated. It was found that the shear strength of spiral/indented cable bolts was lower than that of plain cable bolts. Increasing the pretension load decreased the peak shear load of cable bolts. In general, no debonding was observed for spiral/indented cable bolts during shear testing; however, all tested plain cable bolts were debonded.
Azizivahed, A, Barani, M, Razavi, S, Ghavidel, S, Li, L & Zhang, J 2018, 'Energy storage management strategy in distribution networks utilised by photovoltaic resources', IET Generation, Transmission & Distribution, vol. 12, no. 21, pp. 5627-5638.
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© The Institution of Engineering and Technology 2018. Large penetration of electrical energy storage (EES) units and renewable energy resources in distribution systems can help to improve network profiles (e.g. bus voltage and branch current profiles), and to reduce operational cost as well as power losses. On the other hand, unsecure system operation as a result of involving these units is another challenge to network operators. Therefore, establishing a trade-off between operational cost and security is very important. This study presents a new approach to determine the optimal charging/discharging schedule of EES units in distribution systems by employing multi-objective optimisation methods, which will effectively reduce operational cost and enhance distribution network security. In this regard, a voltage stability index (VSI) is converted into a security index to improve the radial network security. This VSI index is treated as a separate objective function, and a multi-objective strategy is implemented to obtain a set of non-dominated solutions instead of a single optimal solution, which simultaneously minimise both of the operational cost and security index. In order to assess the effectiveness and applicability of the proposed method, it is applied to IEEE standard 33-bus and 136-bus distribution test systems, and then the obtained results are compared with those of existing methodologies.
Azuma, K, Sun, J, Choo, Y, Rokhlenko, Y, Dwyer, JH, Schweitzer, B, Hayakawa, T, Osuji, CO & Gopalan, P 2018, 'Self-Assembly of an Ultrahigh-χ Block Copolymer with Versatile Etch Selectivity', Macromolecules, vol. 51, no. 16, pp. 6460-6467.
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We report the successful synthesis of previously inaccessible poly(3-hydroxystyrene)-block-poly(dimethylsiloxane) (P3HS-b-PDMS) block copolymers (BCPs) with varying volume fractions, molecular weights, and narrow dispersities by sequential living anionic polymerization. The chemical structure and molecular weight were fully characterized by 1H NMR and gel permeation chromatography. The BCP phase behavior was investigated using small-angle X-ray scattering (SAXS) and transmission electron microscopy. Temperature-resolved SAXS measurements from symmetric disordered sample were used to determine the interaction parameter (χ) using mean-field theory. The results provide an estimate for interaction parameter, χHS/DMS(T) = 33.491/T + 0.3126, with an upper bound value of 0.39 at 150 °C. The calculated χ for P3HS-b-PDMS is approximately 4 times higher than that observed in a commonly studied high-χ system, PS-b-PDMS. The ultrahigh interaction parameter observed here affords the formation of well-ordered materials at remarkably low molecular weight. The presence of both PDMS and P3HS provides significant versatility in terms of etch selectivity, while the hydroxystyrene domain offers additional functionality as it can be exploited for immobilizing functional organic moieties.
Ba, X, Guo, Y, Zhu, J & Zhang, C 2018, 'An Equivalent Circuit Model for Predicting the Core Loss in a Claw-Pole Permanent Magnet Motor With Soft Magnetic Composite Core', IEEE Transactions on Magnetics, vol. 54, no. 11, pp. 1-6.
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© 1965-2012 IEEE. Soft magnetic composite (SMC) materials and SMC electromagnetic devices have attracted strong research interest in the past decades. However, SMC devices have large core loss that needs to be put into consideration even at the design stage. Effective and accurate prediction of the core loss becomes crucial for the design and optimization of high-performance motors with these materials. Equivalent circuit model is a widely used method for machine analysis, due to the advantages in the fast calculation with a clear physical mechanism. This paper presents an equivalent circuit model to predict the core loss of a claw-pole permanent magnet motor with SMC stator core. All the parameters including the equivalent core-loss resistance in the equivalent circuit model are identified based on the finite-element method to achieve high accuracy, and the effectiveness of the parameters identification methods is experimentally verified. The proposed equivalent circuit model can predict the core loss and motor's performance efficiently both under no-load and loading conditions.
Baartman, JEM, Temme, AJAM & Saco, PM 2018, 'The effect of landform variation on vegetation patterning and related sediment dynamics', Earth Surface Processes and Landforms, vol. 43, no. 10, pp. 2121-2135.
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AbstractSemi‐arid ecosystems are often spatially self‐organized in typical patterns of vegetation bands with high plant cover interspersed with bare soil areas, also known as ‘tiger bush’. In modelling studies, most often, straight planar slopes were used to analyse vegetation patterning. The effect of slope steepness has been investigated widely, and some studies investigated the effects of microtopography and hillslope orientation. However, at the larger catchment scale, the overall form of the landscape may affect vegetation patterning and these more complex landscapes are much more prevalent than straight slopes. Hence, our objective was to determine the effect of landform variation on vegetation patterning and sediment dynamics. We linked two well‐established models that simulate (a) plant growth, death and dispersal of vegetation, and (b) erosion and sedimentation dynamics. The model was tested on a straight planar hillslope and then applied to (i) a set of simple synthetic topographies with varying curvature and (ii) three more complex, real‐world landscapes of distinct morphology. Results show banded vegetation patterning on all synthetic topographies, always perpendicular to the slope gradient. Interestingly, we also found that movement of bands – a debated phenomenon – seems to be dependent on curvature. Vegetation banding was simulated on the slopes of the alluvial fan and along the valley slopes of the dissected and rolling landscapes. In all landscapes, local valleys developed a full vegetation cover induced by water concentration, which is consistent with observations worldwide. Finally, banded vegetation patterns were found to reduce erosion significantly as compared to other vegetation configurations. © 2018 The Authors. Earth Surface Processes and Landforms published by John Wiley & Sons Ltd.
Baba, AA, Hashmi, RH, Esselle, KP & Weily, AR 2018, 'Improving radiation performance of extremely truncated RCAs through near‐field analysis', IET Microwaves, Antennas & Propagation, vol. 12, no. 12, pp. 1954-1959.
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Baba, AA, Hashmi, RM, Esselle, KP & Weily, AR 2018, 'Compact High-Gain Antenna With Simple All-Dielectric Partially Reflecting Surface', IEEE Transactions on Antennas and Propagation, vol. 66, no. 8, pp. 4343-4348.
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Babaee, M & Castel, A 2018, 'Chloride diffusivity, chloride threshold, and corrosion initiation in reinforced alkali-activated mortars: Role of calcium, alkali, and silicate content', Cement and Concrete Research, vol. 111, pp. 56-71.
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The aim of this study is to investigate systematically the chloride diffusivity and chloride threshold of a wide range of calcium-rich and fly ash-dominated alkali-activated samples in light of their compositional differences. To this end, the effects of various fly ash (FA)-to-slag ratios, of alkali concentrations and of silicate content in the activator were investigated. The electrochemical aspects of the passive samples were also assessed. Results show the prominent role of calcium in the matrix to reduce the chloride diffusivity. While higher alkali concentration increased the porosity and chloride diffusivities in general, lower modulus ratios provided considerably better performance in the FA-dominated samples. Chloride threshold values range between 0.19 (wt% binder mass) for calcium-rich mortars fabricated at low levels of alkalinities and 0.69 for FA-dominated mortars fabricated with highly alkaline activators. Half-cell potential and polarization resistance of alkali-activated samples were in general lower than their Portland cement counterparts.
Babaee, M & Castel, A 2018, 'Water vapor sorption isotherms, pore structure, and moisture transport characteristics of alkali-activated and Portland cement-based binders', Cement and Concrete Research, vol. 113, pp. 99-120.
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Babaee, M, Khan, MSH & Castel, A 2018, 'Passivity of embedded reinforcement in carbonated low-calcium fly ash-based geopolymer concrete', Cement and Concrete Composites, vol. 85, pp. 32-43.
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Babar, A, Bunker, D & Qumer Gill, A 2018, 'Investigating the Relationship between Business Analysts’ Competency and IS Requirements Elicitation: A Thematic-analysis Approach', Communications of the Association for Information Systems, vol. 42, no. 1, pp. 334-362.
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© 2018 by the Association for Information Systems. Researchers and practitioners have consistently reported poor requirements elicitation (RE) as one of the major reasons for information system (IS) project failures. In the last two decades, RE research and practice have focused predominantly on developing tools and techniques for business analysts (BAs) to use and improve RE; however, they have paid little attention to the importance of the competency of the BAs involved in RE. We investigate the relationship between the BAs’ competency and RE through an exploratory study. We applied a thematic network analysis approach, along with a four-stage qualitative data-analysis process, to discover four business view and six system view themes and their relationships to BAs’ competency. Our results indicate that senior, intermediate, and junior BAs performed similarly in selecting stakeholders’ viewpoints and collecting requirements from them; however, senior BAs focused more on high-level requirements than the low-level technical requirements of the system. The results suggest that BAs’ competency play a significant role in RE and that organizations that clearly define BAs’ competency can help them to identify the right BA for the right job.
Babbush, R, Berry, DW, Sanders, YR, Kivlichan, ID, Scherer, A, Wei, AY, Love, PJ & Aspuru-Guzik, A 2018, 'Exponentially more precise quantum simulation of fermions in the configuration interaction representation', Quantum Science and Technology, vol. 3, no. 1, pp. 015006-015006.
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We present a quantum algorithm for the simulation of molecular systems that is asymptotically more efficient than all previous algorithms in the literature in terms of the main problem parameters. As in Babbush et al (2016 New Journal of Physics 18, 033032), we employ a recently developed technique for simulating Hamiltonian evolution using a truncated Taylor series to obtain logarithmic scaling with the inverse of the desired precision. The algorithm of this paper involves simulation under an oracle for the sparse, first-quantized representation of the molecular Hamiltonian known as the configuration interaction (CI) matrix. We construct and query the CI matrix oracle to allow for on-the-fly computation of molecular integrals in a way that is exponentially more efficient than classical numerical methods. Whereas second-quantized representations of the wavefunction require qubits, where N is the number of single-particle spin-orbitals, the CI matrix representation requires qubits, where is the number of electrons in the molecule of interest. We show that the gate count of our algorithm scales at most as .
Bach, Q-V, Le, VT, Yoon, YS, Bui, XT, Chung, W, Chang, SW, Ngo, HH, Guo, W & Nguyen, DD 2018, 'A new hybrid sewage treatment system combining a rolled pipe system and membrane bioreactor to improve the biological nitrogen removal efficiency: A pilot study', Journal of Cleaner Production, vol. 178, pp. 937-946.
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© 2018 Elsevier Ltd A new hybrid pilot plant configuration based on a modularized rolled pipe system (RPS) combined with a submerged flat sheet membrane bioreactor (MBR) was investigated to enhance the sewage treatment and membrane performance. The system was operated under actual conditions for more than four months, that is, at a constant flow rate of 30 m³/d and with two internal recycling ratios. The results indicate that the hybrid system produces an excellent effluent quality and considerably mitigated membrane fouling. The average concentrations of SS, COD, TN, NH4+-N, NO3−-N, and PO43--P remained below 2.81, 8.29, 8.77, 0.15, 8.17, and 1.49 mg/L, respectively. It was estimated that the periodic chemical cleaning of the membrane could be extended to approximately six months. The MBR and RPS can virtually complete nitrification and denitrification, respectively. The highest average denitrification rate of the RPS is 116.95 mg NO3-N/(g MLVSS d), with a hydraulic retention time of 1.05 h. Therefore, the RPS–MBR hybrid system has potential to improve the sewage treatability. The emerging RPS technique can obtain high rates of denitrification coupled with a compact design, ease of installation, and small footprint.
Bah, AO, Qin, P-Y, Ziolkowski, RW, Cheng, Q & Guo, YJ 2018, 'Realization of an Ultra-thin Metasurface to Facilitate Wide Bandwidth, Wide Angle Beam Scanning', Scientific Reports, vol. 8, no. 1.
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AbstractA wide bandwidth, ultra-thin, metasurface is reported that facilitates wide angle beam scanning. Each unit cell of the metasurface contains a multi-resonant, strongly-coupled unequal arm Jerusalem cross element. This element consists of two bent-arm, orthogonal, capacitively loaded strips. The wide bandwidth of the metasurface is achieved by taking advantage of the strong coupling within and between its multi-resonant elements. A prototype of the proposed metasurface has been fabricated and measured. The design concept has been validated by the measured results. The proposed metasurface is able to alleviate the well-known problem of impedance mismatch caused by mutual coupling when the main beam of an array is scanned. In order to validate the wideband and wide scanning ability of the proposed metasurface, it is integrated with a wideband antenna array as a wide angle impedance matching element. The metasurface-array combination facilitates wide angle scanning over a 6:1 impedance bandwidth without the need for bulky dielectrics or multi-layered structures.
Bai, F, Vidal-Calleja, T & Huang, S 2018, 'Robust Incremental SLAM Under Constrained Optimization Formulation', IEEE Robotics and Automation Letters, vol. 3, no. 2, pp. 1207-1214.
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© 2016 IEEE. In this letter, we propose a constrained optimization formulation and a robust incremental framework for the simultaneous localization and mapping problem (SLAM). The new SLAM formulation is derived from the nonlinear least squares (NLS) formulation by mathematically formulating loop-closure cycles as constraints. Under the constrained SLAM formulation, we study the robustness of an incremental SLAM algorithm against local minima and outliers as a constraint/loop-closure cycle selection problem. We find a constraint metric that can predict the objective function growth after including the constraint. By the virtue of the constraint metric, we select constraints into the incremental SLAM according to a least objective function growth principle to increase robustness against local minima and perform χ 2 difference test on the constraint metric to increase robustness against outliers. Finally, using sequential quadratic programming (SQP) as the solver, an incremental SLAM algorithm (iSQP) is proposed. Experimental validations are provided to illustrate the accuracy of the constraint metric and the robustness of the proposed incremental SLAM algorithm. Nonetheless, the proposed approach is currently confined to datasets with sparse loop-closures due to its computational cost.
Bai, L, Wang, J, Ma, X & Lu, H 2018, 'Air Pollution Forecasts: An Overview', International Journal of Environmental Research and Public Health, vol. 15, no. 4, pp. 780-780.
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Air pollution is defined as a phenomenon harmful to the ecological system and the normal conditions of human existence and development when some substances in the atmosphere exceed a certain concentration. In the face of increasingly serious environmental pollution problems, scholars have conducted a significant quantity of related research, and in those studies, the forecasting of air pollution has been of paramount importance. As a precaution, the air pollution forecast is the basis for taking effective pollution control measures, and accurate forecasting of air pollution has become an important task. Extensive research indicates that the methods of air pollution forecasting can be broadly divided into three classical categories: statistical forecasting methods, artificial intelligence methods, and numerical forecasting methods. More recently, some hybrid models have been proposed, which can improve the forecast accuracy. To provide a clear perspective on air pollution forecasting, this study reviews the theory and application of those forecasting models. In addition, based on a comparison of different forecasting methods, the advantages and disadvantages of some methods of forecasting are also provided. This study aims to provide an overview of air pollution forecasting methods for easy access and reference by researchers, which will be helpful in further studies.
Baidya, R, Aguilera, RP, Acuna, P, Vazquez, S & Mouton, HDT 2018, 'Multistep Model Predictive Control for Cascaded H-Bridge Inverters: Formulation and Analysis', IEEE Transactions on Power Electronics, vol. 33, no. 1, pp. 876-886.
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© 1986-2012 IEEE. In this paper, a suitable long prediction horizon (multistep) model predictive control (MPC) formulation for cascaded H-bridge inverters is proposed. The MPC is formulated to include the full steady-state system information in terms of output current and output voltage references. Generally, basic single-step predictive controllers only track the current references. As a distinctive feature, the proposed MPC also tracks the control input references, which in this case is designed to minimize the common-mode voltage (CMV). This allows the controller to address both output current and CMV targets in a single optimization. To reduce the computational effort introduced by a long prediction horizon implementation, the proposed MPC formulation is transformed into an equivalent optimization problem that can be solved by a fast sphere decoding algorithm. Moreover, the benefits of including the control input references in the proposed formulation are analyzed based on this equivalent optimization problem. This analysis is key to understand how the proposed MPC formulation can handle both control targets. Experimental results show that the proposal provides an improved steady-state performance in terms of current distortion, inverter voltages symmetry, and CMV.
Baier-Fuentes, H, Cascón-Katchadourian, J, Sánchez, ÁM, Herrera-Viedma, E & Merigó, J 2018, 'A Bibliometric Overview of the International Journal of Interactive Multimedia and Artificial Intelligence', International Journal of Interactive Multimedia and Artificial Intelligence, vol. 5, no. 3, pp. 9-9.
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Bajan, S, Johnston, M & Hutvagner, G 2018, 'Destabilisation of Argonaute 2 generates a truncated protein: halfAgo2', Matters.
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The Argonaute 2 (Ago2) protein is an essential effector protein in miRNA-mediated
mechanisms that regulate gene expression. Ago2 directly binds to the miRNA, forming
the RISC. RISC function is critical to controlling key biological processes and when
dysregulated can result in disease pathogenesis. Understanding Ago2 protein stability
and turnover will further our understanding in how RISC function is regulated. In human
cells, we discovered a previously unidentified ~55 kDa protein that is a truncated
form of Ago2, that is formed from proteolytic cleavage of the full length Ago2 protein.
Further experiments are needed to determine (i) the detailed mechanism that forms
halfAgo2 (ii) the cellular or environmental triggers or stresses that initiate halfAgo2
production and (iii) if halfAgo2 has a potentially new role in gene regulation.
Balathanigaimani, MS, Haider, MB, Jha, D, Kumar, R, Lee, SJ, Shim, WG, Shon, HK, Kim, SC & Moon, H 2018, 'Nanostructured Biomass Based Carbon Materials from Beer Lees for Hydrogen Storage', Journal of Nanoscience and Nanotechnology, vol. 18, no. 3, pp. 2196-2199.
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The present work describes the preparation of carbon materials from beer lees and their hydrogen adsorption abilities. Activated carbons (ACs) from beer lees were prepared through chemical activation using potassium hydroxide as an activating agent. The low temperature nitrogen adsorption isotherm studies on prepared ACs were conducted at 77 K to determine their physical properties and adsorption energy distribution. The beer lees based carbons have energetically heterogeneous surfaces and high surface area ranging from 1927–2408 m2/g. ACs prepared in this study show the gravimetric hydrogen adsorption capacity of 2.43–2.92 wt% depending on their physical properties
Bano, M, Zowghi, D & Rimini, FD 2018, 'User Involvement in Software Development: The Good, the Bad, and the Ugly.', IEEE Softw., vol. 35, no. 6, pp. 8-11.
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© 2018 IEEE. Merely involving the users in software development won't guarantee system success. User involvement is a complex, multifaceted phenomenon with a good side, a bad side, and an ugly side. A better, deeper understanding of those sides can help project managers develop responsive strategies for increasing user involvement's effectiveness.
Bano, M, Zowghi, D, Kearney, M, Schuck, S & Aubusson, P 2018, 'Mobile learning for science and mathematics school education: A systematic review of empirical evidence.', Comput. Educ., vol. 121, pp. 30-58.
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© 2018 Elsevier Ltd The ubiquity, flexibility, ease of access and diverse capabilities of mobile technologies make them valuable and a necessity in current times. However, they are under-utilized assets in mathematics and science school education. This article analyses the high quality empirical evidence on mobile learning in secondary school science and mathematics education. Our study employed a Systematic Literature Review (SLR) using well-accepted and robust guidelines. The SLR resulted in the detailed analysis of 49 studies (60 papers) published during 2003–2016. Content and thematic analyses were used to ascertain pedagogical approaches, methodological designs, foci, and intended and achieved outcomes of the studies. The apps and technologies used in these studies were further classified for domain, type and context of use. The review has highlighted gaps in existing literature on the topic and has provided insights that have implications for future research.
Baral, P, Rujikiatkamjorn, C, Indraratna, B & Kelly, R 2018, 'Radial consolidation characteristics of soft undisturbed clay based on large specimens', Journal of Rock Mechanics and Geotechnical Engineering, vol. 10, no. 6, pp. 1037-1045.
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Bargi, A, Xu, RYD & Piccardi, M 2018, 'AdOn HDP-HMM: An Adaptive Online Model for Segmentation and Classification of Sequential Data', IEEE Transactions on Neural Networks and Learning Systems, vol. 29, no. 9, pp. 3953-3968.
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© 2012 IEEE. Recent years have witnessed an increasing need for the automated classification of sequential data, such as activities of daily living, social media interactions, financial series, and others. With the continuous flow of new data, it is critical to classify the observations on-the-fly and without being limited by a predetermined number of classes. In addition, a model should be able to update its parameters in response to a possible evolution in the distributions of the classes. This compelling problem, however, does not seem to have been adequately addressed in the literature, since most studies focus on offline classification over predefined class sets. In this paper, we present a principled solution for this problem based on an adaptive online system leveraging Markov switching models and hierarchical Dirichlet process priors. This adaptive online approach is capable of classifying the sequential data over an unlimited number of classes while meeting the memory and delay constraints typical of streaming contexts. In this paper, we introduce an adaptive 'learning rate' that is responsible for balancing the extent to which the model retains its previous parameters or adapts to new observations. Experimental results on stationary and evolving synthetic data and two video data sets, TUM Assistive Kitchen and collated Weizmann, show a remarkable performance in terms of segmentation and classification, particularly for sequences from evolutionary distributions and/or those containing previously unseen classes.
Barker, RA, Eager, D & Sharwood, LN 2018, 'Ensuring safety in public playgrounds is everybody's business.', Med J Aust, vol. 210, no. 1, pp. 9-11.
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When an injury occurs in a children’s playground, who is responsible? Media headlines1,2 have highlighted risks associated with a recently opened playground in north-western Sydney. The playground’s giant tube slide was closed following a spate of injuries to both adult and child patrons. With injuries described as “horrific”, the media questioned “how the 30 m long, 14 m tall slide passed safety rules”.1 While playground injuries are fairly common,3 there are specific multilevel responsibilities required to balance the importance of play and physical activity with mitigation of injury risk. In this article, we review the role of standards in industry governance and injury prevention.
Basack, S & Nimbalkar, S 2018, 'Measured and Predicted Response of Pile Groups in Soft Clay Subjected to Cyclic Lateral Loading', International Journal of Geomechanics, vol. 18, no. 7, pp. 04018073-04018073.
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© 2018 American Society of Civil Engineers. Major offshore and onshore structures, including transport corridors and high-rise buildings, resting on soft compressible clays are often supported by pile foundations. Apart from the usual vertical loading from the superstructures, these piles are usually subjected to large cyclic loads arising from the actions of waves, ship impacts, or moving vehicles. Under such circumstances, vertical and lateral modes of cyclic loading are predominant and affect overall stability. Such repetitive loading on piles leads to reversal of axial stresses in the adjacent soft clay, initiating progressive degradation in soil strength and stiffness that deteriorates the pile capacity with unacceptable displacements. Although several studies have been carried out to investigate the response of a single pile, a detailed investigation on a pile group in soft soil subjected to cyclic lateral loading, which is of immense practical interest to field engineers, had yet to be conducted. In this paper, extensive laboratory model tests with steel-pipe-pile groups in soft cohesive soil were conducted followed by the development of a numerical model that was based on a two-dimensional (2D) dynamic finite-element (FE) approach. The degradation of both axial and lateral capacities of the pile group and the pattern of the degradation with variations in the cyclic-loading parameters were studied. Comparisons of the experimental data with the computed results validated the numerical analysis. The study indicates that both the axial and lateral pile capacities and displacements were significantly influenced by the cyclic-loading parameters (number of cycles, frequency, and amplitude). Relevant design recommendations are presented.
Basack, S, Indraratna, B & Rujikiatkamjorn, C 2018, 'Effectiveness of stone column reinforcement for stabilizing soft ground with reference to transport infrastructure', Geotechnical Engineering, vol. 49, no. 1, pp. 8-14.
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The use of stone columns for soft soil stabilization has numerous advantages compared to other methods. There are many factors controlling performance of stone columns including column geometry and particle morphology. The reinforced soft ground supporting transport infrastructure like the railways and highways is subjected to cyclic loading, usually initiating a partially drained condition. The study reveals that the stone columns are more effective in mitigating the built up of cyclic excess pore water pressure compared to conventional vertical drains. This paper presents a brief overview on the rigorous theoretical and experimental studies carried out by the Authors to investigate the effectiveness of stone column reinforcement for stabilizing soft ground with particular reference to transport infrastructure.
Basack, S, Indraratna, B, Rujikiatkamjorn, C & Siahaan, F 2018, 'Closure to “Modeling the Stone Column Behavior in Soft Ground with Special Emphasis on Lateral Deformation” by Sudip Basack, Buddhima Indraratna, Cholachat Rujikiatkamjorn, and Firman Siahaan', Journal of Geotechnical and Geoenvironmental Engineering, vol. 144, no. 5, pp. 07018008-07018008.
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Basack, S, Siahaan, F, Indraratna, B & Rujikiatkamjorn, C 2018, 'Stone Column–Stabilized Soft-Soil Performance Influenced by Clogging and Lateral Deformation: Laboratory and Numerical Evaluation', International Journal of Geomechanics, vol. 18, no. 6, pp. 04018058-04018058.
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Bayuaji, R, Sigit Darmawan, M, Husin, NA, Anugraha, RB, Budipriyanto, A & Stewart, MG 2018, 'Corrosion damage assessment of a reinforced concrete canal structure of power plant after 20 years of exposure in a marine environment: A case study', Engineering Failure Analysis, vol. 84, pp. 287-299.
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Chloride attack is the primary cause of corrosion problem of concrete structures operate in marine environment. Therefore, concrete structures operate in such environment cannot escape from this corrosion related problem. This paper describes assessment of a reinforced concrete canal structure of power plant after 20 years of exposure in a marine environment. The work covers visual inspection of the structure, on-site and laboratory tests of the structure, analyses the current structural strength based on the tests, and proposing repair and/or strengthening for weak elements. Strength prediction is carried out using average and worst case scenarios. The strength calculations assuming average case scenario shows that by 2025 all the canal have no strength reduction due to corrosion. Calculation using the worst case scenario shows that all the canal by 2025 still comply with the limits specified in Indonesian Concrete Code, even though their strength has been reduced due to corrosion of the reinforcement.
Bazaz, SR, Mehrizi, AA, Ghorbani, S, Vasilescu, S, Asadnia, M & Warkiani, ME 2018, 'A hybrid micromixer with planar mixing units', RSC Advances, vol. 8, no. 58, pp. 33103-33120.
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Taguchi-optimized “hybrid micromixer” has been proposed which can be utilized in a wide range of chemical and biological applications.
Beck, D, Thoms, JAI, Palu, C, Herold, T, Shah, A, Olivier, J, Boelen, L, Huang, Y, Chacon, D, Brown, A, Babic, M, Hahn, C, Perugini, M, Zhou, X, Huntly, BJ, Schwarzer, A, Klusmann, J-H, Berdel, WE, Wörmann, B, Büchner, T, Hiddemann, W, Bohlander, SK, To, LB, Scott, HS, Lewis, ID, D'Andrea, RJ, Wong, JWH & Pimanda, JE 2018, 'A four-gene LincRNA expression signature predicts risk in multiple cohorts of acute myeloid leukemia patients', Leukemia, vol. 32, no. 2, pp. 263-272.
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© 2018 Macmillan Publishers Limited, part of Springer Nature. All rights reserved. Prognostic gene expression signatures have been proposed as clinical tools to clarify therapeutic options in acute myeloid leukemia (AML). However, these signatures rely on measuring large numbers of genes and often perform poorly when applied to independent cohorts or those with older patients. Long intergenic non-coding RNAs (lincRNAs) are emerging as important regulators of cell identity and oncogenesis, but knowledge of their utility as prognostic markers in AML is limited. Here we analyze transcriptomic data from multiple cohorts of clinically annotated AML patients and report that (i) microarrays designed for coding gene expression can be repurposed to yield robust lincRNA expression data, (ii) some lincRNA genes are located in close proximity to hematopoietic coding genes and show strong expression correlations in AML, (iii) lincRNA gene expression patterns distinguish cytogenetic and molecular subtypes of AML, (iv) lincRNA signatures composed of three or four genes are independent predictors of clinical outcome and further dichotomize survival in European Leukemia Net (ELN) risk groups and (v) an analytical tool based on logistic regression analysis of quantitative PCR measurement of four lincRNA genes (LINC4) can be used to determine risk in AML.
Beiranvand Pour, A, Park, T-YS, Park, Y, Hong, JK, Zoheir, B, Pradhan, B, Ayoobi, I & Hashim, M 2018, 'Application of Multi-Sensor Satellite Data for Exploration of Zn–Pb Sulfide Mineralization in the Franklinian Basin, North Greenland', Remote Sensing, vol. 10, no. 8, pp. 1186-1186.
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Geological mapping and mineral exploration programs in the High Arctic have been naturally hindered by its remoteness and hostile climate conditions. The Franklinian Basin in North Greenland has a unique potential for exploration of world-class zinc deposits. In this research, multi-sensor remote sensing satellite data (e.g., Landsat-8, Phased Array L-band Synthetic Aperture Radar (PALSAR) and Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER)) were used for exploring zinc in the trough sequences and shelf-platform carbonate of the Franklinian Basin. A series of robust image processing algorithms was implemented for detecting spatial distribution of pixels/sub-pixels related to key alteration mineral assemblages and structural features that may represent potential undiscovered Zn–Pb deposits. Fusion of Directed Principal Component Analysis (DPCA) and Independent Component Analysis (ICA) was applied to some selected Landsat-8 mineral indices for mapping gossan, clay-rich zones and dolomitization. Major lineaments, intersections, curvilinear structures and sedimentary formations were traced by the application of Feature-oriented Principal Components Selection (FPCS) to cross-polarized backscatter PALSAR ratio images. Mixture Tuned Matched Filtering (MTMF) algorithm was applied to ASTER VNIR/SWIR bands for sub-pixel detection and classification of hematite, goethite, jarosite, alunite, gypsum, chalcedony, kaolinite, muscovite, chlorite, epidote, calcite and dolomite in the prospective targets. Using the remote sensing data and approaches, several high potential zones characterized by distinct alteration mineral assemblages and structural fabrics were identified that could represent undiscovered Zn–Pb sulfide deposits in the study area. This research establishes a straightforward/cost-effective multi-sensor satellite-based remote sensing approach for reconnaissance stages of mineral exploration in hardly accessible parts of the H...
Belhaj, D, Athmouni, K, Ahmed, MB, Aoiadni, N, El Feki, A, Zhou, JL & Ayadi, H 2018, 'Polysaccharides from Phormidium versicolor (NCC466) protecting HepG2 human hepatocellular carcinoma cells and rat liver tissues from cadmium toxicity: Evidence from in vitro and in vivo tests', International Journal of Biological Macromolecules, vol. 113, pp. 813-820.
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© 2018 Elsevier B.V. The in vitro antioxidant, cytotoxic and cytoprotective properties and in vivo hepatoprotective activities of crude polysaccharides extracted from cyanobacteria Phormidim versicolor NCC466 (CFv-PS) were investigated. The CFv-PS, identified as heteropolysaccharides with molecular weight of 63.79 kDa, exhibited relatively strong antioxidant activity, in a concentration-depended manner, in vitro assays. Additionally, CFv-PS did not induce cytotoxic effect on HepG2 human hepatocellular carcinoma cells within the range of tested concentrations (25–150 μg·mL−1) while preventing them against Cd. Moreover, in rats subjected to Cd-induced hepatotoxicity, CFv-PS pretreatment significantly (P < 0.05) reduced the level of ALAT, ASAT, biliburin, MDA, protein carbonyl and DNA damage, and markedly increased enzyme activities in liver tissues. These findings suggest that the cyanobacteria Phormidium versicolor is a potential source of natural products possessing antioxidant, cytoprotective and hepatoprotective properties.
Bellezoni, RA, Sharma, D, Villela, AA & Pereira Junior, AO 2018, 'Water-energy-food nexus of sugarcane ethanol production in the state of Goiás, Brazil: An analysis with regional input-output matrix', Biomass and Bioenergy, vol. 115, pp. 108-119.
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© 2018 Elsevier Ltd Concerns about impacts of biomass growth for biofuel production emphasize the importance of planning energy crops expansion considering land, water, food and biodiversity. Brazil is the second largest ethanol producer worldwide and sugarcane is cultivated in many regions, including the Brazilian Cerrado (a Savannah-type biome). This paper analyses the impacts of first-generation sugarcane expansion in the Paranaíba basin (Goiás State), focusing on how future demand for ethanol could affect local resources availability. The study area is a sugarcane expansion frontier in Brazil, thus, the Cerrado biome should be focus of research considering competition for land and water uses. An economic-ecologic Input-Output (IO) framework was applied to develop a water-energy-food (WEF) nexus analysis. The Goiás’ IO table was expanded to assess water, energy and land uses, GHG emissions and employment levels through six different ethanol supply scenarios. Results show that if sugarcane expansion projected to 2030 considers the Goiás’ extended IO structure for the year 2008, it should cause little impact on land and water availability in the state, due to both the ample availability of suitable pasturelands for sugarcane expansion as well as water in most of the Paranaíba basin. The WEF nexus analysis is a valuable tool on guiding the sustainable management of natural resources considering water, energy, land use and GHG emissions as goals to the same policy. In particular, the hybrid extended IO-WEF nexus framework is useful to design effective biofuel policies, collectively addressing impacts on environmental, social and economic spheres, in a local or broader context.
Bengua, JA, Tuan, HD, Duong, TQ & Poor, HV 2018, 'Joint Sensor and Relay Power Control in Tracking Gaussian Mixture Targets by Wireless Sensor Networks', IEEE Transactions on Signal Processing, vol. 66, no. 2, pp. 492-506.
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© 2017 IEEE. This paper considers a wireless sensor network for locating a static target or tracking a dynamic target, which is characterized a priori by a Gaussian mixture distribution. An amplify- and-forward relay node acts as a wireless bridge in relaying the sensor’s independent observations of the target to a fusion center (FC). Joint power allocation is considered for the sensors and relay to optimize a Bayesian filter, which is deployed at the FC for a global estimate of the target. The mean squared error of the Bayesian filter is already computationally intractable for fixed sensor and relay transmitter power, so power allocation to minimize its mean squared error is a very challenging problem. In this paper, the problem is addressed by an iterative procedure of very low computational complexity. Simulations are provided to support the efficiency of our proposed power allocation.
Berry, DW, Kieferová, M, Scherer, A, Sanders, YR, Low, GH, Wiebe, N, Gidney, C & Babbush, R 2018, 'Improved techniques for preparing eigenstates of fermionic Hamiltonians', npj Quantum Information, vol. 4, no. 1.
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AbstractModeling low energy eigenstates of fermionic systems can provide insight into chemical reactions and material properties and is one of the most anticipated applications of quantum computing. We present three techniques for reducing the cost of preparing fermionic Hamiltonian eigenstates using phase estimation. First, we report a polylogarithmic-depth quantum algorithm for antisymmetrizing the initial states required for simulation of fermions in first quantization. This is an exponential improvement over the previous state-of-the-art. Next, we show how to reduce the overhead due to repeated state preparation in phase estimation when the goal is to prepare the ground state to high precision and one has knowledge of an upper bound on the ground state energy that is less than the excited state energy (often the case in quantum chemistry). Finally, we explain how one can perform the time evolution necessary for the phase estimation based preparation of Hamiltonian eigenstates with exactly zero error by using the recently introduced qubitization procedure.
Besa, C, Wagner, M, Lo, G, Gordic, S, Chatterji, M, Kennedy, P, Stueck, A, Thung, S, Babb, J, Smith, A & Taouli, B 2018, 'Detection of liver fibrosis using qualitative and quantitative MR elastography compared to liver surface nodularity measurement, gadoxetic acid uptake, and serum markers', Journal of Magnetic Resonance Imaging, vol. 47, no. 6, pp. 1552-1561.
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BackgroundMultiparametric magnetic resonance imaging (mpMRI) combining different techniques such as MR elastography (MRE) has emerged as a noninvasive approach to diagnose and stage liver fibrosis with high accuracy allowing for anatomical and functional information.PurposeTo assess the diagnostic performance of mpMRI including qualitative and quantitative assessment of MRE, liver surface nodularity (LSN) measurement, hepatic enhancement ratios postgadoxetic acid, and serum markers (APRI, FIB‐4) for the detection of liver fibrosis.Study TypeIRB‐approved retrospective.SubjectsEighty‐three adult patients.Field Strength/Sequence1.5T and 3.0T MR systems. MRE and T1‐weighted postgadoxetic acid sequences.AssessmentTwo independent observers analyzed qualitative color‐coded MRE maps on a scale of 0–3. Regions of interest were drawn to measure liver stiffness on MRE stiffness maps and on pre‐ and postcontrast T1‐weighted images to measure hepatic enhancement ratios. Software was used to generate LSN measurements. Histopathology was used as the reference standard for diagnosis of liver fibrosis in all patients.Statistical TestsA multivariable logistic analysis was performed to identify independent predictors of liver fibrosis. Receiver operating characteristic (ROC) analysis evaluated the performance of each imaging technique for detection of fibrosis, in comparison with serum markers.ResultsLiver stiffness measured with MRE provided the strongest...
Best, G, Faigl, J & Fitch, R 2018, 'Online planning for multi-robot active perception with self-organising maps', Autonomous Robots, vol. 42, no. 4, pp. 715-738.
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© 2017, Springer Science+Business Media, LLC, part of Springer Nature. We propose a self-organising map (SOM) algorithm as a solution to a new multi-goal path planning problem for active perception and data collection tasks. We optimise paths for a multi-robot team that aims to maximally observe a set of nodes in the environment. The selected nodes are observed by visiting associated viewpoint regions defined by a sensor model. The key problem characteristics are that the viewpoint regions are overlapping polygonal continuous regions, each node has an observation reward, and the robots are constrained by travel budgets. The SOM algorithm jointly selects and allocates nodes to the robots and finds favourable sequences of sensing locations. The algorithm has a runtime complexity that is polynomial in the number of nodes to be observed and the magnitude of the relative weighting of rewards. We show empirically the runtime is sublinear in the number of robots. We demonstrate feasibility for the active perception task of observing a set of 3D objects. The viewpoint regions consider sensing ranges and self-occlusions, and the rewards are measured as discriminability in the ensemble of shape functions feature space. Exploration objectives for online tasks where the environment is only partially known in advance are modelled by introducing goal regions in unexplored space. Online replanning is performed efficiently by adapting previous solutions as new information becomes available. Simulations were performed using a 3D point-cloud dataset from a real robot in a large outdoor environment. Our results show the proposed methods enable multi-robot planning for online active perception tasks with continuous sets of candidate viewpoints and long planning horizons.
Beydoun, G, Dascalu, S, Dominey-Howes, D & Sheehan, A 2018, 'Disaster Management and Information Systems: Insights to Emerging Challenges.', Inf. Syst. Frontiers, vol. 20, no. 4, pp. 649-652.
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BEZDEK, J, KELLER, J, PAL, N, LIN, C-T & GARIBALDI, J 2018, 'Editorial Celebrating 25 Years of the IEEE Transactions on Fuzzy Systems', IEEE Transactions on Fuzzy Systems, vol. 26, no. 1, pp. 1-5.
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Bhowmick, S, Xu, F, Zhang, X & Saha, SC 2018, 'Natural convection and heat transfer in a valley shaped cavity filled with initially stratified water', International Journal of Thermal Sciences, vol. 128, pp. 59-69.
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© 2018 Elsevier Masson SAS Fog is omnipresent in the natural environment, namely valleys and mountains. A strong comprehension of the fluid flow dynamics pertaining to fog formation is of crucial importance. In the present study, the two-dimensional numerical method is used to investigate the transient natural convection in a valley-shaped triangular cavity initially filled with stratified water. A wide range of Rayleigh numbers (2.26 × 105–2.26 × 109) and aspect ratios (0.1–1.0) are considered. The numerical results are verified against experimental results. The development of natural convection flows in the cavity from the start up to the steady state is classified into two stages: an early stage and a transitional stage. Transient natural convection flows in the cavity are described. Spectral analysis is performed for different governing parameters. A simple scaling analysis is performed for the thermal boundary layer and the time scale of the stratification breakup describing the disappearance of fog in the valley is obtained and validated by numerical results. Additionally, mass and heat transfer in the cavity is measured and the scaling relation between the Nusselt number and the Rayleigh number for different aspect ratios are presented.
Bian, X, Jin, W, Gu, Q, Zhou, X, Xi, Y, Tu, R, Han, S-F, Xie, G-J, Gao, S-H & Wang, Q 2018, 'Subcritical n-hexane/isopropanol extraction of lipid from wet microalgal pastes of Scenedesmus obliquus', World Journal of Microbiology and Biotechnology, vol. 34, no. 3, pp. 39-39.
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© 2018, Springer Science+Business Media B.V., part of Springer Nature. Abstract: Subcritical co-solvents of n-hexane/isopropanol were primarily utilized to extract lipid from wet microalgal pastes of Scenedesmus obliquus. The effects of key operational parameters were investigated, and the optimal parameters were obtained: solvent ratio of n-hexane to isopropanol was 3:2 (V:V), phase ratio of co-solvents to microalgal biomass was 35:1 (mL:g), reactor stirring speed was 900 rpm, extraction time was 60 min. Additional pretreatment with acid, ultrasonic and microwave as well as enhanced subcritical pressure/heating treatments were also applied to further study their effects on lipid extraction. The results showed that the lipid recovery rate with acid pretreatment was 8.6 and 6.2% higher than ultrasonic and microwave pretreatment; the optimum enhanced subcritical condition was 55 °C with atmospheric pressure. Under optimal operating conditions, the lipid and FAME yield were 13.5 and 7.2%, which was 82.6 and 135.1% higher than the traditional method. The results indicated that the subcritical n-hexane/isopropanol extraction process had promising application potential. Graphical Abstract: [Figure not available: see fulltext.].
Bickel, B, Cignoni, P, Malomo, L & Pietroni, N 2018, 'State of the Art on Stylized Fabrication.', Comput. Graph. Forum, vol. 37, pp. 325-342.
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Bjarnadottir, S, Li, Y, Reynisson, O & Stewart, MG 2018, 'Reliability-based assessment of climatic adaptation for the increased resiliency of power distribution systems subjected to hurricanes', Sustainable and Resilient Infrastructure, vol. 3, no. 1, pp. 36-48.
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Power distribution systems are vulnerable to hurricanes as has been documented in recent years. Hurricane intensity or/and frequency may change as a result of increased CO2 emissions. This paper proposes six climatic adaptation strategies for timber distribution poles that may aid in mitigating the hurricane damage costs that may be expected to increase because of global climate change. The effectiveness of adaptation is assessed through a life-cycle cost analysis, which includes direct cost (e.g. cost of pole replacement, maintenance, and adaptation) and indirect cost (e.g. cost of power outage to customers). The viability of the adaptation strategies is examined considering three CO2 emission scenarios. Furthermore, the scenario of no climate change is considered in this paper to show the applicability the proposed framework for hurricane risk mitigation under current conditions (i.e. wind speeds remain stationary). This paper finds that certain adaptation measures can effectively reduce costs, resulting in more resilient power distribution systems.
Błachnio, A, Przepiórka, A, Wołońciej, M, Bassam Mahmoud, A, Holdoš, J & Yafi, E 2018, 'Loneliness, Friendship, and Facebook Intrusion. A Study in Poland, Slovakia, Syria, Malaysia, and Ecuador', Studia Psychologica, vol. 60, no. 3, pp. 183-194.
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Blanco-Mesa, F, Gil-Lafuente, AM & Merigo, JM 2018, 'Dynamics of stakeholder relations with multi-person aggregation', Kybernetes, vol. 47, no. 9, pp. 1801-1820.
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PurposeThe purpose of this paper is to develop a novel method to analyse dynamic interactions of stakeholders to explain how a set of agents can act by considering the power/influence positions.Design/methodology/approachA novel mathematical application uses the importance of characteristics algorithm in combination with composition max-min to compare, group and order information according to the importance of its characteristics. The mathematical application is focused on a strategic analysis, evaluating stakeholder dynamics through power relationships.FindingsThe results show a comparison of the relationships among each of the stakeholders to obtain the relative intensity and importance of relationships between them, given by the fuzzy matrix FRInM and the fuzzy matrix FRIM, respectively. This application provides a useful tool for a dynamic analysis of stakeholders in a complex environment, where the best approach to performing a strategic analysis process is sought.Research limitations/implicationsThe main implication of the proposed approach is taking into account the importance of information to establish the boundaries and relationships of each characteristic according to its intensity. However, limitations are due to the nature of this research, based on theoretical assumptions regarding stakeholders and the use of a hypothetical example to show the operation of algorithms.Originality/valueThe primary advantage of this proposition is that it takes into account the im...
BLANCO-MESA, F, GIL-LAFUENTE, AM & MERIGÓ, JM 2018, 'NEW AGGREGATION OPERATORS FOR DECISION-MAKING UNDER UNCERTAINTY: AN APPLICATIONS IN SELECTION OF ENTREPRENEURIAL OPPORTUNITIES', Technological and Economic Development of Economy, vol. 24, no. 2, pp. 335-357.
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The main aim of this paper is to study how economic environment and logic reasoning guidance the decision-making process to start-up a new business by potential entrepreneurs. The study proposes a new method using the family of selection indices with OWA operator, which allows aggregating information according to the level of importance and their level of objectivity and subjectivity in the same formulation within the decision-making process. To develop case study, we have taken into account some industries of the sports sector and some critical environmental factors that influence the competitiveness and entrepreneurship in Colombia to start a new business. The results show in an orderly way all information aggregated, which can help potential investors and entrepreneurs to make a decision based on their preferences. Finally, the applicability of this method in real case can be given in aggregation different sources of information to help at dealing decision-making processes.
Blanco-Mesa, F, Gil-Lafuente, AM & Merigó, JM 2018, 'Subjective stakeholder dynamics relationships treatment: a methodological approach using fuzzy decision-making', Computational and Mathematical Organization Theory, vol. 24, no. 4, pp. 441-472.
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© 2018, Springer Science+Business Media, LLC, part of Springer Nature. Since the stakeholder theory was proposed to explain the interaction among its agents, extensive approaches have been developed. However, the literature continues to suggest the development of new methodologies that allow an analysis of the dynamics and uncertainty of the relationships between each agent. In this sense, this research proposes a novel methodology for the treatment of subjective stakeholder dynamics using fuzzy decision-making. The study proposes a mathematical methodological perspective for the treatment of subjective relationships among stakeholders, which allows a predictive simulation tool to be developed for attitude and personal preferences to analyze the links among all stakeholders. A mathematical application is developed to help the decision-making process in uncertainty concerning the ordering-according-to-their-importance and linking-of-relation algorithms, which are based on notions of relation, gathering and ordering. A numerical example is proposed to understand the method’s usefulness and feasibility. The results approximate how stakeholder ambiguity and fuzziness can be managed considering the decision-maker’s preference subjectivity. In addition, these results highlight the different relationships among each stakeholder, their intensity levels, the incidence linkage loops and the incidence relative on stakeholder behaviors. The main implication of this proposition is to deal with the subjective preferences provide by decision-maker to better interpret environmental and subjective factors. Furthermore, this study contributes to the strategic planning and decision-making processes for operative units within uncertain environment in the short term.
Blanco-Mesa, F, León-Castro, E & Merigó, JM 2018, 'Bonferroni induced heavy operators in ERM decision-making: A case on large companies in Colombia', Applied Soft Computing, vol. 72, pp. 371-391.
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© 2018 Elsevier B.V. Averaging aggregation operators analyse a set of data providing a summary of the results. This study focuses on the Bonferroni mean and the induced and heavy aggregation operators. The aim of the work is to present new aggregation operators that combine these concepts forming the Bonferroni induced heavy ordered weighted average and several particular formulations. This approach represents Bonferroni means with order inducing variables and with weighting vectors that can be higher than one. The paper also develops some extensions by using distance measures forming the Bonferroni induced heavy ordered weighted average distance and several particular cases. The study ends with an application in a large companies risk management problem in Colombia. The main advantage of this approach is that it provides a more general framework for analysing the data in scenarios where the numerical values may have some complexities that should be assessed with complex attitudinal characters.
Bluff, A, Johnston, A & Clarkson, D 2018, 'Interaction, Narrative and Animation in Live Theatre', IEEE Computer Graphics and Applications, vol. 38, no. 2, pp. 8-14.
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© 1981-2012 IEEE. Before embarking on their most ambitious project to date, a cosmically-themed participatory theatre event with interactive 3D visuals housed inside a bespoke dome structure, the interactive artists Andrew Johnston and Andrew Bluff joined the director of Stalker Theatre, David Clarkson in a round-table discussion. They reflected on what it was like to combine physical performance with interactive graphics in a childrens theatre show and discussed how the 360° format might be used to explore the cosmos in their upcoming Big Skies production.
Boo, C, Wang, Y, Zucker, I, Choo, Y, Osuji, CO & Elimelech, M 2018, 'High Performance Nanofiltration Membrane for Effective Removal of Perfluoroalkyl Substances at High Water Recovery', Environmental Science & Technology, vol. 52, no. 13, pp. 7279-7288.
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We demonstrate the fabrication of a loose, negatively charged nanofiltration (NF) membrane with tailored selectivity for the removal of perfluoroalkyl substances with reduced scaling potential. A selective polyamide layer was fabricated on top of a poly(ether sulfone) support via interfacial polymerization of trimesoyl chloride and a mixture of piperazine and bipiperidine. Incorporating high molecular weight bipiperidine during the interfacial polymerization enables the formation of a loose, nanoporous selective layer structure. The fabricated NF membrane possessed a negative surface charge and had a pore diameter of ∼1.2 nm, much larger than a widely used commercial NF membrane (i.e., NF270 with pore diameter of ∼0.8 nm). We evaluated the performance of the fabricated NF membrane for the rejection of different salts (i.e., NaCl, CaCl2, and Na2SO4) and perfluorooctanoic acid (PFOA). The fabricated NF membrane exhibited a high retention of PFOA (∼90%) while allowing high passage of scale-forming cations (i.e., calcium). We further performed gypsum scaling experiments to demonstrate lower scaling potential of the fabricated loose porous NF membrane compared to NF membranes having a dense selective layer under solution conditions simulating high water recovery. Our results demonstrate that properly designed NF membranes are a critical component of a high recovery NF system, which provide an efficient and sustainable solution for remediation of groundwater contaminated with perfluoroalkyl substances.
Boostani, AF, Yazdani, S, Khosroshahi, RA, Jiang, ZY & Wei, D 2018, 'A novel graphene-stimulated semi-solid processing to fabricate advanced aluminium matrix nanocomposites', Materials Science and Engineering: A, vol. 736, pp. 316-322.
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© 2018 Elsevier B.V. This study reveals an unprecedented capacity of flake graphene sheets in manipulating semi-solid deformation of aluminium matrix nanocomposites by restricting the grain growth of the nanograins during the reheating process to significantly enhance (173%) the yield strength of the fabricated composites. The graphene sheets with onion shape have also shown the unique capability in alleviating the agglomeration of SiC nanoparticles, attributed to the manipulated Hamaker constant of these particles as a result of wrapping graphene sheets. A devised mathematical approach has authenticated, for the first time, the effect of wrapping graphene sheets on subtle adjusting the Hamaker constant of SiC nanoparticles to stimulate engulfment of these nanoparticles within solidifying matrix rather than agglomeration at grain boundaries. This, therefore, has resulted in diminishing the porosity and stimulating multi-scaled micro/nano grains, thereby significantly enhancing the tensile properties of the fabricated composites.
Borkert, M, Fisher, KE & Yafi, E 2018, 'The Best, the Worst, and the Hardest to Find: How People, Mobiles, and Social Media Connect Migrants In(to) Europe', Social Media + Society, vol. 4, no. 1, pp. 205630511876442-205630511876442.
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For displaced people, migrating into Europe has highly complex information needs about the journey and destination. Each new need presents problems of where to seek information, how to trust or distrust information, and financial and other costs. The outcomes of receiving poor or false information can cause bodily harm or death, loss of family, or financial ruin. We aim to make two major contributions: First, provide rich insights into digital literacy, information needs, and strategies among Syrian and Iraqi refugees who entered Europe in 2015, a topic rarely dealt with in the literature. Second, we seek to change the dominant perspective on migrants and refugees as passive victims of international events and policies by showing their capacities and skills to navigate the complex landscape of information and border regimes en route to Europe. Building on research at Za’atari refugee camp (Jordan), we surveyed 83 Arab refugees in two centers in Berlin. Analyses address refugees’ temporal information worlds, focusing on the importance and difficulty in finding specific information, how migrants identify mis- and disinformation, and the roles of information and technology mediaries. Findings illustrate the digital capacities refugees employ during and after their journey to Europe; they show social support via social media and highlight the need for a radical shift in thinking about and researching migration in the digital age.
Boroon, MP, Ayani, M-B & Bazaz, SR 2018, 'Estimation of the optimum number and location of nanoparticle injections and the specific loss power for ideal hyperthermia', Journal of Thermal Biology, vol. 72, pp. 127-136.
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Hyperthermia is one of the most appealing methods of cancer treatment in which the temperature of tumor is elevated to reach a desired temperature. One of the methods of increasing tissue temperature is injection of nanoparticle fluids to tumor and applying alternative magnetic field, which is called magnetic nanoparticle hyperthermia method. The total number of injection points, as well as the their location within a tissue play a significant role in this method. Furthermore, the power of heating of a magnetic material per gram or specific loss power (SLP) is another important factor which needs to be investigated. As the uniform temperature of 43 °C is effective enough for a tumor regression in certain specific tissues, the inverse method is applied to find out both the number of injection points and their location. Furthermore, the effective amount of heat generated by nanoparticles is investigated by this technique. Two-dimensional cancerous brain tissue was considered, zero gradients on boundary conditions were assumed, and diffusion equation and Pennes equation, which is regarded as energy equation, were solved, respectively. Conjugate gradient technique as a one way of inverse methods is applied, and unknowns are investigated. The results illustrate that three-point injection with the best injection sites cannot induce a uniform temperate distribution of 43 °C, and although four-point injection can create a uniform temperature elevation, the amount of it cannot reach the 43 °C. Finally, the optimum locations of five-point injection which are ((0.80,3.24), (0.80,0.84), (2.00,2.00), (3.20,3.24), (3.32,0.84)) (all dimensions are in mm) in the studied domain with special loss power of 420 W/g, all of which are obtained after 36 iterations, demonstrate that these conditions can meet the requirements of the magnetic fluid hyperthermia and can be considered for the future usage of researchers and investigators.
Boton, C, Rivest, L, Forgues, D & Jupp, JR 2018, 'Comparison of shipbuilding and construction industries from the product structure standpoint', International Journal of Product Lifecycle Management, vol. 11, no. 3, pp. 191-191.
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The use of building information modelling (BIM) in construction compares to the use of product lifecycle management (PLM) in manufacturing. Previous research has shown that it is possible to improve BIM with the features and the best practices from the PLM approach. This article provides a comparison from the standpoint of the bill of materials (BOM) and product structures. It compares the product beginning of life in both construction and shipbuilding industries. The research then tries to understand the use, form and evolution of product structures and BOM concepts in shipbuilding with the aim of identifying equivalent notions in construction. Research findings demonstrate that similar concepts for structuring information exist in construction; however, the relationship between them is unclear. Further research is therefore required to detail the links identified by the authors and develop an equivalent central structuring backbone as found in PLM platforms.
Bowden, R & Veitch, D 2018, 'Finding the Right Tree: Topology Inference Despite Spatial Dependences', IEEE Transactions on Information Theory, vol. 64, no. 6, pp. 4594-4609.
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© 1963-2012 IEEE. Network tomographic techniques have almost exclusively been built on a strong assumption of mutual independence of link processes. We introduce model classes for link loss processes with non-Trivial spatial dependencies, for which the tree topology is nonetheless identifiable from leaf measurements using multicast probing. We show that these classes are large in a well-defined sense, and we provide an algorithm, SLTD, capable of returning the correct topology with certainty in the limit of infinite data.
Bown, O & Ferguson, S 2018, 'Understanding media multiplicities', Entertainment Computing, vol. 25, pp. 62-70.
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Internet of Things (IoT) technologies enable new forms of media artworks. ‘Media multiplicities’ are defined here as creative media experiences made up of multiples of interacting and coordinated devices. In this paper, we review the state of the art of multiplicitous media artworks and provide a systematic analysis of the novel affordances and different forms such artworks can take, specifically that they are spatial, scalable, scatterable and sensing. We consider the analysis of media multiplicities from the point of view of both user experience and creative production. We offer three primary axes through which a categorisation of multiplicitous media forms can be framed: substrate versus object; composed versus self-organised, and homogeneous versus heterogeneous. We also analyse how the number of elements in the multiplicities (from tens to tens of thousands and beyond) affects the qualities of the experience.
Bracci, M, Tarini, M, Pietroni, N, Livesu, M & Cignoni, P 2018, 'HexaLab.net: an online viewer for hexahedral meshes.', CoRR, vol. abs/1806.06639, pp. 24-36.
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© 2018 Elsevier Ltd We introduce HexaLab: a WebGL application for real time visualization, exploration and assessment of hexahedral meshes. HexaLab can be used by simply opening www.hexalab.net. Our visualization tool targets both users and scholars. Practitioners who employ hexmeshes for Finite Element Analysis, can readily check mesh quality and assess its usability for simulation. Researchers involved in mesh generation may use HexaLab to perform a detailed analysis of the mesh structure, isolating weak points and testing new solutions to improve on the state of the art and generate high quality images. To this end, we support a wide variety of visualization and volume inspection tools. Our system offers also immediate access to a repository containing all the publicly available meshes produced with the most recent techniques for hexmesh generation. We believe HexaLab, providing a common tool for visualizing, assessing and distributing results, will push forward the recent strive for replicability in our scientific community.
Brennan, MJ, Karimi, M, Muggleton, JM, Almeida, FCL, Kroll de Lima, F, Ayala, PC, Obata, D, Paschoalini, AT & Kessissoglou, N 2018, 'On the effects of soil properties on leak noise propagation in plastic water distribution pipes', Journal of Sound and Vibration, vol. 427, pp. 120-133.
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Brereton, M, Soro, A, Sitbon, L, Roe, P, Wyeth, P, Ploderer, B, Vyas, D, Zhang, J, Ambe, A, Wilson, C, Dema, T, Taylor, J, Oliver, J, Munoz, D, Bayor, A, Bircanin, F, Anggarendra, R, Capel, T, Kapuire, G & Wheeler, H 2018, 'Design participation lab', Interactions, vol. 25, no. 2, pp. 14-17.
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Burdon, S, Mooney, G & Kang, K 2018, 'Where Everybody Knows Your Name: Lessons in Innovation from the High-Tech Sector', Journal of Innovation and Business Best Practice, vol. 2018, no. 2018, pp. 1-16.
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This paper examines the major priorities and prevailing values of firms highly regarded for
innovation success within the Australian high-tech sector. In conjunction with the
Information Industry Association of Australia (AIIA),
a survey was undertaken regarding
member perceptions of peer enterprises most admired
for innovation origination and
delivery. 244 responses from 102 organisations were received, analysed and compared.
Direct follow-up with selected enterprises then more closely examined factors deemed key
to sustaining a cycle of innovation leadership. Findings suggest that firms most esteemed by
peers also prioritise the realisation of innovation
over simply making money - yet both high
growth and cash flows are still habitually generated
.Results also show that having a strong
reputation for innovation is a competitive advantage in its own right as they attract
invitation to cross-enterprise ecosystems and beneficial partner alliances. Interestingly
however, topics linked to outsider/peer perceptions
of rival enterprises seem to collect
comparatively limited precedence within innovation
debates. What our study shows is that
balancing an internal reality of innovation with the external perception for innovation can
lead firms to significant improvements in overall commercial performance.
Cagno, E, Neri, A & Trianni, A 2018, 'Broadening to sustainability the perspective of industrial decision-makers on the energy efficiency measures adoption: some empirical evidence', Energy Efficiency, vol. 11, no. 5, pp. 1193-1210.
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© 2018, Springer Science+Business Media B.V., part of Springer Nature. The industry should take further efforts towards increased energy efficiency, that is a major contributor to improve industrial sustainability performance, by implementing energy efficiency measures (EEMs). However, the rate of adoption of these measures is still quite low. Hitherto, EEMs and barriers to their adoption have been evaluated almost exclusively from the viewpoint of energy efficiency decision-makers, not accounting for the broader sustainability perspective. This work aims at understanding whether an industrial sustainability perspective can better address issues related to EEMs adoption, analyzing the question through different viewpoints and insights offered by industrial decision-makers of different industrial sustainability areas within a firm. By doing this, we aim at offering a contribution in the understanding of the low rate of adoption of EEMs. As case studies, we investigated 12 firms from Northern Italy. In comparison to previous literature, results show that an industrial sustainability perspective can better explain the real decision-making process of adopting an EEM. Indeed, people knowledgeable about different industrial sustainability areas may perceive different barriers about the same EEM. EEMs may be negatively affected by reasons related to other areas of industrial sustainability, while positive reciprocal impacts may exist among areas of industrial sustainability; thus, EEMs may have effects on areas other than energy efficiency, and these effects may be perceived only by such areas. The study concludes with some remarks for policy and industrial decision-makers and advice for further research.
Cai, C, Hu, S, Chen, X, Ni, B-J, Pu, J & Yuan, Z 2018, 'Effect of methane partial pressure on the performance of a membrane biofilm reactor coupling methane-dependent denitrification and anammox', Science of The Total Environment, vol. 639, pp. 278-285.
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© 2018 Complete nitrogen removal has recently been demonstrated by integrating anaerobic ammonium oxidation (anammox) and denitrifying anaerobic methane oxidation (DAMO) processes. In this work, the effect of methane partial pressure on the performance of a membrane biofilm reactor (MBfR) consisting of DAMO and anammox microorganisms was evaluated. The activities of DAMO archaea and DAMO bacteria in the biofilm increased significantly with increased methane partial pressure, from 367 ± 9 and 58 ± 22 mg-N L−1d−1 to 580 ± 12 and 222 ± 22 mg-N L−1d−1, respectively, while the activity of anammox bacteria only increased slightly, when the methane partial pressure was elevated from 0.24 to 1.39 atm in the short-term batch tests. The results were supported by a long-term (seven weeks) continuous test, when the methane partial pressure was dropped from 1.39 to 0.78 atm. The methane utilization efficiency was always above 96% during both short-term and long-term tests. Taken together, nitrogen removal rate (especially the nitrate reduction rate by DAMO archaea) and methane utilization efficiency could be maintained at high levels in a broad range of methane partial pressure (0.24–1.39 atm in this study). In addition, a previously established DAMO/anammox biofilm model was used to analyze the experimental data. The observed impacts of methane partial pressure on biofilm activity were well explained by the modeling results. These results suggest that methane partial pressure can potentially be used as a manipulated variable to control reaction rates, ultimately to maintain high nitrogen removal efficiency, according to nitrogen loading rate.
Cai, Q, Turner, BD, Sheng, D & Sloan, S 2018, 'Application of kinetic models to the design of a calcite permeable reactive barrier (PRB) for fluoride remediation', Water Research, vol. 130, pp. 300-311.
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Cancino, CA, Merigo, JM, Torres, JP & Diaz, D 2018, 'A bibliometric analysis of venture capital research', Journal of Economics, Finance and Administrative Science, vol. 23, no. 45, pp. 182-195.
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PurposeThe purpose of this study is to present the evolution of academic research in venture capital (VC) research between 1990 and 2014.Design/methodology/approachThe study analyzes the most influential journals in VC research by analyzing papers, which were published on the Web of Science database.FindingsResults show a steady increasing rate of VC research during the past 25 years. The paper reports the 40 academic journals that permanently publish articles about VC research.Originality/valueThe main contribution of this work is to develop a general overview of the leading journals in VC research, which leads to the development of a future research agenda for bibliometric analysis, such as the review of the most productive and influential authors, universities and countries in VC research.
Cao, F & Li, K 2018, 'A new method for image super-resolution with multi-channel constraints', Knowledge-Based Systems, vol. 146, pp. 118-128.
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Cao, Y, Cao, Y, Wen, S, Huang, T & Zeng, Z 2018, 'Passivity analysis of coupled neural networks with reaction–diffusion terms and mixed delays', Journal of the Franklin Institute, vol. 355, no. 17, pp. 8915-8933.
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In this paper, we intend to discuss the passivity of coupled neural networks (NNs) with reaction–diffusion terms and mixed delays. By constructing appropriate Lyapunov functional, and with the help of liner matrix inequalities, some inequality techniques, several sufficient conditions are derived to guarantee the output strictly passive, input strictly passive, passive of the proposed neural network model. Then, a stability criterion is presented according to the obtained passivity results. Moreover, the proposed neural network model herein is more general than some recent studies, which can improve and enrich the previous research results. Finally, a numerical example is presented to show the effectiveness of the theoretical criteria.
Cao, Y, Romero, J, Olson, JP, Degroote, M, Johnson, PD, Kieferová, M, Kivlichan, ID, Menke, T, Peropadre, B, Sawaya, NPD, Sim, S, Veis, L & Aspuru-Guzik, A 2018, 'Quantum Chemistry in the Age of Quantum Computing', Chemical Reviews, vol. 119, no. 19.
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Practical challenges in simulating quantum systems on classical computershave been widely recognized in the quantum physics and quantum chemistrycommunities over the past century. Although many approximation methods havebeen introduced, the complexity of quantum mechanics remains hard to appease.The advent of quantum computation brings new pathways to navigate thischallenging complexity landscape. By manipulating quantum states of matter andtaking advantage of their unique features such as superposition andentanglement, quantum computers promise to efficiently deliver accurate resultsfor many important problems in quantum chemistry such as the electronicstructure of molecules. In the past two decades significant advances have beenmade in developing algorithms and physical hardware for quantum computing,heralding a revolution in simulation of quantum systems. This article is anoverview of the algorithms and results that are relevant for quantum chemistry.The intended audience is both quantum chemists who seek to learn more aboutquantum computing, and quantum computing researchers who would like to exploreapplications in quantum chemistry.
Cao, Z & Lin, C-T 2018, 'Inherent Fuzzy Entropy for the Improvement of EEG Complexity Evaluation', IEEE Transactions on Fuzzy Systems, vol. 26, no. 2, pp. 1032-1035.
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© 2017 IEEE. In recent years, the concept of entropy has been widely used to measure the dynamic complexity of signals. Since the state of complexity of human beings is significantly affected by their health state, developing accurate complexity evaluation algorithms is a crucial and urgent area of study. This paper proposes using inherent fuzzy entropy (Inherent FuzzyEn) and its multiscale version, which employs empirical mode decomposition and fuzzy membership function (exponential function) to address the dynamic complexity in electroencephalogram (EEG) data. In the literature, the reliability of entropy-based complexity evaluations has been limited by superimposed trends in signals and a lack of multiple time scales. Our proposed method represents the first attempt to use the Inherent FuzzyEn algorithm to increase the reliability of complexity evaluation in realistic EEG applications. We recorded the EEG signals of several subjects under resting condition, and the EEG complexity was evaluated using approximate entropy, sample entropy, FuzzyEn, and Inherent FuzzyEn, respectively. The results indicate that Inherent FuzzyEn is superior to other competing models regardless of the use of fuzzy or nonfuzzy structures, and has the most stable complexity and smallest root mean square deviation.
Cao, Z, Lai, K-L, Lin, C-T, Chuang, C-H, Chou, C-C & Wang, S-J 2018, 'Exploring resting-state EEG complexity before migraine attacks', Cephalalgia, vol. 38, no. 7, pp. 1296-1306.
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Objective Entropy-based approaches to understanding the temporal dynamics of complexity have revealed novel insights into various brain activities. Herein, electroencephalogram complexity before migraine attacks was examined using an inherent fuzzy entropy approach, allowing the development of an electroencephalogram-based classification model to recognize the difference between interictal and preictal phases. Methods Forty patients with migraine without aura and 40 age-matched normal control subjects were recruited, and the resting-state electroencephalogram signals of their prefrontal and occipital areas were prospectively collected. The migraine phases were defined based on the headache diary, and the preictal phase was defined as within 72 hours before a migraine attack. Results The electroencephalogram complexity of patients in the preictal phase, which resembled that of normal control subjects, was significantly higher than that of patients in the interictal phase in the prefrontal area (FDR-adjusted p < 0.05) but not in the occipital area. The measurement of test-retest reliability (n = 8) using the intra-class correlation coefficient was good with r1 = 0.73 ( p = 0.01). Furthermore, the classification model, support vector machine, showed the highest accuracy (76 ± 4%) for classifying interictal and preictal phases using the prefrontal electroencephalogram complexity. Conclusion Entropy-based analytical methods identified enhancement or “normalization” of frontal electroencephalogram complexity during the preictal phase compared with the interictal phase. This classification model, using this complexity feature, may have the potential to provide a preictal alert to migraine without aura patients.
CARLES, M-F, PATRICIA, H, ANTONIO, S & JOSÉ M., M 2018, 'The Forgotten Effects: An Application in the Social Economy of Companies of the Balearic Islands', ECONOMIC COMPUTATION AND ECONOMIC CYBERNETICS STUDIES AND RESEARCH, vol. 52, no. 3/2018, pp. 147-160.
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© 2018, Bucharest University of Economic Studies. All rights reserved. Few studies have analyzed how to improve the results and productivity of companies with very peculiar characteristics, such as social economy entities. This paper determines the principal worth-creating activities for this type of companies that dedicate their activities to the service sector of the Balearic Islands. In order to carry out this work, incidence matrixes and recovery of forgotten effects have been used. Both direct cause and second generation causes that arise in the majority of the socio-economic cases have been identified. In fact, determining the second generation effects, or forgotten effects, is one of the main contributions of this study as it shows that those causes that are usually not foreseen, at least in the first instance, affect notably in the generation of social economy companies value to the service sector of the Balearic Islands.
Castro, J, Lu, J, Zhang, G, Dong, Y & Martinez, L 2018, 'Opinion Dynamics-Based Group Recommender Systems', IEEE Transactions on Systems, Man, and Cybernetics: Systems, vol. 48, no. 12, pp. 2394-2406.
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© 2013 IEEE. With the accessibility to information, users often face the problem of selecting one item (a product or a service) from a huge search space. This problem is known as information overload. Recommender systems (RSs) personalize content to a user's interests to help them select the right item in information overload scenarios. Group RSs (GRSs) recommend items to a group of users. In GRSs, a recommendation is usually computed by a simple aggregation method for individual information. However, the aggregations are rigid and overlook certain group features, such as the relationships between the group members' preferences. In this paper, it is proposed a GRS based on opinion dynamics that considers these relationships using a smart weights matrix to drive the process. In some groups, opinions do not agree, hence the weights matrix is modified to reach a consensus value. The impact of ensuring agreed recommendations is evaluated through a set of experiments. Additionally, a sensitivity analysis studies its behavior. Compared to existing group recommendation models and frameworks, the proposal based on opinion dynamics would have the following advantages: 1) flexible aggregation method; 2) member relationships; and 3) agreed recommendations.
Cetindamar, D 2018, 'Designed by law: Purpose, accountability, and transparency at benefit corporations', Cogent Business & Management, vol. 5, no. 1, pp. 1423787-1423787.
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The article explores the realization of major goals of the Benefit
Corporation (BC) law, which is a corporation form designed for social enterprises in the United States in 2010. BCs have a dual mission of generating both profit and social value and hence they might have the potential to transform society. This paper attempts to observe the first movers established as BCs during the period of 2010–2012. By adopting the institutional theory approach, the study examines the realization of the BC law’s three major goals: purpose, accountability, and transparency.
The paper utilizes the regulatory legitimacy concept to measure the discrepancy between design and implementation of law. The observations point out some of the challenges of establishing new innovative organizations through an institutional intervention of a law. Conclusions consist of implications of the study as well as suggestions
for further studies.
Chaei, MG, Akbarnezhad, A, Castel, A, Lloyd, R, Keyte, L & Foster, S 2018, 'Precision of cement hydration heat models in capturing the effects of SCMs and retarders', Magazine of Concrete Research, vol. 70, no. 23, pp. 1217-1231.
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A major input to numerical simulation models used to predict the risk of early-age thermal cracking in concrete is the hydration heat estimation. The precision of hydration heat estimation models has been extensively verified for different cement compositions in previous studies. However, little has been done to investigate the accuracy of such models for concrete mixes containing supplementary cementitious materials and retarders. This paper presents the results of a series of isothermal calorimetry tests conducted first to investigate the effects of Class F fly ash, ground-granulated blast-furnace slag (GGBFS) and three commonly used retarders (namely, retarder N, sucrose and citrate) on the heat of hydration profile of Australian general-purpose cement under different curing temperatures of 10, 23 and 30°C, and second to evaluate the precision of the two most commonly used hydration heat models in capturing the effects of fly ash, GGBFS, retarders and curing temperature on the hydration profile. The results reveal the possibility of considerable errors in estimating the hydration heat of concrete mixes containing supplementary cementitious materials and retarders under different curing temperatures, highlighting the need for re-calibration of the existing models for locally used materials to avoid misleading errors in numerical simulation of early-age thermal cracking.
Chandra Saha, K 2018, 'Double Lid Driven Cavity with Different Moving Wall Directions for Low Reynolds Number Flow', International Journal of Applied Mathematics and Theoretical Physics, vol. 4, no. 3, pp. 67-67.
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Chang, X, Yan, Y & Nie, L 2018, 'Guest Editorial: Semantic Concept Discovery in MM Data', Multimedia Tools and Applications, vol. 77, no. 3, pp. 2945-2946.
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Chauhan, J, Seneviratne, S, Hu, Y, Misra, A, Seneviratne, A & Lee, Y 2018, 'Breathing-Based Authentication on Resource-Constrained IoT Devices using Recurrent Neural Networks', Computer, vol. 51, no. 5, pp. 60-67.
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Chekli, L, Pathak, N, Kim, Y, Phuntsho, S, Li, S, Ghaffour, N, Leiknes, T & Shon, HK 2018, 'Combining high performance fertiliser with surfactants to reduce the reverse solute flux in the fertiliser drawn forward osmosis process', Journal of Environmental Management, vol. 226, pp. 217-225.
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© 2018 Elsevier Ltd Solutions to mitigate the reverse diffusion of solutes are critical to the successful commercialisation of the fertiliser drawn forward osmosis process. In this study, we proposed to combine a high performance fertiliser (i.e., ammonium sulfate or SOA) with surfactants as additives as an approach to reduce the reverse diffusion of ammonium ions. Results showed that combining SOA with both anionic and non-ionic surfactants can help in reducing the reverse salt diffusion by up to 67%. We hypothesised that, hydrophobic interactions between the surfactant tails and the membrane surface likely constricted membrane pores resulting in increased rejection of ions with large hydrated radii such as SO42−. By electroneutrality, the rejection of the counter ions (i.e., NH4+) also therefore subsequently improved. Anionic surfactant was found to further decrease the reverse salt diffusion due to electrostatic repulsions between the surfactant negatively-charged heads and SO42−. However, when the feed solution contains cations with small hydrated radii (e.g., Na+); it was found that NH4+ ions can be substituted in the DS to maintain its electroneutrality and thus the diffusion of NH4+ to the feed solution was increased.
Chelgani, SC & Matin, SS 2018, 'Study the relationship between coal properties with Gieseler plasticity parameters by random forest', International Journal of Oil, Gas and Coal Technology, vol. 17, no. 1, pp. 113-113.
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Chen, C, Guo, WS, Ngo, HH, Chang, SW, Nguyen, DD, Zhang, J, Liang, S, Guo, JB & Zhang, XB 2018, 'Effects of C/N ratio on the performance of a hybrid sponge-assisted aerobic moving bed-anaerobic granular membrane bioreactor for municipal wastewater treatment', Bioresource Technology, vol. 247, pp. 340-346.
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This study aimed to evaluate the impact of C/N ratio on the performance of a hybrid sponge-assisted aerobic moving bed-anaerobic granular membrane bioreactor (SAAMB-AnGMBR) in municipal wastewater treatment. The results showed that organic removal efficiencies were above 94% at all C/N conditions. Nutrient removal was over 91% at C/N ratio of 100/5 but was negatively affected when decreasing C/N ratio to 100/10. At lower C/N ratio (100/10), more noticeable membrane fouling was caused by aggravated cake formation and pore clogging, and accumulation of extracellular polymeric substances (EPS) in the mixed liquor and sludge cake as a result of deteriorated granular quality. Foulant analysis suggested significant difference existed in the foulant organic compositions under different C/N ratios, and humic substances were dominant when the fastest fouling rate was observed. The performance of the hybrid system was found to recover when gradually increasing C/N ratio from 100/10 to 100/5.
Chen, C, Wang, F, Wen, S, Su, QP, Wu, MCL, Liu, Y, Wang, B, Li, D, Shan, X, Kianinia, M, Aharonovich, I, Toth, M, Jackson, SP, Xi, P & Jin, D 2018, 'Multi-photon near-infrared emission saturation nanoscopy using upconversion nanoparticles', Nature Communications, vol. 9, no. 1.
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AbstractMultiphoton fluorescence microscopy (MPM), using near infrared excitation light, provides increased penetration depth, decreased detection background, and reduced phototoxicity. Using stimulated emission depletion (STED) approach, MPM can bypass the diffraction limitation, but it requires both spatial alignment and temporal synchronization of high power (femtosecond) lasers, which is limited by the inefficiency of the probes. Here, we report that upconversion nanoparticles (UCNPs) can unlock a new mode of near-infrared emission saturation (NIRES) nanoscopy for deep tissue super-resolution imaging with excitation intensity several orders of magnitude lower than that required by conventional MPM dyes. Using a doughnut beam excitation from a 980 nm diode laser and detecting at 800 nm, we achieve a resolution of sub 50 nm, 1/20th of the excitation wavelength, in imaging of single UCNP through 93 μm thick liver tissue. This method offers a simple solution for deep tissue super resolution imaging and single molecule tracking.
Chen, Q, Zhou, Y & Nimbalkar, S 2018, 'Closure to “Estimation of Passive Earth Pressure against Rigid Retaining Wall Considering Arching Effect in Cohesive-Frictional Backfill under Translation Mode” by Yanyan Cai, Qingsheng Chen, Yitao Zhou, Sanjay Nimbalkar, and Jin Yu', International Journal of Geomechanics, vol. 18, no. 7, pp. 07018012-07018012.
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Chen, Q, Zhou, Y & Nimbalkar, S 2018, 'Closure to 'Estimation of passive earth pressure against rigid retaining wall considering arching effect in cohesive- frictional backfill under translation mode' by Yanyan Cai, Qingsheng Chen, Yitao Zhou, Sanjay Nimbalkar, and Jin Yu', International Journal of Geomechanics, vol. 18, no. 7.
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Chen, S, Wang, Z, Liang, J & Yuan, X 2018, 'Uncertainty-aware visual analytics for exploring human behaviors from heterogeneous spatial temporal data', Journal of Visual Languages & Computing, vol. 48, pp. 187-198.
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© 2018 Elsevier Ltd When analyzing human behaviors, we need to construct the human behaviors from multiple sources of data, e.g. trajectory data, transaction data, identity data, etc. The problems we're facing are the data conflicts, different resolution, missing and conflicting data, which together lead to the uncertainty in the spatial temporal data. Such uncertainty in data leads to difficulties and even failure in the visual analytics task for analyzing people behavior, pattern and outliers. However, traditional automatic methods can not solve the problems in such complex scenario, where the uncertain and conflicting patterns are not well-defined. To solve the problems, we proposed a semi-automatic approach, for users to solve the conflicts and identify the uncertainties. To be general, we summarized five types of uncertainties and solutions to conduct the tasks of behavior analysis. Combined with the uncertainty-aware methods, we proposed a visual analytics system to analyze human behaviors, detect patterns and find outliers. Case studies from the IEEE VAST Challenge 2014 dataset confirm the effectiveness of our approach.
Chen, S, Yu, H & Fang, J 2018, 'A novel multi-cell tubal structure with circular corners for crashworthiness', Thin-Walled Structures, vol. 122, pp. 329-343.
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© 2017 Elsevier Ltd Multi-cell structures have proven to own excellent energy absorbing capability and lightweight effect in the automotive and aerospace industries. The cross-sectional configuration of the multi-cell structure has a significant effect on crashworthiness. Unlike existing multi-cell tubes, a new type of five-cell profile with four circular elements at the corners (C5C) was proposed in this study. To investigate the crashworthiness of the new C5C tube, finite element (FE) models were first established by using the nonlinear finite element code LS-DYNA and validated with experimental results. Following that, the comparison of the C5C tube and other multi-cell tubes with the same mass was conducted to quantify the relative merits of the C5C tube. Then, a detailed study was performed to analyze the effect of the corner-cell size and wall thickness. Finally, the optimization design was carried out to seek the optimal structure. The results showed that the new multi-cell structure can absorb much more crash energy than other four types of tubes. Moreover, the energy absorption of this new multi-cell tube C5C was affected by the corner-cell size and wall thickness significantly. A proper corner-cell size and slightly thicker internal ribs were recommended. In addition, the multi-objective particle swarm optimization (MOPSO) algorithm and radial basis function (RBF) surrogate model can optimize the structure effectively. The outcomes of the present study will facilitate the design of multi-cell structures with better crashworthiness.
Chen, S-L, Qin, P-Y, Lin, W & Guo, YJ 2018, 'Pattern-Reconfigurable Antenna With Five Switchable Beams in Elevation Plane', IEEE Antennas and Wireless Propagation Letters, vol. 17, no. 3, pp. 454-457.
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© 2017 IEEE. Pattern-reconfigurable antennas with multiple switchable beams, especially with both boresight and endfire directions, are highly desired for wireless communications. In this letter, a novel pattern-reconfigurable antenna is proposed that provides an efficient solution. By reconfiguring parasitic striplines placed around a radiating dipole and reflecting metal pieces under the dipole using p-i-n diodes, the antenna main beam can be switched to five directions in the elevation plane, approximately from-90(left endfire),-45 , 0 (boresight),+45 to +90(right endfire). The proposed antenna operates at 2.45 GHz with dimensions of about 0.57λ× 0.45\lambda×, 0.28λ. An antenna prototype is fabricated and measured. For all five directional beams, the measured S-{11}| values are below 13 dB, and the measured realized gains range from 5.2 to 6.5 dBi. They agree reasonably well with the simulated ones.
Chen, W, Deng, W, Xu, X, Zhao, X, Vo, JN, Anwer, AG, Williams, TC, Cui, H & Goldys, EM 2018, 'Photoresponsive endosomal escape enhances gene delivery using liposome–polycation–DNA (LPD) nanovectors', Journal of Materials Chemistry B, vol. 6, no. 32, pp. 5269-5281.
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Light-triggered endolysosomal escape enhances gene delivery by photoresponsive LPD nanoparticles.
Chen, W, Peng, J, Hong, H, Shahabi, H, Pradhan, B, Liu, J, Zhu, A-X, Pei, X & Duan, Z 2018, 'Landslide susceptibility modelling using GIS-based machine learning techniques for Chongren County, Jiangxi Province, China', Science of The Total Environment, vol. 626, pp. 1121-1135.
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© 2018 Elsevier B.V. The preparation of a landslide susceptibility map is considered to be the first step for landslide hazard mitigation and risk assessment. However, these maps are accepted as end products that can be used for land use planning. The main goal of this study is to assess and compare four advanced machine learning techniques, namely the Bayes’ net (BN), radical basis function (RBF) classifier, logistic model tree (LMT), and random forest (RF) models, for landslide susceptibility modelling in Chongren County, China. A total of 222 landslide locations were identified in the study area using historical reports, interpretation of aerial photographs, and extensive field surveys. The landslide inventory data was randomly split into two groups with a ratio of 70/30 for training and validation purposes. Fifteen landslide conditioning factors were prepared for landslide susceptibility modelling. The spatial correlation between landslides and conditioning factors was analyzed using the information gain (IG) method. The BN, RBF classifier, LMT, and RF models were constructed using the training dataset. Finally, the receiver operating characteristic (ROC) and statistical measures, including sensitivity, specificity, and accuracy, were employed to validate and compare the predictive capabilities of the models. Out of the tested models, the RF model had the highest sensitivity, specificity, and accuracy values of 0.787, 0.716, and 0.752, respectively, for the training dataset. Overall, the RF model produced an optimized balance for the training and validation datasets in terms of AUC values and statistical measures. The results of this study also demonstrate the benefit of selecting optimal machine learning techniques with proper conditioning selection methods for landslide susceptibility modelling.
Chen, W, Simpson, JM, March, LM, Blyth, FM, Bliuc, D, Tran, T, Nguyen, TV, Eisman, JA & Center, JR 2018, 'Comorbidities Only Account for a Small Proportion of Excess Mortality After Fracture: A Record Linkage Study of Individual Fracture Types', Journal of Bone and Mineral Research, vol. 33, no. 5, pp. 795-802.
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ABSTRACT Nonhip, nonvertebral (NHNV) fractures constitute the majority of osteoporotic fractures, but few studies have examined the association between these fractures, comorbidity, and mortality. Our objective was to examine the relationship between individual nonhip, nonvertebral fractures, comorbidities, and mortality. The prospective population-based cohort of 267,043 subjects (45 and Up Study, Australia) had baseline questionnaires linked to hospital administrative and all-cause mortality data from 2006 to 2013. Associations between fracture and mortality were examined using multivariate, time-dependent Cox models, adjusted for age, prior fracture, body mass index, smoking, and comorbidities (cardiovascular disease, diabetes, stroke, thrombosis, and cancer), and survival function curves. Population attributable fraction was calculated for each level of risk exposure. During 1,490,651 person-years, women and men experienced 7571 and 4571 fractures and 7064 deaths and 11,078 deaths, respectively. In addition to hip and vertebral fractures, pelvis, humerus, clavicle, rib, proximal tibia/fibula, elbow and distal forearm fractures in both sexes, and ankle fractures in men were associated with increased multivariable-adjusted mortality hazard ratios ranging from 1.3 to 3.4. Comorbidity independently added to mortality such that a woman with a humeral fracture and 1 comorbidity had a similarly reduced 5-year survival as that of a woman with a hip fracture and no comorbidities. Population mortality attributable to any fracture without comorbidity was 9.2% in women and 5.3% in men. All proximal nonhip, nonvertebral fractures in women and men were associated with increased mortality risk. Coexistent comorbidities independently further increased mortality. Population attributable risk for mortality for fractures was similar to cardiovascul...
Chen, X, Li, Y, Li, J & Gu, X 2018, 'A dual-loop adaptive control for minimizing time response delay in real-time structural vibration control with magnetorheological (MR) devices', Smart Materials and Structures, vol. 27, no. 1, pp. 015005-015005.
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© 2017 IOP Publishing Ltd. Time delay is a challenge issue faced by the real-time control application of the magnetorheological (MR) devices. Not to deal with it properly may jeopardize the effectiveness of the control, even lead to instability of the control system or catastrophic failure. This paper proposes a dual-loop adaptive control to address the response time delay associated with MR devices. In the proposed dual-loop control, the inner loop is designed to compensate the time delay of MR device induced by the PWM current driver. While the outer loop control can be any structural control algorithm with aims to reducing structural responses of a building during extreme loadings. Here an adaptive control strategy is adopted. To verify the proposed dual-loop control, a smart base isolation system employing magnetorheological elastomer base isolators is used as an example to illustrate the control effect. Numerical study is then conducted using a 5 -storey shear building model equipped with smart base isolation system. The result shows that with the implementation of the inner loop, the control current can instantly follow the control command which reduce the possibility of instability caused by the time delay. Comparative studies are conducted between three control strategies, i.e. dual-loop control, Lyapunov's direct method based control and optimal passive base isolation control. The results of the study have demonstrated that the proposed dual-loop control strategy can achieve much better performance than the other two control strategies.
Chen, X, Porto, CL, Chen, Z, Merenda, A, Allioux, F-M, d'Agostino, R, Magniez, K, Dai, XJ, Palumbo, F & Dumée, LF 2018, 'Single step synthesis of Janus nano-composite membranes by atmospheric aerosol plasma polymerization for solvents separation', Science of The Total Environment, vol. 645, pp. 22-33.
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Solvent permeation across membranes is limited due to physical resistance to diffusion from the selective layer within the membrane and to plasticizing effects generated by the solvent molecules onto the polymeric macromolecular matrix. Nano-composite thin film membranes provide promising routes to generate controlled microstructural separation materials with higher selectivities and permeabilities. Here, the fabrication of nano-composite based on octamethyl-polyhedral oligomeric silsesquioxane - hexamethyldisiloxane thin film membranes is demonstrated by aerosol assisted atmospheric plasma deposition onto pre-formed nano-porous membrane supports for the first time. Stable, atomically smooth and continuous solid films with controllable thickness down to 50 nm were achieved. The deposition process allowed for the control of the wettability of the surfaces to water and organic solvents, leading to the generation of hydrophobic but alcohol-philic surfaces. The liquid entry pressure of the films to water was found to be 8 bar from plasma polymerization as oppose to 3 bar for the bare nano-porous support only. In addition, the ideal separation selectivity for ethanol to water, up to 6.5, highlight the impact of both the surface energy and level of cross-linking of the hexamethyldisiloxane nanostructures on the diffusion mechanisms. This new atmospheric plasma deposition strategy opens-up cost-effective and environmentally friendly routes for the design of the smart Janus membrane with customizable properties and performance.
Chen, X, Yuan, G, Wang, W, Nie, F, Chang, X & Huang, JZ 2018, 'Local Adaptive Projection Framework for Feature Selection of Labeled and Unlabeled Data', IEEE Transactions on Neural Networks and Learning Systems, vol. 29, no. 12, pp. 6362-6373.
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Most feature selection methods first compute a similarity matrix by assigning a fixed value to pairs of objects in the whole data or to pairs of objects in a class or by computing the similarity between two objects from the original data. The similarity matrix is fixed as a constant in the subsequent feature selection process. However, the similarities computed from the original data may be unreliable, because they are affected by noise features. Moreover, the local structure within classes cannot be recovered if the similarities between the pairs of objects in a class are equal. In this paper, we propose a novel local adaptive projection (LAP) framework. Instead of computing fixed similarities before performing feature selection, LAP simultaneously learns an adaptive similarity matrix and a projection matrix with an iterative method. In each iteration, is computed from the projected distance with the learned and W is computed with the learned . Therefore, LAP can learn better projection matrix by weakening the effect of noise features with the adaptive similarity matrix. A supervised feature selection with LAP (SLAP) method and an unsupervised feature selection with LAP (ULAP) method are proposed. Experimental results on eight data sets show the superiority of SLAP compared with seven supervised feature selection methods and the superiority of ULAP compared with five unsupervised feature selection methods.
Chen, X, Yuan, Z & Ni, B-J 2018, 'Nitrite accumulation inside sludge flocs significantly influencing nitrous oxide production by ammonium-oxidizing bacteria', Water Research, vol. 143, pp. 99-108.
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© 2018 Elsevier Ltd This work aims to clarify the role of potential nitrite (NO2−) accumulation inside sludge flocs in N2O production by ammonium-oxidizing bacteria (AOB) at different dissolved oxygen (DO) levels with focus on the conditions of no significant bulk NO2− accumulation (<0.2 mg N/L). To this end, an augmented nitrifying sludge with much higher abundance of nitrite-oxidizing bacteria (NOB) than AOB was enriched and then used for systematically designed batch tests, which targeted a range of DO levels from 0 to 3.0 mg O2/L at a fixed ammonium concentration of 10 mg N/L. A two-pathway N2O model was applied to facilitate the interpretation of batch experimental data, thus shedding light on the relationships between N2O production pathways and key process parameters (i.e., DO and NO2− accumulation inside sludge flocs). The results demonstrated (i) the biomass specific N2O production rate firstly increased and then decreased with DO, with the maximum value of 3.03 ± 0.05 mg N/h/g VSS obtained at DO level of 0.75 mg O2/L, (ii) the AOB denitrification pathway for N2O production was dominant (98.0%) at all DO levels tested even without significant bulk NO2− accumulation (<0.2 mg N/L) observed in the system, but its contribution decreased with DO, (iii) DO had a positive impact on the hydroxylamine pathway for N2O production which therefore increased with DO, and (iv) the nitrite accumulation existed inside the sludge flocs and induced significant N2O production from the AOB denitrification pathway.
Chen, Y, Dong, Y, Sun, Y & Liang, J 2018, 'A Multi-comparable visual analytic approach for complex hierarchical data', Journal of Visual Languages & Computing, vol. 47, pp. 19-30.
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© 2018 Elsevier Ltd Maximum residue limit (MRL) standard which specifies the highest level of every pesticide residue in different agricultural products plays a critical role in food safety. However, such standards which related to the characteristics of pesticides and the classification of agricultural products which organized into a hierarchical structure are complex and vary widely across different regions or countries. So it is a big challenge to compare multi-regional MRL standard data comprehensively. In this paper, we present a multi-comparable visual analytic approach for complex hierarchical data and a visual analytics system (McVA) to support multiple comparison and evaluation of MRL standard. With a cooperative multi-view visual design, our proposed approach links the hierarchies of MRL datasets and provides the capacity for comparison at different levels and dimensions. We also introduce a metric model for evaluating the completeness and strictness of MRL standards quantitatively. The case study of real problems and the positive feedback from domain experts demonstrate the effectiveness of this approach.
Chen, Y, Su, QP, Sun, Y & Yu, L 2018, 'Visualizing Autophagic Lysosome Reformation in Cells Using In Vitro Reconstitution Systems', Current Protocols in Cell Biology, vol. 78, no. 1, pp. 11.24.1-11.24.15.
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AbstractAutophagy is a lysosome‐based degradation pathway. Autophagic lysosome reformation (ALR) is a lysosomal membrane recycling process that marks the terminal step of autophagy. During ALR, LAMP1‐positive tubules, named reformation tubules, are extruded from autolysosomes, and nascent lysosomes are generated from these tubules. By combining proteomic analysis of purified autolysosomes and RNA interference screening of identified candidates, we systematically elucidated the ALR pathway at the molecular level. Based on the key components clathrin, PtdIns(4,5)P2, and the motor protein KIF5B, among others, we reconstituted this process in vitro. This unit describes a detailed method for visualizing ALR in cells during the autophagy process. This unit also present a protocol for reconstituting the ALR tubular protrusion and elongation process in vitro and three methods for preparing materials for in vitro reconstitution: (1) autolysosome purification from cultured cells, (2) liposome preparation, and (3) KIF5B purification and quality testing. © 2018 by John Wiley & Sons, Inc.
Chen, Y, Wu, Y, Wang, D, Li, H, Wang, Q, Liu, Y, Peng, L, Yang, Q, Li, X, Zeng, G & Chen, Y 2018, 'Understanding the mechanisms of how poly aluminium chloride inhibits short-chain fatty acids production from anaerobic fermentation of waste activated sludge', Chemical Engineering Journal, vol. 334, pp. 1351-1360.
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© 2017 Elsevier B.V. Poly aluminum chloride (PAC) is accumulated in waste activated sludge at high levels. However, details of how PAC affects short-chain fatty acids (SCFA) production from anaerobic sludge fermentation has not been documented. This work therefore aims to fill this knowledge gap by analyzing the impact of PAC on the aggregate of sludge flocs, disruption of extracellular polymeric substances (EPS), and the bio-processes of hydrolysis, acidogenesis, and methanogenesis. The relationship between SCFA production and different aluminum species (i.e., Ala, Alb, and Alc) was also identified by controlling different OH/Al ratio and pH in different fermentation systems. Experimental results showed that with the increase of PAC addition from 0 to 40 mg Al per gram of total suspended solids, SCFA yield decreased from 212.2 to 138.4 mg COD/g volatile suspended solids. Mechanism exploration revealed that PAC benefited the aggregates of sludge flocs and caused more loosely- and tightly-bound extracellular polymeric substances remained in sludge cells. Besides, it was found that the hydrolysis, acidiogenesis, and methanogenesis processes were all inhibited by PAC. Although three types of Al species, i.e., Ala (Al monomers, dimer, and trimer), Alb (Al13(AlO4Al12(OH)24(H2O)7 + 12), and Alc (Al polymer molecular weight normally larger than 3000 Da), were co-existed in fermentation systems, their impacts on SCFA production were different. No correlation was found between SCFA and Ala, whereas SCFA production decreased with the contents of Alb and Alc. Compared with Alb, Alc was the major contributor to the decreased SCFA production (R2 = 0.5132 vs R2 = 0.98). This is the first report revealing the underlying mechanism of how PAC affects SCFA production and identifying the contribution of different Al species to SCFA inhibition.
Chen, Z, Wang, D, Sun, M, Hao Ngo, H, Guo, W, Wu, G, Jia, W, Shi, L, Wu, Q, Guo, F & Hu, H-Y 2018, 'Sustainability evaluation and implication of a large scale membrane bioreactor plant', Bioresource Technology, vol. 269, pp. 246-254.
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Membrane bioreactor (MBR) technology is receiving increasing attention in wastewater treatment and reuse. This study presents an integral sustainability evaluation of a full scale MBR plant. The plant is capable of achieving prominent technical performance in terms of high compliance rate, low variation in effluent quality and high removal efficiency during long term operation. It is also more responsive to the new local standard with rigorous limits. However, electricity consumption is found to be the dominant process resulting in elevated life cycle environmental impacts and costs, accounting for 51.6% of the costs. As such, it is suggested to optimize energy use in MBR unit and implement sludge treatment and management. The prolonged membrane life span could also contribute largely to reduced life cycle environmental concerns and expenses. This study is of great theoretical significance and applicable value in guaranteeing the performance and sustainability of large scale MBR schemes.
Chen, Z, Yu, T, Ngo, HH, Lu, Y, Li, G, Wu, Q, Li, K, Bai, Y, Liu, S & Hu, H-Y 2018, 'Assimilable organic carbon (AOC) variation in reclaimed water: Insight on biological stability evaluation and control for sustainable water reuse', Bioresource Technology, vol. 254, pp. 290-299.
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This review highlights the importance of conducting biological stability evaluation due to water reuse progression. Specifically, assimilable organic carbon (AOC) has been identified as a practical indicator for microbial occurrence and regrowth which ultimately influence biological stability. Newly modified AOC bioassays aimed for reclaimed water are introduced. Since elevated AOC levels are often detected after tertiary treatment, the review emphasizes that actions can be taken to either limit AOC levels prior to disinfection or conduct post-treatment (e.g. biological filtration) as a supplement to chemical oxidation based approaches (e.g. ozonation and chlorine disinfection). During subsequent distribution and storage, microbial community and possible microbial regrowth caused by complex interactions are discussed. It is suggested that microbial surveillance, AOC threshold values, real-time field applications and surrogate parameters could provide additional information. This review can be used to formulate regulatory plans and strategies, and to aid in deriving relevant control, management and operational guidance.
Chenari, RJ, Fatahi, B, Ghorbani, A & Alamoti, MN 2018, 'Evaluation of strength properties of cement stabilized sand mixed with EPS beads and fly ash', Geomechanics and Engineering, vol. 14, no. 6, pp. 533-544.
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The importance of using materials cost effectively to enhance the strength and reduce the cost, and weight of earth fill materials in geotechnical engineering led researchers to seek for modifying the soil properties by adding proper additives. Lightweight fill materials made of soil, binder, water, and Expanded polystyrene (EPS) beads are increasingly being used in geotechnical practices. This paper primarily investigates the behavior of sandy soil, modified by EPS particles. Besides, the mechanical properties of blending sand, EPS and the binder material such as fly ash and cement were examined in different mixing ratios using a number of various laboratory studies including the Modified Standard Proctor (MSP) test, the Unconfined Compressive Strength (UCS) test, the California Bearing Ratio (CBR) test and the Direct Shear test (DST). According to the results, an increase of 0.1% of EPS results in a reduction of the density of the mixture for 10%, as well as making the mixture more ductile rather than brittle. Moreover, the compressive strength, CBR value and shear strength parameters of the mixture decreases by an increase of the EPS beads, a trend on the contrary to the increase of cement and fly ash content.
Cheng, D, Gong, Y, Chang, X, Shi, W, Hauptmann, A & Zheng, N 2018, 'Deep feature learning via structured graph Laplacian embedding for person re-identification', Pattern Recognition, vol. 82, pp. 94-104.
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Learning the distance metric between pairs of examples is of great importance for visual recognition, especially for person re-identification (Re-Id). Recently, the contrastive and triplet loss are proposed to enhance the discriminative power of the deeply learned features, and have achieved remarkable success. As can be seen, either the contrastive or triplet loss is just one special case of the Euclidean distance relationships among these training samples. Therefore, we propose a structured graph Laplacian embedding algorithm, which can formulate all these structured distance relationships into the graph Laplacian form. The proposed method can take full advantages of the structured distance relationships among these training samples, with the constructed complete graph. Besides, this formulation makes our method easy-to-implement and super-effective. When embedding the proposed algorithm with the softmax loss for the CNN training, our method can obtain much more robust and discriminative deep features with inter-personal dispersion and intra-personal compactness, which is essential to person Re-Id. We did experiments on top of three popular networks, namely AlexNet [1], DGDNet [2] and ResNet50 [3], on recent four widely used Re-Id benchmark datasets, and it shows that the proposed structure graph Laplacian embedding is very effective.
Cheng, D, Ngo, HH, Guo, W, Liu, Y, Chang, SW, Nguyen, DD, Nghiem, LD, Zhou, J & Ni, B 2018, 'Anaerobic membrane bioreactors for antibiotic wastewater treatment: Performance and membrane fouling issues', Bioresource Technology, vol. 267, pp. 714-724.
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© 2018 Elsevier Ltd Antibiotic wastewater has become a major concern due to the toxicity and recalcitrance of antibiotics. Anaerobic membrane bioreactors (AnMBRs) are considered alternative technology for treating antibiotic wastewater because of their advantages over the conventional anaerobic processes and aerobic MBRs. However, membrane fouling remains the most challenging issue in the AnMBRs’ operation and this limits their application. This review critically discusses: (i) antibiotics removal and antibiotic resistance genes (ARGs) in different types of AnMBRs and the impact of antibiotics on membrane fouling and (ii) the integrated AnMBRs systems for fouling control and removal of antibiotics. The presence of antibiotics in AnMBRs could aggravate membrane fouling by influencing fouling-related factors (i.e., sludge particle size, extracellular polymeric substances (EPS), soluble microbial products (SMP), and fouling-related microbial communities). Conclusively, integrated AnMBR systems can be a practical technology for antibiotic wastewater treatment.
Cheng, DL, Ngo, HH, Guo, WS, Chang, SW, Nguyen, DD, Kumar, SM, Du, B, Wei, Q & Wei, D 2018, 'Problematic effects of antibiotics on anaerobic treatment of swine wastewater', Bioresource Technology, vol. 263, pp. 642-653.
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Swine wastewaters with high levels of organic pollutants and antibiotics have become serious environmental concerns. Anaerobic technology is a feasible option for swine wastewater treatment due to its advantage in low costs and bioenergy production. However, antibiotics in swine wastewater have problematic effects on micro-organisms, and the stability and performance of anaerobic processes. Thus, this paper critically reviews impacts of antibiotics on pH, COD removal efficiencies, biogas and methane productions as well as the accumulation of volatile fatty acids (VFAs) in the anaerobic processes. Meanwhile, impacts on the structure of bacteria and methanogens in anaerobic processes are also discussed comprehensively. Furthermore, to better understand the effect of antibiotics on anaerobic processes, detailed information about antimicrobial mechanisms of antibiotics and microbial functions in anaerobic processes is also summarized. Future research on deeper knowledge of the effect of antibiotics on anaerobic processes are suggested to reduce their adverse environmental impacts.
Cheng, DL, Ngo, HH, Guo, WS, Liu, YW, Zhou, JL, Chang, SW, Nguyen, DD, Bui, XT & Zhang, XB 2018, 'Bioprocessing for elimination antibiotics and hormones from swine wastewater', Science of The Total Environment, vol. 621, pp. 1664-1682.
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© 2017 Elsevier B.V. Antibiotics and hormones in swine wastewater have become a critical concern worldwide due to the severe threats to human health and the eco-environment. Removal of most detectable antibiotics and hormones, such as sulfonamides (SAs), SMs, tetracyclines (TCs), macrolides, and estrogenic hormones from swine wastewater utilizing various biological processes were summarized and compared. In biological processes, biosorption and biodegradation are the two major removal mechanisms for antibiotics and hormones. The residuals in treated effluents and sludge of conventional activated sludge and anaerobic digestion processes can still pose risks to the surrounding environment, and the anaerobic processes’ removal efficiencies were inferior to those of aerobic processes. In contrast, membrane bioreactors (MBRs), constructed wetlands (CWs) and modified processes performed better because of their higher biodegradation of toxicants. Process modification on activated sludge, anaerobic digestion and conventional MBRs could also enhance the performance (e.g. removing up to 98% SMs, 88.9% TCs, and 99.6% hormones from wastewater). The hybrid process combining MBRs with biological or physical technology also led to better removal efficiency. As such, modified conventional biological processes, advanced biological technologies and MBR hybrid systems are considered as a promising technology for removing toxicants from swine wastewater.
Cheng, H-C, Hanson, EP, Datta, N & Hsieh, M-H 2018, 'Non-Asymptotic Classical Data Compression with Quantum Side Information', IEEE Transactions on Information Theory, vol. 67, no. 2, pp. 902-930.
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In this paper, we analyze classical data compression with quantum sideinformation (also known as the classical-quantum Slepian-Wolf protocol) in theso-called large and moderate deviation regimes. In the non-asymptotic setting,the protocol involves compressing classical sequences of finite length $n$ anddecoding them with the assistance of quantum side information. In the largedeviation regime, the compression rate is fixed, and we obtain bounds on theerror exponent function, which characterizes the minimal probability of erroras a function of the rate. Devetak and Winter showed that the asymptotic datacompression limit for this protocol is given by a conditional entropy. For anyprotocol with a rate below this quantity, the probability of error converges toone asymptotically and its speed of convergence is given by the strong converseexponent function. We obtain finite blocklength bounds on this function, anddetermine exactly its asymptotic value. In the moderate deviation regime forthe compression rate, the latter is no longer considered to be fixed. It isallowed to depend on the blocklength $n$, but assumed to decay slowly to theasymptotic data compression limit. Starting from a rate above this limit, wedetermine the speed of convergence of the error probability to zero and showthat it is given in terms of the conditional information variance. Our resultscomplement earlier results obtained by Tomamichel and Hayashi, in which theyanalyzed the so-called small deviation regime of this protocol.
Cheng, L, Acuna, P, Aguilera, RP, Jiang, J, Wei, S, Fletcher, JE & Lu, DDC 2018, 'Model Predictive Control for DC–DC Boost Converters With Reduced-Prediction Horizon and Constant Switching Frequency', IEEE Transactions on Power Electronics, vol. 33, no. 10, pp. 9064-9075.
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© 1986-2012 IEEE. The implementation of multistep direct model predictive control (MPC) for DC-DC boost converters overcomes the well-known issue of nonminimum phase behavior. However, it can lead to a high computational burden depending on the prediction horizon length. In this paper, a simple and computationally efficient MPC method for DC-DC boost converters is proposed. The key novelty of the presented control strategy lies in the way dynamic references are handled. The control strategy is capable of providing suitable references for the inductor current and the output voltage, without requiring additional control loops. Moreover, this reference design allows the predictive controller to be implemented with a single-step prediction horizon. Thus, a significant reduction in the required real-time calculations executed in the control hardware is achieved. To obtain constant switching frequency, the power switch commutation instants within a sampling period are considered as control inputs. Therefore, the predictive controller is formulated as a continuous control set MPC. Additionally, the proposed formulation is able to deal with different operation modes of the converter without changing the controller structure. Finally, an observer is used to dynamically modify the reference to provide robustness to system parameter uncertainties. Simulation and experimental results show an accurate tracking of dynamic inductor current and output voltage references, while respecting the restrictions on maximum inductor current levels of the converter.
Cheng, P, Chen, Z, Zhang, JA, Li, Y & Vucetic, B 2018, 'A Unified Precoding Scheme for Generalized Spatial Modulation', IEEE Transactions on Communications, vol. 66, no. 6, pp. 2502-2514.
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© 1972-2012 IEEE. Generalized spatial modulation (GSM) activates Nt (1 ≤ nt < Nt) available transmit antennas, and information is conveyed through nt modulated symbols as well as the index of the nt activated antennas. GSM strikes an attractive tradeoff between spectrum efficiency and energy efficiency. Linear precoding that exploits channel state information at the transmitter enhances the system error performance. For GSM with nt=1 (the traditional SM), the existing precoding methods suffer from high computational complexity. On the other hand, GSM precoding for nt ≥ 2 is not thoroughly investigated in the open literature. In this paper, we develop a unified precoding design for GSM systems, which universally works for all nt values. Based on the maximum minimum Euclidean distance criterion, we find that the precoding design can be formulated as a large-scale nonconvex quadratically constrained quadratic program problem. Then, we transform this challenging problem into a sequence of unconstrained subproblems by leveraging augmented Lagrangian and dual ascent techniques. These subproblems can be solved in an iterative manner efficiently. Numerical results show that the proposed method can substantially improve the system error performance relative to the GSM without precoding and features extremely fast convergence rate with a very low computational complexity.
Cheng, T, Lu, DD-C & Qin, L 2018, 'Non-Isolated Single-Inductor DC/DC Converter With Fully Reconfigurable Structure for Renewable Energy Applications.', IEEE Trans. Circuits Syst. II Express Briefs, vol. 65-II, no. 3, pp. 351-355.
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© 2017 IEEE. A novel non-isolated three-port converter (NITPC) is introduced in this brief. The purpose of this topology is to integrate a regenerative load such as DC bus and motor with dynamic braking, instead of the widely reported consuming load, with a photovoltaic (PV)-battery system. Conventional methods require either a separate DC-DC converter to process the reversible power flow or employing an isolated three-port converter (TPC), which allows bi-directional power flow between any two ports. However, these methods require many switches, which increases the converter size and control complexity. This brief hence presents a compact but fully functional design by combining and integrating basic converters to form a simplified single-inductor converter structure while keeping a minimum amount of switches. The resultant converter is fully reconfigurable that all possible power flow combinations among the sources and load are achieved through different switching patterns, while preserving the single power processing feature of TPC. This brief presents a design example of the proposed NITPC for a PV-battery powered DC microgrid. Detailed circuitry analysis, operation principles of both DC grid-connected and islanded modes, and experimental results of different modes in steady state and mode transitions are presented.
Cheng, X, Jiang, Z, Monaghan, BJ, Longbottom, RJ, Wei, D, Hee, AC & Jiang, L 2018, 'Degradation of ferritic stainless steels at 1200 °C in air', Materials and Corrosion, vol. 69, no. 1, pp. 63-75.
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Three commercial ferritic stainless steels were investigated at 1200 °C by a thermogravimetric analyser (TGA) in air. The oxidation kinetics of the ferritic stainless steels differed significantly. The adhesion of the Cr2O3 scale, the morphology of the SiO2, with or without (Cr, Mn)3O4 spinel on the top can greatly influence the oxidation and the degradation behaviour of the steels. Although the SUS430 steel had less Cr among the ferritic stainless steels (16.2 wt% Cr), it did not show more degradation behaviour than the B443NT steel (21.0 wt% Cr). The spallation of the protective oxide scale on the B443NT steel was caused by vacancy condensation at the scale/substrate interface where the SiO2 particles were and the developed compressive stresses within the oxide scale during oxidation. (Cr, Mn)3O4 spinel on the top of the Cr2O3 scale on the B445J1M steel influenced its evaporation rate. The thermodynamic aspect of the chemical composition and oxidation atmosphere of the Fe–Cr–O system was also discussed.
Cheng, Z, Zhang, X, Shen, S, Yu, S, Ren, J & Lin, R 2018, 'T-Trail: Link Failure Monitoring in Software-Defined Optical Networks', Journal of Optical Communications and Networking, vol. 10, no. 4, pp. 344-344.
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Monitoring trail (m-trail) provides a striking mechanism for fast and unambiguous link failure localization in all-optical networks. However, allocating dedicated supervisory lightpaths (m-trail) undoubtedly increases total network cost. Accordingly, how to maximally reduce monitoring cost in an optical network is an important issue. To this end, we propose a concept of traffic trail (t-trail) that uses traffic lightpaths, instead of dedicated supervisory lightpaths, to localize a single link failure in the context of a software-defined optical network (SDON). The central controller of an SDON collects routing information of all t-trails in the network. Thus, any link failure can be localized according to the ON-OFF status of the traversing t-trails. We first formulate the problem as an integer linear programming (ILP) model. Since the ILP is not feasible for solving the problem in large-size networks, an efficient heuristic algorithm t-trail allocation (TTA) is proposed to address it. We conduct extensive simulations to evaluate the performance of TTA. The results show that compared with the existing m-trail schemes, TTA can reduce total costs by 20.91% on average.
Chi, L, Li, B, Zhu, X, Pan, S & Chen, L 2018, 'Hashing for Adaptive Real-Time Graph Stream Classification With Concept Drifts', IEEE Transactions on Cybernetics, vol. 48, no. 5, pp. 1591-1604.
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Many applications involve processing networked streaming data in a timely manner. Graph stream classification aims to learn a classification model from a stream of graphs with only one-pass of data, requiring real-time processing in training and prediction. This is a nontrivial task, as many existing methods require multipass of the graph stream to extract subgraph structures as features for graph classification which does not simultaneously satisfy "one-pass" and "real-time" requirements. In this paper, we propose an adaptive real-time graph stream classification method to address this challenge. We partition the unbounded graph stream data into consecutive graph chunks, each consisting of a fixed number of graphs and delivering a corresponding chunk-level classifier. We employ a random hashing function to compress the original node set of graphs in each chunk for fast feature detection when training chunk-level classifiers. Furthermore, a differential hashing strategy is applied to map unlimited increasing features (i.e., cliques) into a fixed-size feature space which is then used as a feature vector for stochastic learning. Finally, the chunk-level classifiers are weighted in an ensemble learning model for graph classification. The proposed method substantially speeds up the graph feature extraction and avoids unbounded graph feature growth. Moreover, it effectively offsets concept drifts in graph stream classification. Experiments on real-world and synthetic graph streams demonstrate that our method significantly outperforms existing methods in both classification accuracy and learning efficiency.
Chia, SR, Chew, KW, Show, PL, Yap, YJ, Ong, HC, Ling, TC & Chang, J-S 2018, 'Analysis of Economic and Environmental Aspects of Microalgae Biorefinery for Biofuels Production: A Review', Biotechnology Journal, vol. 13, no. 6, pp. 1700618-1700618.
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Chia, SR, Ong, HC, Chew, KW, Show, PL, Phang, S-M, Ling, TC, Nagarajan, D, Lee, D-J & Chang, J-S 2018, 'Sustainable approaches for algae utilisation in bioenergy production', Renewable Energy, vol. 129, pp. 838-852.
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Chia, SR, Show, PL, Phang, S-M, Ling, TC & Ong, HC 2018, 'Sustainable approach in phlorotannin recovery from macroalgae', Journal of Bioscience and Bioengineering, vol. 126, no. 2, pp. 220-225.
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Chikara, RK, Chang, EC, Lu, Y-C, Lin, D-S, Lin, C-T & Ko, L-W 2018, 'Monetary Reward and Punishment to Response Inhibition Modulate Activation and Synchronization Within the Inhibitory Brain Network', Frontiers in Human Neuroscience, vol. 12.
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© 2018 Chikara, Chang, Lu, Lin, Lin and Ko. A reward or punishment can modulate motivation and emotions, which in turn affect cognitive processing. The present simultaneous functional magnetic resonance imaging-electroencephalography study examines neural mechanisms of response inhibition under the influence of a monetary reward or punishment by implementing a modified stop-signal task in a virtual battlefield scenario. The participants were instructed to play as snipers who open fire at a terrorist target but withhold shooting in the presence of a hostage. The participants performed the task under three different feedback conditions in counterbalanced order: a reward condition where each successfully withheld response added a bonus (i.e., positive feedback) to the startup credit, a punishment condition where each failure in stopping deduced a penalty (i.e., negative feedback), and a no-feedback condition where response outcome had no consequences and served as a control setting. Behaviorally both reward and punishment conditions led to significantly down-regulated inhibitory function in terms of the critical stop-signal delay. As for the neuroimaging results, increased activities were found for the no-feedback condition in regions previously reported to be associated with response inhibition, including the right inferior frontal gyrus and the pre-supplementary motor area. Moreover, higher activation of the lingual gyrus, posterior cingulate gyrus (PCG) and inferior parietal lobule were found in the reward condition, while stronger activation of the precuneus gyrus was found in the punishment condition. The positive feedback was also associated with stronger changes of delta, theta, and alpha synchronization in the PCG than were the negative or no-feedback conditions. These findings depicted the intertwining relationship between response inhibition and motivation networks.
Chitambar, E, Fortescue, B & Hsieh, M-H 2018, 'The Conditional Common Information in Classical and Quantum Secret Key Distillation', IEEE Transactions on Information Theory, vol. 64, no. 11, pp. 7381-7394.
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© 2018 IEEE. In this paper, we consider two extensions of the Gács-Körner common information to three variables, the conditional common information (cCI) and the coarse-grained conditional common information (ccCI). Both quantities are shown to be useful technical tools in the study of classical and quantum resource transformations. In particular, the ccCI is shown to have an operational interpretation as the optimal rate of secret key extraction from an eavesdropped classical source pXYZ when Alice (X) and Bob (Y) are unable to communicate but share common randomness with the eavesdropper Eve (Z). Moving to the quantum setting, we consider two different ways of generating a tripartite quantum state from classical correlations pXYZ : 1) coherent encodings ∑xyz√pxyz|xyz〉 and 2) incoherent encodings ∑xyzpxyz|xyz〉〈xyz|. We study how well can Alice and Bob extract secret key from these quantum sources using quantum operations compared with the extraction of key from the underlying classical sources pXYZ using classical operations. While the power of quantum mechanics increases Alice and Bob's ability to generate shared randomness, it also equips Eve with a greater arsenal of eavesdropping attacks. Therefore, it is not obvious who gains the greatest advantage for distilling secret key when replacing a classical source with a quantum one. We first demonstrate that the classical key rate of pXYZ is equivalent to the quantum key rate for an incoherent quantum encoding of the distribution. For coherent encodings, we next show that the classical and quantum rates are generally incomparable, and in fact, their difference can be arbitrarily large in either direction. Finally, we introduce a 'zoo' of entangled tripartite states all characterized by the conditional common information of their encoded probability distributions. Remarkably, for these states almost all entanglement measures, such as Alice and Bob's entanglement cost, squashed entanglement, and relative ...
Chiu, SK, Saw, J, Huang, Y, Sonderegger, SE, Wong, NC, Powell, DR, Beck, D, Pimanda, JE, Tremblay, CS & Curtis, DJ 2018, 'A novel role for Lyl1 in primitive erythropoiesis', Development, vol. 145, no. 19.
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Stem Cell Leukemia (Scl or Tal1) and Lymphoblastic Leukemia 1 (Lyl1) are highly related members of the basic helix-loop-helix (bHLH) family of transcription factors that are co- expressed in the erythroid lineage. Previous studies suggest that Scl is essential for primitive erythropoiesis. However, analysis of single-cell RNA-sequencing data of early embryos showed that primitive erythroid cells express both Scl and Lyl1. Therefore, to determine whether Lyl1 can function in primitive erythropoiesis, we crossed conditional Scl knockout mice with mice expressing a Cre recombinase under the control of the Epo receptor, active in erythroid progenitors. Embryos with 20% expression of Scl from E9.5 survived to adulthood. However, mice with reduced expression of Scl and absence of Lyl1 (double knockout; DKO) died at E10.5 due to progressive loss of erythropoiesis. Gene expression profiling of DKO yolk sacs revealed loss of Gata1 and many of the known target genes of the SCL-GATA1 complex. ChIP-seq analyses showed that LYL1 exclusively bound a small subset of SCL targets including GATA1. Together, these data show for the first time that Lyl1 can maintain primitive erythropoiesis.
Choi, I, Milne, DN, Deady, M, Calvo, RA, Harvey, SB & Glozier, N 2018, 'Impact of Mental Health Screening on Promoting Immediate Online Help-Seeking: Randomized Trial Comparing Normative Versus Humor-Driven Feedback', JMIR Mental Health, vol. 5, no. 2, pp. e26-e26.
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Background Given the widespread availability of mental health screening apps, providing personalized feedback may encourage people at high risk to seek help to manage their symptoms. While apps typically provide personal score feedback only, feedback types that are user-friendly and increase personal relevance may encourage further help-seeking. Objective The aim of this study was to compare the effects of providing normative and humor-driven feedback on immediate online help-seeking, defined as clicking on a link to an external resource, and to explore demographic predictors that encourage help-seeking. Methods An online sample of 549 adults were recruited using social media advertisements. Participants downloaded a smartphone app known as “Mindgauge” which allowed them to screen their mental wellbeing by completing standardized measures on Symptoms (Kessler 6-item Scale), Wellbeing (World Health Organization [Five] Wellbeing Index), and Resilience (Brief Resilience Scale). Participants were randomized to receive normative feedback that compared their scores to a reference group or humor-driven feedback that presented their scores in a relaxed manner. Those who scored in the moderate or poor ranges in any measure were encouraged to seek help by clicking on a link to an external online resource. Results A total of 318 participants scored poorly on one or more measures and were provided with an external link after being randomized to receive normative or humor-driven feedback. There was no significant difference of feedback type on clicking on the external link acros...
Choi, I, Milne, DN, Deady, M, Calvo, RA, Harvey, SB & Glozier, N 2018, 'Impact of mental health screening on promoting immediate online help-seeking: Randomized trial comparing normative versus humor-driven feedback', Journal of Medical Internet Research, vol. 20, no. 4.
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Background: Given the widespread availability of mental health screening apps, providing personalized feedback may encourage people at high risk to seek help to manage their symptoms. While apps typically provide personal score feedback only, feedback types that are user-friendly and increase personal relevance may encourage further help-seeking. Objective: The aim of this study was to compare the effects of providing normative and humor-driven feedback on immediate online help-seeking, defined as clicking on a link to an external resource, and to explore demographic predictors that encourage help-seeking. Methods: An online sample of 549 adults were recruited using social media advertisements. Participants downloaded a smartphone app known as “Mindgauge” which allowed them to screen their mental wellbeing by completing standardized measures on Symptoms (Kessler 6-item Scale), Wellbeing (World Health Organization [Five] Wellbeing Index), and Resilience (Brief Resilience Scale). Participants were randomized to receive normative feedback that compared their scores to a reference group or humor-driven feedback that presented their scores in a relaxed manner. Those who scored in the moderate or poor ranges in any measure were encouraged to seek help by clicking on a link to an external online resource. Results: A total of 318 participants scored poorly on one or more measures and were provided with an external link after being randomized to receive normative or humor-driven feedback. There was no significant difference of feedback type on clicking on the external link across all measures. A larger proportion of participants from the Wellbeing measure (170/274, 62.0%) clicked on the links than the Resilience (47/179, 26.3%) or Symptoms (26/75, 34.7%) measures (? =60.35, P<.001). There were no significant demographic factors associated with help-seeking for the Resilience or Wellbeing measures. Participants with a previous episode of poor mental health were l...
Choi, Y, Naidu, G, Jeong, S, Lee, S & Vigneswaran, S 2018, 'Effect of chemical and physical factors on the crystallization of calcium sulfate in seawater reverse osmosis brine', Desalination, vol. 426, pp. 78-87.
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© 2017 Elsevier B.V. A major challenge of seawater reverse osmosis (SWRO) desalination process corresponds to the management of concentrated brine waste because discharging the brine back into the sea influences the marine ecosystem and incurs additional costs to plants. A membrane distillation crystallizer (MDC) can further produce clean water and simultaneously recover valuable resources from the concentrated brine; this is more environmentally and economically optimal. SWRO brine contains salts, which contribute to scaling development during the MDC operation. Hence, the main goals of this study was to observe the crystallization tendency of calcium sulfate (CaSO4) under high salinity and, to examine other inorganic and organic compounds and operational conditions that affect the CaSO4 crystallization. The crystallization tendency of CaSO4 in SWRO brine was examined with respect to different temperatures; changes in pH values; and in the presence of co-existing ions, chemical agents, and organic matters as well as physical factors. The results showed that the size and quantity of crystals formed increased at higher temperatures. Furthermore, an increase in the pH values increased the crystal size. At higher pH, the complexion of NaCl along with CaSO4 was created. Moreover, stirring enhanced CaSO4 crystal formation due to the kinetic mechanism.
Choi, Y, Naidu, G, Jeong, S, Lee, S & Vigneswaran, S 2018, 'Fractional-submerged membrane distillation crystallizer (F-SMDC) for treatment of high salinity solution', Desalination, vol. 440, pp. 59-67.
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© 2018 Elsevier B.V. Membrane distillation with crystallization (MDC) is an attractive process for high saline seawater reverse osmosis (SWRO) brine treatment. MDC produces additional fresh water while simultaneously recovering valuable resources. This study developed a novel approach of fractional-submerged MDC (F-SMDC) process, in which MD and crystallizer are integrated in a feed tank with a submerged membrane. F-SMDC principle is based on the presence of temperature/concentration gradient (TG/CG) in the feed reactor. The operational conditions at the top portion of the feed reactor (higher temperature and lower feed concentration) was well suited for MD operation, while the bottom portion of the reactor (lower temperature and higher concentration) was favourable for crystal growth. F-SMDC performance with direct contact MD to treat brine and produce sodium sulfate (Na2SO4) crystals using TG/CG showed positive results. The TG/CG approach in F-SMDC enabled to achieve higher water recovery for brine treatment with a volume concentration factor (VCF) of over 3.5 compared to VCF of 2.9 with a conventional S-MDC set-up. Further, the high feed concentration and low temperature at the reactor bottom in F-SMDC enabled the formation of Na2SO4 crystals with narrow crystal size distribution.
Chotipant, S, Hussain, FK & Hussain, OK 2018, 'SERNOTATE: An automated approach for business service description annotation for efficient service retrieval and composition', Concurrency and Computation: Practice and Experience, vol. 30, no. 1, pp. e4189-e4189.
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SummaryBusiness service advertisements are today published online to convey essential information about services to customers. However, current Web search engines are unable to search and combine online service advertisements. Semantic service annotation is important for its ability to enable machines to understand the meaning of services and support in effective service retrieval and service composition. Existing research in the area of semantic service annotation has focused on the annotation of Web services in a semi‐automated approach. It cannot be applied to business service information as it is not in the form of Web Services Description Language but in free text format. Moreover, semi‐automated approaches are inappropriate for annotating a large amount of online service information which changes dynamically and they are therefore not suitable for the timely dissemination of service information to customers. To solve these issues, we propose SERNOTATE, which is an automated approach for business service description annotation for efficient service retrieval and composition. We propose new semantic‐based linking approaches, namely, Extended Case‐based Reasoning, vector‐based, and classification‐based, that automatically annotate business services to relevant service concepts. Each approach assists in the single‐label and multi‐label annotation of service terms to concept terms to provide a better representation of services. The experimental results test and validate the applicability of the proposed approaches to the automatic annotation of business service descriptions to service concepts on a real‐world dataset.
Chou, K-P, Prasad, M, Wu, D, Sharma, N, Li, D-L, Lin, Y-F, Blumenstein, M, Lin, W-C & Lin, C-T 2018, 'Robust Feature-Based Automated Multi-View Human Action Recognition System', IEEE Access, vol. 6, pp. 15283-15296.
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© 2013 IEEE. Automated human action recognition has the potential to play an important role in public security, for example, in relation to the multiview surveillance videos taken in public places, such as train stations or airports. This paper compares three practical, reliable, and generic systems for multiview video-based human action recognition, namely, the nearest neighbor classifier, Gaussian mixture model classifier, and the nearest mean classifier. To describe the different actions performed in different views, view-invariant features are proposed to address multiview action recognition. These features are obtained by extracting the holistic features from different temporal scales which are modeled as points of interest which represent the global spatial-temporal distribution. Experiments and cross-data testing are conducted on the KTH, WEIZMANN, and MuHAVi datasets. The system does not need to be retrained when scenarios are changed which means the trained database can be applied in a wide variety of environments, such as view angle or background changes. The experiment results show that the proposed approach outperforms the existing methods on the KTH and WEIZMANN datasets.
Chu Van, T, Ristovski, Z, Surawski, N, Bodisco, TA, Rahman, SMA, Alroe, J, Miljevic, B, Hossain, FM, Suara, K, Rainey, T & Brown, RJ 2018, 'Effect of sulphur and vanadium spiked fuels on particle characteristics and engine performance of auxiliary diesel engines', Environmental Pollution, vol. 243, no. Pt B, pp. 1943-1951.
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© 2018 Elsevier Ltd Particle emission characteristics and engine performance were investigated from an auxiliary, heavy duty, six-cylinder, turbocharged and after-cooled diesel engine with a common rail injection system using spiked fuels with different combinations of sulphur (S) and vanadium (V) spiking. The effect of fuel S content on both particle number (PN) and mass (PM) was clearly observed in this study. Higher PN and PM were observed for fuels with higher S contents at all engine load conditions. This study also found a correlation between fuel S content and nucleation mode particle number concentration which have more harmful impact on human health than larger particles. The highest PN and PM were observed at partial load conditions. In addition, S in fuel resulted in higher viscosity of spiked fuels, which led to lower engine blow-by. Fuel V content was observed in this study, evidencing that it had no clear effect on engine performance and emissions. Increased engine load also resulted in higher engine blow-by. The lower peak of in-cylinder pressure observed at both pre-mixed and diffusion combustion phases with the spiked fuels may be associated with the lower energy content in the fuel blends compared to diesel fuel.
Chu, S, Gao, L, Xiao, M, Luo, Z & Li, H 2018, 'Stress‐based multi‐material topology optimization of compliant mechanisms', International Journal for Numerical Methods in Engineering, vol. 113, no. 7, pp. 1021-1044.
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AbstractIn this paper, a level‐set‐based method is presented to deal with the multi‐material topology optimization of compliant mechanisms with stress constraints. A novel stress‐based multi‐material topology optimization model of compliant mechanisms is proposed. In this model, the multi‐material level set topology description model and the separable stress interpolation scheme are adopted. The weighted sum method is used to deal with the multi‐objective optimization of the output displacement and compliance of compliant mechanisms. The penalty of stresses is also considered in the objective function to control the local stress level in different materials. To solve the optimization problem, the parametric level set method is employed, and the sensitivity analysis is conducted. Application of the method is demonstrated by 2 numerical examples. Results show that the multi‐material structures without undesirable de facto hinges can be obtained. The output displacement and compliance of the compliant mechanisms are optimized, and stress constraints in different materials are simultaneously satisfied.
Chu, S, Gao, L, Xiao, M, Luo, Z, Li, H & Gui, X 2018, 'A new method based on adaptive volume constraint and stress penalty for stress-constrained topology optimization', Structural and Multidisciplinary Optimization, vol. 57, no. 3, pp. 1163-1185.
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© 2017, Springer-Verlag GmbH Germany. This paper focuses on the stress-constrained topology optimization of minimizing the structural volume and compliance. A new method based on adaptive volume constraint and stress penalty is proposed. According to this method, the stress-constrained volume and compliance minimization topology optimization problem is transformed into two simple and related problems: a stress-penalty-based compliance minimization problem and a volume-decision problem. In the former problem, stress penalty is conducted and used to control the local stress level of the structure. To solve this problem, the parametric level set method with the compactly supported radial basis functions is adopted. Meanwhile, an adaptive adjusting scheme of the stress penalty factor is used to improve the control of the local stress level. To solve the volume-decision problem, a combination scheme of the interval search and local search is proposed. Numerical examples are used to test the proposed method. Results show the lightweight design, which meets the stress constraint and whose compliance is simultaneously optimized, can be obtained by the proposed method.
Chuah, C, Wang, J, Tavakoli, J & Tang, Y 2018, 'Novel Bacterial Cellulose-Poly (Acrylic Acid) Hybrid Hydrogels with Controllable Antimicrobial Ability as Dressings for Chronic Wounds', Polymers, vol. 10, no. 12, pp. 1323-1323.
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This investigation examines the combination of poly (acrylic acid) (PAA) and bacterial cellulose (BC) nanofibers to synthesize hydrogel hybrid composites used for wound dressing application. Amoxicillin (AM) was also grafted onto the composites for drug release. Fourier transform infrared analysis and scanning electron microscopy conducted revealed the structure and porosity of the composite being developed, as well as the successful fabrication of BC-PAA composites. The results of mechanical testing and hygroscopicity revealed that the composite shows higher stability than hydrogels which are currently used worldwide, albeit with a slight reduction in swelling capabilities. However, the composite was revealed to be responsive to a rise in pH values with an increase in composite swelling and drug release. These results together with their morphological characteristics suggest that BC-PAA hydrogel hybrid composite is a promising candidate for wound dressing application.
Chuah, S, Li, W, Chen, SJ, Sanjayan, JG & Duan, WH 2018, 'Investigation on dispersion of graphene oxide in cement composite using different surfactant treatments', Construction and Building Materials, vol. 161, pp. 519-527.
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© 2017 Elsevier Ltd Graphene oxide (GO) is a novel class of two-dimensional nanoscale sheet material due to its excellent dispersibility in water, high aspect ratio and good intrinsic strengths. In order to obtain a well-distributed GO-reinforced cement composites, the dispersion of GO in water, alkali and several ionic species are investigated with the aid of UV–vis spectroscopy. High alkalinity and calcium ions are key factors inducing the agglomeration of GO in cement system. Dispersion of GO in simulated pore solution is the culmination of the alkali and salt experiments. Agglomeration of GO occurred when GO contacted with the simulated pore solution, highlighting the necessity to protect GO against such aggressive media. The test on surfactant compatibility was then carried out to ensure GO was effectively dispersed in polycarboxylate, air-entrainment and Gum Arabic admixtures within the pore solution. Polycarboxylate-based superplasticisers gave the most promising results to disperse GO in cement alkaline environment. Flexural experiments was performed to highlight the importance of fabrication protocol on the mechanical properties of GO-cement composites. The result shows that the amount of 0.03% GO by weight of cement can increase the flexural strength of GO-cement composite up to 67%.
Chuang, C-H, Cao, Z, King, J-T, Wu, B-S, Wang, Y-K & Lin, C-T 2018, 'Brain Electrodynamic and Hemodynamic Signatures Against Fatigue During Driving', Frontiers in Neuroscience, vol. 12, no. MAR, pp. 1-12.
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© 2018 Chuang, Cao, King, Wu, Wang and Lin. Fatigue is likely to be gradually cumulated in a prolonged and attention-demanding task that may adversely affect task performance. To address the brain dynamics during a driving task, this study recruited 16 subjects to participate in an event-related lane-departure driving experiment. Each subject was instructed to maintain attention and task performance throughout an hour-long driving experiment. The subjects' brain electrodynamics and hemodynamics were simultaneously recorded via 32-channel electroencephalography (EEG) and 8-source/16-detector functional near-infrared spectroscopy (fNIRS). The behavior performance demonstrated that all subjects were able to promptly respond to lane-deviation events, even if the sign of fatigue arose in the brain, which suggests that the subjects were fighting fatigue during the driving experiment. The EEG event-related analysis showed strengthening alpha suppression in the occipital cortex, a common brain region of fatigue. Furthermore, we noted increasing oxygenated hemoglobin (HbO) of the brain to fight driving fatigue in the frontal cortex, primary motor cortex, parieto-occipital cortex and supplementary motor area. In conclusion, the increasing neural activity and cortical activations were aimed at maintaining driving performance when fatigue emerged. The electrodynamic and hemodynamic signatures of fatigue fighting contribute to our understanding of the brain dynamics of driving fatigue and address driving safety issues through the maintenance of attention and behavioral performance.
Chubb, CT, Tomamichel, M & Korzekwa, K 2018, 'Moderate deviation analysis of majorisation-based resource interconversion', Phys. Rev. A, vol. 99, no. 3, p. 032332.
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We consider the problem of interconverting a finite amount of resourceswithin all theories whose single-shot transformation rules are based on amajorisation relation, e.g. the resource theories of entanglement and coherence(for pure state transformations), as well as thermodynamics (forenergy-incoherent transformations). When only finite resources are available weexpect to see a non-trivial trade-off between the rate $r_n$ at which $n$copies of a resource state $\rho$ can be transformed into $nr_n$ copies ofanother resource state $\sigma$, and the error level $\varepsilon_n$ of theinterconversion process, as a function of $n$. In this work we derive theoptimal trade-off in the so-called moderate deviation regime, where the rate ofinterconversion $r_n$ approaches its optimum in the asymptotic limit ofunbounded resources ($n\to\infty$), while the error $\epsilon_n$ vanishes inthe same limit. We find that the moderate deviation analysis exhibits aresonance behaviour which implies that certain pairs of resource states can beinterconverted at the asymptotically optimal rate with negligible error, evenin the finite $n$ regime.
Clarke, C, Liu, D, Wang, F, Liu, Y, Chen, C, Ton-That, C, Xu, X & Jin, D 2018, 'Large-scale dewetting assembly of gold nanoparticles for plasmonic enhanced upconversion nanoparticles', Nanoscale, vol. 10, no. 14, pp. 6270-6276.
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The integrated methods of core shell upconversion nanoparticle synthesis, thermal annealing and gold dewetting produce gold-decorated upconversion nanoparticles with enhanced emission.
Clement, S, Chen, W, Deng, W & Goldys, EM 2018, 'X-ray radiation-induced and targeted photodynamic therapy with folic acid-conjugated biodegradable nanoconstructs', International Journal of Nanomedicine, vol. Volume 13, pp. 3553-3570.
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Clemon, LM & Zohdi, TI 2018, 'On the tolerable limits of granulated recycled material additives to maintain structural integrity', Construction and Building Materials, vol. 167, pp. 846-852.
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© 2018 Elsevier Ltd Production and maker spaces are increasingly generating mixed plastic material waste of varying quality from 3-D printers. Industrial interest is growing in embedding granulated recycled particulate material additives into a virgin binding matrix. Examples include the introduction of granulated mixed recycled materials into 3-D printer material, concrete, and pavement. The stress load-sharing between the particulate additive and the binding matrix is an important factor in design and development of these composite materials. With mixed material additives, a designer is interested in the variation of such predicted load-sharing. However, experimental development is costly and time-consuming, thus analytical and semi-analytical estimates are desired for accelerated development. In this work, we expand on previous analytically correlated phase-averaged micro- and macrostructural loading to include variational effects present in mixed recycled material. In addition, model trade-offs are provided to aid designers in quickly selecting application specific mixtures. This framework identifies the stress contributions, and their variation, to reduce product development time and costs, which could greatly accelerate material recycling and reuse for improved infrastructure materials, low-cost 3-D printer filament, and reduced waste towards a more circular economy.
Cliff, O, Prokopenko, M & Fitch, R 2018, 'Minimising the Kullback–Leibler Divergence for Model Selection in Distributed Nonlinear Systems', Entropy, vol. 20, no. 2, pp. 51-51.
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The Kullback–Leibler (KL) divergence is a fundamental measure of information geometry that is used in a variety of contexts in artificial intelligence. We show that, when system dynamics are given by distributed nonlinear systems, this measure can be decomposed as a function of two information-theoretic measures, transfer entropy and stochastic interaction. More specifically, these measures are applicable when selecting a candidate model for a distributed system, where individual subsystems are coupled via latent variables and observed through a filter. We represent this model as a directed acyclic graph (DAG) that characterises the unidirectional coupling between subsystems. Standard approaches to structure learning are not applicable in this framework due to the hidden variables; however, we can exploit the properties of certain dynamical systems to formulate exact methods based on differential topology. We approach the problem by using reconstruction theorems to derive an analytical expression for the KL divergence of a candidate DAG from the observed dataset. Using this result, we present a scoring function based on transfer entropy to be used as a subroutine in a structure learning algorithm. We then demonstrate its use in recovering the structure of coupled Lorenz and Rössler systems.
Cliff, OM, Saunders, DL & Fitch, R 2018, 'Robotic ecology: Tracking small dynamic animals with an autonomous aerial vehicle', Science Robotics, vol. 3, no. 23.
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Estimation algorithms for wildlife tracking with an autonomous aerial robot are supported by field validation with wild swift parrots.
Coglitore, D, Merenda, A, Giamblanco, N, Dumée, LF, Janot, J-M & Balme, S 2018, 'Metal alloy solid-state nanopores for single nanoparticle detection', Physical Chemistry Chemical Physics, vol. 20, no. 18, pp. 12799-12807.
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We design metal alloy nanopore to detect nanoparticle and propose an original model to estimate the relative current blockade.
Coiera, E, Kocaballi, B, Halamka, J & Laranjo, L 2018, 'Author Correction: The digital scribe', npj Digital Medicine, vol. 1, no. 1.
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The original version of the published Article contained an error in the spelling of the third Author’s name. “John Halamaka” has been changed to “John Halamka”. This has been corrected in the HTML and PDF version of the Article.
Coiera, E, Kocaballi, B, Halamka, J & Laranjo, L 2018, 'The digital scribe', npj Digital Medicine, vol. 1, no. 1.
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AbstractCurrent generation electronic health records suffer a number of problems that make them inefficient and associated with poor clinical satisfaction. Digital scribes or intelligent documentation support systems, take advantage of advances in speech recognition, natural language processing and artificial intelligence, to automate the clinical documentation task currently conducted by humans. Whilst in their infancy, digital scribes are likely to evolve through three broad stages. Human led systems task clinicians with creating documentation, but provide tools to make the task simpler and more effective, for example with dictation support, semantic checking and templates. Mixed-initiative systems are delegated part of the documentation task, converting the conversations in a clinical encounter into summaries suitable for the electronic record. Computer-led systems are delegated full control of documentation and only request human interaction when exceptions are encountered. Intelligent clinical environments permit such augmented clinical encounters to occur in a fully digitised space where the environment becomes the computer. Data from clinical instruments can be automatically transmitted, interpreted using AI and entered directly into the record. Digital scribes raise many issues for clinical practice, including new patient safety risks. Automation bias may see clinicians automatically accept scribe documents without checking. The electronic record also shifts from a human created summary of events to potentially a full audio, video and sensor record of the clinical encounter. Digital scribes promisingly offer a gateway into the clinical workflow for more advanced support for diagnostic, prognostic and therapeutic tasks.
Combes, J, Ferrie, C, Leifer, MS & Pusey, MF 2018, 'Why protective measurement does not establish the reality of the quantum state', Quantum Studies: Mathematics and Foundations, vol. 5, no. 2, pp. 189-211.
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Cook, AJ, Ng, B, Gargiulo, GD, Hindmarsh, D, Pitney, M, Lehmann, T & Hamilton, TJ 2018, 'Instantaneous VO2 from a wearable device', Medical Engineering & Physics, vol. 52, pp. 41-48.
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© 2018 IPEM We present a method for calculating instantaneous oxygen uptake (VO2) through the use of a non-invasive and non-obtrusive (i.e. without a face mask) wearable device, together with its clinical evaluation against a standard technique based upon expired gas calorimetry. This method can be integrated with existing wearable devices, we implemented it in the “Device for Reliable Energy Expenditure Monitoring” (DREEM). The DREEM comprises a single lead electrocardiogram (ECG) device combined with a tri-axial accelerometer and is worn around the waist. Our clinical evaluation tests the developed method against a gold standard for VO2, expired gas calorimetry, using an ethically approved protocol comprising active exercise and sedentary periods. The study was performed on 42 participants from a wide sample population including healthy people, athletes and an at-risk health group including persons affected by obesity. We developed an algorithm combining heart rate (HR) and the integral of absolute acceleration (IAA), with results showing a correlation of r = 0.93 for instantaneous VO2, and r = 0.97 for 3 min mean VO2, this is a considerably improved estimation of VO2 in comparison to methods utilising HR and IAA independently.
Corsetti, S, Rabl, T, McGloin, D & Nabi, G 2018, 'Raman spectroscopy for accurately characterizing biomolecular changes in androgen‐independent prostate cancer cells', Journal of Biophotonics, vol. 11, no. 3, pp. e201700166-e201700166.
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Metastatic prostate cancer resistant to hormonal manipulation is considered the advanced stage of the disease and leads to most cancer‐related mortality. With new research focusing on modulating cancer growth, it is essential to understand the biochemical changes in cells that can then be exploited for drug discovery and for improving responsiveness to treatment. Raman spectroscopy has a high chemical specificity and can be used to detect and quantify molecular changes at the cellular level. Collection of large data sets generated from biological samples can be employed to form discriminatory algorithms for detection of subtle and early changes in cancer cells. The present study describes Raman finger printing of normal and metastatic hormone‐resistant prostate cancer cells including analyses with principal component analysis and linear discrimination. Amino acid‐specific signals were identified, especially loss of arginine band. Androgen‐resistant prostate cancer cells presented a higher content of phenylalanine, tyrosine, DNA and Amide III in comparison to PNT2 cells, which possessed greater amounts of L‐arginine and had a B conformation of DNA. The analysis utilized in this study could reliably differentiate the 2 cell lines (sensitivity 95%; specificity 88%).
Cu Thi, P, Ball, JE & Dao, NH 2018, 'Uncertainty Estimation Using the Glue and Bayesian Approaches in Flood Estimation: A case Study—Ba River, Vietnam', Water, vol. 10, no. 11, pp. 1641-1641.
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In the last few decades tremendous progress has been made in the use of catchment models for the analysis and understanding of hydrologic systems. A common application involves the use of these models to predict flows at catchment outputs. However, the outputs predicted by these models are often deterministic because they focused only on the most probable forecast without an explicit estimate of the associated uncertainty. This paper uses Bayesian and Generalized Likelihood Uncertainty Estimation (GLUE) approaches to estimate uncertainty in catchment modelling parameter values and uncertainty in design flow estimates. Testing of join probability of both these estimates has been conducted for a monsoon catchment in Vietnam. The paper focuses on computational efficiency and the differences in results, regardless of the philosophies and mathematical rigor of both methods. It was found that the application of GLUE and Bayesian techniques resulted in parameter values that were statistically different. The design flood quantiles estimated by the GLUE method were less scattered than those resulting from the Bayesian approach when using a closer threshold value (1 standard deviation departed from the mean). More studies are required to evaluate the impact of threshold in GLUE on design flood estimation.
Cui, L, Hu, H, Yu, S, Yan, Q, Ming, Z, Wen, Z & Lu, N 2018, 'DDSE: A novel evolutionary algorithm based on degree-descending search strategy for influence maximization in social networks', Journal of Network and Computer Applications, vol. 103, pp. 119-130.
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Influence maximization (IM) is the problem of finding a small subset of nodes in a social network so that the number of nodes influenced by this subset can be maximized. Influence maximization problem plays an important role in viral marketing and information diffusions. The existing solutions to influence maximization perform badly in either efficiency or accuracy. In this study, we analyze the causes for the low efficiency of the greedy approaches and propose a more efficient algorithm called degree-descending search evolution (DDSE). Firstly, we propose a degree-descending search strategy (DDS). DDS is capable of generating a node set whose influence spread is comparable to the degree centrality. Based on DDS, we develop an evolutionary algorithm that is capable of improving the efficiency significantly by eliminating the time-consuming simulations of the greedy algorithms. Experimental results on real-world social networks demonstrate that DDSE is about five orders of magnitude faster than the state-of-art greedy method while keeping competitive accuracy, which can verify the high effectiveness and efficiency of our proposed algorithm for influence maximization.
Cui, L, Yue, L, Wen, D & Qin, L 2018, 'K-Connected Cores Computation in Large Dual Networks.', Data Sci. Eng., vol. 3, no. 4, pp. 293-306.
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© 2018, The Author(s). Computing k- cores is a fundamental and important graph problem, which can be applied in many areas, such as community detection, network visualization, and network topology analysis. Due to the complex relationship between different entities, dual graph widely exists in the applications. A dual graph contains a physical graph and a conceptual graph, both of which have the same vertex set. Given that there exist no previous studies on the k- core in dual graphs, we formulate a k-connected core (k- CCO) model in dual graphs. A k- CCO is a k- core in the conceptual graph, and also connected in the physical graph. Given a dual graph and an integer k, we propose a polynomial time algorithm for computing all k- CCOs. We also propose three algorithms for computing all maximum-connected cores (MCCO), which are the existing k- CCOs such that a (k+ 1) -CCO does not exist. We further study a subgraph search problem, which is computing a k- CCO that contains a set of query vertices. We propose an index-based approach to efficiently answer the query for any given parameter k. We conduct extensive experiments on six real-world datasets and four synthetic datasets. The experimental results demonstrate the effectiveness and efficiency of our proposed algorithms.
Cui, Q, Gu, Y, Ni, W, Zhang, X, Tao, X, Zhang, P & Liu, RP 2018, 'Preserving Reliability of Heterogeneous Ultra-Dense Distributed Networks in Unlicensed Spectrum', IEEE Communications Magazine, vol. 56, no. 6, pp. 72-78.
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© 1979-2012 IEEE. This article investigates the prominent dilemma between capacity and reliability in heterogeneous ultra-dense distributed networks, and advocates a new measure of effective capacity to quantify the maximum sustainable data rate of a link while preserving the quality of service of the link in such networks. Recent breakthroughs are brought forth in developing the theory of the effective capacity in heterogeneous ultra-dense distributed networks. Potential applications of the effective capacity are demonstrated on the admission control, power control, and resource allocation of such networks, with substantial gains revealed over existing technologies. This new measure is of particular interest to ultra-dense deployment of the emerging 5G wireless networks in the unlicensed spectrum, leveraging the capacity gain brought by the use of the unlicensed band and the stringent reliability sustained by 5G in future heterogeneous network environments.
Cui, Z, Wang, J, Zhang, H, Ngo, HH, Jia, H, Guo, W, Gao, F, Yang, G & Kang, D 2018, 'Investigation of backwashing effectiveness in membrane bioreactor (MBR) based on different membrane fouling stages', Bioresource Technology, vol. 269, pp. 355-362.
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In this study the effect of different fouling stages of hollow fiber membranes on effective backwashing length in MBR has been investigated. Computational fluid dynamics (CFD) is imported to simulate backwashing process. A multi-physics coupling model for free porous media flow, convective mass transfer and diluted species transport was established. The laser bijection sensors (LBS) were imported to monitor the backwashing solution position inside fiber lumen. Simulation results indicated that membrane fouling degree could change the velocity of backwash solution inside fiber lumen and make a further effect on effective backwash length. The signal variations of LBS are in accordance with the simulation results. The backwashing process can only play an active role when the filtration pressure is below the critical TMP. It can be concluded that backwash duration in industrial applications need to be set based on changes in TMP.
D’Urso, G, Smith, SL, Mettu, R, Oksanen, T & Fitch, R 2018, 'Multi-vehicle refill scheduling with queueing', Computers and Electronics in Agriculture, vol. 144, pp. 44-57.
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© 2017 We consider the problem of refill scheduling for a team of vehicles or robots that must contend for access to a single physical location for refilling. The objective is to minimise time spent in travelling to/from the refill station, and also time lost to queuing (waiting for access). In this paper, we present principled results for this problem in the context of agricultural operations. We first establish that the problem is NP-hard and prove that the maximum number of vehicles that can usefully work together is bounded. We then focus on the design of practical algorithms and present two solutions. The first is an exact algorithm based on dynamic programming that is suitable for small problem instances. The second is an approximate anytime algorithm based on the branch and bound approach that is suitable for large problem instances with many robots. We present simulated results of our algorithms for three classes of agricultural work that cover a range of operations: spot spraying, broadcast spraying and slurry application. We show that the algorithm is reasonably robust to inaccurate prediction of resource utilisation rate, which is difficult to estimate in cases such as spot application of herbicide for weed control, and validate its performance in simulation using realistic scenarios with up to 30 robots.
da Rocha, CG & Kemmer, S 2018, 'Integrating product and process design in construction', Construction Management and Economics, vol. 36, no. 9, pp. 535-543.
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© 2018, © 2018 Informa UK Limited, trading as Taylor & Francis Group. Product modularity namely the notion that products can be decomposed into parts (or modules) has been widely applied in manufacturing but not in construction, precluding this industry to also benefit from it. The narrow definition of a module, which is often simplistically equated to a sub-assembly produced off-site, and the lack of integration between product and process design, which is typical in construction, are argued to be two root causes of such problem. This paper starts by discussing the operational implications of misaligned decisions in these two domains in an empirical study addressing a high-rise apartments building project. Seven guidelines are then devised using a Design Science Research (DSR) approach for integrating product (product modularity and modules) and process (work structure and work packages) design. The results indicate that product modularity can be applied for improving operations regardless of the construction method(s) used. Yet, a revised understanding of modules (as a material, a component, a non-volumetric or a volumetric sub-assembly) is needed in addition to a coordinated product and process design, particularly for traditional construction.
da Rocha, CG & Miron, LIG 2018, 'The House Factory: A Simulation Game for Understanding Mass Customization in House Building', Journal of Professional Issues in Engineering Education and Practice, vol. 144, no. 1, pp. 05017007-05017007.
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Dadzie, J, Runeson, G & Ding, G 2018, 'Determinants of sustainable upgrade for energy efficiency – the case of existing buildings in Australia', Energy Procedia, vol. 153, pp. 284-289.
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© 2018 The Authors. Published by Elsevier Ltd. The impact of existing buildings on the environment is on the rise; thus to achieve environmental sustainability requires sustainable upgrade (SU) of existing built facilities. Over the years, SU has focused on technologies with little attention given to the nature and conditions of existing buildings. The purpose of this paper is to identify existing building characteristics that impact SU. A detailed literature review on the nature and characteristics of existing buildings, as well as energy and environmental performance was undertaken. A survey questionnaire with all the determinants of existing buildings was administered to sustainability and construction professionals in Australia. The results show that size of building, age of building, U-value of wall, U-value of ceiling, area of external wall, thickness of insulation materials, occupancy, size of window opening, life span of sustainable technologies, and the type of building impact sustainable upgrade of existing buildings for energy efficiency.
Dadzie, J, Runeson, G, Ding, G & Bondinuba, F 2018, 'Barriers to Adoption of Sustainable Technologies for Energy-Efficient Building Upgrade—Semi-Structured Interviews', Buildings, vol. 8, no. 4, pp. 57-57.
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Globally, only 2% of existing building stock is built yearly; the remaining 98% already exist. Energy consumption and indoor thermal comfort of the existing building stock are not encouraging. This is due to many challenges associated with existing buildings; the challenges range from cracks, leakages, poor insulation, heat losses and high rate of unsustainable technologies. This paper investigates possible barriers facing the adoption and application of sustainable technologies (STs) for sustainable or energy-efficient upgrade of existing buildings. New STs are manufactured on a regular basis to meet improved energy efficiency standards, yet there are minimal actions/attempts to adopt and apply improved technologies in existing buildings for energy efficiency. Indeed, there are limited studies focused on the use of qualitative approaches to identify barriers to adoption and use of STs. Thus, a semi-structured interview approach was adopted and applied using sustainability/energy efficiency professionals, building services engineers, project managers, architects, and facility managers in Australia. The results indicate that barriers to the adoption and application of sustainable technologies are perceived benefits in demolish-and-build, age of building, cost of STs, perceived poor payback time, unreliable energy-savings projections, existing design, hidden and overall cost of renovation, and cost of STs.
Dai, S, Tymchenko, M, Xu, Z-Q, Tran, TT, Yang, Y, Ma, Q, Watanabe, K, Taniguchi, T, Jarillo-Herrero, P, Aharonovich, I, Basov, DN, Tao, TH & Alù, A 2018, 'Internal Nanostructure Diagnosis with Hyperbolic Phonon Polaritons in Hexagonal Boron Nitride', Nano Letters, vol. 18, no. 8, pp. 5205-5210.
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Copyright © 2018 American Chemical Society. Imaging materials and inner structures with resolution below the diffraction limit has become of fundamental importance in recent years for a wide variety of applications. We report subdiffractive internal structure diagnosis of hexagonal boron nitride by exciting and imaging hyperbolic phonon polaritons. On the basis of their unique propagation properties, we are able to accurately locate defects in the crystal interior with nanometer resolution. The precise location, size, and geometry of the concealed defects are reconstructed by analyzing the polariton wavelength, reflection coefficient, and their dispersion. We have also studied the evolution of polariton reflection, transmission, and scattering as a function of defect size and photon frequency. The nondestructive high-precision polaritonic structure diagnosis technique introduced here can be also applied to other hyperbolic or waveguide systems and may be deployed in the next-generation biomedical imaging, sensing, and fine structure analysis.
Damanik, N, Ong, HC, Tong, CW, Mahlia, TMI & Silitonga, AS 2018, 'A review on the engine performance and exhaust emission characteristics of diesel engines fueled with biodiesel blends', Environmental Science and Pollution Research, vol. 25, no. 16, pp. 15307-15325.
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© 2018, Springer-Verlag GmbH Germany, part of Springer Nature. Biodiesels have gained much popularity because they are cleaner alternative fuels and they can be used directly in diesel engines without modifications. In this paper, a brief review of the key studies pertaining to the engine performance and exhaust emission characteristics of diesel engines fueled with biodiesel blends, exhaust aftertreatment systems, and low-temperature combustion technology is presented. In general, most biodiesel blends result in a significant decrease in carbon monoxide and total unburned hydrocarbon emissions. There is also a decrease in carbon monoxide, nitrogen oxide, and total unburned hydrocarbon emissions while the engine performance increases for diesel engines fueled with biodiesels blended with nano-additives. The development of automotive technologies, such as exhaust gas recirculation systems and low-temperature combustion technology, also improves the thermal efficiency of diesel engines and reduces nitrogen oxide and particulate matter emissions.
Das, A, Suwanwiwat, H, Ferrer, MA, Pal, U & Blumenstein, M 2018, 'Thai Automatic signature verification System Employing Textural Features', IET Biometrics, vol. 7, no. 6, pp. 615-627.
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© The Institution of Engineering and Technology 2018. This study focuses on a comprehensive study of Automatic Signature Verification (ASV) for off-line Thai signatures; an investigation was carried out to characterise the challenges in Thai ASV and to baseline the performance of Thai ASV employing baseline features, being Local Binary Pattern, Local Directional Pattern, Local Binary and Directional Patterns combined (LBDP), and the baseline shape/feature-based hidden Markov model. As there was no publicly available Thai signature database found in the literature, the authors have developed and proposed a database considering real-world signatures from Thailand. The authors have also identified their latent challenges and characterised Thai signature-based ASV. The database consists of 5,400 signatures from 100 signers. Thai signatures could be bi-script in nature, considering the fact that a single signature can contain only Thai or Roman characters or contain both Roman and Thai, which poses an interesting challenge for script-independent SV. Therefore, along with the baseline experiments, the investigation on the influence and nature of bi-script ASV was also conducted. From the equal error rates and Bhattacharyya distance, the score achieved in the experiments indicate that the Thai SV scenario is a script-independent problem. The open research area on this subject of research has also been addressed.
De Medeiros, JF, Da Rocha, CG & Ribeiro, JLD 2018, 'Design for sustainable behavior (DfSB): Analysis of existing frameworks of behavior change strategies, experts' assessment and proposal for a decision support diagram', Journal of Cleaner Production, vol. 188, pp. 402-415.
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Deady, M, Johnston, D, Milne, D, Glozier, N, Peters, D, Calvo, R & Harvey, S 2018, 'Preliminary Effectiveness of a Smartphone App to Reduce Depressive Symptoms in the Workplace: Feasibility and Acceptability Study', JMIR mHealth and uHealth, vol. 6, no. 12, pp. e11661-e11661.
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© Mark Deady, David Johnston, David Milne, Nick Glozier, Dorian Peters, Rafael Calvo, Samuel Harvey. Background: The workplace represents a unique setting for mental health interventions. Due to range of job-related factors, employees in male-dominated industries are at an elevated risk. However, these at-risk groups are often overlooked. HeadGear is a smartphone app–based intervention designed to reduce depressive symptoms and increase well-being in these populations. Objective: This paper presents the development and pilot testing of the app’s usability, acceptability, feasibility, and preliminary effectiveness. Methods: The development process took place from January 2016 to August 2017. Participants for prototype testing (n=21; stage 1) were recruited from industry partner organizations to assess acceptability and utility. A 5-week effectiveness and feasibility pilot study (n=84; stage 2) was then undertaken, utilizing social media recruitment. Demographic data, acceptability and utility questionnaires, depression (Patient Health Questionnaire-9), and other mental health measures were collected. Results: The majority of respondents felt HeadGear was easy to use (92%), easily understood (92%), were satisfied with the app (67%), and would recommend it to a friend (75%; stage 1). Stage 2 found that compared with baseline, depression and anxiety symptoms were significantly lower at follow-up (t30=2.53; P=.02 and t30=2.18; P=.04, respectively), days of sick leave in past month (t28=2.38; P=.02), and higher self-reported job performance (t28=−2.09; P=.046; stage 2). Over 90% of respondents claimed it helped improve their mental fitness, and user feedback was again positive. Attrition was high across the stages. Conclusions: Overall, HeadGear was well received, and preliminary findings indicate it may provide an innovative new platform for improving mental health outcomes. Unfortunately, attrition was a significant issue, and findings should be interpreted...
Deady, M, Johnston, D, Milne, D, Glozier, N, Peters, D, Calvo, R & Harvey, S 2018, 'Preliminary effectiveness of a smartphone app to reduce depressive symptoms in the workplace: Feasibility and acceptability study', Journal of Medical Internet Research, vol. 20, no. 12.
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© Mark Deady, David Johnston, David Milne, Nick Glozier, Dorian Peters, Rafael Calvo, Samuel Harvey. Background: The workplace represents a unique setting for mental health interventions. Due to range of job-related factors, employees in male-dominated industries are at an elevated risk. However, these at-risk groups are often overlooked. HeadGear is a smartphone app–based intervention designed to reduce depressive symptoms and increase well-being in these populations. Objective: This paper presents the development and pilot testing of the app’s usability, acceptability, feasibility, and preliminary effectiveness. Methods: The development process took place from January 2016 to August 2017. Participants for prototype testing (n=21; stage 1) were recruited from industry partner organizations to assess acceptability and utility. A 5-week effectiveness and feasibility pilot study (n=84; stage 2) was then undertaken, utilizing social media recruitment. Demographic data, acceptability and utility questionnaires, depression (Patient Health Questionnaire-9), and other mental health measures were collected. Results: The majority of respondents felt HeadGear was easy to use (92%), easily understood (92%), were satisfied with the app (67%), and would recommend it to a friend (75%; stage 1). Stage 2 found that compared with baseline, depression and anxiety symptoms were significantly lower at follow-up (t30=2.53; P=.02 and t30=2.18; P=.04, respectively), days of sick leave in past month (t28=2.38; P=.02), and higher self-reported job performance (t28=−2.09; P=.046; stage 2). Over 90% of respondents claimed it helped improve their mental fitness, and user feedback was again positive. Attrition was high across the stages. Conclusions: Overall, HeadGear was well received, and preliminary findings indicate it may provide an innovative new platform for improving mental health outcomes. Unfortunately, attrition was a significant issue, and findings should be interpreted...
Deady, M, Johnston, DA, Glozier, N, Milne, D, Choi, I, Mackinnon, A, Mykletun, A, Calvo, RA, Gayed, A, Bryant, R, Christensen, H & Harvey, SB 2018, 'A smartphone application for treating depressive symptoms: study protocol for a randomised controlled trial', BMC Psychiatry, vol. 18, no. 1, pp. 1-9.
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© 2018 The Author(s). Background: Depression is a commonly occurring disorder linked to diminished role functioning and quality of life. The development of treatments that overcome barriers to accessing treatment remains an important area of clinical research as most people delay or do not receive treatment at an appropriate time. The workplace is an ideal setting to roll-out an intervention, particularly given the substantial psychological benefits associated with remaining in the workforce. Mobile health (mhealth) interventions utilising smartphone applications (apps) offer novel solutions to disseminating evidence based programs, however few apps have undergone rigorous testing. The present study aims to evaluate the effectiveness of a smartphone app designed to treat depressive symptoms in workers. Methods: The present study is a multicentre randomised controlled trial (RCT), comparing the effectiveness of the intervention to that of an attention control. The primary outcome measured will be reduced depressive symptoms at 3 months. Secondary outcomes such as wellbeing and work performance will also be measured. Employees from a range of industries will be recruited via a mixture of targeted social media advertising and Industry partners. Participants will be included if they present with likely current depression at baseline. Following baseline assessment (administered within the app), participants will be randomised to receive one of two versions of the Headgear application: 1) Intervention (a 30-day mental health intervention focusing on behavioural activation and mindfulness), or 2) attention control app (mood monitoring for 30 days). Participants will be blinded to their allocation. Analyses will be conducted within an intention to treat framework using mixed modelling. Discussion: The results of this trial will provide valuable information about the effectiveness of mhealth interventions in the treatment of depressive symptoms in a workplace context.
Deady, M, Johnston, DA, Glozier, N, Milne, D, Choi, I, Mackinnon, A, Mykletun, A, Calvo, RA, Gayed, A, Bryant, R, Christensen, H & Harvey, SB 2018, 'Smartphone application for preventing depression: study protocol for a workplace randomised controlled trial', BMJ Open, vol. 8, no. 7, pp. e020510-e020510.
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IntroductionDepression is the leading cause of life years lost due to disability. Appropriate prevention has the potential to reduce the incidence of new cases of depression, however, traditional prevention approaches face significant scalability issues. Prevention programmes delivered by via smartphone applications provide a potential solution. The workplace is an ideal setting to roll out this form of intervention, particularly among industries that are unlikely to access traditional health initiatives and whose workplace characteristics create accessibility and portability issues. The study aims to evaluate the effectiveness of a smartphone application designed to prevent depression and improve well-being. The effectiveness of the app as a universal, selective and indicated prevention tool will also be evaluated.Methods and analysisA multicentre randomised controlled trial, to determine the effectiveness of the intervention compared with an active mood monitoring control in reducing depressive symptoms (primary outcome) and the prevalence of depression at 3 months, with secondary outcomes assessing well-being and work performance. Employees from a range of industries will be invited to participate. Participants with likely current depression at baseline will be excluded. Following baseline assessment, participants, blinded to their allocation, will be randomised to receive one of two versions of the application: headgear (a 30-day mental health intervention) or a control application (mood monitoring for 30 days). Both versions of the app contain a risk calculator to provide a measure of future risk. Analyses will be conducted within an intention-to-treat framework using mixed modelling, with additional analyses conducted to compare the moderating effect of baseline risk level and depression symptom severity on the intervention’s effectiveness.
Deng, L, Ngo, H-H, Guo, W, Wang, J & Zhang, H 2018, 'Evaluation of a new sponge addition-microbial fuel cell system for removing nutrient from low C/N ratio wastewater', Chemical Engineering Journal, vol. 338, pp. 166-175.
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© 2018 This study developed a new microbial fuel cell (MFC) system (Sponge-MFC), which consisted of a cathodic chamber with an added sponge and two anodic chambers, for low carbon/nitrogen (C/N) wastewater treatment. When operating in the closed-circuit state, the Sponge-MFC(C) demonstrated its superior electrochemical performance compared to the closed-circuit MFC. This superiority took the form of higher coulombic efficiencies, voltage outputs, current densities and power densities. Adding a sponge could reduce the cathode's charge transfer resistance and solution resistance, and improve its capacitance, thus increasing cathodic reaction rate and power outputs. Simultaneous nitrification denitrification (SND) and bioelectrochemical denitrification processes on the cathode coupled with the sponge's SND process were responsible for efficient removal of nitrogen from the Sponge-MFC(C). Fluorescent in situ hybridization (FISH) analysis revealed that nitrifying bacteria and highly diversified denitrifying bacteria were distributed at the cathode's outer layer and inner layer, respectively. Higher phosphorus removal efficiencies (82.06 ± 1.21%) in the Sponge-MFC(C) than that in the MFC(C) (53.97 ± 2.32%) could be ascribed to biological phosphorus removal and precipitation of phosphate salts on the cathode. These results suggested the Sponge-MFC(C) could accomplish better electrochemical behaviors and nutrient removal due to sponge addition when treating wastewater with low C/N ratio.
Deng, W, Chen, W, Clement, S, Guller, A, Zhao, Z, Engel, A & Goldys, EM 2018, 'Controlled gene and drug release from a liposomal delivery platform triggered by X-ray radiation', Nature Communications, vol. 9, no. 1, p. 2713.
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AbstractLiposomes have been well established as an effective drug delivery system, due to simplicity of their preparation and unique characteristics. However conventional liposomes are unsuitable for the on-demand content release, which limits their therapeutic utility. Here we report X-ray-triggerable liposomes incorporating gold nanoparticles and photosensitizer verteporfin. The 6 MeV X-ray radiation induces verteporfin to produce singlet oxygen, which destabilises the liposomal membrane and causes the release of cargos from the liposomal cavity. This triggering strategy is demonstrated by the efficiency of gene silencing in vitro and increased effectiveness of chemotherapy in vivo. Our work indicates the feasibility of a combinatorial treatment and possible synergistic effects in the course of standard radiotherapy combined with chemotherapy delivered via X-ray-triggered liposomes. Importantly, our X-ray-mediated liposome release strategy offers prospects for deep tissue photodynamic therapy, by removing its depth limitation.
Deng, W, Goldys, EM & Zhao, Z 2018, 'Release of doxorubicin from liposomes by x-ray radiation', Nanomedicine: Nanotechnology, Biology and Medicine, vol. 14, no. 5, pp. 1753-1753.
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Deng, Z, Chen, J, Zhang, T, Cao, L & Wang, S 2018, 'Generalized Hidden-Mapping Minimax Probability Machine for the training and reliability learning of several classical intelligent models', Information Sciences, vol. 436-437, pp. 302-319.
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© 2018 Elsevier Inc. Minimax Probability Machine (MPM) is a binary classifier that optimizes the upper bound of the misclassification probability. This upper bound of the misclassification probability can be used as an explicit indicator to characterize the reliability of the classification model and thus makes the classification model more transparent. However, the existing related work is constrained to linear models or the corresponding nonlinear models by applying the kernel trick. To relax such constraints, we propose the Generalized Hidden-Mapping Minimax Probability Machine (GHM-MPM). GHM-MPM is a generalized MPM. It is capable of training many classical intelligent models, such as feedforward neural networks, fuzzy logic systems, and linear and kernelized linear models for classification tasks, and realizing the reliability learning of these models simultaneously. Since the GHM-MPM, similarly to the classical MPM, was originally developed only for binary classification, it is further extended to multi-class classification by using the obtained reliability indices of the binary classifiers of two arbitrary classes. The experimental results show that GHM-MPM makes the trained models more transparent and reliable than those trained by classical methods.
Deng, Z, He, T, Ding, W & Cao, Z 2018, 'A Multimodel Fusion Engine for Filtering Webpages', IEEE Access, vol. 6, pp. 66062-66071.
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OAPA Fusing multiple existing models for filtering webpages can mitigate the shortcomings of individual filtering models. To provide an engine for such fusion, we propose a multimodel fusion engine for filtering webpages (MMFEFWP) for the extraction of target webpages. This engine can handle large datasets of webpages crawled from websites and supports five individual filtering models and the fusion of any two of them. There are two possible fusion methods: one is to simultaneously satisfy the conditions of both individual models, and the other is to satisfy the conditions of one of the two individual models. We present the functions, architecture, and software design of the proposed engine. We use recall ratio (RR) and precision ratio (PR) as the evaluation indices of the filtering models and propose rules describing how PR and RR change when individual models are fused. We use 200,000 webpages collected by crawling the popular online shopping website "www.jd.com" as the experimental dataset to verify these rules. The experimental results show that two-model fusion can improve either PR or RR. Thus, the proposed engine has good practical value for engineering applications.
Depczynski, B, Young, T & White, C 2018, 'A high ankle-brachial index is associated with obesity and low serum 25-hydroxyvitamin D in patients with diabetes', Journal of Clinical & Translational Endocrinology, vol. 11, pp. 7-10.
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Deveci, Ö & Shannon, AG 2018, 'The quaternion-Pell sequence', Communications in Algebra, vol. 46, no. 12, pp. 5403-5409.
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© 2018, © 2018 Taylor & Francis. In this paper, we define the quaternion-Pell sequence and derive the generating matrix of the sequence. Then we produce the semigroups using the multiplicative orders of the generating matrix of the quaternion-Pell sequence when read modulo α. We also study the quaternion-Pell sequence modulo α and then we give the relationship among the periods of the quaternion-Pell sequence modulo α and the orders of the semigroups obtained. In addition, we extend the quaternion-Pell sequence to groups. Finally, we obtain the periods of the quaternion-Pell sequences in dihedral groups D 2m as applications of the results obtained.
Dickson-Deane, C, Bradshaw, AC & Asino, TI 2018, 'Recognizing the Inseparability of Culture, Learning, and Technology', TechTrends, vol. 62, no. 4, pp. 310-311.
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Ding, C, Sun, H-H, Ziolkowski, RW & Jay Guo, Y 2018, 'A Dual Layered Loop Array Antenna for Base Stations With Enhanced Cross-Polarization Discrimination', IEEE Transactions on Antennas and Propagation, vol. 66, no. 12, pp. 6975-6985.
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© 1963-2012 IEEE. This paper presents a novel dual-loop array antenna targeted at current and future base station applications. The antenna has four rectangular loops and four trapezoidal loops printed on the front and back sides, respectively, of a substrate placed above a flat square reflector. All eight loop radiators are excited simultaneously with properly designed feed networks to achieve its ±45° polarization states. The trapezoidal loops act like folded (electric) dipoles; the rectangular loops act primarily as magnetic dipoles. The combination of these two loop arrays leads to a type of magnetoelectric loop antenna that has stable directivity patterns with high cross-polarization discrimination (XPD) values across a 45.5% operational fractional bandwidth from 1.7 to 2.7 GHz. A fabricated and measured prototype confirms the simulation results and demonstrates that the half-power beamwidths in the horizontal plane vary between 63° and 70°, the XPD values are >20 dB in the boresight direction, and are >10 dB within the entire cellular coverage angular range:-60 θ 60°.
Ding, KC, Xiaoyu, Y, Xin, R & Qi, K 2018, 'Design analysis of high-rise buildings in the view of wind environment——A case study of four seasons green block in Hangzhou Qianjiang new city', Xi'an Jianzhu Keji Daxue Xuebao/Journal of Xi'an University of Architecture & Technology, vol. 50, no. 6, pp. 884-900.
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Due to the trend of high-rise and densification of urban buildings, high-rise buildings have a significant impact on the wind environment in their plots, and further affect the comfort of outdoor pedestrians to improve the wind environment around high-rise buildings, which is an urgent problem to be solved. First of all, in this paper, six high-rise buildings in Qianjiang New Town, Hangzhou City, were measured and the location of the building group towards the outdoor wind environment was selected and the points were determined. Then, by constantly changing the orientation of the building blocks, eight typical layouts were obtained. Finally, the CFD fluid dynamics simulation software phoenics was used to analyze the distribution of the wind speed ratio at the height (1.5 m). It is found that the change of the building orientation can achieve the optimization of the surrounding wind environment of the high-rise buildings. This paper, by exploring the relationship between wind environment and building orientation, provides a reference for the design of high-rise building groups in the region.
Ding, W, Lin, C-T & Prasad, M 2018, 'Hierarchical co-evolutionary clustering tree-based rough feature game equilibrium selection and its application in neonatal cerebral cortex MRI', Expert Systems with Applications, vol. 101, pp. 243-257.
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© 2018 Elsevier Ltd A wide variety of feature selection methods have been developed as promising solutions to find the classification pattern inside increasing applications. But the exploring efficient, flexible and robust feature selection method to handle the rising big data is still an exciting challenge. This paper presents a novel hierarchical co-evolutionary clustering tree-based rough feature game equilibrium selection algorithm (CTFGES). It aims to select out the high-quality feature subsets, which can enrich the research of feature selection and classification in the heterogeneous big data. Firstly, we construct a flexible hierarchical co-evolutionary clustering tree model to speed up the process of feature selection, which can effectively extract the features from the parent and children branches of four-layer co-evolutionary clustering tree. Secondly, we design a mixed co-evolutionary game equilibrium scheme with adaptive dynamics to guide parent and children branch subtrees to approach the optimal equilibrium regions, and enable their feature sets to converge stably to the Nash equilibrium. So both noisy heterogeneous features and non-identified redundant ones can be further eliminated. Finally, the extensive experiments on various big datasets are conducted to demonstrate the more excellent performance of CTFGES, in terms of accuracy, efficiency and robustness, compared with the representative feature selection algorithms. In addition, the proposed CTFGES algorithm has been successfully applied into the feature segmentation of large-scale neonatal cerebral cortex MRI with varying noise ratios and intensity non-uniformity levels. The results indicate that it can be adaptive to derive from the cortical folding surfaces and achieves the satisfying consistency with medical experts, which will be potential significance for successfully assessing the impact of aberrant brain growth on the neurodevelopment of neonatal cerebrum.
Ding, W, Lin, C-T, Chen, S, Zhang, X & Hu, B 2018, 'Multiagent-consensus-MapReduce-based attribute reduction using co-evolutionary quantum PSO for big data applications', Neurocomputing, vol. 272, pp. 136-153.
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© 2017 Elsevier B.V. The attribute reduction for big data applications has become an urgent challenge in pattern recognition, machine learning and data mining. In this paper, we introduce the multi-agent consensus MapReduce optimization model and co-evolutionary quantum PSO with self-adaptive memeplexes for designing the attribute reduction method, and propose a multiagent-consensus-MapReduce-based attribute reduction algorithm (MCMAR). Firstly, the co-evolutionary quantum PSO with self-adaptive memeplexes is designed for grouping particles into different memeplexes, which aims to explore the search space and locate the global best region during the attribute reduction of big datasets. Secondly, the four layers neighborhood radius framework with compensatory scheme is constructed to partition big attribute sets by exploiting the interdependency among multiple-relevant-attribute sets. Thirdly, a novel multi-agent consensus MapReduce optimization model is adopted to perform the multiple-relevance-attribute reduction, in which five kinds of agents are used to conduct the ensemble co-evolutionary optimization. So the uniform reduction framework of different agents’ co-evolutionary game under the bounded rationality is further refined. Fourthly, the approximation MapReduce parallelism mechanism is permitted to formalize to the multi-agent co-evolutionary consensus structure, interaction and adaptation, which enhances different agents to share their solutions. Finally, extensive experimental studies substantiate the effectiveness and accuracy of MCMAR on some well-known benchmark datasets. Moreover, successful applications in big medical datasets are expected to dramatically scaling up MCMAR for complex infant brain MRI in terms of efficiency and feasibility.
Ding, W, Lin, C-T, Prasad, M, Cao, Z & Wang, J 2018, 'A Layered-Coevolution-Based Attribute-Boosted Reduction Using Adaptive Quantum-Behavior PSO and Its Consistent Segmentation for Neonates Brain Tissue', IEEE Transactions on Fuzzy Systems, vol. 26, no. 3, pp. 1177-1191.
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© 1993-2012 IEEE. The main challenge of attribute reduction in large data applications is to develop a new algorithm to deal with large, noisy, and uncertain large data linking multiple relevant data sources, structured or unstructured. This paper proposes a new and efficient layered-coevolution-based attribute-boosted reduction algorithm (LCQ-ABR∗) using adaptive quantum-behavior particle swarm optimization (PSO). First, the quantum rotation angle of an evolutionary particle is updated by a dynamic change of self-adapting step size. Second, a self-adaptive partitioning strategy is employed to group particles into different memeplexes, and the quantum-behavior mechanism with the particles' states depicted by the wave function cooperates to achieve superior performance in their respective memeplexes. Third, a new layered coevolutionary model with multiagent interaction is constructed to decompose a complex attribute set, and it can self-adapt the attribute sizes among different layers and produce the reasonable decompositions by exploiting any interdependence among multiple relevant attribute subsets. Fourth, the decomposed attribute subsets are evolved to compute the positive region and discernibility matrix by using their best quantum particles, and the global optimal reduction set is induced successfully. Finally, extensive comparative experiments are provided to illustrate that LCQ-ABR∗ has better feasibility and effectiveness of attribute reduction on large-scale and uncertain dataset problems with complex noise as compared with representative algorithms. Moreover, LCQ-ABR∗ can be successfully applied in the consistent segmentation for neonatal brain three-dimensional MRI, and the consistent segmentation results further demonstrate its stronger applicability.
Ding, Z, Dong, Y, Kou, G, Palomares, I & Yu, S 2018, 'Consensus formation in opinion dynamics with online and offline interactions at complex networks', International Journal of Modern Physics C, vol. 29, no. 07, pp. 1850046-1850046.
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Nowadays, with the development of information communication technology and Internet, more and more people receive information and exchange their opinions with others via online environments (e.g. Twitter, Facebook, Weibo, and WeChat). According to eMarketer Report [Worldwide Internet and Mobile Users: eMarketer’s Updated Estimates and Forecast for 2015–2020 (eMarketer Report). Published October 11, 2016, https://www.emarketer.com/Report/Worldwide-Internet-Mobile-Users-eMarketers-Updated-Estimates-Forecast-20152020/2001897 ).], by the end of 2016, more than 3.2 billion individuals worldwide will use the Internet regularly, accounting for nearly 45% of the world population. By contrast, the other half of the global population still obtain information and regularly exchange their opinions in a more traditional way (e.g. face to face). Generally, the speed at which information spreads and opinions are exchanged and updated in an online environment is much faster than in an offline environment. This paper focuses on jointly investigating the challenge of consensus formation in opinion dynamics with online and offline interactions. Without loss of generality, we assume the speed at which information spreads and opinions are exchanged and updated in an online environment is [Formula: see text] times as fast as in an offline environment. We demonstrate that the update speed ratio in mixed online and offline environments (i.e. [Formula: see text]) strongly impacts the consensus formation at complex networks: a large update speed ratio of online and offline environments (i.e. [Formula: see text]) makes it difficult for all agents to reach consensus in opinion dynamics. Furthermore, these effects are often further intensified as the number of online participating agents increases.
Do, MH, Ngo, HH, Guo, WS, Liu, Y, Chang, SW, Nguyen, DD, Nghiem, LD & Ni, BJ 2018, 'Challenges in the application of microbial fuel cells to wastewater treatment and energy production: A mini review', Science of The Total Environment, vol. 639, pp. 910-920.
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© 2018 Wastewater is now considered to be a vital reusable source of water reuse and saving energy. However, current wastewater has multiple limitations such as high energy costs, large quantities of residuals being generated and lacking in potential resources. Recently, great attention has been paid to microbial fuel cells (MFCs) due to their mild operating conditions where a variety of biodegradable substrates can serve as fuel. MFCs can be used in wastewater treatment facilities to break down organic matter, and they have also been analysed for application as a biosensor such as a sensor for biological oxygen which demands monitoring. MFCs represent an innovation technology solution that is simple and rapid. Despite the advantages of this technology, there are still practical barriers to consider including low electricity production, current instability, high internal resistance and costly materials used. Thus, many problems must be overcome and doing this requires a more detailed analysis of energy production, consumption, and application. Currently, real-world applications of MFCs are limited due to their low power density level of only several thousand mW/m2. Efforts are being made to improve the performance and reduce the construction and operating costs of MFCs. This paper explores several aspects of MFCs such as anode, cathode and membrane, and in an effort to overcome the practical challenges of this system.
Dong, F, Lu, J, Zhang, G & Li, K 2018, 'Active Fuzzy Weighting Ensemble for Dealing with Concept Drift', International Journal of Computational Intelligence Systems, vol. 11, no. 1, pp. 438-438.
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© 2018, the Authors. The concept drift problem is a pervasive phenomenon in real-world data stream applications. It makes well-trained static learning models lose accuracy and become outdated as time goes by. The existence of different types of concept drift makes it more difficult for learning algorithms to track. This paper proposes a novel adaptive ensemble algorithm, the Active Fuzzy Weighting Ensemble, to handle data streams involving concept drift. During the processing of data instances in the data streams, our algorithm first identifies whether or not a drift occurs. Once a drift is confirmed, it uses data instances accumulated by the drift detection method to create a new base classifier. Then, it applies fuzzy instance weighting and a dynamic voting strategy to organize all the existing base classifiers to construct an ensemble learning model. Experimental evaluations on seven datasets show that our proposed algorithm can shorten the recovery time of accuracy drop when concept drift occurs, adapt to different types of concept drift, and obtain better performance with less computation costs than the other adaptive ensembles.
Dong, F, Zhang, G, Lu, J & Li, K 2018, 'Fuzzy competence model drift detection for data-driven decision support systems', Knowledge-Based Systems, vol. 143, pp. 284-294.
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© 2017 Elsevier B.V. This paper focuses on concept drift in business intelligence and data-driven decision support systems (DSSs). The assumption of a fixed distribution in the data renders conventional static DSSs inaccurate and unable to make correct decisions when concept drift occurs. However, it is important to know when, how, and where concept drift occurs so a DSS can adjust its decision processing knowledge to adapt to an ever-changing environment at the appropriate time. This paper presents a data distribution-based concept drift detection method called fuzzy competence model drift detection (FCM-DD). By introducing fuzzy sets theory and replacing crisp boundaries with fuzzy ones, we have improved the competence model to provide a better, more refined empirical distribution of the data stream. FCM-DD requires no prior knowledge of the underlying distribution and provides statistical guarantee of the reliability of the detected drift, based on the theory of bootstrapping. A series of experiments show that our proposed FCM-DD method can detect drift more accurately, has good sensitivity, and is robust.
Dong, X, Gong, Y & Cao, L 2018, 'F-NSP+: A fast negative sequential patterns mining method with self-adaptive data storage', Pattern Recognition, vol. 84, pp. 13-27.
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© 2018 Elsevier Ltd Mining negative sequential patterns (NSP) is an important tool for nonoccurring behavior analysis, and it is much more challenging than mining positive sequential patterns (PSPs) due to the high computational complexity and huge search space when obtaining the support of negative sequential candidates (NSCs). Very few NSP mining algorithms are available and most of them are very inefficient since they obtain the support of NSC by scanning the database repeatedly. Instead, the state-of-the-art NSP mining algorithm e-NSP only uses the PSP's information stored in an array structure to ‘calculate' the support of NSC by equations, without database re-scanning. This makes e-NSP highly efficient, particularly on sparse datasets. However, when datasets become dense, the key process to obtain the support of NSC in e-NSP becomes very time-consuming and needs to be improved. In this paper, we propose a novel and efficient data structure, a bitmap, to obtain the support of NSC. We correspondingly propose a fast NSP mining algorithm, f-NSP, which uses a bitmap to store the PSP's information and then obtain the support of NSC only by bitwise operations, which is much faster than the hash method in e-NSP. Experimental results on real-world and synthetic datasets show that f-NSP is not only tens to hundreds of times faster than e-NSP, but also saves more than ten-fold the storage spaces of e-NSP, particularly on dense datasets with a large number of elements in a sequence or a small number of itemsets. Further, we find that f-NSP consumes more storage space than e-NSP when PSP's support is less than a support threshold sdsup, a value obtained through our theoretical analysis of storage space. Accordingly, we propose a self-adaptive storage strategy and a corresponding algorithm f-NSP+ to overcome this deficiency. f-NSP+ can automatically choose a bitmap or an array structure to store PSP information according to PSP support. Experimental results sho...
Dong, Y, Fatahi, B, Khabbaz, H & Zhang, H 2018, 'Influence of particle contact models on soil response of poorly graded sand during cavity expansion in discrete element simulation', Journal of Rock Mechanics and Geotechnical Engineering, vol. 10, no. 6, pp. 1154-1170.
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© 2018 Institute of Rock and Soil Mechanics, Chinese Academy of Sciences The discrete element method (DEM) has been extensively adopted to investigate many complex geotechnical related problems due to its capability to incorporate the discontinuous nature of granular materials. In particular, when simulating large deformations or distortion of soil (e.g. cavity expansion), DEM can be very effective as other numerical solutions may experience convergence problems. Cavity expansion theory has widespread applications in geotechnical engineering, particularly to the problems concerning in situ testing, pile installation and so forth. In addition, the behaviour of geomaterials in a macro-level is utterly determined by microscopic properties, highlighting the importance of contact models. Despite the fact that there are numerous contact models proposed to mimic the realistic behaviour of granular materials, there are lack of studies on the effects of these contact models on the soil response. Hence, in this study, a series of three-dimensional numerical simulations with different contact constitutive models was conducted to simulate the response of sandy soils during cylindrical cavity expansion. In this numerical investigation, three contact models, i.e. linear contact model, rolling resistance contact model, and Hertz contact model, are considered. It should be noted that the former two models are linear based models, providing linearly elastic and frictional plasticity behaviours, whereas the latter one consists of nonlinear formulation based on an approximation of the theory of Mindlin and Deresiewicz. To examine the effects of these contact models, several cylindrical cavities were created and expanded gradually from an initial radius of 0.055 m to a final radius of 0.1 m. The numerical predictions confirm that the calibrated contact models produced similar results regarding the variations of cavity pressure, radial stress, deviatoric stress, volumetric ...
Dorji, P, Choi, J, Kim, DI, Phuntsho, S, Hong, S & Shon, HK 2018, 'Membrane capacitive deionisation as an alternative to the 2nd pass for seawater reverse osmosis desalination plant for bromide removal', Desalination, vol. 433, pp. 113-119.
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© 2018 Elsevier B.V. Most Australian surface and ground waters have relatively high concentration of bromide between 400 and 8000 μg/L and even higher concentration in seawater between 60,000–78,000 μg/L. Although bromide is not regulated, even at low concentrations of 50–100 μg/L, it can lead to the formation of several types of harmful disinfection by-products (DBPs) during the disinfection process. One of the major concerns with brominated DBPs is the formation of bromate (BrO3−), a serious carcinogen that is formed when water containing a high concentration of bromide is disinfected. As a result, bromate is highly regulated in Australian water standards with the maximum concentration of 20 μg/L in the drinking water. Since seawater reverse osmosis (SWRO) desalination plays an important role in augmenting fresh water supplies in Australia, SWRO plants in Australia usually adopt 2nd pass brackish water reverse osmosis (BWRO) for effective bromide removal, which is not only energy-intensive to operate but also has higher capital cost. In this study, we evaluated the feasibility of membrane capacitive deionisation (MCDI) as one of the alternatives to the 2nd pass BWRO for effective bromide removal in a more energy efficient way.
Dorneburg, C, Fischer, M, Barth, TFE, Mueller-Klieser, W, Hero, B, Gecht, J, Carter, DR, de Preter, K, Mayer, B, Christner, L, Speleman, F, Marshall, GM, Debatin, K-M & Beltinger, C 2018, 'LDHA in Neuroblastoma Is Associated with Poor Outcome and Its Depletion Decreases Neuroblastoma Growth Independent of Aerobic Glycolysis', Clinical Cancer Research, vol. 24, no. 22, pp. 5772-5783.
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Abstract Purpose: To investigate whether lactate dehydrogenase A (LDHA), an important component of the LDH tetramer crucial for aerobic glycolysis, is associated with patient outcome and constitutes a therapeutic target in neuroblastoma (NB). Experimental Design: Expression of LDHA mRNA and protein was determined in 709 and 110 NB patient samples, respectively, and correlated with survival and risk factors. LDHA and LDHB were depleted in human NB cell lines by CRISPR/Cas9 and shRNA, respectively, and aerobic glycolysis, clonogenicity, and tumorigenicity were determined. Expression of LDHA in relation to MYCN was measured in NB cell lines and in the TH-MYCN NB mouse model. Results: Expression of LDHA, both on the mRNA and the protein level, was significantly and independently associated with decreased patient survival. Predominant cytoplasmic localization of LDHA protein was associated with poor outcome. Amplification and expression of MYCN did not correlate with expression of LDHA in NB cell lines or TH-MYCN mice, respectively. Knockout of LDHA inhibited clonogenicity, tumorigenicity, and tumor growth without abolishing LDH activity or significantly decreasing aerobic glycolysis. Concomitant depletion of LDHA and the isoform LDHB ablated clonogenicity while not abrogating LDH activity or decreasing aerobic glycolysis. The isoform LDHC was not expressed. Conclusions: High expression of LDHA is independently associated with outcome of NB, and NB cells can be inhibited by depletion of LDHA or LDHB. This inhibition appears to be unrelated to LDH activity and aerobic glycolysis. Thus, investigations of inhibitory mechanisms beyond attenuation of aerobic glycolysis are warranted, both in NB and normal cells. Clin Cancer Res; 24(22); 5772–83. ©2018 AACR.
Douglas, A, Torpy, F, Surawski, N & Irga, P 2018, 'Mapping Urban Aerosolized Fungi: Predicting Spatial and Temporal Indoor Concentrations', Human Ecology Review, vol. 24, no. 2, pp. 81-103.
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Du, Y, Hsieh, M-H, Liu, T & Tao, D 2018, 'A Grover-search Based Quantum Learning Scheme for Classification', New J. Phys., vol. 23, no. 2, p. 023020.
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The hybrid quantum-classical learning scheme provides a prominent way toachieve quantum advantages on near-term quantum devices. A concrete exampletowards this goal is the quantum neural network (QNN), which has been developedto accomplish various supervised learning tasks such as classification andregression. However, there are two central issues that remain obscure when QNNis exploited to accomplish classification tasks. First, a quantum classifierthat can well balance the computational cost such as the number of measurementsand the learning performance is unexplored. Second, it is unclear whetherquantum classifiers can be applied to solve certain problems that outperformtheir classical counterparts. Here we devise a Grover-search based quantumlearning scheme (GBLS) to address the above two issues. Notably, most existingQNN-based quantum classifiers can be seamlessly embedded into the proposedscheme. The key insight behind our proposal is reformulating the classificationtasks as the search problem. Numerical simulations exhibit that GBLS canachieve comparable performance with other quantum classifiers under variousnoise settings, while the required number of measurements is dramaticallyreduced. We further demonstrate a potential quantum advantage of GBLS overclassical classifiers in the measure of query complexity. Our work providesguidance to develop advanced quantum classifiers on near-term quantum devicesand opens up an avenue to explore potential quantum advantages in variousclassification tasks.
Du, Y, Hsieh, M-H, Liu, T & Tao, D 2018, 'The Expressive Power of Parameterized Quantum Circuits', Phys. Rev. Research, vol. 2, no. 3, p. 033125.
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Parameterized quantum circuits (PQCs) have been broadly used as a hybridquantum-classical machine learning scheme to accomplish generative tasks.However, whether PQCs have better expressive power than classical generativeneural networks, such as restricted or deep Boltzmann machines, remains an openissue. In this paper, we prove that PQCs with a simple structure alreadyoutperform any classical neural network for generative tasks, unless thepolynomial hierarchy collapses. Our proof builds on known results from tensornetworks and quantum circuits (in particular, instantaneous quantum polynomialcircuits). In addition, PQCs equipped with ancillary qubits for post-selectionhave even stronger expressive power than those without post-selection. Weemploy them as an application for Bayesian learning, since it is possible tolearn prior probabilities rather than assuming they are known. We expect thatit will find many more applications in semi-supervised learning where priordistributions are normally assumed to be unknown. Lastly, we conduct severalnumerical experiments using the Rigetti Forest platform to demonstrate theperformance of the proposed Bayesian quantum circuit.
Dua, K, Rapalli, VK, Shukla, SD, Singhvi, G, Shastri, MD, Chellappan, DK, Satija, S, Mehta, M, Gulati, M, Pinto, TDJA, Gupta, G & Hansbro, PM 2018, 'Multi-drug resistant Mycobacterium tuberculosis & oxidative stress complexity: Emerging need for novel drug delivery approaches', Biomedicine & Pharmacotherapy, vol. 107, pp. 1218-1229.
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© 2018 Elsevier Masson SAS Tuberculosis (caused by Mycobacterium tuberculosis, Mtb) treatment involves multiple drug regimens for a prolonged period. However, the therapeutic benefit is often limited by poor patient compliance, subsequently leading to treatment failure and development of antibiotic resistance. Notably, oxidative stress is a crucial underlying factor that adversely influences the various treatment regimens in tuberculosis. Little information is available with advanced drug delivery systems that could be effectively utilized, in particular, for targeting the oxidative stress in tuberculosis. Thus, this presents an opportunity to review the utility of various available, controlled-release drug delivery systems (e.g., microspheres, liposomes, niosomes, solid lipid nanoparticles, dendrimers) that could be beneficial in tuberculosis treatments. This will help the biological and formulation scientists to pave a new path in formulating a treatment regimen for multi-drug resistant Mtb.
Duong, HC, Álvarez, IRC, Nguyen, TV & Nghiem, LD 2018, 'Membrane distillation to regenerate different liquid desiccant solutions for air conditioning', Desalination, vol. 443, pp. 137-142.
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© 2018 The capacity of membrane distillation (MD) to regenerate three commonly used liquid desiccant solutions (i.e. CaCl2, LiCl, and a mixture of CaCl2/LiCl) for liquid desiccant air-conditioners (LDAC) was evaluated. The results demonstrate considerable impact of the concentration polarisation effect on the process water flux during MD regeneration of these three desiccant solutions. For each of these liquid desiccant solutions, the experimentally measured water flux of the MD process was about half of the calculated value using the process mass transfer coefficient (Km) obtained during the process characterisation without taking into account the concentration polarisation effect. The observed deviation between the experimentally measured and calculated process water flux indicates the need to include the concentration polarisation effect in the model for calculating water flux. Although Ca2+ concentration in the CaCl2 and CaCl2/LiCl liquid desiccant solutions exceeded the solubility limit for CaCO3, membrane scaling was not observed. Nevertheless, there was evidence that membrane fouling might occur during extended MD regeneration of liquid desiccant solutions containing CaCl2.
Duong, HC, Ansari, AJ, Nghiem, LD, Pham, TM & Pham, TD 2018, 'Low Carbon Desalination by Innovative Membrane Materials and Processes', Current Pollution Reports, vol. 4, no. 4, pp. 251-264.
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Duong, HC, Chuai, D, Woo, YC, Shon, HK, Nghiem, LD & Sencadas, V 2018, 'A novel electrospun, hydrophobic, and elastomeric styrene-butadiene-styrene membrane for membrane distillation applications', Journal of Membrane Science, vol. 549, pp. 420-427.
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© 2017 In this study, a novel hydrophobic, microporous membrane was fabricated from styrene-butadiene-styrene (SBS) polymer using electrospinning and evaluated for membrane distillation applications. Compared to a commercially available polytetrafluoroethylene (PTFE) membrane, the SBS membrane had larger membrane pore size and fiber diameter and comparable membrane porosity. The fabricated SBS showed slightly lower water flux than the PTFE membrane because it was two times thicker. However, the SBS membrane had better salt rejection and most importantly could be fabricated via a simple process. The SBS membrane was also more hydrophobic than the reference PTFE membrane. In particular, as temperature of the reference water liquid increased to 60 °C, the SBS membrane remained hydrophobic with a contact angle of 100° whereas the PTFE became hydrophilic with a contact angle of less than 90°. The hydrophobic membrane surface prevented the intrusion of liquid into the membrane pores, thus improving the salt rejection of the SBS membrane. In addition, the SBS membrane had superior mechanical strength over the PTFE membrane. Using the SBS membrane, stable water flux was achieved throughout an extended MD operation period of 120 h to produce excellent quality distillate (over 99.7% salt rejection) from seawater.
Duong, NMH, Xu, Z-Q, Kianinia, M, Su, R, Liu, Z, Kim, S, Bradac, C, Li, L-J, Solntsev, A, Liu, J & Aharonovich, I 2018, 'Enhanced Emission from WSe2 Monolayers Coupled to Circular Bragg Gratings', ACS Photonics, vol. 5, no. 10, pp. 3950-3955.
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Two-dimensional transition-metal dichalcogenides (TMDC) are of great interestfor on-chip nanophotonics due to their unique optoelectronic properties. Here,we propose and realize coupling of tungsten diselenide (WSe2) monolayers tocircular Bragg grating structures to achieve enhanced emission. The interactionbetween WSe2 and the resonant mode of the structure results in Purcell-enhancedemission, while the symmetric geometrical structure improves the directionalityof the out-coupling stream of emitted photons. Furthermore, this hybridstructure produces a record high contrast of the spin valley readout (> 40%)revealed by the polarization resolved photoluminescence (PL) measurements. Ourresults are promising for on-chip integration of TMDC monolayers with opticalresonators for nanophotonic circuits.
Durán Santomil, P, Otero González, L, Martorell Cunill, O & Merigó Lindahl, JM 2018, 'Backtesting an equity risk model under Solvency II', Journal of Business Research, vol. 89, pp. 216-222.
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© 2018 Elsevier Inc. Backtesting is a technique for validating internal models under Solvency II, which allows for evaluating the discrepancies between the results provided by a model and real observations. This paper aims to establish various backtesting tests and to show their applications to equity risk in Solvency II. Normal and empirical models with a rolling window are used to determine VaR at the 99.5% confidence level over a one-year time horizon. The proposed methodology performs the backtesting of annualized returns arising from the accumulation of daily returns. The results show that even if a model is conservative when tested out of a sample, it may be inadequate when evaluated in a sample, thereby highlighting the problems inherent in the out-of-sample backtesting proposed by the regulator.
Dyson, LE & Frawley, JK 2018, 'A Student-Generated Video Careers Project', International Journal of Mobile and Blended Learning, vol. 10, no. 4, pp. 32-51.
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This article describes how in recent years, the multimedia recording capabilities of mobile devices have been used increasingly to create a more active, learner-centred educational experience. Despite the proven value of student-generated multimedia projects, there are still gaps in our understanding of how students learn during them. This article reports on a project in which first-year information technology students interviewed IT professionals in their workplace and video-recorded the interview to enable sharing with their peers. In order to understand the statistically significant increases found in students' learning, student diaries and reflections were analyzed qualitatively. Factors found to contribute to learning included: the iterative nature of student activities; the multiple, evolving representations of knowledge as students proceeded through the project; the importance of the workplace context in engaging students and enhancing learning; the affordance of mobile technology for capturing and sharing this context; and the collaborative and metacognitive processes fostered by the project.
Ebrahimi, M, ShafieiBavani, E, Wong, R & Chen, F 2018, 'Twitter user geolocation by filtering of highly mentioned users', Journal of the Association for Information Science and Technology, vol. 69, no. 7, pp. 879-889.
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Geolocated social media data provide a powerful source of information about places and regional human behavior. Because only a small amount of social media data have been geolocation‐annotated, inference techniques play a substantial role to increase the volume of annotated data. Conventional research in this area has been based on the text content of posts from a given user or the social network of the user, with some recent crossovers between the text‐ and network‐based approaches. This paper proposes a novel approach to categorize highly‐mentioned users (celebrities) into Local and Global types, and consequently use Local celebrities as location indicators. A label propagation algorithm is then used over the refined social network for geolocation inference. Finally, we propose a hybrid approach by merging a text‐based method as a back‐off strategy into our network‐based approach. Empirical experiments over three standard Twitter benchmark data sets demonstrate that our approach outperforms state‐of‐the‐art user geolocation methods.
Eeshwarasinghe, D, Loganathan, P, Kalaruban, M, Sounthararajah, DP, Kandasamy, J & Vigneswaran, S 2018, 'Removing polycyclic aromatic hydrocarbons from water using granular activated carbon: kinetic and equilibrium adsorption studies', Environmental Science and Pollution Research, vol. 25, no. 14, pp. 13511-13524.
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© 2018, Springer-Verlag GmbH Germany, part of Springer Nature. Polycyclic aromatic hydrocarbons (PAHs) constitute a group of highly persistent, toxic and widespread environmental micropollutants that are increasingly found in water. A study was conducted in removing five PAHs, specifically naphthalene, acenaphthylene, acenaphthene, fluorene and phenanthrene, from water by adsorption onto granular activated carbon (GAC). The pseudo-first-order (PFO) model satisfactorily described the kinetics of adsorption of the PAHs. The Weber and Morris diffusion model’s fit to the data showed that there were faster and slower rates of intra-particle diffusion probably into the mesopores and micropores of the GAC, respectively. These rates were negatively related to the molar volumes of the PAHs. Batch equilibrium adsorption data fitted well to the Langmuir, Freundlich and Dubinin–Radushkevich models, of which the Freundlich model exhibited the best fit. The adsorption affinities were related to the hydrophobicity of the PAHs as determined by the log Kow values. Free energies of adsorption calculated from the Dubinin–Radushkevich model and the satisfactory kinetic data fitting to the PFO model suggested physical adsorption of the PAHs. Adsorption of naphthalene, acenaphthylene and acenaphthene in fixed-bed columns containing a mixture of GAC (0.5 g) + sand (24.5 g) was satisfactorily simulated by the Thomas model.
El-Sayed, H, Sankar, S, Daraghmi, Y-A, Tiwari, P, Rattagan, E, Mohanty, M, Puthal, D & Prasad, M 2018, 'Accurate Traffic Flow Prediction in Heterogeneous Vehicular Networks in an Intelligent Transport System Using a Supervised Non-Parametric Classifier', Sensors, vol. 18, no. 6, pp. 1696-1696.
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Heterogeneous vehicular networks (HETVNETs) evolve from vehicular ad hoc networks (VANETs), which allow vehicles to always be connected so as to obtain safety services within intelligent transportation systems (ITSs). The services and data provided by HETVNETs should be neither interrupted nor delayed. Therefore, Quality of Service (QoS) improvement of HETVNETs is one of the topics attracting the attention of researchers and the manufacturing community. Several methodologies and frameworks have been devised by researchers to address QoS-prediction service issues. In this paper, to improve QoS, we evaluate various traffic characteristics of HETVNETs and propose a new supervised learning model to capture knowledge on all possible traffic patterns. This model is a refinement of support vector machine (SVM) kernels with a radial basis function (RBF). The proposed model produces better results than SVMs, and outperforms other prediction methods used in a traffic context, as it has lower computational complexity and higher prediction accuracy.
El-Sayed, H, Sankar, S, Prasad, M, Puthal, D, Gupta, A, Mohanty, M & Lin, C-T 2018, 'Edge of Things: The Big Picture on the Integration of Edge, IoT and the Cloud in a Distributed Computing Environment', IEEE Access, vol. 6, pp. 1706-1717.
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© 2013 IEEE. A centralized infrastructure system carries out existing data analytics and decision-making processes from our current highly virtualized platform of wireless networks and the Internet of Things (IoT) applications. There is a high possibility that these existing methods will encounter more challenges and issues in relation to network dynamics, resulting in a high overhead in the network response time, leading to latency and traffic. In order to avoid these problems in the network and achieve an optimum level of resource utilization, a new paradigm called edge computing (EC) is proposed to pave the way for the evolution of new age applications and services. With the integration of EC, the processing capabilities are pushed to the edge of network devices such as smart phones, sensor nodes, wearables, and on-board units, where data analytics and knowledge generation are performed which removes the necessity for a centralized system. Many IoT applications, such as smart cities, the smart grid, smart traffic lights, and smart vehicles, are rapidly upgrading their applications with EC, significantly improving response time as well as conserving network resources. Irrespective of the fact that EC shifts the workload from a centralized cloud to the edge, the analogy between EC and the cloud pertaining to factors such as resource management and computation optimization are still open to research studies. Hence, this paper aims to validate the efficiency and resourcefulness of EC. We extensively survey the edge systems and present a comparative study of cloud computing systems. After analyzing the different network properties in the system, the results show that EC systems perform better than cloud computing systems. Finally, the research challenges in implementing an EC system and future research directions are discussed.
Erfani, SS & Abedin, B 2018, 'Impacts of the use of social network sites on users' psychological well‐being: A systematic review', Journal of the Association for Information Science and Technology, vol. 69, no. 7, pp. 900-912.
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As Social Network Sites (SNSs) are increasingly becoming part of people's everyday lives, the implications of their use need to be investigated and understood. We conducted a systematic literature review to lay the groundwork for understanding the relationship between SNS use and users' psychological well‐being and for devising strategies for taking advantage of this relationship. The review included articles published between 2003 and 2016, extracted from major academic databases. Findings revealed that the use of SNSs is both positively and negatively related to users' psychological well‐being. We discuss the factors that moderate this relationship and their implications on users' psychological well‐being. Many of the studies we reviewed lacked a sound theoretical justification for their findings and most involved young and healthy students, leaving other cohorts of SNS users neglected. The paper concludes with the presentation of a platform for future investigation.
Erwin, E, Surjosatyo, A, Sulistyo, N, Meurahindra, M & Soemardi, T 2018, 'The effect of hybrid savonius and darrieus turbine on the change of wake recovery and improvement of wind energy harvesting', Journal of Applied Engineering Science, vol. 16, no. 3, pp. 416-423.
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© 2018 Institut za Istrazivanja. All rights reserved. The energy crisis encourages the development of renewable energy; one of the potential renewable energy is wind. In the field of wind turbine there is a two-way development of the utilization of wind energy, first by making a large wind turbine, the second by making a wind farm energy with a relatively small wind turbine.This hybrid VAWT wind turbine (Sultan Wind Turbine) is designed to work optimally on a farm array, on a wind turbine farm array will always cause a wake effect that will reduce overall wind turbine and farm array performance, an investigation with a CFD simulation is required to predict how far the wake effect will be before farm array build.The use of simulation software has been widely used to predict the effects of this wake, and experiments in the laboratory have also been done to predict the effects of a wake as well.This study'spurpose is to predict the distance area of the recovery wake behindthe wind turbine, this distance which will be the reference distance between wind turbine units and determining the density of the turbine in a farm. Simulation using Computational Fluid Dynamics (CFD), with a method of Multi Frame Reference (MRF). Analysis using descriptive and inferential method in statistics such as mean, Kolmogorov-Smirnov Z and KruskalWalis test.From the analysis of simulation results and data processing descriptively and analytic statistic, it can be concluded from the data given, the distance of x/D=4, wind speed has recovery to the value near the input speed and no significant change to x/D= 9. Then it can be concluded that the distance between two windturbines that can be used is a distance of 3.6 meters.These data suggest that the hybrid farm array VAWT savonius and darrieus have a higher power density compared to HAWT. From this power density calculation the hybrid VAWT has a greater electrical potential up to 300 percent compared to the HAWT farm array.
Eskandari, M, Li, L & Moradi, MH 2018, 'Improving power sharing in islanded networked microgrids using fuzzy-based consensus control', Sustainable Energy, Grids and Networks, vol. 16, pp. 259-269.
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© 2018 Elsevier Ltd The rising world-wide trend toward developing clean energy resources has caused dispersed installation of renewable energy resources (RESs) in distribution grids. Microgrid (MG) concept is proposed as a key factor in optimal and secure integration of, mostly converter-based, RESs into power systems. One of the major challenges related to MG control is ineffectiveness of droop control in accurate power sharing which is affected by the feeder impedance. In this paper, a fuzzy-based consensus control protocol is developed to address this issue in multi-bus MGs (MBMGs). Consensus signals are inserted into the conventional droop controller as complementary part to overcome the drawback of the droop control in power sharing in MBMGs. Dynamic fuzzy coefficients of consensus signals are designed to model X/R ratio of the grid impedance in the control system. In addition, a novel small signal model of MBMG is developed, by considering the conventional droop control, MBMG power network and power lines impedance to design and assess performance of the control system. Consensus control is also incorporated into the proposed control system of MBMG to analyze the stability. Simulation results are presented to assess effectiveness of the control strategy in MATLAB\Simulink.
Esmaili, N, Piccardi, M, Kruger, B & Girosi, F 2018, 'Analysis of healthcare service utilization after transport-related injuries by a mixture of hidden Markov models', PLOS ONE, vol. 13, no. 11, pp. e0206274-e0206274.
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© 2018 Esmaili et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Background Transport injuries commonly result in significant disease burden, leading to physical disability, mental health deterioration and reduced quality of life. Analyzing the patterns of healthcare service utilization after transport injuries can provide an insight into the health of the affected parties, allow improved health system resource planning, and provide a baseline against which any future system-level interventions can be evaluated. Therefore, this research aims to use time series of service utilization provided by a compensation agency to identify groups of claimants with similar utilization patterns, describe such patterns, and characterize the groups in terms of demographic, accident type and injury type. Methods To achieve this aim, we have proposed an analytical framework that utilizes latent variables to describe the utilization patterns over time and group the claimants into clusters based on their service utilization time series. To perform the clustering without dismissing the temporal dimension of the time series, we have used a well-established statistical approach known as the mixture of hidden Markov models (MHMM). Ensuing the clustering, we have applied multinomial logistic regression to provide a description of the clusters against demographic, injury and accident covariates. Results We have tested our model with data on psychology service utilization from one of the main compensation agencies for transport accidents in Australia, and found that three clear clusters of service utilization can be evinced from the data. These three clusters correspond to claimants who have tended to use the services 1) only briefly after the accident; 2) for an intermediate period of time...
Fahmideh, M & Beydoun, G 2018, 'Reusing empirical knowledge during cloud computing adoption.', J. Syst. Softw., vol. 138, pp. 124-157.
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Fan, X, He, X, Xiang, C, Puthal, D, Gong, L, Nanda, P & Fang, G 2018, 'Towards System Implementation and Data Analysis for Crowdsensing Based Outdoor RSS Maps', IEEE Access, vol. 6, pp. 47535-47545.
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© 2013 IEEE. With the explosive usage of smart mobile devices, sustainable access to wireless networks (e.g., Wi-Fi) has become a pervasive demand. Most mobile users expect seamless network connection with low cost. Indeed, this can be achieved by using an accurate received signal strength (RSS) map of wireless access points. While existing methods are either costly or unscalable, the recently emerged mobile crowdsensing (MCS) paradigm is a promising technique for building RSS maps. MCS applications leverage pervasive mobile devices to collaboratively collect data. However, the heterogeneity of devices and the mobility of users could cause inherent noises and blank spots in collected data set. In this paper, we study how to: 1) tame the sensing noises from heterogenous mobile devices and 2) construct accurate and complete RSS maps with random mobility of crowdsensing participants. First, we build a mobile crowdsensing system called i Map to collect RSS measurements with heterogeneous mobile devices. Second, through observing experimental results, we build statistical models of sensing noises and derive different parameters for each kind of mobile device. Third, we present the signal transmission model with measurement error model, and we propose a novel signal recovery scheme to construct accurate and complete RSS maps. The evaluation results show that the proposed method can achieve 90% and 95% recovery rate in geographic coordinate system and polar coordinate system, respectively.
Fan, X, Zhao, J, Ren, F, Wang, Y, Feng, Y, Ding, L, Zhao, L, Shang, Y, Li, J, Ni, J, Jia, B, Liu, Y & Chang, Z 2018, 'Dimerization of p15RS mediated by a leucine zipper–like motif is critical for its inhibitory role on Wnt signaling', Journal of Biological Chemistry, vol. 293, no. 20, pp. 7618-7628.
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© 2018 Fan et al. We previously demonstrated that p15RS, a newly discovered tumor suppressor, inhibits Wnt/-catenin signaling by interrupting the formation of -cateninTCF4 complex. However, it remains unclear how p15RS helps exert such an inhibitory effect on Wnt signaling based on its molecular structure. In this study, we reported that dimerization of p15RS is required for its inhibition on the transcription regulation of Wnt-targeted genes. We found that p15RS forms a dimer through a highly conserved leucine zipper–like motif in the coiled-coil terminus domain. In particular, residues Leu-248 and Leu-255 were identified as being responsible for p15RS dimerization, as mutation of these two leucines into prolines disrupted the homodimer formation of p15RS and weakened its suppression of Wnt signaling. Functional studies further confirmed that mutations of p15RS at these residues results in diminishment of its inhibition on cell proliferation and tumor formation. We therefore concluded that dimerization of p15RS governed by the leucine zipper–like motif is critical for its inhibition of Wnt/-catenin signaling and tumorigenesis.
Fang, J, Sun, G, Qiu, N, Pang, T, Li, S & Li, Q 2018, 'On hierarchical honeycombs under out-of-plane crushing', International Journal of Solids and Structures, vol. 135, pp. 1-13.
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© 2017 Hierarchy has been introduced to honeycomb structures in pursuing ultralight materials with outstanding mechanical properties. Nevertheless, the hierarchical honeycombs under the out-of-plane loads have not been well studied experimentally and analytically for energy absorption to date. This study aimed to apply a special structural hierarchy to the honeycomb by replacing the sides of hexagons with smaller hexagons. The quasi-static test of the hierarchical honeycomb specimen was first conducted experimentally to investigate the crushing behaviours; and then the corresponding finite element (FE) analyses were performed. Finally, the analytical solutions to the mean crushing force and plateau stress were derived based on the simplified super folding element (SSFE) method. It was shown that the experimental data and numerical results agreed well in terms of crushing force versus displacement relation and energy absorption characteristics; and the analytical results were validated by the experimental test. Importantly, the hierarchy could improve the energy absorption; and the increase in the order and number of replacement hexagons could excavate the advantage even further. Specifically, the second order honeycomb characterized by five smaller replacement hexagons at each order can yield a plateau stress 2.63 and 4.16 times higher than the regular honeycomb and the aluminium foam, respectively. While it might lead to global bending, structural hierarchy provides new architectural configurations for developing novel ultralight materials with exceptional energy absorption capacity under out-of-plane loads.
Fanos, AM & Pradhan, B 2018, 'Laser Scanning Systems and Techniques in Rockfall Source Identification and Risk Assessment: A Critical Review', Earth Systems and Environment, vol. 2, no. 2, pp. 163-182.
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Rockfall poses risk to people, their properties and to transportation ways in mountainous and hilly regions. This catastrophe shows various characteristics such as vast distribution, sudden occurrence, variable magnitude, strong fatalness and randomicity. Therefore, prediction of rockfall phenomenon both spatially and temporally is a challenging task. Digital Terrain model (DTM) is one of the most significant elements in rockfall source identification and risk assessment. Light detection and ranging (LiDAR) is the most advanced effective technique to derive high-resolution and accurate DTM. This paper presents a critical overview of rockfall phenomenon (definition, triggering factors, motion modes and modeling) and LiDAR technique in terms of data pre-processing, DTM generation and the factors that can be obtained from this technique for rockfall source identification and risk assessment. It also reviews the existing methods that are utilized for the evaluation of the rockfall trajectories and their characteristics (frequency, velocity, bouncing height and kinetic energy), probability, susceptibility, hazard and risk. Detail consideration is given on quantitative methodologies in addition to the qualitative ones. Various methods are demonstrated with respect to their application scales (local and regional). Additionally, attention is given to the latest improvement, particularly including the consideration of the intensity of the phenomena and the magnitude of the events at chosen sites.
Fanos, AM, Pradhan, B, Mansor, S, Yusoff, ZM & Abdullah, AFB 2018, 'A hybrid model using machine learning methods and GIS for potential rockfall source identification from airborne laser scanning data', Landslides, vol. 15, no. 9, pp. 1833-1850.
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© 2018, Springer-Verlag GmbH Germany, part of Springer Nature. The main objectives of this paper are to design and evaluate a hybrid approach based on Gaussian mixture model (GMM) and random forest (RF) for detecting rockfall source areas using airborne laser scanning data. The former model was used to calculate automatically slope angle thresholds for different type of landslides such as shallow, translational, rotational, rotational-translational, complex, debris flow, and rockfalls. After calculating the slope angle thresholds, a homogenous morphometric land use area (HMLA) was constructed to improve the performance of the model computations and reduce the sensitivity of the model to the variations in different conditioning factors. After that, the support vector machine (SVM) was applied in addition to backward elimination (BE) to select and rank the conditioning factors considering the type of landslides. Then, different machine learning methods [artificial neural network (ANN), logistic regression (LR), and random forest (RF) were trained with the selected best factors and previously prepared inventory datasets. The best fit method (RF) was then used to generate the probability maps and then the source areas were detected by combining the slope raster (reclassified according to the thresholds found by the GMM model) and the probability maps. The accuracy assessment shows that the proposed hybrid model could detect the potential rockfalls with an accuracy of 0.92 based on training data and 0.96 on validation data. Overall, the proposed model is an efficient model for identifying rockfall source areas in the presence of other types of landslides with an accepted generalization performance.
Farizal, F, Aji, R, Rachman, A, Nasruddin, N & Mahlia, TMI 2018, 'Indonesia’s Municipal Solid Waste 3R and Waste to Energy Programs', Makara Journal of Technology, vol. 21, no. 3, pp. 153-153.
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Farrok, O, Islam, MR, Guo, Y, Zhu, J & Xu, W 2018, 'A Novel Design Procedure for Designing Linear Generators', IEEE Transactions on Industrial Electronics, vol. 65, no. 2, pp. 1846-1854.
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IEEE A number of research works have been carried out based on the optimization of linear generators for harvesting oceanic wave energy, but no significant method of shape optimization for determination of the optimal shape of linear generator has been found. Moreover, inclusion of some parameters, such as shape of linear generator & #x0027;s translator and stator, has been considered out of the scope of the conventional, adaptive or knowledge based genetic algorithm. This paper proposes a novel method through which any type of linear generator & #x0027;s shape can be optimized graphically. A mathematical model of the proposed method including human intervened genetic algorithm is presented. The proposed method has been applied to a direct-drive system based linear generator where the maximization of electrical power output and minimization of steel core volume have been considered as the optimization objectives. The optimization parameters have been further optimized graphically within functional volumetric and electromagnetic constraints to achieve improved design solutions. The proposed method has included comprehensive geometric dimensions, magnetic and electrical parameters. Finally, the shape of steel cores of the translator and special m-shaped stator of the linear generator is determined and simulated using the copper wire. This optimized shape of the linear generator is capable of satisfying the multi-objectives of maximal electrical power generation and reduction of its size. The ANSYS/Ansoft software has been used to create the platform for analyses of the whole system.
Farrok, O, Islam, MR, Islam Sheikh, MR, Guo, Y, Zhu, J & Lei, G 2018, 'Oceanic Wave Energy Conversion by a Novel Permanent Magnet Linear Generator Capable of Preventing Demagnetization', IEEE Transactions on Industry Applications, vol. 54, no. 6, pp. 6005-6014.
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© 1972-2012 IEEE. In the conventional permanent magnet linear generators (PMLGs) used for oceanic wave energy conversion system, demagnetization could cause everlasting degradation in electrical power generation. This paper presents a new design that can be applied to various PMLGs to avoid demagnetization. To check the effectiveness of the proposed technique, a PMLG is considered, which allows both the fixed and variable length of airgaps for analysis. The finite element analysis is used by using the software package ANSYS/Ansoft to simulate the testing PMLG for two conditions: with and without using the proposed technique. Different parameters and characteristics of the PMLG under both conditions are presented in detail. Both the simulation and test results show that the proposed design is able to avoid the demagnetization problem successfully.
Farrok, O, Islam, MR, Sheikh, MRI, Guo, Y & Zhu, JG 2018, 'A Split Translator Secondary Stator Permanent Magnet Linear Generator for Oceanic Wave Energy Conversion', IEEE Transactions on Industrial Electronics, vol. 65, no. 9, pp. 7600-7608.
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IEEE Almost all flux switching permanent magnet linear generators (FSPMLGs) and Vernier hybrid machines contain a heavy solid translator due to their design limitations for electricity generation from the oceanic waves. This paper presents the new design of a FSPMLG in which the translator weight is reduced and an additional static steel core is inserted inside the translator cavity to improve the magnetic flux linkage of the main stator. The generated voltage, current, power, efficiency, core loss, force ripples and cogging force minimization of the proposed FSPMLG are presented. From the dynamic model of the oceanic wave, it is shown that the translator with lower mass could generate electricity more effectively. The special stator and translator sets have been optimized by using the genetic algorithm before they are used in the proposed FSPMLG. To analyze the performance and verify the feasibility of the new design of FSPMLG, the finite element analysis is performed by using the commercial software package ANSYS/Ansoft.
Fatahi, B, Van Nguyen, Q, Xu, R & Sun, W-J 2018, 'Three-Dimensional Response of Neighboring Buildings Sitting on Pile Foundations to Seismic Pounding', International Journal of Geomechanics, vol. 18, no. 4, pp. 04018007-04018007.
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© 2018 American Society of Civil Engineers. Seismic pounding occurs when the separation gap between buildings and structures is not wide enough, particularly during major earthquake events; this can cause them to collide, causing local damage or, in extreme cases, collapse. This study investigated the impact that this separation gap has on the seismic response of midrise buildings supported on piles while considering seismic soil-pile-structure interaction (SSPSI). To achieve this aim, three 15-story reinforced concrete buildings sitting on pile foundations and with five different separation gaps under excitations from the 1994 Northridge and 1995 Kobe earthquakes were numerically simulated. This study used three-dimensional numerical modeling to simultaneously capture the effects of seismic pounding and SSPSI. Because the considered structure, pile foundation, and soil deposit are three-dimensional in nature, the adopted three-dimensional numerical modeling can provide a more realistic simulation to capture the seismic behavior of the system. The nonlinear behavior of structural elements was included, and the dynamic soil properties were obtained from field data and backbone curves. A contact pair interface with small-sliding surface-to-surface formulation between buildings was used to capture possible seismic pounding, and contact interfaces with a finite-sliding formulation were used to simulate the interaction between the piles and the soil. The results, including lateral building deflections, interstory drifts, structural shear forces, foundation rocking, lateral pile deflections, and the distributions of bending moments and shear forces of the piles, are presented and discussed. The findings of this study will give engineers a better insight into the possible effects of seismic pounding on the seismic performance of buildings, and the response of endbearing piles in soft soils.
Fattah, IMR, Ming, C, Chan, QN, Wehrfritz, A, Pham, PX, Yang, W, Kook, S, Medwell, PR, Yeoh, GH, Hawkes, ER & Masri, AR 2018, 'Spray and Combustion Investigation of Post Injections under Low-Temperature Combustion Conditions with Biodiesel', Energy & Fuels, vol. 32, no. 8, pp. 8727-8742.
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Post injection is a multiple-injection strategy that is commonly used as a particulate matter control measure to reduce soot emissions, yet the mechanisms and the interactions between the main and post injections are only vaguely understood. For this work, experiments were performed to assess the effects of varying dwell time between the main and post injections in a compression-ignition (CI) engine environment simulated using a constant-volume combustion chamber. The ambient density, bulk temperature, and oxygen concentration used for this work were controlled at 19.4 kg/m3, 900 K, and 15 vol % O2, respectively. A canola oil-based biodiesel was tested and injected at a fixed injection pressure of 100 MPa into the simulated CI engine environment. A mass ratio of 80%-20% was maintained between the main and post injections, with the dwell time between the injections varied from 1.5 to 2.5 ms. Comparative measurements were performed using the same fuel and injection schedules, but at a higher ambient gas temperature condition of 1100 K. Optical diagnostics methods, including diffused-back illumination and high-speed flame luminosity imaging, were used to assess the spray and combustion processes of the post injection test case. Under the conditions of this work, it was found that the ignition delays, ignition locations, and flame lift-off lengths of the post injection flames are consistently shorter than those of the main injections, with the variations influenced by the extent of the interaction of the post injection with the combustion products from the main injection. A two-color pyrometry technique was also used to measure the soot temperature and soot concentration factor information on the main-post injection cases. The data revealed a greater interaction between the main and post injections resulted in a more rapid development of the soot zone of the post injection with higher temperature after ignition. The distribution of the most probable soot co...
Faunce, TA, Prest, J, Su, D, Hearne, SJ & Iacopi, F 2018, 'On-grid batteries for large-scale energy storage: Challenges and opportunities for policy and technology', MRS Energy & Sustainability, vol. 5, no. 1.
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ABSTRACT
Feng, J, Wu, D, Gao, W & Li, G 2018, 'Hybrid uncertain natural frequency analysis for structures with random and interval fields', Computer Methods in Applied Mechanics and Engineering, vol. 328, pp. 365-389.
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This paper presents a robust non-deterministic free vibration analysis for engineering structures involving hybrid, yet spatially dependent, uncertain system parameters. Distinguished from the conventional hybrid uncertain eigenvalue problem, the concept of interval field is enclosed with random field model such that, both the stochastic and non-stochastic representations of the spatial dependency of the uncertainties are simultaneously incorporated within a unified non-deterministic free vibration analysis. In order to determine the probabilistic characteristics (i.e., means and standard deviations) of the extremities of structural natural frequencies, an extended unified interval stochastic sampling (X-UISS) method is implemented for the purpose of effective hybrid uncertain free vibration analysis. By meticulously blending sharpness-promised interval eigenvalue analysis with stochastic sampling techniques, the stochastic profiles (i.e., probability density functions (PDFs) and the cumulative distribution functions (CDFs)) of the extreme bounds of the structural natural frequencies can be rigorously established by utilizing the adequate statistical inference methods. The applicability and effectiveness of the proposed computational framework are evidently demonstrated through the numerical investigations on various practically motivated engineering structures.
Feng, X, Wan, W, Xu, RYD, Chen, H, Li, P & Sánchez, JA 2018, 'A perceptual quality metric for 3D triangle meshes based on spatial pooling', Frontiers of Computer Science, vol. 12, no. 4, pp. 798-812.
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Feng, X, Wan, W, Xu, RYD, Perry, S, Zhu, S & Liu, Z 2018, 'A new mesh visual quality metric using saliency weighting-based pooling strategy', Graphical Models, vol. 99, pp. 1-12.
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© 2018 Elsevier Inc. Several metrics have been proposed to assess the visual quality of 3D triangular meshes during the last decade. In this paper, we propose a mesh visual quality metric by integrating mesh saliency into mesh visual quality assessment. We use the Tensor-based Perceptual Distance Measure metric to estimate the local distortions for the mesh, and pool local distortions into a quality score using a saliency weighting-based pooling strategy. Three well-known mesh saliency detection methods are used to demonstrate the superiority and effectiveness of our metric. Experimental results show that our metric with any of three saliency maps performs better than state-of-the-art metrics on the LIRIS/EPFL general-purpose database. We generate a synthetic saliency map by assembling salient regions from individual saliency maps. Experimental results reveal that the synthetic saliency map achieves better performance than individual saliency maps, and the performance gain is closely correlated with the similarity between the individual saliency maps.
Feng, X, Wan, W, Yi Da Xu, R, Perry, S, Li, P & Zhu, S 2018, 'A novel spatial pooling method for 3D mesh quality assessment based on percentile weighting strategy', Computers & Graphics, vol. 74, pp. 12-22.
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Fernandez, E, Hossain, MJ & Nizami, MSH 2018, 'Game-theoretic approach to demand-side energy management for a smart neighbourhood in Sydney incorporating renewable resources', Applied Energy, vol. 232, pp. 245-257.
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Fernández-Barrera, J, Bernabé-Rubio, M, Casares-Arias, J, Rangel, L, Fernández-Martín, L, Correas, I & Alonso, MA 2018, 'The actin-MRTF-SRF transcriptional circuit controls tubulin acetylation via α-TAT1 gene expression', The Journal of Cell Biology, vol. 217, no. 3, pp. 929-944.
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The role of formins in microtubules is not well understood. In this study, we have investigated the mechanism by which INF2, a formin mutated in degenerative renal and neurological hereditary disorders, controls microtubule acetylation. We found that silencing of INF2 in epithelial RPE-1 cells produced a dramatic drop in tubulin acetylation, increased the G-actin/F-actin ratio, and impaired myocardin-related transcription factor (MRTF)/serum response factor (SRF)–dependent transcription, which is known to be repressed by increased levels of G-actin. The effect on tubulin acetylation was caused by the almost complete absence of α-tubulin acetyltransferase 1 (α-TAT1) messenger RNA (mRNA). Activation of the MRTF-SRF transcriptional complex restored α-TAT1 mRNA levels and tubulin acetylation. Several functional MRTF-SRF–responsive elements were consistently identified in the α-TAT1 gene. The effect of INF2 silencing on microtubule acetylation was also observed in epithelial ECV304 cells, but not in Jurkat T cells. Therefore, the actin-MRTF-SRF circuit controls α-TAT1 transcription. INF2 regulates the circuit, and hence microtubule acetylation, in cell types where it has a prominent role in actin polymerization.
Fitch, R, Isler, V, Tokekar, P & Scaramuzza, D 2018, 'Guest editorial: Special issue on active perception', Autonomous Robots, vol. 42, no. 2, pp. 175-176.
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Fonseca, A, Kerick, S, King, J-T, Lin, C-T & Jung, T-P 2018, 'Brain Network Changes in Fatigued Drivers: A Longitudinal Study in a Real-World Environment Based on the Effective Connectivity Analysis and Actigraphy Data', Frontiers in Human Neuroscience, vol. 12.
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© 2018 Fonseca, Kerick, King, Lin and Jung. The analysis of neurophysiological changes during driving can clarify the mechanisms of fatigue, considered an important cause of vehicle accidents. The fluctuations in alertness can be investigated as changes in the brain network connections, reflected in the direction and magnitude of the information transferred. Those changes are induced not only by the time on task but also by the quality of sleep. In an unprecedented 5-month longitudinal study, daily sampling actigraphy and EEG data were collected during a sustained-attention driving task within a near-real-world environment. Using a performance index associated with the subjects' reaction times and a predictive score related to the sleep quality, we identify fatigue levels in drivers and investigate the shifts in their effective connectivity in different frequency bands, through the analysis of the dynamical coupling between brain areas. Study results support the hypothesis that combining EEG, behavioral and actigraphy data can reveal new features of the decline in alertness. In addition, the use of directed measures such as the Convergent Cross Mapping can contribute to the development of fatigue countermeasure devices.
Forouzesh, M, Shen, Y, Yari, K, Siwakoti, YP & Blaabjerg, F 2018, 'High-Efficiency High Step-Up DC–DC Converter With Dual Coupled Inductors for Grid-Connected Photovoltaic Systems', IEEE Transactions on Power Electronics, vol. 33, no. 7, pp. 5967-5982.
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© 1986-2012 IEEE. This paper introduces a non-isolated high step-up DC-DC converter with dual coupled inductors suitable for distributed generation applications. By implementing an input parallel connection, the proposed DC-DC structure inherits shared input current with low ripple, which also requires small capacitive filter at its input. Moreover, this topology can reach high voltage gain by using dual coupled inductors in series connection at the output stage. The proposed converter uses active clamp circuits with a shared clamp capacitor for the main switches. In addition to the active clamp circuit, the leakage energy is recycled to the output by using an integrated regenerative snubber. Indeed, these circuits allow soft-switching conditions, i.e., zero voltage switching and zero current switching for active and passive switching devices, respectively. The mentioned features along with a common ground connection of the input and output make the proposed topology a proper candidate for transformer-less grid-connected photovoltaic systems. The operating performance, analysis and mathematical derivations of the proposed DC-DC converter have been demonstrated in the paper. Moreover, the main features of the proposed converter have been verified through experimental results of a 1-kW laboratory prototype.
Fortunato, L, Pathak, N, Ur Rehman, Z, Shon, H & Leiknes, T 2018, 'Real-time monitoring of membrane fouling development during early stages of activated sludge membrane bioreactor operation', Process Safety and Environmental Protection, vol. 120, pp. 313-320.
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© 2018 Institution of Chemical Engineers Non-invasive analysis and a final destructive analysis were employed to study the fouling formation during the initial days of AS-MBR operation. The fouling layer development was quantified in-situ non-invasively with Optical Coherence Tomography (OCT). The increase in biomass thickness was related to the transmembrane pressure (TMP) and to the increase in concentration of soluble microbial products (SMP) in the reactor The OCT non-destructive analysis allowed normalizing the final autopsy values for the amount of biomass deposited on the membrane. After 8 days of operation, the cake layer presented a biomass activity of 400 pg/mm3 of intra-ATP and EPS concentration of 9.8 mg/ mm3. The microbial community analysis of sludge and biofouling on the membrane surface revealed the abundance of Proteobacteria.
Frawley, JK & Dyson, LE 2018, 'Literacies and Learning in Motion', International Journal of Mobile and Blended Learning, vol. 10, no. 4, pp. 52-72.
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Mobile and participatory cultures have led to widespread change in the way we communicate; emphasizing user generated content and digital multimedia. In this environment, informal learning may occur through digital and networked activities, with literacy no longer limited to alphabetic and character-based texts. This article explores adult learners' new literacies within the context of a digital mobile storytelling project. A qualitative approach is used to explore the artifacts and practices of nine adult participants who comprise the study. Participants created a range of fiction, non-fiction, poetry and diary-style content in a variety of modes and media. Outcomes from content analysis, interview and survey methods depict mobile digital literacies as characteristically situated, experiential and multimodal. The mobile and participatory nature of this project was catalytic to participants' imaginative re-interpretation of the world around them as sources for meaning making and transformation. This paper contributes a case example of mobile learning with adults in a community setting.
Fu, A, Li, S, Yu, S, Zhang, Y & Sun, Y 2018, 'Privacy-preserving composite modular exponentiation outsourcing with optimal checkability in single untrusted cloud server', Journal of Network and Computer Applications, vol. 118, pp. 102-112.
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© 2018 Elsevier Ltd Outsourcing computing allows users with resource-constrained devices to outsource their complex computation workloads to cloud servers, which is more economical for cloud customers. However, since users lose direct control of the computation task, possible threats need to be addressed, such as data privacy and the correctness of results. Modular exponentiation is one of the most basic and time-consuming operations but widely applied in the field of cryptography. In this paper, we propose two new and efficient algorithms for secure outsourcing of single and multiple composite modular exponentiations. Unlike the algorithms based on two untrusted servers, we outsource modular exponentiation operation to only a single server, eliminating the possible collusion attack with two servers. Moreover, we put forward a new mathematical division method, which hides the base and exponent of the outsourced data, without exposing sensitive information to the cloud server. In addition, compared with other state-of-the-art algorithms, our scheme shows a remarkable improvement in checkability, enabling the user to detect any misbehavior with the optimal probability close to 1. Finally, we use our proposed algorithms as a subroutine to realize Shamir's Identity-Based Signature Scheme and Identity-Based Multi-Signatures Scheme.
Fu, A, Li, Y, Yu, S, Yu, Y & Zhang, G 2018, 'DIPOR: An IDA-based dynamic proof of retrievability scheme for cloud storage systems', Journal of Network and Computer Applications, vol. 104, pp. 97-106.
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As cloud storage has become more and more ubiquitous, there are a large number of consumers renting cloud storage services. However, as users lose direct control over the data, the integrity and availability of the outsourced data become a big concern for users. Accordingly, how to verify the integrity of stored data and retrieve the availability of the corrupted data has become an urgent problem. Moreover, in most cases, users' data is not always static, but needs to be updated. In this paper, we propose a dynamic proof of retrievability scheme for cloud storage system, named as DIPOR. The DIPOR not only can retrieve the original data of corrupted blocks by using partial healthy data stored in healthy servers, but also support for updating operations of data. Furthermore, the number of forks in our scheme is not fixed, which means we can always look for the optimal forks based on the number of data blocks. In addition, the security analysis indicates that our scheme is provably secure and the performance evaluations show the efficiency of the proposed scheme.
Fu, A, Zhu, Y, Yang, G, Yu, S & Yu, Y 2018, 'Secure outsourcing algorithms of modular exponentiations with optimal checkability based on a single untrusted cloud server', Cluster Computing, vol. 21, no. 4, pp. 1933-1947.
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Fu, Q, Ranji-Burachaloo, H, Liu, M, McKenzie, TG, Tan, S, Reyhani, A, Nothling, MD, Dunstan, DE & Qiao, GG 2018, 'Controlled RAFT polymerization facilitated by a nanostructured enzyme mimic', Polymer Chemistry, vol. 9, no. 35, pp. 4448-4454.
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A nanostructured MOF composite was utilized as an enzyme mimic for the generation of hydroxyl radicals from hydrogen peroxide, which can subsequently initiate RAFT polymerizations in aqueous or organic media.
Fujioka, T, Hoang, AT, Okuda, T, Takeuchi, H, Tanaka, H & Nghiem, LD 2018, 'Water Reclamation Using a Ceramic Nanofiltration Membrane and Surface Flushing with Ozonated Water', International Journal of Environmental Research and Public Health, vol. 15, no. 4, pp. 799-799.
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A new membrane fouling control technique using ozonated water flushing was evaluated for direct nanofiltration (NF) of secondary wastewater effluent using a ceramic NF membrane. Experiments were conducted at a permeate flux of 44 L/m2h to evaluate the ozonated water flushing technique for fouling mitigation. Surface flushing with clean water did not effectively remove foulants from the NF membrane. In contrast, surface flushing with ozonated water (4 mg/L dissolved ozone) could effectively remove most foulants to restore the membrane permeability. This surface flushing technique using ozonated water was able to limit the progression of fouling to 35% in transmembrane pressure increase over five filtration cycles. Results from this study also heighten the need for further development of ceramic NF membrane to ensure adequate removal of pharmaceuticals and personal care products (PPCPs) for water recycling applications. The ceramic NF membrane used in this study showed approximately 40% TOC rejection, and the rejection of PPCPs was generally low and highly variable. It is expected that the fouling mitigation technique developed here is even more important for ceramic NF membranes with smaller pore size and thus better PPCP rejection.
Fujioka, T, Kodamatani, H, Takeuchi, H, Tanaka, H & Nghiem, LD 2018, 'Online monitoring of N-nitrosodimethylamine for the removal assurance of 1,4-dioxane and other trace organic compounds by reverse osmosis', Environmental Science: Water Research & Technology, vol. 4, no. 12, pp. 2021-2028.
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Online monitoring of N-nitrosodimethylamine (NDMA) during reverse osmosis (RO) treatment was effective in ensuring the removal of trace organic chemicals, particularly 1,4-dioxane.
Fujioka, T, Nguyen, KH, Hoang, AT, Ueyama, T, Yasui, H, Terashima, M & Nghiem, LD 2018, 'Biofouling Mitigation by Chloramination during Forward Osmosis Filtration of Wastewater', International Journal of Environmental Research and Public Health, vol. 15, no. 10, pp. 2124-2124.
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Pre-concentration is essential for energy and resource recovery from municipal wastewater. The potential of forward osmosis (FO) membranes to pre-concentrate wastewater for subsequent biogas production has been demonstrated, although biofouling has also emerged as a prominent challenge. This study, using a cellulose triacetate FO membrane, shows that chloramination of wastewater in the feed solution at 3–8 mg/L residual monochloramine significantly reduces membrane biofouling. During a 96-h pre-concentration, flux in the chloraminated FO system decreased by only 6% and this flux decline is mostly attributed to the increase in salinity (or osmotic pressure) of the feed due to pre-concentration. In contrast, flux in the non-chloraminated FO system dropped by 35% under the same experimental conditions. When the feed was chloraminated, the number of bacterial particles deposited on the membrane surface was significantly lower compared to a non-chloraminated wastewater feed. This study demonstrated, for the first time, the potential of chloramination to inhibit bacteria growth and consequently biofouling during pre-concentration of wastewater using a FO membrane.
Fujioka, T, O'Rourke, BE, Michishio, K, Kobayashi, Y, Oshima, N, Kodamatani, H, Shintani, T & Nghiem, LD 2018, 'Transport of small and neutral solutes through reverse osmosis membranes: Role of skin layer conformation of the polyamide film', Journal of Membrane Science, vol. 554, pp. 301-308.
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© 2018 Elsevier B.V. The polyamide skin layer of reverse osmosis (RO) membranes was characterised using advanced and complementary analytical techniques to investigate the mechanisms underlying the permeation of contaminants of emerging concern in potable water reuse – N-nitrosodimethylamine (NDMA) and N-nitrosomethylethylamine (NMEA). This study used five RO membrane samples with similar membrane properties. The five RO membrane samples spanned over a large range of water permeance (0.9–5.8 L/m2 h bar) as well as permeation of NDMA (9–66%) and NMEA (3–29%). Despite these differences among the five RO membranes, characterisations of the skin layer using positron annihilation lifetime spectroscopy, atomic force microscopy and field emission scanning electron microscopy revealed almost no variation in their free-volume hole-radius (0.270–0.275 nm), effective surface area (198–212%) and thickness (30–35 nm) of the skin layer. The results suggest that there could be other RO skin layer properties, such as the interconnectivity of the protuberances within the polyamide skin layer additional to the free-volume hole-size and thickness of the skin layer, which can also govern water and solute permeation.
Gan, YY, Ong, HC, Ling, TC, Zulkifli, NWM, Wang, C-T & Yang, Y-C 2018, 'Thermal conductivity optimization and entropy generation analysis of titanium dioxide nanofluid in evacuated tube solar collector', Applied Thermal Engineering, vol. 145, pp. 155-164.
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Gan, YY, Ong, HC, Show, PL, Ling, TC, Chen, W-H, Yu, KL & Abdullah, R 2018, 'Torrefaction of microalgal biochar as potential coal fuel and application as bio-adsorbent', Energy Conversion and Management, vol. 165, pp. 152-162.
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Gandomi, AH & Alavi, AH 2018, 'Metaheuristics in Reliability and Risk Analysis', ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering, vol. 4, no. 3, pp. 02018001-02018001.
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Gandomi, AH & Goldman, BW 2018, 'Parameter-less population pyramid for large-scale tower optimization', Expert Systems with Applications, vol. 96, pp. 175-184.
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The parameter-less population pyramid (P3) is a recent evolutionary computation algorithm proposed for black box optimization. Shown to be efficient for a variety of benchmark problems, P3 replaces the conventional constant population model with expanding sets of expanding populations. We investigated how this new metaheuristic optimization algorithm would transfer to optimize large-scale tower structure problems involving different constraints: geometric and mechanical. P3 is examined by optimizing two discrete tower design problems, 26-story and 35- story tower structures. The performance of P3 is compared with other well-known evolutionary algorithms for black-box optimization including random restart hill climbing, parameter-less hierarchical Bayesian optimization algorithm, differential evolution, and a modified genetic algorithm. The results show that does P3 not only finds the best final solutions, but it also reaches high quality solutions much faster than the other algorithms This fast optimization is vital for the tedious and large-scale structural engineering problems. Finally, the unique search features used in the P3 and the implications for future studies are discussed.
Gandomi, AH & Kashani, AR 2018, 'Probabilistic evolutionary bound constraint handling for particle swarm optimization', Operational Research, vol. 18, no. 3, pp. 801-823.
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Keeping the search space between the valid domains is one of the most important necessities for most of the optimization problems. Among the optimization algorithms, particle swarm optimization (PSO) is highly likely to violate boundary limitations easily because of its oscillating behavior. Therefore, PSO is led to be sensitive to bound constraint handling (BCH) method. This matter has not been taken to account very much until now. This study attempt to apply and explore the efficiency of one of the most recent BCH schemes called evolutionary boundary constraint handling (EBCH) on PSO. In addition, probabilistic evolutionary boundary constraint handling (PEBCH) is also introduced in this study as an update on EBCH approach. As a complementary step of previous efforts, in the current document, PSO with both EBCH and PEBCH are utilized to solve several benchmark functions and the results are compared to other approaches in the literature. The results reveal that, in most cases, the EBCH and PEBCH can considerably improve the performance of the PSO algorithm in comparison with other BCH methods.
Gao, J, Li, H, Luo, Z, Gao, L & Li, P 2018, 'Topology optimization of micro-structured materials featured with the specific mechanical properties', International Journal of Computational Methods, vol. 17, no. 3.
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Micro-structured materials consisting of an array of microstructures areengineered to provide the specific material properties. This present workinvestigates the design of cellular materials under the framework of level set,so as to optimize the topologies and shapes of these porous materialmicrostructures. Firstly, the energy-based homogenization method (EBHM) isapplied to evaluate the material effective properties based on the topology ofthe material cell, where the effective elasticity property is evaluated by theaverage stress and strain theorems. Secondly, a parametric level set method(PLSM) is employed to optimize the microstructural topology until the specificmechanical properties can be achieved, including the maximum bulk modulus, themaximum shear modulus and their combinations, as well as the negative Poisson'sratio (NPR). The complicated topological shape optimization of the materialmicrostructure has been equivalent to evolve the sizes of the expansioncoefficients in the interpolation of the level set function. Finally, severalnumerical examples are fully discussed to demonstrate the effectiveness of thedeveloped method. A series of new and interesting material cells with thespecific mechanical properties can be found.
Gao, K, Gao, W, Wu, B, Wu, D & Song, C 2018, 'Nonlinear primary resonance of functionally graded porous cylindrical shells using the method of multiple scales', Thin-Walled Structures, vol. 125, pp. 281-293.
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An analytical method is proposed for the nonlinear primary resonance analysis of cylindrical shells made of functionally graded (FG) porous materials subjected to a uniformly distributed harmonic load including the damping effect. The Young's modulus, shear modulus and density of porous materials are assumed to vary through the thickness direction based on the assumption of a common mechanical feature of the open-cell foam. Three types of FG porous distributions, namely symmetric porosity distribution, non-symmetric porosity stiff or soft distribution and uniform porosity distribution are considered in this paper. Theoretical formulations are derived based on Donnell shell theory (DST) and accounting for von-Kármán strain-displacement relation and damping effect. The first mode of deflection function that satisfies the boundary conditions is introduced into this nonlinear governing partial differential equation and then a Galerkin-based procedure is utilized to obtain a Duffing-type nonlinear ordinary differential equation with a cubic nonlinear term. Finally, the governing equation is solved analytically by conducting the method of multiple scales (MMS) which results in frequency-response curves of FG porous cylindrical shells in the presence of damping effect. The detailed parametric studies on porosity distribution, porosity coefficient, damping ratio, amplitude and frequency of the external harmonic excitation, aspect ratio and thickness ratio, shown that the distribution type of FG porous cylindrical shells significantly affects primary resonance behavior and the response presents a hardening-type nonlinearity, which provides a useful help for the design and optimize of FG porous shell-type devices working under external harmonic excitation.
Gao, K, Gao, W, Wu, D & Song, C 2018, 'Nonlinear dynamic buckling of the imperfect orthotropic E-FGM circular cylindrical shells subjected to the longitudinal constant velocity', International Journal of Mechanical Sciences, vol. 138-139, pp. 199-209.
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In this study, an analytical approach on the nonlinear dynamic buckling of the orthotropic circular cylindrical shells made of exponential law functionally graded material (E-FGM) subjected to the longitudinal constant velocity is investigated with the incorporation of mercurial damping effect. The material properties are assumed to vary gradually in the thickness direction according to an exponential distribution function of the volume fraction of constituent materials. Theoretical formulations are derived based on improved Donnell shell theory (DST) and accounting for von-Kármán strain–displacement relation, initial imperfection and damping effect. By applying Galerkin method and Airy's stress function, the obtained nonlinear differential equations are solved numerically by the fourth-order Runge–Kutta method. The nonlinear dynamic stability of the orthotropic FG cylindrical shell is assessed based on Budiansky–Roth criterion. Additionally, a parametric study is conducted to demonstrate the effects of various velocities, initial imperfections, damping ratios, inhomogeneous parameters on nonlinear dynamic buckling behavior of an imperfect orthotropic FG cylindrical shell. Comparing results with those in other publications validates the proposed method.
Gao, K, Gao, W, Wu, D & Song, C 2018, 'Nonlinear dynamic stability of the orthotropic functionally graded cylindrical shell surrounded by Winkler-Pasternak elastic foundation subjected to a linearly increasing load', Journal of Sound and Vibration, vol. 415, pp. 147-168.
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This paper focuses on the dynamic stability behaviors of the functionally graded (FG) orthotropic circular cylindrical shell surrounded by the two-parameter (Winkler-Pasternak) elastic foundation subjected to a linearly increasing load with the consideration of damping effect. The material properties are assumed to vary gradually in the thickness direction based on an exponential distribution function of the volume fraction of constituent materials. Equations of motion are derived from Hamilton's principle and the nonlinear compatibility equation is considered by the means of modified Donnell shell theory including large deflection. Then the nonlinear dynamic buckling equation is solved by a hybrid analytical-numerical method (combined Galerkin method and fourth-order Runge-Kutta method). The nonlinear dynamic stability of the FG orthotropic cylindrical shell is assessed based on Budiansky-Roth criterion. Additionally, effects of different parameters such as various inhomogeneous parameters, loading speeds, damping ratios and aspect ratios and thickness ratios of the structure on dynamic buckling are discussed in details. Finally, the proposed method is validated with published literature.
Gao, L, Chen, J, Liu, Y, Yamauchi, Y, Huang, Z & Kong, X 2018, 'Revealing the chemistry of an anode-passivating electrolyte salt for high rate and stable sodium metal batteries', Journal of Materials Chemistry A, vol. 6, no. 25, pp. 12012-12017.
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A compact and conductive solid-electrolyte interphase formed by NaDFOB enables high performance of sodium metal batteries.
Gao, W, Wu, D, Gao, K, Chen, X & Tin-Loi, F 2018, 'Structural reliability analysis with imprecise random and interval fields', Applied Mathematical Modelling, vol. 55, pp. 49-67.
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This paper investigates the issue of reliability assessment for engineering structures involving mixture of stochastic and non-stochastic uncertain parameters through the Finite Element Method (FEM). Non-deterministic system inputs modelled by both imprecise random and interval fields have been incorporated, so the applicability of the structural reliability analysis scheme can be further promoted to satisfy the intricate demand of modern engineering application. The concept of robust structural reliability profile for systems involving hybrid uncertainties is discussed, and then a new computational scheme, namely the unified interval stochastic reliability sampling (UISRS) approach, is proposed for assessing the safety of engineering structures. The proposed method provides a robust semi-sampling scheme for assessing the safety of engineering structures involving multiple imprecise random fields with various distribution types and interval fields simultaneously. Various aspects of structural reliability analysis with multiple imprecise random and interval fields are explored, and some theoretically instructive remarks are also reported herein.
Gao, X, Zhang, T, Du, J & Guo, YJ 2018, 'Design, modelling and simulation of a monolithic high-T c superconducting terahertz mixer', Superconductor Science and Technology, vol. 31, no. 11, pp. 115010-115010.
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© 2018 IOP Publishing Ltd. This paper presents a novel concept and design of a full monolithic integrated high-T c superconducting (HTS) Josephson junction terahertz (THz) harmonic mixer coupled with a circularly polarized (CP) antenna. The fully on-chip mixer device is very compact in size and utilizes the CP antenna to enhance the polarization orientation flexibility in coupling THz radiation. Electromagnetic simulations are carried out to optimize the coupling efficiency and axial ratio of the THz CP antenna, and the signal transmission and isolation characteristics of the monolithic circuit. An equivalent circuit model of the HTS THz mixer is then established and simulation is performed based on our previously measured step-edge Josephson junction characteristics to evaluate the device performance and validate the concept of design. The results show that a superior performance could be achieved from such a monolithic HTS mixer device, which is significantly better than any HTS THz harmonic mixers reported to date.
Gardner, A & Willey, K 2018, 'Academic identity reconstruction: the transition of engineering academics to engineering education researchers', Studies in Higher Education, vol. 43, no. 2, pp. 234-250.
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The field of research (FoR) that an academic participates in is both a manifestation of, and a contributor to the development of their identity. When an academic changes that FoR the question then arises as to how they reconcile this change with their identity. This paper uses the identity-trajectory framework to analyse the discourse of 19 engineering academics in relation to their educational research. The findings reveal insights into the identity changes experienced in the transition from typical engineering academic to engineering education researcher. Participants’ responses illustrate how various aspects of their research activities contribute to the development of the networking and intellectual strands of their academic identity as engineering education researchers, and the effect of their university environment on this development. Conference participation was found to be an important contributor to progression of the intellectual and networking strands of identity-trajectory for researchers at all stages of development, although for different reasons.
Gaviria-Marin, M, Merigo, JM & Popa, S 2018, 'Twenty years of theJournal of Knowledge Management: a bibliometric analysis', Journal of Knowledge Management, vol. 22, no. 8, pp. 1655-1687.
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PurposeIn 2017, theJournal of Knowledge Management(JKM) celebrates its 20th anniversary. This study aims to show an updated analysis of their publications to provide a general overview of the journal, focusing on a bibliometric analysis of its publications between 1997 and 2016.Design/methodology/approachThe methodology involves two procedures: a performance analysis and a science mapping analysis of JKM. The performance analysis uses a series of bibliometric indicators such ash-index, productivity and citations. This analysis considers different dimensions, including papers, authors, universities and countries. VOSviewer software is used to carry out the mapping of science of JKM, which, based on the concurrence of key words and co-citation points of view, seeks to graphically analyze the structure of the references of this journal.FindingsThere is a positive evolution in the number of publications (although with certain oscillations), which shows a growing interest in publishing in JKM. The USA and the UK lead the publications in this journal, although at a regional level, Europe is the most productive. The low participation of emerging economies in JKM is also observed.Practical implicationsThe paper will identify the leading trends in the journal in terms of papers, authors, institutions, countries, journals and keywords. This study is useful for obtaining a quick snapshot of what is happening in the journal.Originality/valueFrom the h...
George, L, Lehmann, T & Hamilton, TJ 2018, 'A reconfigurable dual-output buck-boost switched-capacitor converter using adaptive gain and discrete frequency scaling control', Microelectronics Journal, vol. 73, pp. 59-74.
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Ghabrial, A, Franklin, D & Zaidi, H 2018, 'A Monte Carlo simulation study of the impact of novel scintillation crystals on performance characteristics of PET scanners', Physica Medica, vol. 50, pp. 37-45.
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The purpose of this study is to validate a Monte Carlo simulation model for the clinical Siemens Biograph mCT PET scanner using the GATE simulation toolkit, and to evaluate the performance of six different scintillation materials in this model using the National Electrical Manufactures Association (NEMA) NU 2-2007 protocol.A model of the Biograph mCT PET detection system and its geometry was developed. NEMA NU 2-2007 phantoms were also modelled. The accuracy of the developed scanner model was validated through a comparison of the simulation results from GATE, SimSET and PeneloPET toolkits, and experimental data obtained using the NEMA NU 2-2007 protocols. The evaluated performance metrics included count rate performance, spatial resolution, sensitivity, and scatter fraction (SF). Thereafter, the mCT PET scanner was simulated with six different candidate high-performance scintillation materials, including LSO, LaBr3, CeBr3, LuAP, GLuGAG and LFS-3, and its performance evaluated according to the NEMA NU 2-2007 specifications.The Monte Carlo simulation model demonstrates good agreement with the experimental data and results from other simulation packages. For instance, the scatter fraction calculated using GATE simulation is 34.35% while the experimentally measured value is 33.2%, 38.48% for the SimSET, and 34.8% for the PeneloPET toolkit. The best-performing scintillation materials were found to be LuAP, LSO and LFS-3, while GLuGAG offers acceptable performance if cost is the dominant concern.The main performance characteristics of the Biograph mCT PET scanner can be simulated accurately using GATE with a good agreement with other Monte Carlo simulation packages and experimental measurements. Newly developed scintillators show promise and offer alternative options for the design of novel generation PET scanners.
Ghaffari Jadidi, M, Valls Miro, J & Dissanayake, G 2018, 'Gaussian processes autonomous mapping and exploration for range-sensing mobile robots', Autonomous Robots, vol. 42, no. 2, pp. 273-290.
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© 2017, Springer Science+Business Media, LLC. Most of the existing robotic exploration schemes use occupancy grid representations and geometric targets known as frontiers. The occupancy grid representation relies on the assumption of independence between grid cells and ignores structural correlations present in the environment. We develop a Gaussian processes (GPs) occupancy mapping technique that is computationally tractable for online map building due to its incremental formulation and provides a continuous model of uncertainty over the map spatial coordinates. The standard way to represent geometric frontiers extracted from occupancy maps is to assign binary values to each grid cell. We extend this notion to novel probabilistic frontier maps computed efficiently using the gradient of the GP occupancy map. We also propose a mutual information-based greedy exploration technique built on that representation that takes into account all possible future observations. A major advantage of high-dimensional map inference is the fact that such techniques require fewer observations, leading to a faster map entropy reduction during exploration for map building scenarios. Evaluations using the publicly available datasets show the effectiveness of the proposed framework for robotic mapping and exploration tasks.
Ghanbarikarekani, M, Qu, X, Zeibots, M & Qi, W 2018, 'Minimizing the Average Delay at Intersections via Presignals and Speed Control', Journal of Advanced Transportation, vol. 2018, pp. 1-8.
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Urban intersections have been well recognized as bottlenecks of urban transport systems. It is thus important to propose and implement strategies for increasing the efficiency of public and private transportation systems as a whole. In order to achieve this goal, an additional signal could be set up near the intersection to give priority to buses through stopping vehicles in advance of the main intersection as a presignal. It has been increasingly popular in urban cities. While presignals indeed reduce the average delay per traveler, they cause extra stops of private vehicles, which might compromise the overall efficiency, safety, and sustainability. This paper aims to propose a model to improve presignals by reducing the vehicles’ number of stops behind the presignals. By applying the method, vehicles would be able to adjust their speed based on traffic conditions as well as buses’ speed and approach. Numerical analyses have been conducted to determine the conditions required for implementing this method.
Gharehbaghi, S, Gandomi, AH, Achakpour, S & Omidvar, MN 2018, 'A hybrid computational approach for seismic energy demand prediction', Expert Systems with Applications, vol. 110, pp. 335-351.
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In this paper, a hybrid genetic programming (GP) with multiple genes is implemented for developing prediction models of spectral energy demands. A multi-objective strategy is used for maximizing the accuracy and minimizing the complexity of the models. Both structural properties and earthquake characteristics are considered in prediction models of four demand parameters. Here, the earthquake records are classified based on soil type assuming that different soil classes have linear relationships in terms of GP genes. Therefore, linear regression analysis is used to connect genes for different soil types, which results in a total of sixteen prediction models. The accuracy and effectiveness of these models were assessed using different performance metrics and their performance was compared with several other models. The results indicate that not only the proposed models are simple, but also they outperform other spectral energy demand models proposed in the literature.
Ghasemi, K, Pradhan, B & Jena, R 2018, 'Spatial Identification of Key Alteration Minerals Using ASTER and Landsat 8 Data in a Heavily Vegetated Tropical Area', Journal of the Indian Society of Remote Sensing, vol. 46, no. 7, pp. 1061-1073.
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© 2018, Indian Society of Remote Sensing. The Central Gold Belt (CGB) of Malaysia is a major host to gold deposits. Penjom, Raub, Selising and Buffalo reef are major gold mines in CGB. The study area, Selinsing gold mine, is located at the northwest of Pahang province on the lineament known as the Raub Bentong Suture. Presence of dense vegetation and cloud cover in tropical regions are main obstacles in alteration mapping using satellite imageries. In this study, Landsat 8 and ASTER level 1B images were used to map clay minerals and quartz rich zones at Selinsing gold mine and surrounding areas. Direct principal component analysis (DPCA), matched filtering (MF) and band ratio were the effective methods used in this study. High concentration of clay minerals was detected using band ratio 6/7, DPC2 and MF and ratio 14/12 was carried out to highlight quartz rich zones. The results of image processing methods were verified by in situ inspection and X-ray diffraction analyses. The results show that, in spite of limited bedrock exposure, the known gold prospects and potential areas of mineralization can be recognized by the methods employed in this study.
Ghasemi, M, Ghavidel, S, Aghaei, J, Akbari, E & Li, L 2018, 'CFA optimizer: A new and powerful algorithm inspired by Franklin's and Coulomb's laws theory for solving the economic load dispatch problems', International Transactions on Electrical Energy Systems, vol. 28, no. 5, pp. e2536-e2536.
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Copyright © 2018 John Wiley & Sons, Ltd. This paper presents a new efficient algorithm inspired by Franklin's and Coulomb's laws theory that is referred to as CFA algorithm, for finding the global solutions of optimal economic load dispatch problems in power systems. CFA is based on the impact of electrically charged particles on each other due to electrical attraction and repulsion forces. The effectiveness of the CFA in different terms is tested on basic benchmark problems. Then, the quality of the CFA to achieve accurate results in different aspects is examined and proven on economic load dispatch problems including 4 different size cases, 6, 10, 15, and 110-unit test systems. Finally, the results are compared with other inspired algorithms as well as results reported in the literature. The simulation results provide evidence for the well-organized and efficient performance of the CFA algorithm in solving great diversity of nonlinear optimization problems.
Ghavidel, S, Azizivahed, A & Li, L 2018, 'A hybrid Jaya algorithm for reliability–redundancy allocation problems', Engineering Optimization, vol. 50, no. 4, pp. 698-715.
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© 2017 Informa UK Limited, trading as Taylor & Francis Group. This article proposes an efficient improved hybrid Jaya algorithm based on time-varying acceleration coefficients (TVACs) and the learning phase introduced in teaching–learning-based optimization (TLBO), named the LJaya-TVAC algorithm, for solving various types of nonlinear mixed-integer reliability–redundancy allocation problems (RRAPs) and standard real-parameter test functions. RRAPs include series, series–parallel, complex (bridge) and overspeed protection systems. The search power of the proposed LJaya-TVAC algorithm for finding the optimal solutions is first tested on the standard real-parameter unimodal and multi-modal functions with dimensions of 30–100, and then tested on various types of nonlinear mixed-integer RRAPs. The results are compared with the original Jaya algorithm and the best results reported in the recent literature. The optimal results obtained with the proposed LJaya-TVAC algorithm provide evidence for its better and acceptable optimization performance compared to the original Jaya algorithm and other reported optimal results.
Gheisari, S, Catchpoole, DR, Charlton, A & Kennedy, PJ 2018, 'Convolutional Deep Belief Network with Feature Encoding for Classification of Neuroblastoma Histological Images', Journal of Pathology Informatics, vol. 9, no. 1, pp. 17-17.
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© 2018 Journal of Pathology Informatics. Background: Neuroblastoma is the most common extracranial solid tumor in children younger than 5 years old. Optimal management of neuroblastic tumors depends on many factors including histopathological classification. The gold standard for classification of neuroblastoma histological images is visual microscopic assessment. In this study, we propose and evaluate a deep learning approach to classify high-resolution digital images of neuroblastoma histology into five different classes determined by the Shimada classification. Subjects and Methods: We apply a combination of convolutional deep belief network (CDBN) with feature encoding algorithm that automatically classifies digital images of neuroblastoma histology into five different classes. We design a three-layer CDBN to extract high-level features from neuroblastoma histological images and combine with a feature encoding model to extract features that are highly discriminative in the classification task. The extracted features are classified into five different classes using a support vector machine classifier. Data: We constructed a dataset of 1043 neuroblastoma histological images derived from Aperio scanner from 125 patients representing different classes of neuroblastoma tumors. Results: The weighted average F-measure of 86.01% was obtained from the selected high-level features, outperforming state-of-the-art methods. Conclusion: The proposed computer-aided classification system, which uses the combination of deep architecture and feature encoding to learn high-level features, is highly effective in the classification of neuroblastoma histological images.
Gheisari, S, Catchpoole, DR, Charlton, A, Melegh, Z, Gradhand, E & Kennedy, PJ 2018, 'Computer Aided Classification of Neuroblastoma Histological Images Using Scale Invariant Feature Transform with Feature Encoding', Diagnostics, vol. 8, no. 3, pp. 56-56.
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Neuroblastoma is the most common extracranial solid malignancy in early childhood. Optimal management of neuroblastoma depends on many factors, including histopathological classification. Although histopathology study is considered the gold standard for classification of neuroblastoma histological images, computers can help to extract many more features some of which may not be recognizable by human eyes. This paper, proposes a combination of Scale Invariant Feature Transform with feature encoding algorithm to extract highly discriminative features. Then, distinctive image features are classified by Support Vector Machine classifier into five clinically relevant classes. The advantage of our model is extracting features which are more robust to scale variation compared to the Patched Completed Local Binary Pattern and Completed Local Binary Pattern methods. We gathered a database of 1043 histologic images of neuroblastic tumours classified into five subtypes. Our approach identified features that outperformed the state-of-the-art on both our neuroblastoma dataset and a benchmark breast cancer dataset. Our method shows promise for classification of neuroblastoma histological images.
Ghorbani, S, Eyni, H, Bazaz, SR, Nazari, H, Asl, LS, Zaferani, H, Kiani, V, Mehrizi, AA & Soleimani, M 2018, 'Hydrogels Based on Cellulose and its Derivatives: Applications, Synthesis, and Characteristics', Polymer Science, Series A, vol. 60, no. 6, pp. 707-722.
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Hydrogels are mainly structures formed from biopolymers and/or polyelectrolytes, and contain large amounts of trapped water. Smart cellulose-based superabsorbent hydrogels are the new generation of scaffold which fabricated directly from native cellulose (including bacterial cellulose) via cellulose dissolution. Cellulose has many hydroxyl groups and can be used to prepare hydrogels with fascinating structures and properties. Cellulose hydrogels based on its derivatives, including methyl cellulose (MC), hydroxypropyl cellulose (HPC), hydroxypropylmethyl cellulose (HPMC), and carboxymethyl cellulose (CMC) can be fabricated by various methods. On the basis of the cross-linking method, the hydrogels can be divided into chemical and physical gels. Physical gels are formed by molecular self-assembly through ionic or hydrogen bonds, while chemical gels are formed by covalent bonds. Composite smart hydrogels are prepared using cellulose in conjunction with other polymers through blending, formation of polyelectrolyte complexes, and interpenetrating polymer networks (IPNs) technology. According to type of superabsorbent cellulose-based hydrogels fabrication methods, there are many various techniques to evaluate quality of them. Briefly, some of these means generally used to assess the hydrogel are described as following. The obtained gel membranes are characterized by infrared spectroscopy, scanning electron microscopy, thermo gravimetric analysis, and mechanical tests in order to investigate the crosslinking occurrence and modifications of cellulose resulting from the synthetic process, morphology of the hydrogels, their thermal stability, and viscoelastic extensional properties, respectively. This review highlights the recent progress in smart cellulose-based superabsorbent hydrogel designs, fabrication approaches and characterization methods, leading to the development of cellulose based smart superabsorbent hydrogels.
Ghorbani, S, Eyni, H, Tiraihi, T, Salari Asl, L, Soleimani, M, Atashi, A, Pour Beiranvand, S & Ebrahimi Warkiani, M 2018, 'Combined effects of 3D bone marrow stem cell-seeded wet-electrospun poly lactic acid scaffolds on full-thickness skin wound healing', International Journal of Polymeric Materials and Polymeric Biomaterials, vol. 67, no. 15, pp. 905-912.
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© 2017 Taylor & Francis. Tissue engineering has emerged as an alternative treatment to traditional grafts for skin wound healing. Three-dimensional nanofibers have been used extensively for this purpose due to their excellent biomedical-related properties. In this study, high porous 3D poly lactic acid nanofibrous scaffolds (PLA-S) were prepared by wet-electrospinning technique and seeded with rat bone-marrow stem cells (BMSCs) to characterize the biocompatibility and therapeutic efficacy of these fibers on the treating full-thickness dermal wounds. The results of in vitro andin vivo studies indicate that the 3D fibrous PLA-S can be a potential wound dressing for wound repair, particularly when seeded with BMSCs. GRAPHICAL ABSTRACT.
Ghosh, S & Lee, JE-Y 2018, 'Piezoelectric-on-silicon Lorentz force magnetometers based on radial contour mode disk resonators', Sensors and Actuators A: Physical, vol. 281, pp. 185-195.
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Gill, AQ, Henderson-Sellers, B & Niazi, M 2018, 'Scaling for agility: A reference model for hybrid traditional-agile software development methodologies', Information Systems Frontiers, vol. 20, no. 2, pp. 315-341.
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© 2016, Springer Science+Business Media New York. The adoption of agility at a large scale often requires the integration of agile and non-agile development elements for architecting a hybrid adaptive methodology. The challenge is ”which elements or components (agile or non-agile) are relevant to develop the context-aware hybrid adaptive methodology reference architecture?” This paper addresses this important challenge and develops a hybrid adaptive methodology reference architecture model using a qualitative constructive empirical research approach. In this way, we have uncovered the agility, abstraction, business value, business policy, rules, legal, context and facility elements or components that have not been explicitly modelled or discussed in International Standards (IS) such as the ISO/IEC 24744 metamodel. It is anticipated that a context-aware hybrid adaptive methodology can be architected by using the proposed context-aware hybrid adaptive methodology reference architecture elements for a particular situation when using a situational method engineering approach.
Girish, B, Gainder, S, Saha, SC & Krishnappa, D 2018, 'Rare Presentation of Catastrophic Antiphospholipid Syndrome with Myocarditis in Post-partum Period: Case Report and Review of Literature', The Journal of Obstetrics and Gynecology of India, vol. 68, no. 1, pp. 70-72.
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Goldsmith, R & Willey, K 2018, 'The otherness of writing in the engineering curriculum: A practice architectures perspective', JOURNAL OF ACADEMIC LANGUAGE AND LEARNING, vol. 12, no. 1, pp. A97-A114.
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Engineering students are expected to graduate with high level written and oral communication, yet these expectations continue to fall short despite repeated calls by industry and by accrediting bodies such as Engineers Australia for engineering faculties to address this issue. One explanation for this ongoing challenge is that the prevailing practices of engineering education constrain rather than enable the development of writing practices in the engineering curriculum, in part because writing practices are viewed as ‘other’, and as not belonging to engineering knowledge.
We argue that the reasons for the view of ‘otherness’ of writing practices in the engineering curriculum relate ontologically to the construction of engineering identities, and epistemologically to perspectives of engineering and writing as being different types of knowledge. Drawing on
elements of identities of engineering educators and students, research on engineering knowledge and legitimation code theory, the authors explore these ideas through the lens of practice architectures theory. The analysis reveals that dominant practices in engineering education place writing practices outside what is seen to be engineering, although there are exceptions.
The authors conclude that the practice architectures of the engineering curriculum which prefigure writing as being what engineers are not expected to be ‘good at’, and not as important as technical skills,
are so much a part of the ‘unspoken narratives’ of engineering educators that writing practices are marginalised. When they become part of what engineers do, they are re-framed as ‘documentation’. This suggests that writing practices can be seen as intrinsic to engineering education and practice if or when they are re-framed as engineering practice.
Golhani, K, Balasundram, SK, Vadamalai, G & Pradhan, B 2018, 'A review of neural networks in plant disease detection using hyperspectral data', Information Processing in Agriculture, vol. 5, no. 3, pp. 354-371.
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© 2018 China Agricultural University This paper reviews advanced Neural Network (NN) techniques available to process hyperspectral data, with a special emphasis on plant disease detection. Firstly, we provide a review on NN mechanism, types, models, and classifiers that use different algorithms to process hyperspectral data. Then we highlight the current state of imaging and non-imaging hyperspectral data for early disease detection. The hybridization of NN-hyperspectral approach has emerged as a powerful tool for disease detection and diagnosis. Spectral Disease Index (SDI) is the ratio of different spectral bands of pure disease spectra. Subsequently, we introduce NN techniques for rapid development of SDI. We also highlight current challenges and future trends of hyperspectral data.
Golkarian, A, Naghibi, SA, Kalantar, B & Pradhan, B 2018, 'Groundwater potential mapping using C5.0, random forest, and multivariate adaptive regression spline models in GIS', Environmental Monitoring and Assessment, vol. 190, no. 3.
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© 2018, Springer International Publishing AG, part of Springer Nature. Ever increasing demand for water resources for different purposes makes it essential to have better understanding and knowledge about water resources. As known, groundwater resources are one of the main water resources especially in countries with arid climatic condition. Thus, this study seeks to provide groundwater potential maps (GPMs) employing new algorithms. Accordingly, this study aims to validate the performance of C5.0, random forest (RF), and multivariate adaptive regression splines (MARS) algorithms for generating GPMs in the eastern part of Mashhad Plain, Iran. For this purpose, a dataset was produced consisting of spring locations as indicator and groundwater-conditioning factors (GCFs) as input. In this research, 13 GCFs were selected including altitude, slope aspect, slope angle, plan curvature, profile curvature, topographic wetness index (TWI), slope length, distance from rivers and faults, rivers and faults density, land use, and lithology. The mentioned dataset was divided into two classes of training and validation with 70 and 30% of the springs, respectively. Then, C5.0, RF, and MARS algorithms were employed using R statistical software, and the final values were transformed into GPMs. Finally, two evaluation criteria including Kappa and area under receiver operating characteristics curve (AUC-ROC) were calculated. According to the findings of this research, MARS had the best performance with AUC-ROC of 84.2%, followed by RF and C5.0 algorithms with AUC-ROC values of 79.7 and 77.3%, respectively. The results indicated that AUC-ROC values for the employed models are more than 70% which shows their acceptable performance. As a conclusion, the produced methodology could be used in other geographical areas. GPMs could be used by water resource managers and related organizations to accelerate and facilitate water resource exploitation.
Gong, B, Wang, S, Sloan, SW, Sheng, D & Tang, C 2018, 'Modelling Coastal Cliff Recession Based on the GIM–DDD Method', Rock Mechanics and Rock Engineering, vol. 51, no. 4, pp. 1077-1095.
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Gong, C, Li, Z, Chang, X & Luo, Y 2018, 'Learning-Based Multimedia Analyses and Applications', Advances in Multimedia, vol. 2018, pp. 1-2.
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Gong, L, Heitor, A & Indraratna, B 2018, 'An approach to measure infill matric suction of irregular infilled rock joints under constant normal stiffness shearing', Journal of Rock Mechanics and Geotechnical Engineering, vol. 10, no. 4, pp. 653-660.
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Gonzales, R, Park, M, Tijing, L, Han, D, Phuntsho, S & Shon, H 2018, 'Modification of Nanofiber Support Layer for Thin Film Composite Forward Osmosis Membranes via Layer-by-Layer Polyelectrolyte Deposition', Membranes, vol. 8, no. 3, pp. 70-70.
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Electrospun nanofiber-supported thin film composite membranes are among the most promising membranes for seawater desalination via forward osmosis. In this study, a high-performance electrospun polyvinylidenefluoride (PVDF) nanofiber-supported thin film composite (TFC) membrane was successfully fabricated after molecular layer-by-layer polyelectrolyte deposition. Negatively-charged electrospun polyacrylic acid (PAA) nanofibers were deposited on electrospun PVDF nanofibers to form a support layer consisted of PVDF and PAA nanofibers. This resulted to a more hydrophilic support compared to the plain PVDF nanofiber support. The PVDF-PAA nanofiber support then underwent a layer-by-layer deposition of polyethylenimine (PEI) and PAA to form a polyelectrolyte layer on the nanofiber surface prior to interfacial polymerization, which forms the selective polyamide layer of TFC membranes. The resultant PVDF-LbL TFC membrane exhibited enhanced hydrophilicity and porosity, without sacrificing mechanical strength. As a result, it showed high pure water permeability and low structural parameter values of 4.12 L m−2 h−1 bar−1 and 221 µm, respectively, significantly better compared to commercial FO membrane. Layer-by-layer deposition of polyelectrolyte is therefore a useful and practical modification method for fabrication of high performance nanofiber-supported TFC membrane.
Gonzalez Cruz, C, Naderpour, M & Ramezani, F 2018, 'Water resource selection and optimisation for shale gas developments in Australia: A combinatorial approach', Computers & Industrial Engineering, vol. 124, pp. 1-11.
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Gour, G, Jennings, D, Buscemi, F, Duan, R & Marvian, I 2018, 'Quantum majorization and a complete set of entropic conditions for quantum thermodynamics', Nature Communications, vol. 9, no. 1.
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AbstractWhat does it mean for one quantum process to be more disordered than another? Interestingly, this apparently abstract question arises naturally in a wide range of areas such as information theory, thermodynamics, quantum reference frames, and the resource theory of asymmetry. Here we use a quantum-mechanical generalization of majorization to develop a framework for answering this question, in terms of single-shot entropies, or equivalently, in terms of semi-definite programs. We also investigate some of the applications of this framework, and remarkably find that, in the context of quantum thermodynamics it provides the first complete set of necessary and sufficient conditions for arbitrary quantum state transformations under thermodynamic processes, which rigorously accounts for quantum-mechanical properties, such as coherence. Our framework of generalized thermal processes extends thermal operations, and is based on natural physical principles, namely, energy conservation, the existence of equilibrium states, and the requirement that quantum coherence be accounted for thermodynamically.
Gracia, L, Perez-Vidal, C & Valls-Miro, J 2018, 'Advanced Mathematical Methods for Collaborative Robotics', Mathematical Problems in Engineering, vol. 2018, pp. 1-3.
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Gracia, L, Solanes, JE, Muñoz-Benavent, P, Esparza, A, Valls Miro, J & Tornero, J 2018, 'Cooperative transport tasks with robots using adaptive non-conventional sliding mode control', Control Engineering Practice, vol. 78, pp. 35-55.
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© 2018 Elsevier Ltd This work presents a hybrid position/force control of robots aimed at handling applications using multi-task and sliding mode ideas. The proposed robot control is based on a novel adaptive non-conventional sliding mode control used to robustly satisfy a set of inequality constraints defined to accomplish the cooperative transport task. In particular, these constraints are used to guarantee the reference parameters imposed by the task (e.g., keeping the load at a desired orientation) and to guide the robot using the human operator's forces detected by a force sensor located at the robot tool. Another feature of the proposal is the multi-layered nature of the strategy, where a set of four tasks are defined with different priorities. The effectiveness of the proposed adaptive non-conventional sliding mode control is illustrated by simulation results. Furthermore, the applicability and feasibility of the proposed robot control for transport tasks are substantiated by experimental results using a redundant 7R manipulator.
Gracia, L, Solanes, JE, Muñoz-Benavent, P, Valls Miro, J, Perez-Vidal, C & Tornero, J 2018, 'Adaptive Sliding Mode Control for Robotic Surface Treatment Using Force Feedback', Mechatronics, vol. 52, pp. 102-118.
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© 2018 Elsevier Ltd This work presents a hybrid position-force control of robots in order to apply surface treatments such as polishing, grinding, finishing, deburring, etc. The robot force control is designed using sliding mode concepts to benefit from robustness. In particular, the sliding mode force task is defined using equality constraints to attain the desired tool pressure on the surface, as well as to keep the tool orientation perpendicular to the surface. In order to deal with sudden changes in material stiffness, which are ultimately transferred to the polishing tool and can produce instability and compromise polishing performance, several adaptive switching gain laws are considered and compared. Moreover, a lower priority tracking controller is defined to follow the desired reference trajectory on the surface being polished. Hence, deviations from the reference trajectory are allowed if such deviations are required to satisfy the constraints mentioned above. Finally, a third-level task is also considered for the case of redundant robots in order to use the remaining degrees of freedom to keep the manipulator close to the home configuration with safety in mind. The main advantages of the method are increased robustness and low computational cost. The applicability and effectiveness of the proposed approach are substantiated by experimental results using a redundant 7R manipulator: the Rethink Robotics Sawyer collaborative robot.
Graham, C, Smith, W, Moncur, W & van den Hoven, E 2018, 'Introduction: Mortality in Design', Design Issues, vol. 34, no. 1, pp. 3-14.
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Gray, S, Voinov, A, Paolisso, M, Jordan, R, BenDor, T, Bommel, P, Glynn, P, Hedelin, B, Hubacek, K, Introne, J, Kolagani, N, Laursen, B, Prell, C, Schmitt Olabisi, L, Singer, A, Sterling, E & Zellner, M 2018, 'Purpose, processes, partnerships, and products: four Ps to advance participatory socio‐environmental modeling', Ecological Applications, vol. 28, no. 1, pp. 46-61.
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AbstractIncluding stakeholders in environmental model building and analysis is an increasingly popular approach to understanding ecological change. This is because stakeholders often hold valuable knowledge about socio‐environmental dynamics and collaborative forms of modeling produce important boundary objects used to collectively reason about environmental problems. Although the number of participatory modeling (PM) case studies and the number of researchers adopting these approaches has grown in recent years, the lack of standardized reporting and limited reproducibility have prevented PM's establishment and advancement as a cohesive field of study. We suggest a four‐dimensional framework (4P) that includes reporting on dimensions of (1) the Purpose for selecting a PM approach (the why); (2) the Process by which the public was involved in model building or evaluation (the how); (3) the Partnerships formed (the who); and (4) the Products that resulted from these efforts (the what). We highlight four case studies that use common PM software‐based approaches (fuzzy cognitive mapping, agent‐based modeling, system dynamics, and participatory geospatial modeling) to understand human–environment interactions and the consequences of ecological changes, including bushmeat hunting in Tanzania and Cameroon, agricultural production and deforestation in Zambia, and groundwater management in India. We demonstrate how standardizing communication about PM case studies can lead to innovation and new insights about model‐base...
Gu, Y, Cui, Q, Chen, Y, Ni, W, Tao, X & Zhang, P 2018, 'Effective Capacity Analysis in Ultra-Dense Wireless Networks With Random Interference', IEEE Access, vol. 6, pp. 19499-19508.
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© 2013 IEEE. Ultra-dense networks (UDNs) provide a promising paradigm to cope with exponentially increasing mobile traffic. However, a little work has to date considered unsaturated traffic with Quality-of-Service (QoS) requirements. This paper presents a new cross-layer analytical model to capture the unsaturated traffic of a UDN in the presence of QoS requirements. The effiective capacity (EC) of the UDN is derived, taking into account small-scale channel fading and possible interference. Key properties of the EC are revealed. The amount of traffic impacts EC of the UDN due to the sophisticated interactions among small base stations operating in the same frequency. The maximization of total EC is formulated as a non-cooperative game in this paper. The best-response function is derived, iteratively searching the Nash equilibrium point. System simulation results indicate that our proposed model is accurate. The simulations also show the maximum allowed arrival rate with the QoS guarantee, compared with the full interference model.
Gu, Y, Gu, M, Long, Y, Xu, G, Yang, Z, Zhou, J & Qu, W 2018, 'An enhanced short text categorization model with deep abundant representation', World Wide Web, vol. 21, no. 6, pp. 1705-1719.
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© 2018, Springer Science+Business Media, LLC, part of Springer Nature. Short text categorization is a crucial issue to many applications, e.g., Information Retrieval, Question-Answering System, MRI Database Construction and so forth. Many researches focus on data sparsity and ambiguity issues in short text categorization. To tackle these issues, we propose a novel short text categorization strategy based on abundant representation, which utilizes Bi-directional Recurrent Neural Network(Bi-RNN) with Long Short-Term Memory(LSTM) and topic model to catch more contextual and semantic information. Bi-RNN enriches contextual information, and topic model discovers more latent semantic information for abundant text representation of short text. Experimental results demonstrate that the proposed model is comparable to state-of-the-art neural network models and method proposed is effective.
Gulzar, M, Mahmood, K, Zahid, R, Alabdulkarem, A, Masjuki, HH, Kalam, MA, Varman, M, Zulkifli, NWM, Ahmad, P & Malik, MSS 2018, 'The effect of particle size on the dispersion and wear protection ability of MoS2 particles in polyalphaolefin and trimethylolpropane ester', Proceedings of the Institution of Mechanical Engineers, Part J: Journal of Engineering Tribology, vol. 232, no. 8, pp. 987-998.
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The effect of particle size and surfactant on dispersion stability and wear protection ability was experimentally evaluated for polyalphaolefin (PAO 10) and bio-based base oil (palm trimethylolpropane ester) added with molybdenum disulfide (MoS2) particles. Nanolubricants were developed by adding 1 wt% of MoS2 particles that varied in size. In addition to the variation in particle size, an anionic surfactant was also used to analyze its interaction with both types of nanoparticles for stable suspensions and for the related effects on the antiwear characteristics. The wear protection characteristics of the formulations were evaluated by four-ball extreme pressure tests and piston ring on cylinder sliding wear tests. The wear surfaces were analyzed by scanning electron microscopy along with an energy-dispersive X-ray and an atomic force microscopy. The MoS2 nanoparticles with a nominal size of 20 nm exhibited a better load-carrying capacity, while better sliding wear protection was provided by nanoparticles with a nominal size of 50 nm.
Gunawardane, K & Kularatna, N 2018, 'Supercapacitor‐assisted low dropout regulator technique: a new design approach to achieve high‐efficiency linear DC–DC converters', IET Power Electronics, vol. 11, no. 2, pp. 229-238.
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Guntuku, SC, Zhou, JT, Roy, S, Lin, W & Tsang, IW 2018, '‘Who Likes What and, Why?’ Insights into Modeling Users’ Personality Based on Image ‘Likes’', IEEE Transactions on Affective Computing, vol. 9, no. 1, pp. 130-143.
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© 2010-2012 IEEE. The increased proliferation of data production technologies (e.g., cameras) and consumption avenues (e.g., social media) has led to images and videos being utilized by users to convey innate preferences and tastes. This has opened up the possibility of using multimedia as a source for user-modeling. This work attempts to model personality traits (based on the Five Factor Theory) of users using a collection of images they tag as 'favorite' (or like) on Flickr. First, a set of semantic features are proposed to be used for representing different concepts in images which influence users to like them. The addition of the proposed features led to improvement over state-of-the-art by 12 percent. Second, a novel machine learning approach is developed to model users' personality based on the image features (resulting in upto 15 percent improvement). Third, efficacy of the semantic features and the modeling approach is shown in recommending images based on personality modeling. Using the modeling approach, recommendations are made regarding the factors that might influence users with different personality traits to like an image.
Guo, J, Yang, T, Yuan, J & Zhang, JA 2018, 'A Novel Linear Physical-Layer Network Coding Scheme for Y-Channel Without Transmitter CSI', IEEE Transactions on Vehicular Technology, vol. 67, no. 10, pp. 10049-10053.
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© 1967-2012 IEEE. We propose a novel linear physical-layer network coding (NC) scheme for a fading Y-channel without channel state information at transmitters. In this three-user scheme, each user intends to realize a full data exchange with the other two users via a relay. Instead of directly decoding the users' messages from the received signal, the relay determines NC generator matrices and reconstructs linear NC codewords from its received signals to facilitate the information exchange. We present an explicit solution for NC generator matrices that minimize the NC error probability at high SNRs. We also present and prove an approximation of the NC error probability of the proposed scheme at high SNRs. Numerical results show that the proposed scheme outperforms existing ones, and its performance can be well characterized by the approximation.
Guo, J, Yuan, J & Zhang, J 2018, 'An Achievable Throughput Scaling Law of Wireless Device-to-Device Caching Networks With Distributed MIMO and Hierarchical Cooperations', IEEE Transactions on Wireless Communications, vol. 17, no. 1, pp. 492-505.
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© 2002-2012 IEEE. In this paper, we propose a new caching scheme for a random wireless device-to-device (D2D) network of n nodes with local caches, where each node intends to download files from a prefixed library via D2D links. Our proposed caching delivery includes two stages, employing distributed MIMO and hierarchical cooperations, respectively. The distributed MIMO is applied to the first stage between source nodes and neighbors of the destination node. The induced multiplexing gain and diversity gain increase the number of simultaneous transmissions, improving the throughput of the network. The hierarchical cooperations are applied to the second stage to facilitate the transmissions between the destination node and its neighbors. The two stages together exploit spatial degrees of freedom as well as spatial reuse. We develop an uncoded random caching placement strategy to serve this cooperative caching delivery. Analytical results show that the average aggregate throughput of the network scales almost linearly with n, with a vanishing outage probability. Furthermore, we derive an explicit expression of the optimal throughput as a function of system parameters, such as pathloss factor under a target outage probability. Analytical and numerical results demonstrate that our proposed scheme outperforms existing ones when the local cache size is limited.
Guo, Q, Zhang, Y, Celler, BG & Su, SW 2018, 'State-Constrained Control of Single-Rod Electrohydraulic Actuator With Parametric Uncertainty and Load Disturbance', IEEE Transactions on Control Systems Technology, vol. 26, no. 6, pp. 2242-2249.
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IEEE The suppression of disturbances under parametric uncertainties is one of the most common control problems in electrohydraulic systems, as both disturbances and uncertainties often significantly degrade the tracking performance and bias the load pressure of the electrohydraulic actuator (EHA). This brief presents a state-constrained control of single-rod EHA to restrict the position tracking error to a prescribed accuracy and guarantee the load pressure in the maximal power boundary. Furthermore, a dynamic surface is designed to avoid the explosion of complexity due to the repeatedly calculated differentiations of the virtual control variables in the backstepping iteration. Integrating with a disturbance observer and the parametric estimation law, this state-constrained controller guarantees the asymptotic convergence of system state error under parametric uncertainties and large load disturbances. The effectiveness of the proposed controller has been demonstrated by a comparative experiment on the motion control of the two-degree-of-freedom robotic arm.
Guo, Y, Xie, H, Zhang, J, Wang, W, Ngo, HH, Guo, W, Kang, Y & Zhang, B 2018, 'Improving nutrient removal performance of surface flow constructed wetlands in winter using hardy submerged plant-benthic fauna systems', RSC Advances, vol. 8, no. 73, pp. 42179-42188.
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A novel hardy submerged plant-benthic fauna systems to enhance the performance of surface flow constructed wetlands in winter.
Guo, YJ, Qin, P-Y, Chen, S-L, Lin, W & Ziolkowski, RW 2018, 'Advances in Reconfigurable Antenna Systems Facilitated by Innovative Technologies', IEEE Access, vol. 6, pp. 5780-5794.
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© 2013 IEEE. Future fifth generation (5G) wireless platforms will require reconfigurable antenna systems to meet their performance requirements in compact, light-weight, and cost-effective packages. Recent advances in reconfigurable radiating and receiving structures have been enabled by a variety of innovative technology solutions. Examples of reconfigurable partially reflective surface antennas, reconfigurable filtennas, reconfigurable Huygens dipole antennas, and reconfigurable feeding network-enabled antennas are presented and discussed. They represent novel classes of frequency, pattern, polarization, and beam-direction reconfigurable systems realized by the innovative combinations of radiating structures and circuit components.
Guo, Z, Le, AN, Feng, X, Choo, Y, Liu, B, Wang, D, Wan, Z, Gu, Y, Zhao, J, Li, V, Osuji, CO, Johnson, JA & Zhong, M 2018, 'Janus Graft Block Copolymers: Design of a Polymer Architecture for Independently Tuned Nanostructures and Polymer Properties', Angewandte Chemie International Edition, vol. 57, no. 28, pp. 8493-8497.
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AbstractThe graft‐through synthesis of Janus graft block copolymers (GBCPs) from branched macromonomers composed of various combinations of homopolymers is presented. Self‐assembly of GBCPs resulted in ordered nanostructures with ultra‐small domain sizes down to 2.8 nm (half‐pitch). The grafted architecture introduces an additional parameter, the backbone length, which enables control over the thermomechanical properties and processability of the GBCPs independently of their self‐assembled nanostructures. The simple synthetic route to GBCPs and the possibility of using a variety of polymer combinations contribute to the universality of this technique.
Guo, Z, Le, AN, Feng, X, Choo, Y, Liu, B, Wang, D, Wan, Z, Gu, Y, Zhao, J, Li, V, Osuji, CO, Johnson, JA & Zhong, M 2018, 'Janus Graft Block Copolymers: Design of a Polymer Architecture for Independently Tuned Nanostructures and Polymer Properties', Angewandte Chemie, vol. 130, no. 28, pp. 8629-8633.
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AbstractThe graft‐through synthesis of Janus graft block copolymers (GBCPs) from branched macromonomers composed of various combinations of homopolymers is presented. Self‐assembly of GBCPs resulted in ordered nanostructures with ultra‐small domain sizes down to 2.8 nm (half‐pitch). The grafted architecture introduces an additional parameter, the backbone length, which enables control over the thermomechanical properties and processability of the GBCPs independently of their self‐assembled nanostructures. The simple synthetic route to GBCPs and the possibility of using a variety of polymer combinations contribute to the universality of this technique.
H. Almabrok, M, G. McLaughlan, R & Vessalas, K 2018, 'EFFECT OF SYNTHETIC DRILL CUTTINGS ON MORTAR PROPERTIES', Malaysian Journal of Civil Engineering, vol. 30, no. 3, pp. 405-414.
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Drill cuttings from oil exploration are recognised as a major environmental concern. Current cost-effective treatment technologies often involve sending treated products to landfill without any potential end-use thereby rendering these solutions unsustainable. There is potential for using drill cuttings comprising of oily, saline and clayey waste materials as fine aggregate replacements in structural concretes requiring characteristic compressive strength from 20-32 MPa. Research into the hydration process as well as evaluating the fresh and hardened properties of mortars incorporating synthetic drill cuttings were undertaken. Replacement of sand by synthetic drill cuttings (up to 25% by weight) produced mortar with accelerated hydration as well as reduced flow and density. In addition, the 28-day compressive strength of mortar incorporating synthetic drill cuttings decreased by up to 50%. Satisfactory strength for all sand replacement levels evaluated in mortars was still attainable for reuse of these synthetic of drill cuttings as fine aggregate replacements in structural concretes.
Ha, Q, Royel, S & Balaguer, C 2018, 'Low-energy structures embedded with smart dampers', Energy and Buildings, vol. 177, pp. 375-384.
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Building structures, subject to dynamic loadings or external disturbances, may undergo destructive vibrations and encounter different degrees of deformation. Modeling and control techniques can be applied to effectively damp out these vibrations and maintain structural health with a low energy cost. Smart structures embedded with semi-active control devices, offer a promising solution to the problem. The smart damping concept has been proven to be an effective approach for input energy shaping and sup- pressing unwanted vibrations in structural control for buildings embedded with magnetorheological fluid dampers (MRDs). In this paper, the dissipation energy in MRD is studied by using results from induced hysteretic effect of structural vibrations while the fluid is placed under a controlled magnetic field. Then, a frequency-shaped second-order sliding mode controller (FS2SMC) is designed along with a low-pass filter to implement the desired dynamic sliding surface, wherein the frequency responses of the hysteretic MRD is represented by its magnitude and phase describing functions. The proposed controller can thus shape the frequency characteristics of the equivalent dynamics for the MRD-embedded structure against induced vibrations, and hence, dissipate the energy flow within the smart devices to prevent structural damage. Simulation results for a 10-floor building model equipped with current-controlled MRDs, subject to horizontal seismic excitations validate the proposed technique for low-energy structures with smart devices. The closed-loop performance and comparison in terms of energy signals indicate that the pro- posed method allows not only to reduce induced vibrations and input energy, but also its spectrum can be adjusted to prevent natural modes of the structure under external excitations.
Halliday, BJ, Fukuzawa, R, Markie, DM, Grundy, RG, Ludgate, JL, Black, MA, Skeen, JE, Weeks, RJ, Catchpoole, DR, Roberts, AGK, Reeve, AE & Morison, IM 2018, 'Germline mutations and somatic inactivation of TRIM28 in Wilms tumour', PLOS Genetics, vol. 14, no. 6, pp. e1007399-e1007399.
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© 2018 Halliday et al. http://creativecommons.org/licenses/by/4.0/ Wilms tumour is a childhood tumour that arises as a consequence of somatic and rare germline mutations, the characterisation of which has refined our understanding of nephrogenesis and carcinogenesis. Here we report that germline loss of function mutations in TRIM28 predispose children to Wilms tumour. Loss of function of this transcriptional co-repressor, which has a role in nephrogenesis, has not previously been associated with cancer. Inactivation of TRIM28, either germline or somatic, occurred through inactivating mutations, loss of heterozygosity or epigenetic silencing. TRIM28-mutated tumours had a monomorphic epithelial histology that is uncommon for Wilms tumour. Critically, these tumours were negative for TRIM28 immunohistochemical staining whereas the epithelial component in normal tissue and other Wilms tumours stained positively. These data, together with a characteristic gene expression profile, suggest that inactivation of TRIM28 provides the molecular basis for defining a previously described subtype of Wilms tumour, that has early age of onset and excellent prognosis.
Hamdani, Rizal, S, Riza, M & Mahlia, TMI 2018, 'Mechanical properties of concrete containing beeswax/dammar gum as phase change material for thermal energy storage', AIMS Energy, vol. 6, no. 3, pp. 521-529.
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© 2018 the Author(s). This study aims to investigate the mechanical properties of concrete containing phase change materials (PCM). This research begins with the investigation of melting temperature, enthalpy, the thermal conductivity of the phase change materials using the T-history method, followed by preparation of concrete containing PCM, and finally testing of mechanical properties of concrete through compressive strength test. This study used beeswax, tallow, and dammar gum as PCM mixture. From the results of the PCM properties test, shows that the latent heat energy content from beeswax and tallow exhibit an excellent potential to be used as PCM, while dammar gum is benefited in increasing the thermal conductivity of concrete containing PCM. From concrete specimen test containing 10%, 20% and 30% PCM with 7 days and 28 days aged, the results exhibit that the mechanical properties of the concrete decreased along with the increasing of PCM content. The same test also conducted at the PCM melting temperature. Therefore, the concrete compressive strength test conducted at 45 °C. From the test results, the concrete compressive strength decreased about 3-24% of PCM-0% concrete compressive strength. Drastic compressive strength reduction tends to occur in PCM-Tallow concrete mixture. This study concluded that the PCM is potentially useful as a heat energy absorber material in buildings and lightweight concrete rather than construction structures.
Han, B, Pan, Y & Tsang, IW 2018, 'Robust Plackett–Luce model for k-ary crowdsourced preferences', Machine Learning, vol. 107, no. 4, pp. 675-702.
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© 2017, The Author(s). The aggregation of k-ary preferences is an emerging ranking problem, which plays an important role in several aspects of our daily life, such as ordinal peer grading and online product recommendation. At the same time, crowdsourcing has become a trendy way to provide a plethora of k-ary preferences for this ranking problem, due to convenient platforms and low costs. However, k-ary preferences from crowdsourced workers are often noisy, which inevitably degenerates the performance of traditional aggregation models. To address this challenge, in this paper, we present a RObust PlAckett–Luce (ROPAL) model. Specifically, to ensure the robustness, ROPAL integrates the Plackett–Luce model with a denoising vector. Based on the Kendall-tau distance, this vector corrects k-ary crowdsourced preferences with a certain probability. In addition, we propose an online Bayesian inference to make ROPAL scalable to large-scale preferences. We conduct comprehensive experiments on simulated and real-world datasets. Empirical results on “massive synthetic” and “real-world” datasets show that ROPAL with online Bayesian inference achieves substantial improvements in robustness and noisy worker detection over current approaches.
Han, B, Tsang, IW, Chen, L, Yu, CP & Fung, S-F 2018, 'Progressive Stochastic Learning for Noisy Labels', IEEE Transactions on Neural Networks and Learning Systems, vol. 29, no. 10, pp. 5136-5148.
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© 2018 IEEE. Large-scale learning problems require a plethora of labels that can be efficiently collected from crowdsourcing services at low cost. However, labels annotated by crowdsourced workers are often noisy, which inevitably degrades the performance of large-scale optimizations including the prevalent stochastic gradient descent (SGD). Specifically, these noisy labels adversely affect updates of the primal variable in conventional SGD. To solve this challenge, we propose a robust SGD mechanism called progressive stochastic learning (POSTAL), which naturally integrates the learning regime of curriculum learning (CL) with the update process of vanilla SGD. Our inspiration comes from the progressive learning process of CL, namely learning from 'easy' tasks to 'complex' tasks. Through the robust learning process of CL, POSTAL aims to yield robust updates of the primal variable on an ordered label sequence, namely, from 'reliable' labels to 'noisy' labels. To realize POSTAL mechanism, we design a cluster of 'screening losses,' which sorts all labels from the reliable region to the noisy region. To sum up, POSTAL using screening losses ensures robust updates of the primal variable on reliable labels first, then on noisy labels incrementally until convergence. In theory, we derive the convergence rate of POSTAL realized by screening losses. Meanwhile, we provide the robustness analysis of representative screening losses. Experimental results on UCI1 simulated and Amazon Mechanical Turk crowdsourcing data sets show that the POSTAL using screening losses is more effective and robust than several existing baselines.1UCI is the abbreviation of University of California Irvine.
Han, F, Wei, D, Ngo, HH, Guo, W, Xu, W, Du, B & Wei, Q 2018, 'Performance, microbial community and fluorescent characteristic of microbial products in a solid-phase denitrification biofilm reactor for WWTP effluent treatment', Journal of Environmental Management, vol. 227, pp. 375-385.
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Microbial products, i.e. extracellular polymeric substance (EPS) and soluble microbial product (SMP), have a significant correlation with microbial activity of biologically based systems. In present study, the spectral characteristics of two kinds of microbial products were comprehensively evaluated in a solid-phase denitrification biofilm reactor for WWTP effluent treatment by using poly (butylene succinate) (PBS) as carbon source. After the achievement of PBS-biofilm, nitrate and total nitrogen removal efficiencies were high of 97.39 ± 1.24% and 96.38 ± 1.1%, respectively. The contents of protein and polysaccharide were changed different degrees in both LB-EPS and TB-EPS. Excitation-emission matrix (EEM) implied that protein-like substances played a significant role in the formation of PBS-biofilm. High-throughput sequencing result implied that the proportion of denitrifying bacteria, including Simplicispira, Dechloromonas, Diaphorobacter, Desulfovibrio, increased to 9.2%, 7.4%, 4.8% and 3.6% in PBS-biofilm system, respectively. According to EEM-PARAFAC, two components were identified from SMP samples, including protein-like substances for component 1 and humic-like and fulvic acid-like substances for component 2, respectively. Moreover, the fluorescent scores of two components expressed significant different trends to reaction time. Gas chromatography-mass spectrometer (GC-MS) implied that some new organic matters were produced in the effluent of SP-DBR due to biopolymer degradation and denitrification processes. The results could provide a new insight about the formation and stability of solid-phase denitrification PBS-biofilm via the point of microbial products.
Han, L, Liu, S, Han, S, Jia, W & Lei, J 2018, 'Owner based malware discrimination', Future Generation Computer Systems, vol. 80, pp. 496-504.
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© 2016 Elsevier B.V. A piece of malware code can be harmful in one's system but totally harmless in another's. In this paper, we point out that the detection of malicious code or software is actually a matter of discrimination which depends on the owners of the computer systems. We propose an owner based malicious software discrimination model, named as Unlimited Register Machine of Owners (URMO). First, we characterize and analyze the limitations of existing discrimination techniques in theory by using the discrimination model of Unlimited Register Machine (URM) and then move on to construct the URMO discrimination model by giving the two important elements of malicious behavior: an operation and the object of the operation. The relationship between an operation and the object of the operation is fundamental to solving the relativity of the discrimination problem about malice, which is also the advantage of the URMO model. Finally, by applying the model to discriminate real-world malware and comparing it with existing popular antivirus software, we demonstrate the effectiveness and superior performance of the URMO model.
Han, W, Zhang, H-P, Tavakoli, J, Campbell, J & Tang, Y 2018, 'Polydopamine as sizing on carbon fiber surfaces for enhancement of epoxy laminated composites', Composites Part A: Applied Science and Manufacturing, vol. 107, pp. 626-632.
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Carbon fiber reinforced polymer (CFRP) laminate normally has plastic dominant crack propagation behavior, inducing potential insecurity in the safety and reliability of structures in practical applications. In this study, we report a simple process to increase the stability of crack growth by using polydopamine (PDA) as sizing on the surface of carbon fiber (CF) fabric. The crack propagation behavior changes from a saw-tooth-shaped curve in neat CFRP laminate to a relatively smooth trending curve in PDA coated CFRP laminate with increased Mode I interlaminar fracture toughness. Enhanced impact strength and interlaminar shear strength of PDA coated CFRP laminates is also observed. A single fiber pull-out experiment and morphological study reveal that, with PDA coating on CF fabrics, cracks tend to fracture through the epoxy matrix rather than between fiber and matrix interfaces. The use of PDA as sizing on the CF contributes to improving the load transfer between the CF and the polymer matrix by enhancing the interfaces between the epoxy and the CF, increasing the friction of the fractured interface, reducing unstable crack growth, and thereby enhancing interfacial fracture toughness and impact performance.
Han, Z, Wu, M, Zhu, Q & Yang, J 2018, 'Two-dimensional multizone sound field reproduction using a wave-domain method', The Journal of the Acoustical Society of America, vol. 144, no. 3, pp. EL185-EL190.
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This paper addresses a two-dimensional multizone sound field reproduction approach using a wave-domain method. The desired sound fields in the bright and dark zones are described as orthogonal expansions of basis functions over the regions. The loudspeaker weights are obtained by maximizing the contrast among multiple zones in the wave domain. Simulation results demonstrate that compared with the conventional acoustic contrast control approach, the proposed method improves the level of acoustic contrast and array gain over the entire control region and is less sensitive to the selection of the regularization parameter.
Handique, L & Chakraborty, S 2018, 'A new four-parameter extension of Burr-XII distribution: its properties and applications', Japanese Journal of Statistics and Data Science, vol. 1, no. 2, pp. 271-296.
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Handojoseno, AMA, Naik, GR, Gilat, M, Shine, JM, Nguyen, TN, Ly, QT, Lewis, SJG & Nguyen, HT 2018, 'Prediction of Freezing of Gait in Patients with Parkinson's Disease Using EEG Signals.', Stud Health Technol Inform, vol. 246, pp. 124-131.
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Freezing of gait (FOG) is an episodic gait disturbance affecting initiation and continuation of locomotion in many Parkinson's disease (PD) patients, causing falls and a poor quality of life. FOG can be experienced on turning and start hesitation, passing through doorways or crowded areas dual tasking, and in stressful situations. Electroencephalography (EEG) offers an innovative technique that may be able to effectively foresee an impending FOG. From data of 16 PD patients, using directed transfer function (DTF) and independent component analysis (ICA) as data pre-processing, and an optimal Bayesian neural network as a predictor of a transition of 5 seconds before the impending FOG occurs in 11 in-group PD patients, we achieved sensitivity and specificity of 85.86% and 80.25% respectively in the test set (5 out-group PD patients). This study therefore contributes to the development of a non-invasive device to prevent freezing of gait in PD.
Hanh, LTM, Binh, NT & Tung, KT 2018, 'Parallel Mutant Execution Techniques in Mutation Testing Process for Simulink Models', Journal of Telecommunications and Information Technology, vol. 4, no. 2017, pp. 90-100.
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Mutation testing – a fault-based technique for software testing – is a computationally expensive approach. One of the powerful methods to improve the performance of mutation without reducing effectiveness is to employ parallel processing, where mutants and tests are executed in parallel. This approach reduces the total time needed to accomplish the mutation analysis. This paper proposes three strategies for parallel execution of mutants on multicore machines using the Parallel Computing Toolbox (PCT) with the Matlab Distributed Computing Server. It aims to demonstrate that the computationally intensive software testing schemes, such as mutation, can be facilitated by using parallel processing. The experiments were carried out on eight different Simulink models. The results represented the efficiency of the proposed approaches in terms of execution time during the testing process.
Hannan, MA, Faisal, M, Ker, PJ, Mun, LH, Parvin, K, Mahlia, TMI & Blaabjerg, F 2018, 'A Review of Internet of Energy Based Building Energy Management Systems: Issues and Recommendations', IEEE Access, vol. 6, pp. 38997-39014.
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© 2013 IEEE. A building energy management system (BEMS) is a sophisticated method used for monitoring and controlling a building's energy requirements. A number of potential studies were conducted in nearly or net zero energy buildings (nZEBs) for the optimization of building energy consumption through efficient and sustainable ways. Moreover, policy makers are approving measures to improve building energy efficiency in order to foster sustainable energy usages. However, the intelligence of existing BEMSs or nZEBs is inadequate, because of the static set points for heating, cooling, and lighting, the complexity of large amounts of BEMS data, data loss, and network problems. To solve these issues, a BEMS or nZEB solution based on the Internet of energy (IoE) provides disruptive opportunities for revolutionizing sustainable building energy management. This paper presents a critical review of the potential of an IoE-based BEMS for enhancing the performance of future generation building energy utilization. The detailed studies of the IoE architecture, typical nZEB configuration, different generations of nZEB, and smart building energy systems for future BEMS are investigated. The operations, advantages, and limitations of the existing BEMSs or nZEBs are illustrated. A comprehensive review of the different types of IoE-based BEMS technologies, such as energy routers, storage systems and materials, renewable sources, and plug-and-play interfaces, is then presented. The rigorous review indicates that existing BEMSs require advanced controllers integrated with IoE-based technologies for sustainable building energy usage. The main objective of this review is to highlight several issues and challenges of the conventional controllers and IoE applications of BEMSs or nZEBs. Accordingly, the review provides several suggestions for the research and development of the advanced optimized controller and IoE of future BEMSs. All the highlighted insights and recommendatio...
Hao, S, Shi, C, Niu, Z & Cao, L 2018, 'Concept coupling learning for improving concept lattice-based document retrieval', Engineering Applications of Artificial Intelligence, vol. 69, pp. 65-75.
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© 2017 Elsevier Ltd The semantic information in any document collection is critical for query understanding in information retrieval. Existing concept lattice-based retrieval systems mainly rely on the partial order relation of formal concepts to index documents. However, the methods used by these systems often ignore the explicit semantic information between the formal concepts extracted from the collection. In this paper, a concept coupling relationship analysis model is proposed to learn and aggregate the intra- and inter-concept coupling relationships. The intra-concept coupling relationship employs the common terms of formal concepts to describe the explicit semantics of formal concepts. The inter-concept coupling relationship adopts the partial order relation of formal concepts to capture the implicit dependency of formal concepts. Based on the concept coupling relationship analysis model, we propose a concept lattice-based retrieval framework. This framework represents user queries and documents in a concept space based on fuzzy formal concept analysis, utilizes a concept lattice as a semantic index to organize documents, and ranks documents with respect to the learned concept coupling relationships. Experiments are performed on the text collections acquired from the SMART information retrieval system. Compared with classic concept lattice-based retrieval methods, our proposed method achieves at least 9%, 8% and 15% improvement in terms of average MAP, IAP@11 and P@10 respectively on all the collections.
Hasan, ASMM, Hoq, MT & Thollander, P 2018, 'Energy management practices in Bangladesh's iron and steel industries', Energy Strategy Reviews, vol. 22, pp. 230-236.
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The aim of this paper was to study energy management and improved energy efficiency among large iron and steel mills in Bangladesh. The results show that there are some barriers to energy management practices among large steel mills, the most important barriers being the perceived absence of cost-effective technical measures, high perceived risks due to uncertain future energy costs and poor information quality. However, this study has shown that the reduction in energy costs due to improved energy efficiency constitutes the most important driver for energy efficiency in the studied steel mills. The results also show that most of the steel mills have not had any technical energy efficiency improvement measures implemented in the production process. Moreover, the steel mills seem unfamiliar with the concept of including energy service companies, and the lack of information or awareness seems to be the main reason behind this. The paper also finds that energy efficiency is perceived to be able to be improved by 6%–8% through energy management practices.
Hassan, M, Liu, D & Paul, G 2018, 'Collaboration of Multiple Autonomous Industrial Robots through Optimal Base Placements', Journal of Intelligent & Robotic Systems, vol. 90, no. 1-2, pp. 113-132.
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© 2017, Springer Science+Business Media B.V. Multiple autonomous industrial robots can be of great use in manufacturing applications, particularly if the environment is unstructured and custom manufacturing is required. Autonomous robots that are equipped with manipulators can collaborate to carry out manufacturing tasks such as surface preparation by means of grit-blasting, surface coating or spray painting, all of which require complete surface coverage. However, as part of the collaboration process, appropriate base placements relative to the environment and the target object need to be determined by the robots. The problem of finding appropriate base placements is further complicated when the object under consideration is large and has a complex geometric shape, and thus the robots need to operate from a number of base placements in order to obtain complete coverage of the entire object. To address this problem, an approach for Optimization of Multiple Base Placements (OMBP) for each robot is proposed in this paper. The approach aims to optimize base placements for multi-robot collaboration by taking into account task-specific objectives such as makespan, fair workload division amongst the robots, and coverage percentage; and manipulator-related objectives such as torque and manipulability measure. In addition, the constraint of robots maintaining an appropriate distance between each other and relative to the environment is taken into account. Simulated and real-world experiments are carried out to demonstrate the effectiveness of the approach and to verify that the simulated results are accurate and reliable.
Hassanzadeh-Barforoushi, A, Law, AMK, Hejri, A, Asadnia, M, Ormandy, CJ, Gallego-Ortega, D & Ebrahimi Warkiani, M 2018, 'Static droplet array for culturing single live adherent cells in an isolated chemical microenvironment', Lab on a Chip, vol. 18, no. 15, pp. 2156-2166.
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Rapid and reliable capture and analysis of single cells in a chemically isolated static droplet array for fast-tracking single cell discoveries.
Hawari, AH, Al-Qahoumi, A, Ltaief, A, Zaidi, S & Altaee, A 2018, 'Dilution of seawater using dewatered construction water in a hybrid forward osmosis system', Journal of Cleaner Production, vol. 195, pp. 365-373.
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© 2018 Elsevier Ltd In this study, dewatered construction water was used for the first time as the feed solution in a combined pretreatment-forward osmosis process to dilute seawater (i.e. draw solution) for further desalination. It was found that at a feed solution and a draw solution flow rate of 2.2 L min−1 gave the optimum membrane flux with minimal fouling effects. The addition of a spacer in the membrane feed side was effective at low flow rates (0.8 and 1.5 L min−1). The feed solution was then pretreated using two methods: settling and multimedia filtration and used in the forward osmosis unit at a low flow rate of 0.8 L min−1 using a spacer at the feed side. Results revealed a significant increase in the forward osmosis membrane flux by 64.3% when multimedia filtration was carried out with a flux reduction of 7.7%. While the settling method achieved only 13.5% increase in the permeate flux and 12.5% flux reduction. The multimedia filtration process removed most of the particles that would cause fouling which resulted in an elevated and more consistent membrane flux. Results also showed that the water flux was 1.3 times higher when the membrane's active layer was facing the draw solution than when it was facing the feed solution. Cost analysis showed that forward osmosis treatment of dewatered construction water was 7.88 $.day−1 and it was slightly cheaper when the forward osmosis operates in the pressure retarded osmosis mode.
Haydar, H, Far, H & Saleh, A 2018, 'Portal steel trusses vs. portal steel frames for long‐span industrial buildings', Steel Construction, vol. 11, no. 3, pp. 205-217.
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AbstractPortal frames and portal truss structures are two of the most cost‐effective and sustainable structural forms for the design and construction of long‐span industrial buildings. Although the use of both structure types as steel‐clad structures is widely accepted, due to frame complexity and variation of frame types for use in single‐storey buildings with spans > 30 m, literature providing a comprehensive investigation of the concepts of portal trusses and portal frames is scarce. This study compares the behaviour of a portal truss configuration with pitched portal frames for use in industrial buildings with spans > 30 m, focusing on weight, costs and construction time. Furthermore, this study entails a numerical investigation that utilizes the SAP2000 computer program to model and structurally optimize the member properties for both portal frame and portal truss configurations. Based on the results obtained from the investigation, it has become apparent that, due to the smaller sections used, the portal truss configurations are lighter and cheaper to fabricate and construct in comparison to the pitched portal frames, which, however, require a shorter construction time.
He, F, Jiang, F, Jiang, Y & Ling, SH 2018, 'New microscopic image sequence‐driven cell deformation model', The Journal of Engineering, vol. 2018, no. 16, pp. 1587-1589.
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He, Q, Wang, J & Lu, H 2018, 'A hybrid system for short-term wind speed forecasting', Applied Energy, vol. 226, pp. 756-771.
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© 2018 Elsevier Ltd Wind speed forecasting is important for high-efficiency utilization of wind energy. Correspondingly, numerous researchers have always focused on the development of reliable forecasting models of wind speed, which is often noisy, unstable and irregular. Current approaches could adapt to various wind speed data. However, many of these usually ignore the importance of the selection of the modeling sample, which often results in poor forecasting performance. In this study, a hybrid forecasting system is proposed that contains three modules: data preprocessing, data clustering, and forecasting modules. In this system, the decomposing technique is applied to reduce the influence of noise within the raw data series to obtain a more stable sequence that is conducive to extract traits from the original data. To extract the characteristic of similarity within wind speed data, a kernel-based fuzzy c-means clustering algorithm is used in data clustering module. In the forecasting module, a sample with a highly similar fluctuation pattern is selected as training dataset, and which could reduce the training requirement of model to improve the forecasting accuracy. The experimental results indicate that the developed system outperforms the discussed traditional forecasting models with respect to forecasting accuracy.
He, T, Cai, L, Meng, T, Chen, L, Deng, Z & Cao, Z 2018, 'Parallel Community Detection Based on Distance Dynamics for Large-Scale Network', IEEE Access, vol. 6, pp. 42775-42789.
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© 2013 IEEE. Data mining task is a challenge on finding a high-quality community structure from large-scale networks. The distance dynamics model was proved to be active on regular-size network community, but it is difficult to discover the community structure effectively from the large-scale network (0.1-1 billion edges), due to the limit of machine hardware and high time complexity. In this paper, we proposed a parallel community detection algorithm based on the distance dynamics model called P-Attractor, which is capable of handling the detection problem of large networks community. Our algorithm first developed a graph partitioning method to divide large network into lots of sub-networks, yet maintaining the complete neighbor structure of the original network. Then, the traditional distance dynamics model was improved by the dynamic interaction process to simulate the distance evolution of each sub-network. Finally, we discovered the real community structure by removing all external edges after evolution process. In our extensive experiments on multiple synthetic networks and real-world networks, the results showed the effectiveness and efficiency of P-Attractor, and the execution time on 4 threads and 32 threads are around 10 and 2 h, respectively. Our proposed algorithm is potential to discover community from a billion-scale network, such as Uk-2007.
He, T, Lu, DD-C, Li, L, Zhang, J, Zheng, L & Zhu, J 2018, 'Model-Predictive Sliding-Mode Control for Three-Phase AC/DC Converters', IEEE Transactions on Power Electronics, vol. 33, no. 10, pp. 8982-8993.
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© 1986-2012 IEEE. This paper presents a model-predictive sliding-mode control (MPSMC) scheme for a three-phase ac/dc converter to achieve better stability and dynamic performances. In the conventional model-predictive control method, a proportional-integral (PI) controller is used to generate the active power reference. This traditional model-predictive PI control (MPPIC) scheme, however, produces a large overshoot/undershoot, a long settling time, and a large steady-state error under disturbances. To overcome these deficiencies, a sliding-mode controller is employed to replace the PI controller. Since the control law and the controller are designed based on the system model, the proposed MPSMC scheme can reduce the effects of unexpected disturbances, such as the output voltage demand and the resistance load variations. Both methods have been simulated in MATLAB/Simulink during various disturbances. Compared with the performances of MPPIC, the results obtained from MPSMC show that the settling time of the dc voltage can be minimized by about 91%, and the overshoot can be eliminated from 9.13% during the steady-state progress. The active and reactive power from MPSMC can also be controlled to the desired values, respectively, with a much smaller overshoot/undershoot and a faster response speed. Similar dynamic improvements can be achieved with MPSMC when the dc voltage demand varies. The simulation results are validated by experimental results.
He, X, Liang, D & Bolton, MD 2018, 'Run-out of cut-slope landslides: mesh-free simulations', Géotechnique, vol. 68, no. 1, pp. 50-63.
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This study uses an incompressible smoothed-particle hydrodynamics (ISPH) model to investigate the run-out and deposit morphology of granular materials flowing down cut slopes. The primary aim is to study the influence of various factors on the run-out and to summarise a quantitative relationship for direct use in landslide hazard management. In the model, the granular materials are modelled as a rigid perfectly plastic material with a Coulomb yield surface. The coupled continuity equation and momentum equation are solved by a semi-implicit algorithm. The model is first validated and its results are carefully compared with various controlled experiments regarding granular flows. The model reproduces the flows and correctly predicts the deposition profiles under various conditions. Then, the computational results are used to study the run-out and mobility of landslides. For granular columns collapsing onto a flat surface, a normalised run-out and a new scaling relationship are proposed, which are supported by numerous measured and numerical results. A similar relationship for the run-out of granular rectangles on steep slopes has also been explored. It is found that the normalised run-out is mainly determined by the slope angle and the normalised drop height. Furthermore, three types of idealised cut-slope landslides are simulated to study the influence of the initial landslide shape on the run-out. It is found that the normalised run-out of these idealised cut-slope landslides is smaller than that of granular rectangles on slopes of the same angles and drop heights. The difference between the run-outs is found to be mainly determined by the proportion of the whole mass that initially lies above a predictable discontinuity plane.
He, X, Liang, D, Wu, W, Cai, G, Zhao, C & Wang, S 2018, 'Study of the interaction between dry granular flows and rigid barriers with an SPH model', International Journal for Numerical and Analytical Methods in Geomechanics, vol. 42, no. 11, pp. 1217-1234.
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SummaryThis study uses an incompressible smoothed‐particle hydrodynamics model to investigate the interaction between dry granular material flows and rigid barriers. The primary aim is to summarise some practical guidelines for the design of debris‐resisting barriers. The granular materials are modelled as a rigid‐perfectly plastic material where the plastic flow corresponds to the critical state. The coupled continuity equation and momentum equation are solved by a semi‐implicit algorithm. Compared with flows in controlled flume experiments, the model adequately reproduces both the kinetic of the flows and the impact force under various conditions. Then the numerical simulations are used to study the detailed interaction process. It is illustrated quantitatively that the interaction force consists of two parts, ie, the earth pressure force caused by the weight of the soil and a dynamic force caused by the internal deformation (flowing mass on top of a dead zone). For the estimation of impact load, this study suggests that an increased earth pressure coefficient depending on the Froude number should be incorporated into the hydrostatic model.
He, X, Wang, K, Huang, H & Liu, B 2018, 'QoE-Driven Big Data Architecture for Smart City', IEEE Communications Magazine, vol. 56, no. 2, pp. 88-93.
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In the era of big data, the applications/services of the smart city are expected to offer end users better QoE than in a conventional smart city. Nevertheless, various types of sensors will produce an increasing volume of big data along with the implementation of a smart city, where we face redundant and diverse data. Therefore, providing satisfactory QoE will become the major challenge in the big-data-based smart city. In this article, to enhance the QoE, we propose a novel big data architecture consisting of three planes: The data storage plane, the data processing plane, and the data application plane. The data storage plane stores a wide variety of data collected by sensors and originating from different data sources. Then the data processing plane filters, analyzes, and processes the ocean of data to make decisions autonomously for extracting high-quality information. Finally, the application plane initiates the execution of the events corresponding to the decisions delivered from the data processing plane. Under this architecture, we particularly use machine learning techniques, trying to acquire accurate data and deliver precise information to end users. Simulation results indicate that our proposals could achieve high QoE performance for the smart city.
He, Y, Dong, X, Kang, G, Fu, Y, Yan, C & Yang, Y 2018, 'Asymptotic Soft Filter Pruning for Deep Convolutional Neural Networks', IEEE Transactions on Cybernetics, vol. 50, no. 8, pp. 3594-3604.
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Deeper and wider Convolutional Neural Networks (CNNs) achieve superiorperformance but bring expensive computation cost. Accelerating suchover-parameterized neural network has received increased attention. A typicalpruning algorithm is a three-stage pipeline, i.e., training, pruning, andretraining. Prevailing approaches fix the pruned filters to zero duringretraining, and thus significantly reduce the optimization space. Besides, theydirectly prune a large number of filters at first, which would causeunrecoverable information loss. To solve these problems, we propose anAsymptotic Soft Filter Pruning (ASFP) method to accelerate the inferenceprocedure of the deep neural networks. First, we update the pruned filtersduring the retraining stage. As a result, the optimization space of the prunedmodel would not be reduced but be the same as that of the original model. Inthis way, the model has enough capacity to learn from the training data.Second, we prune the network asymptotically. We prune few filters at first andasymptotically prune more filters during the training procedure. Withasymptotic pruning, the information of the training set would be graduallyconcentrated in the remaining filters, so the subsequent training and pruningprocess would be stable. Experiments show the effectiveness of our ASFP onimage classification benchmarks. Notably, on ILSVRC-2012, our ASFP reduces morethan 40% FLOPs on ResNet-50 with only 0.14% top-5 accuracy degradation, whichis higher than the soft filter pruning (SFP) by 8%.
He, Y, Jayawickrama, BA, Dutkiewicz, E, Srikanteswara, S & Mueck, M 2018, 'Priority Access and General Authorized Access Interference Mitigation in the Spectrum Access System', IEEE Transactions on Vehicular Technology, vol. 67, no. 6, pp. 4969-4983.
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© 1967-2012 IEEE. To meet the capacity needs of next generation wireless communications, the U.S. Federal Communications Commission has recently introduced the spectrum access system. Spectrum is shared between three tiers - incumbents, priority access licensees (PAL), and general authorized access (GAA) licensees. When the incumbents are absent, PAL and GAA share the spectrum under the constraint that GAA ensure the interference to PAL is no more than $-$40 dBm with at least 99% confidence. We consider the scenario where locations are not shared between PAL and GAA. We propose a PAL-GAA cochannel interference mitigation technique that does not expose base station locations. Our approach relies on GAA sharing the distribution and maximum number of transmitters in a finite area. We show how PAL can derive the distribution of the aggregate interference using the probability density function and characteristic function, and notify GAA about the exclusion zones in space that will guarantee that the interference requirement is met. We also propose a numerical approximation using inverse fast Fourier and discrete Fourier transforms. Analytically calculated distribution aligns well with the numerical results. Additionally, we formulate an optimization problem for the optimal exclusion zone size. We analytically prove convexity of the problem. Our approach reduces the exclusion zone size by over 42%, which gives significantly more spectral opportunities to GAA in the spatial domain.
He, Y, Wan, Z, Liu, X, Zheng, X, Zeng, G & Zhang, J 2018, 'A CASCADED MULTILEVEL CONVERTER BASED ON SOC CLOSED LOOP TRACKING', Progress In Electromagnetics Research C, vol. 88, pp. 103-115.
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© 2018, Electromagnetics Academy. All rights reserved. This paper proposes a cascaded multilevel converter to reduce the number of IGBT switches for the purpose of improving system stability and decreasing switching losses. This converter can eliminate second-order ripple caused by energy exchange between grid and batteries, and thus extend battery life. This cascaded connection between the equivalent buck/boost circuit and the half-bridge inverter is also able to reduce the number of switch tubes. A control strategy based on state of charge (SOC) closed-loop tracking is designed to implement t0068e errorless follow-up control of average SOC values for electric vehicle batteries. The equivalent circuit under different working modes of the topology is analyzed, and the effectiveness of the control strategy is verified. Simulated and experimental results show that this converter can effectively achieve grid connection requirements and balance the battery units to meet practical needs.
He, Y, Wang, M, Chen, X, Pohmann, R, Polimeni, JR, Scheffler, K, Rosen, BR, Kleinfeld, D & Yu, X 2018, 'Ultra-Slow Single-Vessel BOLD and CBV-Based fMRI Spatiotemporal Dynamics and Their Correlation with Neuronal Intracellular Calcium Signals', Neuron, vol. 97, no. 4, pp. 925-939.e5.
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He, Z, Zhang, S, Teng, J, Yao, Y & Sheng, D 2018, 'A coupled model for liquid water-vapor-heat migration in freezing soils', Cold Regions Science and Technology, vol. 148, pp. 22-28.
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Herr, D, Paler, A, Devitt, SJ & Nori, F 2018, 'A local and scalable lattice renormalization method for ballistic quantum computation', npj Quantum Information, vol. 4, no. 1, pp. 1-8.
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AbstractA recent proposal has shown that it is possible to perform linear-optics quantum computation using a ballistic generation of the lattice. Yet, due to the probabilistic generation of its cluster state, it is not possible to use the fault-tolerant Raussendorf lattice, which requires a lower failure rate during the entanglement-generation process. Previous work in this area showed proof-of-principle linear-optics quantum computation, while this paper presents an approach to it which is more practical, satisfying several key constraints. We develop a classical measurement scheme that purifies a large faulty lattice to a smaller lattice with entanglement faults below threshold. A single application of this method can reduce the entanglement error rate to 7% for an input failure rate of 25%. Thus, we can show that it is possible to achieve fault tolerance for ballistic methods.
Herr, D, Paler, A, Devitt, SJ & Nori, F 2018, 'Lattice surgery on the Raussendorf lattice', Quantum Science and Technology, vol. 3, no. 3, pp. 035011-035011.
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© 2018 IOP Publishing Ltd. Lattice surgery is a method to perform quantum computation fault-tolerantly by using operations on boundary qubits between different patches of the planar code. This technique allows for universal planar code computation without eliminating the intrinsic two-dimensional nearest-neighbor properties of the surface code that eases physical hardware implementations. Lattice surgery approaches to algorithmic compilation and optimization have been demonstrated to be more resource efficient for resource-intensive components of a fault-tolerant algorithm, and consequently may be preferable over braid-based logic. Lattice surgery can be extended to the Raussendorf lattice, providing a measurement-based approach to the surface code. In this paper we describe how lattice surgery can be performed on the Raussendorf lattice and therefore give a viable alternative to computation using braiding in measurement-based implementations of topological codes.
Hill, M & Tran, N 2018, 'MicroRNAs Regulating MicroRNAs in Cancer', Trends in Cancer, vol. 4, no. 7, pp. 465-468.
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© 2018 MicroRNAs (miRNA) are capable of self-regulation, termed miRNA to miRNA interaction. Very little is known about these interactions and their impact on the cellular milieu. We discuss known miRNA to miRNA interactions, potential mechanisms, and their role in cancer.
Ho, L & Fatahi, B 2018, 'Analytical solution to axisymmetric consolidation of unsaturated soil stratum under equal strain condition incorporating smear effects', International Journal for Numerical and Analytical Methods in Geomechanics, vol. 42, no. 15, pp. 1890-1913.
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SummaryThis paper proposes closed‐form analytical solutions to the axisymmetric consolidation of an unsaturated soil stratum using the equal strain hypothesis. Following the 1‐dimensional (1D) consolidation theory for unsaturated soil mechanics, polar governing equations describing the air and water flows are first presented on the basis of Fick's law and Darcy's law, respectively. The current study takes into account the peripheral smear caused by an installation of vertical drain. Separation of variables and Laplace transformation are mainly adopted in the analytical derivation to obtain final solutions. Then, the hydraulic conductivity ratio, the radius of influence zone and smear parameters influencing time‐dependent excess pore pressures, and the average degree of consolidation are graphically interpreted. In this study, a comparison made between the proposed equal strain results and the existing free strain results suggests that both hypotheses would deliver similar predictions. Moreover, it is found that the smear zone resulting from vertical drain installations would hinder the consolidation rate considerably.
Ho, L, Fatahi, B & Khabbaz, H 2018, 'Analytical Solution to One-Dimensional Consolidation in Unsaturated Soil Deposit Incorporating Time-Dependent Diurnal Temperature Variation', International Journal of Geomechanics, vol. 18, no. 5, pp. 04018029-04018029.
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© 2018 American Society of Civil Engineers. Several experimental studies have demonstrated that temperature changes may significantly influence the deformation of unsaturated soils. Thus, there is an essential need to develop a predictive framework for unsaturated consolidation capturing the nonisothermal effect. This paper presents an analytical solution to the one-dimensional (1D) consolidation of unsaturated soil deposit in response to temperature variation. A set of governing equations of flow incorporating the nonisothermal condition were first obtained. Then, Fourier sine series and the Laplace transformation were used to derive solutions based on these governing equations. This study highlighted the effect of diurnal temperature variation on pore pressures and soil deformation at different depths while considering two conditions of interest: (1) no external applied load, and (2) application of step loading to the ground surface. In addition, the thermal diffusivity characterizing the consolidation behavior of unsaturated soils was also investigated and is discussed in this paper. It is predicted that a decrease in thermal diffusivity would attenuate the effects of diurnal temperature on the unsaturated consolidation.
Ho, N, Peng, H, Mayoh, C, Liu, PY, Atmadibrata, B, Marshall, GM, Li, J & Liu, T 2018, 'Delineation of the frequency and boundary of chromosomal copy number variations in paediatric neuroblastoma', Cell Cycle, vol. 17, no. 6, pp. 749-758.
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Hoang, DT, Niyato, D, Nguyen, DN, Dutkiewicz, E, Wang, P & Han, Z 2018, 'A Dynamic Edge Caching Framework for Mobile 5G Networks', IEEE Wireless Communications, vol. 25, no. 5, pp. 95-103.
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© 2002-2012 IEEE. Mobile edge caching has emerged as a new paradigm to provide computing, networking resources, and storage for a variety of mobile applications. That helps achieve low latency, high reliability, and improve efficiency in handling a very large number of smart devices and emerging services (e.g., IoT, industry automation, virtual reality) in mobile 5G networks. Nonetheless, the development of mobile edge caching is challenged by the decentralized nature of edge nodes, their small coverage, limited computing, and storage resources. In this article, we first give an overview of mobile edge caching in 5G networks. After that, its key challenges and current approaches are discussed. We then propose a novel caching framework. Our framework allows an edge node to authorize the legitimate users and dynamically predicts and updates their content demands using the matrix factorization technique. Based on the prediction, the edge node can adopt advanced optimization methods to determine optimal content to store so as to maximize its revenue and minimize the average delay of its mobile users. Through numerical results, we demonstrate that our proposed framework provides not only an effective caching approach, but also an efficient economic solution for the mobile service provider.
Hoang, TM, Ngo, HQ, Duong, TQ, Tuan, HD & Marshall, A 2018, 'Cell-Free Massive MIMO Networks: Optimal Power Control Against Active Eavesdropping', IEEE Transactions on Communications, vol. 66, no. 10, pp. 4724-4737.
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© 1972-2012 IEEE. This paper studies the security aspect of a recently introduced 'cell-free massive MIMO' network under a pilot spoofing attack. First, a simple method to recognize the presence of this type of an active eavesdropping attack to a particular user is shown. In order to deal with this attack, we consider the problem of maximizing the achievable data rate of the attacked user or its achievable secrecy rate. The corresponding problems of minimizing the power consumption subject to security constraints are also considered in parallel. Path-following algorithms are developed to solve the posed optimization problems under different power allocation to access points (APs). Under equip-power allocation to APs, these optimization problems admit closed-form solutions. Numerical results show their efficiency.
Ho-Le, TP, Pham, HM, Center, JR, Eisman, JA, Nguyen, HT & Nguyen, TV 2018, 'Prediction of changes in bone mineral density in the elderly: contribution of “osteogenomic profile”', Archives of Osteoporosis, vol. 13, no. 1.
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© 2018, International Osteoporosis Foundation and National Osteoporosis Foundation. Summary: The contribution of genetic variants to longitudinal bone loss has not been well documented. We constructed an “osteogenomic profile” based on 62 BMD-associated genetic variants and showed that the profile was significantly associated with bone loss, independently from baseline BMD and age. The osteogenomic profile can help predict bone loss in an individual. Introduction: The rate of longitudinal bone loss (ΔBMD) is a risk factor for fracture. The variation in ΔBMD is partly determined by genetic factors. This study sought to define the association between an osteogenomic profile and ΔBMD. Methods: The osteogenomic profile was created from 62 BMD-associated SNPs from genome-wide association studies (GWAS) that were genotyped in 1384 elderly men and women aged 60+ years. Weighted genetic risk scores (GRS) were constructed for each individual by summing the products of the number of risk alleles and the sex-specific regression coefficients [associated with BMD from GWAS]. ΔBMD, expressed as annual percent change-in-BMD, was determined by linear regression analysis for each individual who had had at least two femoral neck BMD measurements. Results: The mean ΔBMD was − 0.65% (SD 1.64%) for women and − 0.57% (SD 1.40%) for men, and this difference was not statistically significant (P = 0.32). In women, each unit increase in GRS was associated with 0.21% (SE 0.10) higher ΔBMD at the femoral neck (P = 0.036), and this association was independent of baseline BMD and age. In logistic regression analysis, each unit increase of GRS was associated with 41% odds (95%CI: 1.07–1.87) of rapid bone loss (ΔBMD ≤ − 1.2%/year; mean of rapid loss group = − 2.2%/year). There was no statistically significant association between ΔBMD and GRS in men. Conclusions: We conclude that the osteogenomic profile constructed from BMD-associated genetic variants is modestly associated with long-...
Hong, H, Liu, J, Bui, DT, Pradhan, B, Acharya, TD, Pham, BT, Zhu, A-X, Chen, W & Ahmad, BB 2018, 'Landslide susceptibility mapping using J48 Decision Tree with AdaBoost, Bagging and Rotation Forest ensembles in the Guangchang area (China)', CATENA, vol. 163, pp. 399-413.
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© 2018 Elsevier B.V. Landslides are a manifestation of slope instability causing different kinds of damage affecting life and property. Therefore, high-performance-based landslide prediction models are useful to government institutions for developing strategies for landslide hazard prevention and mitigation. Development of data mining based algorithms shows that high-performance models can be obtained using ensemble frameworks. The primary objective of this study is to investigate and compare the use of current state-of-the-art ensemble techniques, such as AdaBoost, Bagging, and Rotation Forest, for landslide susceptibility assessment with the base classifier of J48 Decision Tree (JDT). The Guangchang district (Jiangxi province, China) was selected as the case study. Firstly, a landslide inventory map with 237 landslide locations was constructed; the landslide locations were then randomly divided into a ratio of 70/30 for the training and validating models. Secondly, fifteen landslide conditioning factors were prepared, such as slope, aspect, altitude, topographic wetness index (TWI), stream power index (SPI), sediment transport index (STI), plan curvature, profile curvature, lithology, distance to faults, distance to rivers, distance to roads, land use, normalized difference vegetation index (NDVI), and rainfall. Relief-F with the 10-fold cross-validation method was applied to quantify the predictive ability of the conditioning factors and for feature selection. Using the JDT and its three ensemble techniques, a total of four landslide susceptibility models were constructed. Finally, the overall performance of the resulting models was assessed and compared using area under the receiver operating characteristic (ROC) curve (AUC) and statistical indexes. The result showed that all landslide models have high performance (AUC > 0.8). However, the JDT with the Rotation Forest model presents the highest prediction capability (AUC = 0.855), followed by the JD...
Hong, H, Pradhan, B, Sameen, MI, Kalantar, B, Zhu, A & Chen, W 2018, 'Improving the accuracy of landslide susceptibility model using a novel region-partitioning approach', Landslides, vol. 15, no. 4, pp. 753-772.
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© 2017, Springer-Verlag GmbH Germany. Landslide is a natural disaster that threatens human lives and properties worldwide. Numerous have been conducted on landslide susceptibility mapping (LSM), in which each has attempted to improve the accuracy of final outputs. This study presents a novel region-partitioning approach for LSM to understand the effects of partitioning a focused region into smaller areas on the prediction accuracy of common regression models. Results showed that the partitioning of the study area into two regions using the proposed method improved the prediction rate from 0.77 to 0.85 when support vector machine was used, and from 0.87 to 0.88 when logistic regression model was utilized. The spatial agreements of the models were also improved after partitioning the area into two regions based on Shannon entropy equations. Our comparative study indicated that the proposed method outperformed the geographically weighted regression model that considered the spatial variations in landslide samples. Overall, the main advantages of the proposed method are improved accuracy and the reduction of the effects of spatial variations exhibited in landslide-conditioning factors.
Ho-Pham, LT, Chau, PMN, Do, AT, Nguyen, HC & Nguyen, TV 2018, 'Type 2 diabetes is associated with higher trabecular bone density but lower cortical bone density: the Vietnam Osteoporosis Study', Osteoporosis International, vol. 29, no. 9, pp. 2059-2067.
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© 2018, International Osteoporosis Foundation and National Osteoporosis Foundation. Summary: It is not clear why type 2 diabetes (T2D) has an increased risk of fracture despite higher areal bone mineral density. This study showed that compared with controls, T2D patients had higher trabecular bone density but lower cortical bone density, resulting in a lower bone strength. Introduction: To define the association between type 2 diabetes and bone architecture and measures of bone strength. Methods: The study was part of the Vietnam Osteoporosis Study, in which 1115 women and 614 men aged ≥ 30 were randomly recruited from Ho Chi Minh City. HbA1c levels were measured with analyzers ADAMS™ A1c HA-8160 (Arkray, Kyoto, Japan). The diagnosis of T2D was made if HbA1c was ≥ 6.5%. Trabecular and cortical volumetric bone density (vBMD) was measured in the forearm and leg by a pQCT XCT2000 (Stratec, Germany). Polar stress strain index (pSSI) was derived from the pQCT measurements. Difference in bone parameters between T2D and non-diabetic individuals was assessed by the number of standard deviations (effect size [ES]) by the propensity score analysis. Results: The prevalence of T2D was ~ 8%. The results of propensity score matching for age, sex, and body mass index in 137 pairs of diabetic and non-diabetic individuals showed that T2D patients had significantly higher distal radius trabecular vBMD (ES 0.26; 95% CI, 0.02 to 0.50), but lower cortical vBMD (ES − 0.22; − 0.46 to 0.00) and reduced pSSI (ES − 0.23; − 0.47 to − 0.02) compared with non-diabetic individuals. Multiple linear regression analysis based on the entire sample confirmed the results of the propensity score analysis. Conclusion: Compared with non-diabetic individuals, patients with T2D have greater trabecular but lower cortical vBMD which leads to lower bone strength.
Ho-Pham, LT, Ho-Le, TP, Mai, LD, Do, TM, Doan, MC & Nguyen, TV 2018, 'Sex-difference in bone architecture and bone fragility in Vietnamese', Scientific Reports, vol. 8, no. 1.
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AbstractThis study sought to define the sex-difference in trabecular and cortical bone parameters in Vietnamese individuals. The study involved 1404 women and 864 men aged between 20 and 86 years who were recruited from Ho Chi Minh City, Vietnam. Trabecular and cortical volumetric BMD were measured at the proximal tibia and proximal radius at 4%, 38%, and 66% points, using a peripheral quantitative computed tomography XCT2000 (Stratec, Germany). Polar strength strain index was estimated from cortical bone parameters. Changes in bone parameters were assessed by the multiple linear regression model. Among individuals aged 20–39 years, women had significantly lower peak trabecular BMD at both the radius (40%) and tibia (16%) than men, but the age-related reduction in trabecular BMD were similar between two sexes. For cortical BMD, peak values in women and men were comparable, but the age-related diminution was greater in women than men. At any age, polar strength strain index in women was lower than men, and the difference was mainly attributable to cortical bone area and total bone mass. We conclude that in the elderly, sex-related difference in trabecular BMD is originated during growth, but sex-related difference in cortical BMD is determined by differential age-related bone loss.
Hoque, MA-A, Phinn, S, Roelfsema, C & Childs, I 2018, 'Assessing tropical cyclone risks using geospatial techniques', Applied Geography, vol. 98, pp. 22-33.
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Hoque, MA-A, Phinn, S, Roelfsema, C & Childs, I 2018, 'Modelling tropical cyclone risks for present and future climate change scenarios using geospatial techniques', International Journal of Digital Earth, vol. 11, no. 3, pp. 246-263.
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Hossain, MA, Pota, HR, Hossain, MJ & Haruni, AMO 2018, 'Active power management in a low-voltage islanded microgrid', International Journal of Electrical Power & Energy Systems, vol. 98, pp. 36-47.
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Hossain, MJ, Rafi, FHM, Town, G & Lu, J 2018, 'Multifunctional Three-Phase Four-Leg PV-SVSI With Dynamic Capacity Distribution Method', IEEE Transactions on Industrial Informatics, vol. 14, no. 6, pp. 2507-2520.
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Hossain, N, Zaini, J, Jalil, R & Mahlia, TMI 2018, 'The Efficacy of the Period of Saccharification on Oil Palm (Elaeis guineensis) Trunk Sap Hydrolysis', International Journal of Technology, vol. 9, no. 4, pp. 652-652.
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© IJTech 2018. This study investigates the enzymatic hydrolysis rate of Oil Palm (Elaeis guineensis) Trunk (OPT) sap in terms of the length of saccharification process with the aim to elevate sugar production. Emphasis was placed on the reaction time and addition of supplements such epsom salt (MgSO4) and alanine amino acid (C3H7NO2) to accelerate the efficiency of Saccharomyces cerevisiae containing the enzyme invertase. A whole oil palm trunk was divided into four different sections, upper, middle-1, middle-2 and bottom with separate experiments over 10 days enzymatic reaction period. The highest saccharification rate was shown as 13.47% on the tenth day. This result indicates that the increase in the saccharification rate was positively correlated with the length of hydrolysis. Moreover, the sample with nutrients achieved the highest sugar output, 17.91% on the fourth day of hydrolysis which was 4.44% higher than the hydrolysis rate of the sample without nutrients. In the presence of complex OPT sugars, together with other essential elements, epsom salt and alanine amino acid, S.cerevisiae achieved a higher hydrolysis metabolism to simple sugars as the cells strived to produce energy and regenerated the invertase. Moreover, the upper part of the OPT rendered the highest potential for sugar production with levels of 21.2% with supplements and 15.6% without. From this experimental analysis, a conventional saccharification method was optimized through the addition of nutrients and a prolonged (10 days) hydrolysis process which yielded an increase in sugar production.
Hosseinzadeh, A, Najafpoor, AA, Jafari, AJ, Jazani, RK, Baziar, M, Bargozin, H & Piranloo, FG 2018, 'Application of response surface methodology and artificial neural network modeling to assess non-thermal plasma efficiency in simultaneous removal of BTEX from waste gases: Effect of operating parameters and prediction performance', Process Safety and Environmental Protection, vol. 119, pp. 261-270.
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Hou, Z, Wang, Y, Sui, Y, Gu, J, Zhao, T & Zhou, X 2018, 'Managing high-performance computing applications as an on-demand service on federated clouds', Computers & Electrical Engineering, vol. 67, pp. 579-595.
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© 2018 Elsevier Ltd There are several challenges (e.g., imbalance between supply and demand of hardware resources and software licenses, and usability) under modern High-Performance Computing (HPC) environment. As a means of providing an on-demand service for end users, we propose a Software-as-a-Service (SaaS) approach for managing commercial HPC applications as a Web-based service deployed on top of federated clouds. Some inter-trusted private or public clouds are federated to create a unified service platform with a large amount of hardware resources. In addition, an on-demand, pay-per-use model for Web-service-enabled HPC applications is proposed. Further, we provide an economic analysis of the proposed approach from the perspective of end users, cloud service providers, and Independent Software Vendors (ISVs). We conduct a simulation using two HPC application services on three federated clouds. A combined Quality of Service (QoS) and economic evaluation demonstrates a better effect of the proposed approach comparing with existing HPC platforms.
Hou, ZJ, Yang, Y, Chiu, L, Zhu, X & Xue, Q 2018, 'Wideband Millimeter-Wave On-Chip Quadrature Coupler With Improved In-Band Flatness in 0.13-<inline-formula> <tex-math notation='LaTeX'>$\mu$ </tex-math> </inline-formula>m SiGe Technology', IEEE Electron Device Letters, vol. 39, no. 5, pp. 652-655.
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© 1980-2012 IEEE. This letter proposes a compact and broadband quadrature coupler with a center frequency of 55 GHz, which consists of a 90° broadside coupled-line to support the differential signal propagation and two T-type L-C networks to support the common signal propagation. To analyze the proposed coupler, an equivalent circuit model is provided for estimation of the distributed and lumped component values. The measured results of the proposed on-chip quadrature coupler show that the return loss and isolation are greater than 20 dB with a bandwidth of 105%, while the insertion loss is about -0.85 dB. The magnitude imbalances are less than 1 dB within the bandwidth of 56% and the phase differences are with ±1° errors within the bandwidth of 96.9%. The chip size, excluding the test pads, is only 0.31 × 0.22 mm2.
Hou, ZJ, Yang, Y, Chiu, L, Zhu, X, Dutkiewicz, E, Vardaxoglou, JC & Xue, Q 2018, 'A W-Band Balanced Power Amplifier Using Broadside Coupled Strip-Line Coupler in SiGe BiCMOS 0.13-<inline-formula> <tex-math notation='LaTeX'>$\mu\text{m}$ </tex-math> </inline-formula> Technology', IEEE Transactions on Circuits and Systems I: Regular Papers, vol. 65, no. 7, pp. 2139-2150.
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© 2004-2012 IEEE. Load-variation insensitivity, for impedance matching between power amplifiers (PAs) and transmitting antennas, contributes to challenging the design of millimeter-wave wireless systems. In this paper, a W -band two-way balanced PA based on a compact quadrature coupler with a broadside coupled strip-line (BCSL) as the core is presented to enhance the load-variation insensitivity and stability. The proposed coupler is truly broadband with low amplitude and phase imbalance. The proposed W -band balanced PA achieves higher power-added efficiency (PAE) and unsaturated output power {P} -{\mathrm{ sat}} over wide frequency bandwidth. The W -band balanced PA is implemented in a 0.13- \mu \text{m} SiGe BiCMOS process and achieves a measured {P} -{\mathrm{ sat}} of 16.3 dBm and a peak PAE of 14.1% at 100 GHz (with 1.6-V power supply). The measured {P} -{\mathrm{ sat}} with 1-dB bandwidth is from 91 to 102 GHz. The measured results present the feasibility of the compact quadrature coupler. The total chip surface area (with pads) is 0.64 mm2, where the size of the proposed quadrature coupler area is only 0.04 mm2.
Hou, ZJ, Yang, Y, Zhu, X, Li, YC, Dutkiewicz, E & Xue, Q 2018, 'A Compact and Low-Loss Bandpass Filter Using Self-Coupled Folded-Line Resonator With Capacitive Feeding Technique', IEEE Electron Device Letters, vol. 39, no. 10, pp. 1-1.
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© 1980-2012 IEEE. This letter proposes a compact and low-loss on-chip bandpass filter (BPF) design in (Bi)-CMOS technology. The proposed BPF consists of a self-coupled folded-line resonator and a pair of metal-insulator-metal capacitors. The proposed resonator has a property of flexible self-resonant frequency to form a transmission zero, which is analyzed in detail by a simplified LC equivalent circuit. Moreover, the parametric studies of the feeding capacitance for the proposed BPF design have been performed to demonstrate the tenability of the resonant frequency. For verification, the proposed BPF is fabricated in a standard 0.13-μ m (Bi)-CMOS technology. The measured results show that the proposed BPF has a notch with 25.4-dB suppression at 65 GHz and an insertion loss of 1.66 dB in the passband. The chip size of the device, excluding the test pads, is only 0.009 mm2 (0.11 × 0.086 mm2).
How, HG, Masjuki, HH, Kalam, MA & Teoh, YH 2018, 'Influence of injection timing and split injection strategies on performance, emissions, and combustion characteristics of diesel engine fueled with biodiesel blended fuels', Fuel, vol. 213, pp. 106-114.
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How, HG, Masjuki, HH, Kalam, MA, Teoh, YH & Chuah, HG 2018, 'Effect of Calophyllum Inophyllum biodiesel-diesel blends on combustion, performance, exhaust particulate matter and gaseous emissions in a multi-cylinder diesel engine', Fuel, vol. 227, pp. 154-164.
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Hu, C, Lu, J, Liu, X & Zhang, G 2018, 'Robust vehicle routing problem with hard time windows under demand and travel time uncertainty', Computers & Operations Research, vol. 94, pp. 139-153.
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© 2018 Elsevier Ltd Due to an increase in customer-oriented service strategies designed to meet more complex and exacting customer requirements, meeting a scheduled time window has become an important part of designing vehicle routes for logistics activities. However, practically, the uncertainty in travel times and customer demand often means vehicles miss these time windows, increasing service costs and decreasing customer satisfaction. In an effort to find a solution that meets the needs of real-world logistics, we examine the vehicle routing problem with hard time windows under demand and travel time uncertainty. To address the problem, we build a robust optimization model based on novel route-dependent uncertainty sets. However, due to the complex nature of the problem, the robust model is only able to tackle small-sized instances using standard solvers. Therefore, to tackle large instances, we design a two-stage algorithm based on a modified adaptive variable neighborhood search heuristic. The first stage of the algorithm minimizes the total number of vehicle routes, while the second stage minimizes the total travel distance. Extensive computational experiments are conducted with modified versions of Solomon's benchmark instances. The numerical results show that the proposed two-stage algorithm is able to find optimal solutions for small-sized instances and good-quality robust solutions for large-sized instances with little increase to the total travel distance and/or the number of vehicles used. A detailed analysis of the results also reveals several managerial insights for decision-makers in the logistics industry.
Hu, H, Liu, X, Zhao, J & Guo, Y 2018, 'Analysis and Minimization of Detent End Force in Linear Permanent Magnet Synchronous Machines', IEEE Transactions on Industrial Electronics, vol. 65, no. 3, pp. 2475-2486.
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© 1982-2012 IEEE. In this paper, the end forces caused by the longitude end effects in linear permanent magnet synchronous machines (LPMSMs) are analyzed and minimized. First, the left/right-end forces are calculated based on an analytical model and the Maxwell stress tensor, in which the optimal integration surfaces are investigated. Then, based on the spectrum analysis of the left/right-end forces, two different methods are adopted to minimize the fundamental and high-order harmonics, respectively. The optimal length of the primary iron is obtained from the phase difference of the fundamental and a two-step iteration instead of the trial-and-error with the finite element method. Furthermore, step-skewed auxiliary irons are added to the primary end to eliminate the high-order harmonics. Third, to reduce the secondary end effect when the primary moves to the secondary end, a compensation method of adding mirror permanent magnet is proposed and good results are obtained. Finally, an LPMSM prototype is manufactured and experiments are conducted. The experimental results verify the theoretical study.
Hu, J, Zhang, Q, Lee, D-J & Ngo, HH 2018, 'Feasible use of microbial fuel cells for pollution treatment', Renewable Energy, vol. 129, pp. 824-829.
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© 2017 Elsevier Ltd. The microbial fuel cells (MFC) can directly transform chemical energy in feed substance to electricity by anodic aspiration pathways. This mini review provides an order-of-magnitude argument that MFC has much lower catalyst density at electrode surface and much higher diffusional resistance for substrates than the chemical fuel cell, the former should not be used as an energy generation unit; rather, it should be applied in low power density level applications such as biofilm wastewater treatment. The literature studies using MFC for pollution treatment are discussed.
Hu, L, Chen, Q, Zhao, H, Jian, S, Cao, L & Cao, J 2018, 'Neural Cross-Session Filtering: Next-Item Prediction Under Intra- and Inter-Session Context', IEEE Intelligent Systems, vol. 33, no. 6, pp. 57-67.
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© 2018 IEEE. Classic recommender systems (RSs) often repeatedly recommend similar items to user historical profiles or recent purchases. For this, session-based RSs (SBRSs) are extensively studied in recent years. Current SBRSs often assume a rigid-order sequence, which does not fit in many real-world cases. In fact, the next-item recommendation depends on not only current session context but also historical sessions which are often neglected by current SBRSs. Accordingly, an SBRS over relaxed-order sequences with both intra- and inter-context is more pragmatic. Inspired by the successful experience in modern language modeling, we design an efficient neural architecture to model both intra- and inter-context for next item prediction.
Hu, Y, Wang, XC, Ngo, HH, Sun, Q & Yang, Y 2018, 'Anaerobic dynamic membrane bioreactor (AnDMBR) for wastewater treatment: A review', Bioresource Technology, vol. 247, pp. 1107-1118.
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© 2017 Elsevier Ltd Recently, an increasing level of attention has focused on the emerging technology of anaerobic dynamic membrane bioreactors (AnDMBRs), owing to its merits such as low membrane module cost, easy control of membrane fouling, low energy consumption and sludge production, as well as biogas production. As research on AnDMBRs is still in the nascent stage, an introduction of bioreactor configurations, dynamic membrane (DM) module, and DM layer formation and cleaning is firstly presented. The process performance of the AnDMBR for wastewater treatment is then reviewed with regard to pollutant removal, DM filterability, biogas production, and potential advantages over the conventional anaerobic membrane bioreactor (AnMBR). In addition, the important parameters affecting process performance are briefly discussed. Lastly, the challenges encountered and perspectives regarding the future development of the AnDMBR process to promote its practical applications are presented.
Hu, Y, Zheng, L, Yang, Y & Huang, Y 2018, 'Twitter100k: A Real-World Dataset for Weakly Supervised Cross-Media Retrieval', IEEE Transactions on Multimedia, vol. 20, no. 4, pp. 927-938.
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© 2017 IEEE. This paper contributes a new large-scale dataset for weakly supervised cross-media retrieval, named Twitter100k. Current datasets, such as Wikipedia, NUS Wide, and Flickr30k, have two major limitations. First, these datasets are lacking in content diversity, i.e., only some predefined classes are covered. Second, texts in these datasets are written in well-organized language, leading to inconsistency with realistic applications. To overcome these drawbacks, the proposed Twitter100k dataset is characterized by two aspects: it has 100 000 image-text pairs randomly crawled from Twitter, and thus, has no constraint in the image categories; and text in Twitter100k is written in informal language by the users. Since strongly supervised methods leverage the class labels that may be missing in practice, this paper focuses on weakly supervised learning for cross-media retrieval, in which only text-image pairs are exploited during training. We extensively benchmark the performance of four subspace learning methods and three variants of the correspondence AutoEncoder, along with various text features on Wikipedia, Flickr30k, and Twitter100k. As a minor contribution, we also design a deep neural network to learn cross-modal embeddings for Twitter100k. Inspired by the characteristic of Twitter100k, we propose a method to integrate optical character recognition into cross-media retrieval. The experiment results show that the proposed method improves the baseline performance.
Huang, J, Duan, Q, Guo, S, Yan, Y & Yu, S 2018, 'Converged Network-Cloud Service Composition with End-to-End Performance Guarantee', IEEE Transactions on Cloud Computing, vol. 6, no. 2, pp. 545-557.
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The crucial role of networking in cloud computing calls for federated management of both computing and networking resources for end-to-end service provisioning. Application of the Service-Oriented Architecture (SOA) in both cloud computing and networking enables a convergence of network and cloud service provisioning. One of the key challenges to high performance converged network-cloud service provisioning lies in composition of network and cloud services with end-to-end performance guarantee. In this paper, we propose a QoS-aware service composition approach to tackling this challenging issue. We first present a system model for network-cloud service composition and formulate the service composition problem as a variant of Multi-Constrained Optimal Path (MCOP) problem. We then propose an approximation algorithm to solve the problem and give theoretical analysis on properties of the algorithm to show its effectiveness and efficiency for QoS-aware network-cloud service composition. Performance of the proposed algorithm is evaluated through extensive experiments and the obtained results indicate that the proposed method achieves better performance in service composition than the best current MCOP approaches.
Huang, L, Li, M, Ngo, HH, Guo, W, Xu, W, Du, B, Wei, Q & Wei, D 2018, 'Spectroscopic characteristics of dissolved organic matter from aquaculture wastewater and its interaction mechanism to chlorinated phenol compound', Journal of Molecular Liquids, vol. 263, pp. 422-427.
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© 2017 In present study, the characteristics of dissolved organic matter (DOM) from aquaculture wastewater and its interaction to 4-chlorophenol (4-CP) was evaluated via a spectroscopic approach. According to EEM-PARAFAC analysis, two components were derived from the interaction samples between DOM and 4-CP, including humic-like and fulvic-like substances for component 1 and protein-like substances for component 2, respectively. The fluorescence intensity scores of two PARAFAC-derived components decreased with increasing 4-CP concentration. Synchronous fluorescence coupled to two-dimensional correlation spectroscopy (2D-COS) implied that DOM fractions quenched different degrees and occurred in the order of fulvic-like and humic-like fractions > protein-like fraction. Moreover, the quenching mechanisms were mainly caused by static quenching process. It was also found from Fourier transform infrared spectroscopy that the main functional groups for interaction between 4-CP and DOM were O–H stretching and C[dbnd]O stretching vibration. The obtained results provided a spectroscopic approach for characterizing the interaction between organic pollutant and DOM from aquaculture wastewater.
Huang, L, Li, M, Si, G, Wei, J, Ngo, HH, Guo, W, Xu, W, Du, B, Wei, Q & Wei, D 2018, 'Assessment of microbial products in the biosorption process of Cu(II) onto aerobic granular sludge: Extracellular polymeric substances contribution and soluble microbial products release', Journal of Colloid and Interface Science, vol. 527, pp. 87-94.
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© 2018 In the present study, the responses of microbial products in the biosorption process of Cu(II) onto aerobic granular sludge were evaluated by using batch and spectroscopic approaches. Batch experimental data showed that extracellular polymeric substances (EPSs) contributed to Cu(II) removal from an aqueous solution, especially when treating low metal concentrations, whereas soluble microbial products (SMPs) were released under the metal stress during biosorption process. A three-dimensional excitation-emission matrix (3D-EEM) identified four main fluorescence peaks in the EPS, i.e., tryptophan protein-like, aromatic protein-like, humic-like and fulvic acid-like substances, and their fluorescence intensities decreased gradually in the presence of Cu(II) during the sorption process. Particularly, tryptophan protein-like substances quenched the Cu(II) binding to a much higher extent through a static quenching process with less than one class of binding sites. According to the synchronous fluorescence spectra, the whole fluorescence intensity of released SMP samples expressed an increased trend with different degrees along with contact time. Two-dimensional correlation spectroscopy (2D-COS) suggested that the fulvic-like fluorescence fraction might be more susceptible to metal exposure than other fractions. The result of molecular weight distribution demonstrated that the SMPs released from the biosorption process differed significantly according to contact time. The result obtained could provide new insights into the responses of microbial products from aerobic granular sludge with heavy metal treatment.
Huang, W, Alem, L, Tecchia, F & Duh, HB-L 2018, 'Augmented 3D hands: a gesture-based mixed reality system for distributed collaboration', Journal on Multimodal User Interfaces, vol. 12, no. 2, pp. 77-89.
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Huang, W, Li, J & Alem, L 2018, 'Towards Preventative Healthcare: A Review of Wearable and Mobile Applications.', Stud Health Technol Inform, vol. 251, pp. 11-14.
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Wearable and mobile devices are now commonly used in our daily activities, giving users instant access to various information. One the one hand, wearable and mobile technologies are developing at a fast rate and have been increasingly ubiquitous. On the other hand, the potential of their application in health is yet to be fully explored. This paper attempts to sketch an overview of wearable and mobile applications in the healthcare domain. We first review how various wearable and mobile applications are being used to monitor and manage health conditions. Then how connections between physiological factors and psychological factors can help with disease prevention is presented. Finally, challenges and future directions for further developments of these emerging technologies in health are discussed.
Huang, X, Zhang, J, Wu, Q, Fan, L & Yuan, C 2018, 'A Coarse-to-Fine Algorithm for Matching and Registration in 3D Cross-Source Point Clouds', IEEE Transactions on Circuits and Systems for Video Technology, vol. 28, no. 10, pp. 2965-2977.
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© 1991-2012 IEEE. We propose an efficient method to deal with the matching and registration problem found in cross-source point clouds captured by different types of sensors. This task is especially challenging due to the presence of density variation, scale difference, a large proportion of noise and outliers, missing data, and viewpoint variation. The proposed method has two stages: in the coarse matching stage, we use the ensemble of shape functions descriptor to select potential K regions from the candidate point clouds for the target. In the fine stage, we propose a scale embedded generative Gaussian mixture models registration method to refine the results from the coarse matching stage. Following the fine stage, both the best region and accurate camera pose relationships between the candidates and target are found. We conduct experiments in which we apply the method to two applications: one is 3D object detection and localization in street-view outdoor (LiDAR/VSFM) cross-source point clouds and the other is 3D scene matching and registration in indoor (KinectFusion/VSFM) cross-source point clouds. The experiment results show that the proposed method performs well when compared with the existing methods. It also shows that the proposed method is robust under various sensing techniques, such as LiDAR, Kinect, and RGB camera.
Huang, Y, Cao, L, Zhang, J, Pan, L & Liu, Y 2018, 'Exploring Feature Coupling and Model Coupling for Image Source Identification', IEEE Transactions on Information Forensics and Security, vol. 13, no. 12, pp. 3108-3121.
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© 2005-2012 IEEE. Recently, there has been great interest in feature-based image source identification. Previous statistical learning-based methods usually regarded the identification process as a classification problem. They assumed the dependence of features and the dependence of models. However, the two assumptions are usually problematic because of the genuine coupling of features and models. To address the issues, in this paper, we propose a novel image source identification scheme. For the feature coupling, a coupled feature representation is adopted to analyze the coupled interaction among features. The coupling relations among features and their powers are measured with Pearson's correlations and integrated in a Taylor-like expansion manner. Regarding model coupling, a new coupled probability representation is developed. The model coupling relationships are characterized with conditional probabilities induced by the confusion matrix and then combined with the law of total probability. The experiments carried out on the Dresden image collection confirm the effectiveness of the proposed scheme. Via mining the feature coupling and model coupling, the identification accuracy can be significantly improved.
Huang, Y, Ng, ECY, Zhou, JL, Surawski, NC, Chan, EFC & Hong, G 2018, 'Eco-driving technology for sustainable road transport: A review', Renewable and Sustainable Energy Reviews, vol. 93, pp. 596-609.
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© 2018 Elsevier Ltd Road transport consumes significant quantities of fossil fuel and accounts for a significant proportion of CO2 and pollutant emissions worldwide. The driver is a major and often overlooked factor that determines vehicle performance. Eco-driving is a relatively low-cost and immediate measure to reduce fuel consumption and emissions significantly. This paper reviews the major factors, research methods and implementation of eco-driving technology. The major factors of eco-driving are acceleration/deceleration, driving speed, route choice and idling. Eco-driving training programs and in-vehicle feedback devices are commonly used to implement eco-driving skills. After training or using in-vehicle devices, immediate and significant reductions in fuel consumption and CO2 emissions have been observed with slightly increased travel time. However, the impacts of both methods attenuate over time due to the ingrained driving habits developed over the years. These findings imply the necessity of developing quantitative eco-driving patterns that could be integrated into vehicle hardware so as to generate more constant and uniform improvements, as well as developing more effective and lasting training programs and in-vehicle devices. Current eco-driving studies mainly focus on the fuel savings and CO2 reduction of individual vehicles, but ignore the pollutant emissions and the impacts at network levels. Finally, the challenges and future research directions of eco-driving technology are elaborated.
Huang, Y, Organ, B, Zhou, JL, Surawski, NC, Hong, G, Chan, EFC & Yam, YS 2018, 'Emission measurement of diesel vehicles in Hong Kong through on-road remote sensing: Performance review and identification of high-emitters', Environmental Pollution, vol. 237, pp. 133-142.
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© 2018 Elsevier Ltd A two-year remote sensing measurement program was carried out in Hong Kong to obtain a large dataset of on-road diesel vehicle emissions. Analysis was performed to evaluate the effect of vehicle manufacture year (1949–2015) and engine size (0.4–20 L) on the emission rates and high-emitters. The results showed that CO emission rates of larger engine size vehicles were higher than those of small vehicles during the study period, while HC and NO were higher before manufacture year 2006 and then became similar levels between manufacture years 2006 and 2015. CO, HC and NO of all vehicles showed an unexpectedly increasing trend during 1998–2004, in particular ≥6001 cc vehicles. However, they all decreased steadily in the last decade (2005–2015), except for NO of ≥6001 cc vehicles during 2013–2015. The distributions of CO and HC emission rates were highly skewed as the dirtiest 10% vehicles emitted much higher emissions than all the other vehicles. Moreover, this skewness became more significant for larger engine size or newer vehicles. The results indicated that remote sensing technology would be very effective to screen the CO and HC high-emitters and thus control the on-road vehicle emissions, but less effective for controlling NO emissions. No clear correlation was observed between the manufacture year and percentage of high-emitters for ≤3000 cc vehicles. However, the percentage of high-emitters decreased with newer manufacture year for larger vehicles. In addition, high-emitters of different pollutants were relatively independent, in particular NO emissions, indicating that high-emitter screening criteria should be defined on a CO-or-HC-or-NO basis, rather than a CO-and-HC-and-NO basis.
Huang, Y, Organ, B, Zhou, JL, Surawski, NC, Hong, G, Chan, EFC & Yam, YS 2018, 'Remote sensing of on-road vehicle emissions: Mechanism, applications and a case study from Hong Kong', Atmospheric Environment, vol. 182, pp. 58-74.
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© 2018 Elsevier Ltd Vehicle emissions are a major contributor to air pollution in cities and have serious health impacts to their inhabitants. On-road remote sensing is an effective and economic tool to monitor and control vehicle emissions. In this review, the mechanism, accuracy, advantages and limitations of remote sensing were introduced. Then the applications and major findings of remote sensing were critically reviewed. It was revealed that the emission distribution of on-road vehicles was highly skewed so that the dirtiest 10% vehicles accounted for over half of the total fleet emissions. Such findings highlighted the importance and effectiveness of using remote sensing for in situ identification of high-emitting vehicles for further inspection and maintenance programs. However, the accuracy and number of vehicles affected by screening programs were greatly dependent on the screening criteria. Remote sensing studies showed that the emissions of gasoline and diesel vehicles were significantly reduced in recent years, with the exception of NOx emissions of diesel vehicles in spite of greatly tightened automotive emission regulations. Thirdly, the experience and issues of using remote sensing for identifying high-emitting vehicles in Hong Kong (where remote sensing is a legislative instrument for enforcement purposes) were reported. That was followed by the first time ever identification and discussion of the issue of frequent false detection of diesel high-emitters using remote sensing. Finally, the challenges and future research directions of on-road remote sensing were elaborated.
Huang, Y, Yam, YS, Lee, CKC, Organ, B, Zhou, JL, Surawski, NC, Chan, EFC & Hong, G 2018, 'Tackling nitric oxide emissions from dominant diesel vehicle models using on-road remote sensing technology', Environmental Pollution, vol. 243, no. Pt B, pp. 1177-1185.
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© 2018 Elsevier Ltd Remote sensing provides a rapid detection of vehicle emissions under real driving condition. Remote sensing studies showed that diesel nitrogen oxides emissions changed little or were even increasing in recent years despite the tightened emission standards. To more accurately and fairly evaluate the emission trends, it is hypothesized that analysis should be detailed for individual vehicle models as each model adopted different emissions control technologies and retrofitted the engine/vehicle at different time. Therefore, this study was aimed to investigate the recent nitric oxide (NO) emission trends of the dominant diesel vehicle models using a large remote sensing dataset collected in Hong Kong. The results showed that the diesel vehicle fleet was dominated by only seven models, accounting for 78% of the total remote sensing records. Although each model had different emission levels and trends, generally all the dominant models showed a steady decrease or stable level in the fuel based NO emission factors (g/kg fuel) over the period studied except for BaM1 and BdM2. A significant increase was observed for the BaM1 2.49 L and early 2.98 L models during 2005–2011, which we attribute to the change in the diesel fuel injection technology. However, the overall mean NO emission factor of all the vehicles was stable during 1991–2006 and then decreased steadily during 2006–2016, in which the emission trends of individual models were averaged out and thus masked. Nevertheless, the latest small, medium and heavy diesel vehicles achieved similar NO emission factors due to the converging of operation windows of the engine and emission control devices. The findings suggested that the increasingly stringent European emission standards were not very effective in reducing the NO emissions of some diesel vehicle models in the real world. The European emission regulations were not very effective in reducing the NO emissions from some diesel vehicle...
Huber, S, Koenig, R & Tomamichel, M 2018, 'Jointly constrained semidefinite bilinear programming with an application to Dobrushin curves', IEEE Trans Inf Theory, vol. 56, no. 5, pp. 2934-2950.
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We propose a branch-and-bound algorithm for minimizing a bilinear functionalof the form \[ f(X,Y) = \mathrm{tr}((X\otimesY)Q)+\mathrm{tr}(AX)+\mathrm{tr}(BY) , \] of pairs of Hermitian matrices$(X,Y)$ restricted by joint semidefinite programming constraints. Thefunctional is parametrized by self-adjoint matrices $Q$, $A$ and $B$. Thisproblem generalizes that of a bilinear program, where $X$ and $Y$ belong topolyhedra. The algorithm converges to a global optimum and yields upper andlower bounds on its value in every step. Various problems in quantuminformation theory can be expressed in this form. As an example application, wecompute Dobrushin curves of quantum channels, giving upper bounds on classicalcoding with energy constraints.
Huo, S, Liu, M, Wu, L, Liu, M, Xu, M, Ni, W & Yan, Y-M 2018, 'Methanesulfonic acid-assisted synthesis of N/S co-doped hierarchically porous carbon for high performance supercapacitors', Journal of Power Sources, vol. 387, pp. 81-90.
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Husin, H, Solo, BB, Ibrahim, IM, Chyuan, OH & Roslan, A 2018, 'Weight loss effect and potentiodynamic polarization response of 1-butyl-3-methylimidazolium chloride ionic liquid in highly acidic medium', Journal of Engineering Science and Technology, vol. 13, no. 4, pp. 1005-1015.
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Ionic liquids are increasingly being used as corrosion inhibitors when oil and gas industries started to give focus on sustainability and green impact in their operations. In this study, 1-butyl-3-methylimidazolium chloride ionic liquid in 2M HCl medium has been investigated on mild steel, stainless steel and aluminium bars by using weight loss technique and potentiodynamic polarization measurement. Results showed that 1-butyl-3-methylimidazolium chloride is able to reduce the weight loss of aluminium metal under acidic corrosive surrounding up to 11% compared to that of without the presence of 1-butyl-3-methylimidazolium chloride. Based on potentiodynamic polarization response, percentage of corrosion inhibition efficiency is found to be up to 99.3%. In summary, 1-butyl-3-methylimidazolium chloride is highly potential to act as an anti-corrosion agent, even in a very low concentration.
Hussain, W, Hussain, FK, Hussain, O, Bagia, R & Chang, E 2018, 'Risk-based framework for SLA violation abatement from the cloud service provider’s perspective', The Computer Journal, vol. 61, no. 9, pp. 1306-1322.
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© The British Computer Society 2018. The constant increase in the growth of the cloud market creates new challenges for cloud service providers. One such challenge is the need to avoid possible service level agreement (SLA) violations and their consequences through good SLA management. Researchers have proposed various frameworks and have made significant advances in managing SLAs from the perspective of both cloud users and providers. However, none of these approaches guides the service provider on the necessary steps to take for SLA violation abatement; that is, the prediction of possible SLA violations, the process to follow when the system identifies the threat of SLA violation, and the recommended action to take to avoid SLA violation. In this paper, we approach this process of SLA violation detection and abatement from a risk management perspective. We propose a Risk Management-based Framework for SLA violation abatement (RMF-SLA) following the formation of an SLA which comprises SLA monitoring, violation prediction and decision recommendation. Through experiments, we validate and demonstrate the suitability of the proposed framework for assisting cloud providers to minimize possible service violations and penalties.
Hussain, W, Hussain, FK, Saberi, M, Hussain, OK & Chang, E 2018, 'Comparing time series with machine learning-based prediction approaches for violation management in cloud SLAs', Future Generation Computer Systems, vol. 89, pp. 464-477.
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© 2018 In cloud computing, service level agreements (SLAs) are legal agreements between a service provider and consumer that contain a list of obligations and commitments which need to be satisfied by both parties during the transaction. From a service provider's perspective, a violation of such a commitment leads to penalties in terms of money and reputation and thus has to be effectively managed. In the literature, this problem has been studied under the domain of cloud service management. One aspect required to manage cloud services after the formation of SLAs is to predict the future Quality of Service (QoS) of cloud parameters to ascertain if they lead to violations. Various approaches in the literature perform this task using different prediction approaches however none of them study the accuracy of each. However, it is important to do this as the results of each prediction approach vary according to the pattern of the input data and selecting an incorrect choice of a prediction algorithm could lead to service violation and penalties. In this paper, we test and report the accuracy of time series and machine learning-based prediction approaches. In each category, we test many different techniques and rank them according to their order of accuracy in predicting future QoS. Our analysis helps the cloud service provider to choose an appropriate prediction approach (whether time series or machine learning based) and further to utilize the best method depending on input data patterns to obtain an accurate prediction result and better manage their SLAs to avoid violation penalties.
Hussaini, SKK, Indraratna, B & Vinod, JS 2018, 'A critical review of the performance of geosynthetic-reinforced railroad ballast', Geotechnical Engineering, vol. 49, no. 4, pp. 31-41.
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In the recent times, railway organizations across the world have resorted to the use of geosynthetics as a low-cost solution to stabilize ballast. In this view, extensive studies have been conducted worldwide to assess the performance of geosynthetic-reinforced ballast under various loading conditions. This paper evaluates the various benefits the rail industry could attain because of the geosynthetic reinforcement. A review of literature reveals that geogrid arrests the lateral spreading of ballast, reduces the extent of permanent vertical settlement and minimizes the particle breakage. The geogrid was also found to reduce the extent of volumetric compressions in ballast. The overall performance improvement due to geogrid was observed to be a function of the interface efficiency factor (φ). Moreover, studies also established the additional role of geogrids in reducing the differential track settlements and diminishing the stresses at the subgrade level. The geosynthetics were found to be more beneficial in case of tracks resting on soft subgrades. Furthermore, the benefits of geosynthetics in stabilizing ballast were found to be significantly higher when placed within the ballast. The optimum placement location of geosynthetics has been reported by several researchers to be about 200-250 mm below the sleeper soffit for a conventional ballast depth of 300-350 mm. A number of field investigations and track rehabilitation schemes also confirmed the role of geosynthetics/geogrids in stabilizing the tracks thereby helping in removing the stringent speed restrictions that were imposed earlier, and enhancing the time interval between maintenance operations.
Huynh, NV, Hoang, DT, Nguyen, DN, Dutkiewicz, E, Niyato, D & Wang, P 2018, 'Optimal and Low-Complexity Dynamic Spectrum Access for RF-Powered Ambient Backscatter System with Online Reinforcement Learning', IEEE TRANSACTIONS ON COMMUNICATIONS, vol. 67, no. 8, pp. 5736-5752.
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Ambient backscatter has been introduced with a wide range of applications forlow power wireless communications. In this article, we propose an optimal andlow-complexity dynamic spectrum access framework for RF-powered ambientbackscatter system. In this system, the secondary transmitter not only harvestsenergy from ambient signals (from incumbent users), but also backscatters thesesignals to its receiver for data transmission. Under the dynamics of theambient signals, we first adopt the Markov decision process (MDP) framework toobtain the optimal policy for the secondary transmitter, aiming to maximize thesystem throughput. However, the MDP-based optimization requires completeknowledge of environment parameters, e.g., the probability of a channel to beidle and the probability of a successful packet transmission, that may not bepractical to obtain. To cope with such incomplete knowledge of the environment,we develop a low-complexity online reinforcement learning algorithm that allowsthe secondary transmitter to 'learn' from its decisions and then attain theoptimal policy. Simulation results show that the proposed learning algorithmnot only efficiently deals with the dynamics of the environment, but alsoimproves the average throughput up to 50% and reduces the blocking probabilityand delay up to 80% compared with conventional methods.
Huynh, NV, Hoang, DT, Niyato, D, Wang, P & Kim, DI 2018, 'Optimal Time Scheduling for Wireless-Powered Backscatter Communication Networks', IEEE Wireless Communications Letters, vol. 7, no. 5, pp. 820-823.
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This letter introduces a novel wireless-powered backscatter communicationsystem which allows sensors to utilize RF signals transmitted from a dedicatedRF energy source to transmit data. In the proposed system, when the RF energysource transmits RF signals, the sensors are able to backscatter the RF signalsto transmit date to the gateway and/or harvest energy from the RF signals fortheir operations. By integrating backscattering and energy harvestingtechniques, we can optimize the network throughput of the system. Inparticular, we first formulate the time scheduling problem for the system, andthen propose an optimal solution using convex optimization to maximize theoverall network throughput. Numerical results show a significant throughputgain achieved by our proposed design over two other baseline schemes.
Idrees, MO & Pradhan, B 2018, 'Geostructural stability assessment of cave using rock surface discontinuity extracted from terrestrial laser scanning point cloud', Journal of Rock Mechanics and Geotechnical Engineering, vol. 10, no. 3, pp. 534-544.
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© 2018 Institute of Rock and Soil Mechanics, Chinese Academy of Sciences The use of terrestrial laser scanning (TLS) in the caves has been growing drastically over the last decade. However, TLS application to cave stability assessment has not received much attention of researchers. This study attempted to utilize rock surface orientations obtained from TLS point cloud collected along cave passages to (1) investigate the influence of rock geostructure on cave passage development, and (2) assess cave stability by determining areas susceptible to different failure types. The TLS point cloud was divided into six parts (Entry hall, Chamber, Main hall, Shaft 1, Shaft 2 and Shaft 3), each representing different segments of the cave passages. Furthermore, the surface orientation information was extracted and grouped into surface discontinuity joint sets. The computed global mean and best–fit planes of the entire cave show that the outcrop dips 290° with a major north-south strike. But at individual level, the passages with dip angle between 26° and 80° are featured with dip direction of 75°–322°. Kinematic tests reveal the potential for various failure modes of rock slope. Our findings show that toppling is the dominant failure type accounting for high-risk rockfall in the cave, with probabilities of 75.26%, 43.07% and 24.82% in the Entry hall, Main hall and Shaft 2, respectively. Unlike Shaft 2 characterized by high risk of the three failure types (32.49%, 24.82% and 50%), the chamber and Shaft 3 passages are not suffering from slope failure. The results also show that the characteristics of rock geostructure considerably influence the development of the cave passages, and four sections of the cave are susceptible to different slope failure types, at varying degrees of risk.
Imani, MH, Ghadi, MJ, Ghavidel, S & Li, L 2018, 'Demand Response Modeling in Microgrid Operation: a Review and Application for Incentive-Based and Time-Based Programs', Renewable and Sustainable Energy Reviews, vol. 94, pp. 486-499.
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© 2018 Elsevier Ltd During recent years, with the advent of restructuring in power systems as well as the increase of electricity demand and global fuel energy prices, challenges related to implementing demand response programs (DRPs) have gained remarkable attention of independent system operators (ISOs) and customers, aiming at the improvement of attributes of the load curve and reduction of energy consumption as well as benefiting customers. In this paper, different types of DRPs are modeled based on price elasticity of the demand and the concept of customer benefit. Besides, the impact of implementing DRPs on the operation of grid-connected microgrid (MG) is analyzed. Moreover, several scenarios are presented in order to model uncertainties interfering MG operations including failure of generation units and random outages of transmission lines and upstream line, error in load demand forecasting, uncertainty in production of renewable energies (wind and solar) based distributed generation units, and the possibility that customers do not respond to scheduled interruptions. Simulations are conducted for two principal categories of DRP including incentive-based programs and time-based programs on an 11-bus MG over a 24-h period and also a 14-bus MG over a period of 336 h (two weeks). Simulation results indicate the effects of DRPs on total operation costs, customer's benefit, and load curve as well as determining optimal use of energy resources in the MG operation. In this regard, prioritizing of DRPs on the MG operation is required.
Inan, DI, Beydoun, G & Opper, S 2018, 'Agent-Based Knowledge Analysis Framework in Disaster Management.', Inf. Syst. Frontiers, vol. 20, pp. 783-802.
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© 2017 Springer Science+Business Media, LLC Disaster Management (DM) is a complex set of interrelated activities. The activities are often knowledge-intensive and time sensitive. Timely sharing of the required knowledge is critical for DM. For recurring disasters (e.g. floods), developed countries tend to have dedicated document repositories of Disaster Management Plans (DISPLANs) that can be accessed as needs arise. However, accessing the appropriate plan in a timely manner, and sharing activities between plans, often requires significant domain knowledge and intimate understanding of the plans in the first place. This paper introduces an Agent-Based (AB) knowledge analysis method to convert DISPLANs into a collection of knowledge units that can be stored into a unified repository. The repository of DM actions then enables the mixing and matching of knowledge between different plans. The repository is structured as a layered abstraction according to Meta Object Facility (MOF). We use the flood DISPLANs plans used by SES (State Emergency Service), an authoritative DM agency in New South Wales (NSW) State of Australia (hereinafter referred to as SES NSW) to illustrate and give a preliminary validation of the approach. It is illustrated by using displans along the flood-prone Murrumbidgee river in central NSW.
Inan, DI, Beydoun, G & Pradhan, B 2018, 'Developing a decision support system for Disaster Management: Case study of an Indonesia volcano eruption', International Journal of Disaster Risk Reduction, vol. 31, pp. 711-721.
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© 2018 Elsevier Ltd Disaster Management activities often focus on specific tasks (e.g. evacuation, logistic or coordination) and are confined to one specific DM phase (e.g. Preparedness or Response). New awareness about an external change, be it environmental or organisational, typically act as a trigger for such focussed activities. A variety of views or stakeholders are also involved in those activities, and their various concerns get often intertwined. This work advocates the use of a Decision Support System (DSS) that can be deployed as a single access point. Such a system requires a sufficient amount of representative knowledge, and facilities to avail the knowledge to the appropriate stakeholders in an appropriate form. With the multitude of stakeholders and their varying knowledge requirements, the system will need to present the knowledge differently according to the stakeholders needs in their decision making process. Such processes can vary, e.g. whether for policy making or for operational real time responses. This paper presents a hybrid of knowledge elicitation and retrieval mechanisms, some are top down and others are bottom up. The mechanisms make use of the Meta Object Facility (MOF) to structure and present the knowledge appropriately according to different interests and roles. A case study of the recent Mt. Agung volcano eruption in Bali Indonesia is successfully used to demonstrate the efficacy of the mechanisms proposed and the resultant DSS.
Indraratna, B, Baral, P, Rujikiatkamjorn, C & Perera, D 2018, 'Class A and C predictions for Ballina trial embankment with vertical drains using standard test data from industry and large diameter test specimens', Computers and Geotechnics, vol. 93, pp. 232-246.
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Indraratna, B, Ferreira, FB, Qi, Y & Ngo, TN 2018, 'Application of geoinclusions for sustainable rail infrastructure under increased axle loads and higher speeds', Innovative Infrastructure Solutions, vol. 3, no. 1, p. 69.
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Given the ongoing demand for faster trains for carrying heavier loads, conventional ballasted railroads require considerable upgrading in order to cope with the increasing traffic-induced stresses. During train operations, ballast deteriorates due to progressive breakage and fouling caused by the infiltration of fine particles from the surface or mud-pumping from the underneath layers (e.g. sub-ballast, sub-grade), which decreases the load bearing capacity, impedes drainage and increases the deformation of ballasted tracks. Suitable ground improvement techniques involving geosynthetics and resilient rubber sheets are commonly employed to enhance the stability and longevity of rail tracks. This keynote paper focuses mainly on research projects undertaken at the University of Wollongong to improve track performance by emphasising the main research outcomes and their practical implications. Results from laboratory tests, computational modelling and field trials have shown that track behaviour can be significantly improved by the use of geosynthetics, energy-absorbing rubber mats, rubber crumbs and infilled-recycled tyres. Full-scale monitoring of instrumented track sections supported by rail industry (ARTC) has been performed, and the obtained field data for in situ stresses and deformations could verify the track performance, apart from validating the numerical simulations. The research outcomes provide promising approaches that can be incorporated into current track design practices to cater for high-speed freight trains carrying heavier loads.
Indraratna, B, Israr, J & Li, M 2018, 'Inception of geohydraulic failures in granular soils – an experimental and theoretical treatment', Géotechnique, vol. 68, no. 3, pp. 233-248.
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This paper outlines an experimental investigation into seepage-induced failures in soils subjected to static and cyclic loading. Internally stable, marginal and unstable soils are characterised by heave, composite heave–piping and suffusion that develops immediately upon instability. In this study, the stable specimens exhibited heave at larger hydraulic gradients than the unstable specimens failing by suffusion at relatively smaller hydraulic gradients. Under no external load (i.e. self-weight only), the relative density (Rd) and particle size distribution (PSD) in tandem controlled the internal stability of soils, although the effective stress magnitude (σ′vt) also had a role to play under both static and cyclic loading conditions. Instability in soils was governed by specific combinations of their geo-hydro-mechanical characteristics such as PSD, Rd, stress reduction factor, critical hydraulic gradients and associated effective stress levels. These factors are combined to model the development and inception of instability, and the paper offers visual guides as a practical tool for practitioners. Each soil has a unique critical envelope related to its PSD and Rd, and a critical path with its inclination that depends on the hydro-mechanical conditions. The current results of internal erosion tests conducted by the authors plus those adopted from published literature are used to verify the proposed model.
Indraratna, B, Qi, Y & Heitor, A 2018, 'Evaluating the Properties of Mixtures of Steel Furnace Slag, Coal Wash, and Rubber Crumbs Used as Subballast', Journal of Materials in Civil Engineering, vol. 30, no. 1, pp. 04017251-04017251.
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Indraratna, B, Sun, Q, Heitor, A & Grant, J 2018, 'Performance of Rubber Tire-Confined Capping Layer under Cyclic Loading for Railroad Conditions', Journal of Materials in Civil Engineering, vol. 30, no. 3, pp. 06017021-06017021.
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Ingkiriwang, YG & Far, H 2018, 'Numerical investigation of the design of single‐span steel portal frames using the effective length and direct analysis methods', Steel Construction, vol. 11, no. 3, pp. 184-191.
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AbstractThe era of globalization enables the design, fabrication and erection of steel structures to take place in different locations far away from each other. Therefore, a widely acceptable steel design standard is required, and designers should be familiar with alternative specifications that may be considerably different from one another. This study deals with single‐span unbraced steel portal frames and makes a comparison between the design methodologies adopted by the Australian and American design provisions, in particular, the effective length method (ELM) and direct analysis method (DAM). A brief discussion on the main features of both standards is also presented. Furthermore, the results of the parametric study are portrayed, highlighting the differences between these two design standards regarding stress interaction. Finally, of the two aforementioned methods, the most applicable optimization method for the design and development of cost‐effective industrial portal frame buildings is proposed with respect to the structure geometry.
Ishac, K & Suzuki, K 2018, 'LifeChair: A Conductive Fabric Sensor-Based Smart Cushion for Actively Shaping Sitting Posture', Sensors, vol. 18, no. 7, pp. 2261-2261.
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The LifeChair is a smart cushion that provides vibrotactile feedback by actively sensing and classifying sitting postures to encourage upright posture and reduce slouching. The key component of the LifeChair is our novel conductive fabric pressure sensing array. Fabric sensors have been explored in the past, but a full sensing solution for embedded real world use has not been proposed. We have designed our system with commercial use in mind, and as a result, it has a high focus on manufacturability, cost-effectiveness and adaptiveness. We demonstrate the performance of our fabric sensing system by installing it into the LifeChair and comparing its posture detection accuracy with our previous study that implemented a conventional flexible printed PCB-sensing system. In this study, it is shown that the LifeChair can detect all 11 postures across 20 participants with an improved average accuracy of 98.1%, and it demonstrates significantly lower variance when interfacing with different users. We also conduct a performance study with 10 participants to evaluate the effectiveness of the LifeChair device in improving upright posture and reducing slouching. Our performance study demonstrates that the LifeChair is effective in encouraging users to sit upright with an increase of 68.1% in time spent seated upright when vibrotactile feedback is activated.
Islam, M, Mithulananthan, N & Hossain, MJ 2018, 'Dynamic Voltage Support by TL-PV Systems to Mitigate Short-Term Voltage Instability in Residential DN', IEEE Transactions on Power Systems, vol. 33, no. 4, pp. 4360-4370.
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Islam, MS, Saha, SC, Gemci, T, Yang, IA, Sauret, E & Gu, YT 2018, 'Polydisperse Microparticle Transport and Deposition to the Terminal Bronchioles in a Heterogeneous Vasculature Tree', Scientific Reports, vol. 8, no. 1.
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AbstractThe atmospheric particles from different sources, and the therapeutic particles from various drug delivery devices, exhibit a complex size distribution, and the particles are mostly polydisperse. The limited available in vitro, and the wide range of in silico models have improved understanding of the relationship between monodisperse particle deposition and therapeutic aerosol transport. However, comprehensive polydisperse transport and deposition (TD) data for the terminal airways is still unavailable. Therefore, to benefit future drug therapeutics, the present numerical model illustrates detailed polydisperse particle TD in the terminal bronchioles for the first time. Euler-Lagrange approach and Rosin-Rammler diameter distribution is used for polydisperse particles. The numerical results show higher deposition efficiency (DE) in the right lung. Specifically, the larger the particle diameter (dp > 5 μm), the higher the DE at the bifurcation area of the upper airways is, whereas for the smaller particle (dp < 5 μm), the DE is higher at the bifurcation wall. The overall deposition pattern shows a different deposition hot spot for different diameter particle. These comprehensive lobe-specific polydisperse particle deposition studies will increase understanding of actual inhalation for particle TD, which could potentially increase the efficiency of pharmaceutical aerosol delivery at the targeted position of the terminal airways.
Ismaiel, B, Abolhasan, M, Ni, W, Smith, DB, Franklin, DR & Jamalipour, A 2018, 'Analysis of Effective Capacity and Throughput of Polling-Based Device-To-Device Networks.', IEEE Trans. Veh. Technol., vol. 67, no. 9, pp. 8656-8666.
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© 1967-2012 IEEE. Next-generation wireless networks will give rise to heterogeneous networks by integrating multiple wireless access technologies to provide seamless mobility to mobile users with high-speed wireless connectivity. Device-to-device (D2D) communication has proven to be a promising technology that can increase the capacity and coverage of wireless networks. The D2D communication was first introduced in long-term evolution advanced (LTE-A) and has gained immense popularity for the offloading traffic using the licensed and unlicensed band. Challenges arise from resource allocation, provision of quality-of-service (QoS), and the quantification of capacity in an unlicensed band due to the distributed nature of Wi-Fi. In this paper, we propose an analytical performance model for the scalable MAC protocol (SC-MP) in which a resource allocation mechanism is based on the IEEE 802.11 point coordinated function to access the Wi-Fi channel for voice and video/multimedia traffic. In the SC-MP, D2D communication is applied to further offload the video/multimedia traffic. In particular, this paper establishes a three-state semi-Markovian model to derive a closed-form expression of effective capacity in terms of transmission rate and quality-of-service. Further, the SC-MP is analytically modeled using the four-state traditional Markov model to derive the saturation throughput. The analytical results are validated through simulations, hence, proving the appropriateness of the model.
Ismaiel, B, Abolhasan, M, Ni, W, Smith, DB, Franklin, DR, Dutkiewicz, E, Krunz, M & Jamalipour, A 2018, 'PCF-Based LTE Wi-Fi Aggregation for Coordinating and Offloading the Cellular Traffic to D2D Network.', IEEE Trans. Veh. Technol., vol. 67, no. 12, pp. 12193-12203.
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© 2018 IEEE. Device-to-device (D2D) communication is a promising technology towards 5G networks. D2D communication can offload traffic using licensed/unlicensed band by establishing a direct communication between two users without traversing the base station or core network. However, one of the major challenges of D2D communication is resource allocation and guaranteeing quality-of-service (QoS). In this paper, we establish an optimal queuing scheduling and resource allocation problem for three-tier heterogeneous network based on LTE Wi-Fi aggregation, to offload voice/multimedia traffic from licensed band to unlicensed band using scalable MAC protocol (SC-MP) under various static delay constraints. The access mechanism used for Wi-Fi in SC-MP is point coordination function, which further offloads the multimedia traffic using D2D communication in unlicensed band. Resource allocation and optimal joint queuing scheduling problems are formulated with diverse QoS guarantee between licensed and unlicensed band to minimize the bandwidth of licensed band. Furthermore, an iterative algorithm is proposed to express the nonconvex problem as a series of subproblems based on block coordinate descent and difference of two convex functions (D.C) program. We have simulated the proposed scheme using two scenarios: Voice traffic using licensed band and voice traffic using both licensed and unlicensed band, whereas multimedia traffic uses unlicensed band for both the scenarios. The simulation results show that both the schemes perform better than the existing scheme and scenario 2 outperforms scenario 1.
Israr, J & Indraratna, B 2018, 'Assessment of internal stability of filters under static and cyclic loading: An experimental and theoretical treatment', Australian Geomechanics Journal, vol. 53, no. 4, pp. 103-116.
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The occurrence of internal instability may significantly affect geo-mechanical characteristics of granular filters such as permeability and particle size distribution, consequently rendering them ineffective in retaining the protected base soils and thereby endangering the structural stability. This paper presents the results of 65 hydraulic tests performed on ten different granular soils compacted at varying relative densities between 0 and 100% and subjected to an upward hydraulic flow under both static and cyclic conditions. It was observed that the internal stability is a function of particle gradation and relative density in tandem, i.e. constriction size distribution, under static conditions. However, the agitation and pore pressure development under cyclic loading triggered excessively premature internal erosion in filters. Based on the analysis, new constriction-based criteria proposed for both static and cyclic conditions that showed remarkable accuracy in correctly assessing the potential of instability of filters compared to many existing criteria. Moreover, a new hydromechanical model is presented that could accurately capture the correct potential of instability of filters, thereby contributing toward increased confidence level for practical design of filters. Two practical design examples presented to demonstrate the implications of this research study in practice to conclude this paper.
Israr, J & Indraratna, B 2018, 'Mechanical response and pore pressure generation in granular filters subjected to uniaxial cyclic loading', Canadian Geotechnical Journal, vol. 55, no. 12, pp. 1756-1768.
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This paper presents results from a series of piping tests carried out on a selected range of granular filters under static and cyclic loading conditions. The mechanical response of filters subjected to cyclic loading could be characterized in three distinct phases; namely, (I) pre-shakedown, (II) post-shakedown, and (III) post-critical (i.e., the occurrence of internal erosion). All the permanent geomechanical changes such, as erosion, permeability variations, and axial strain developments, took place during phases I and III, while the specimen response remained purely elastic during phase II. The post-critical occurrence of erosion incurred significant settlement that may not be tolerable for high-speed railway substructures. The analysis revealed that a cyclic load would induce excess pore-water pressure, which, in corroboration with steady seepage forces and agitation due to dynamic loading, could then cause internal erosion of fines from the specimens. The resulting excess pore pressure is a direct function of the axial strain due to cyclic densification, as well as the loading frequency and reduction in permeability. A model based on strain energy is proposed to quantify the excess pore-water pressure, and subsequently validated using current and existing test results from published studies.
Ivanyos, G, Kulkarni, R, Qiao, Y, Santha, M & Sundaram, A 2018, 'On the complexity of trial and error for constraint satisfaction problems', Journal of Computer and System Sciences, vol. 92, pp. 48-64.
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© 2017 Elsevier Inc. In 2013 Bei, Chen and Zhang introduced a trial and error model of computing, and applied to some constraint satisfaction problems. In this model the input is hidden by an oracle which, for a candidate assignment, reveals some information about a violated constraint if the assignment is not satisfying. In this paper we initiate a systematic study of constraint satisfaction problems in the trial and error model, by adopting a formal framework for CSPs, and defining several types of revealing oracles. Our main contribution is to develop a transfer theorem for each type of the revealing oracle. To any hidden CSP with a specific type of revealing oracle, the transfer theorem associates another CSP in the normal setting, such that their complexities are polynomial-time equivalent. This in principle transfers the study of a large class of hidden CSPs to the study of normal CSPs. We apply the transfer theorems to get polynomial-time algorithms or hardness results for several families of concrete problems.
Ivanyos, G, Qiao, Y & Subrahmanyam, KV 2018, 'Constructive non-commutative rank computation is in deterministic polynomial time', computational complexity, vol. 27, no. 4, pp. 561-593.
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© 2018, Springer International Publishing AG, part of Springer Nature. We extend the techniques developed in Ivanyos et al. (Comput Complex 26(3):717–763, 2017) to obtain a deterministic polynomial-time algorithm for computing the non-commutative rank of linear spaces of matrices over any field. The key new idea that causes a reduction in the time complexity of the algorithm in Ivanyos et al. (2017) from exponential time to polynomial time is a reduction procedure that keeps the blow-up parameter small, and there are two methods to implement this idea: the first one is a greedy argument that removes certain rows and columns, and the second one is an efficient algorithmic version of a result of Derksen & Makam (Adv Math 310:44–63, 2017b), who were the first to observe that the blow-up parameter can be controlled. Both methods rely crucially on the regularity lemma from Ivanyos et al. (2017). In this note, we improve that lemma by removing a coprime condition there.
Jamil, S, Jeong, S & Vigneswaran, S 2018, 'Application of forward osmosis membrane in nanofiltration mode to treat reverse osmosis concentrate from wastewater reclamation plants', Water Science and Technology, vol. 77, no. 8, pp. 1990-1997.
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Abstract Reverse osmosis concentrate (ROC) from wastewater reclamation plants have high concentrations of organic and inorganic compounds, which have to be removed before its disposal. Forward osmosis (FO) and nanofiltration (NF) membranes were tested to treat the ROC for possible water reuse. This research investigated the combined and individual influence of organic and inorganic matter on the fouling of NF and FO membranes. The results revealed that the NF membrane removed most of the organic compounds and some inorganics. The study further highlighted that the FO membrane at NF mode removed the majority of the inorganic compounds and some organics from the ROC. A pretreatment of granulated activated carbon (GAC) adsorption removed 90% of the organic compounds from ROC. In addition, GAC adsorption and acid pretreatment of ROC improved the net water permeate flux by 17% when an FO membrane was used in the NF system. Acid treatment (by bringing the pH down to 5) helped to remove inorganic ions. Therefore, the resultant permeate can be recycled back to the RO water reclamation plant to improve its efficiency.
Jan, MA, Nanda, P, He, X & Liu, RP 2018, 'A Sybil attack detection scheme for a forest wildfire monitoring application', Future Generation Computer Systems, vol. 80, pp. 613-626.
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Wireless Sensor Networks (WSNs) have experienced phenomenal growth over the past decade. They are typically deployed in human-inaccessible terrains to monitor and collect time-critical and delay-sensitive events. There have been several studies on the use of WSN in different applications. All such studies have mainly focused on Quality of Service (QoS) parameters such as delay, loss, jitter, etc. of the sensed data. Security provisioning is also an important and challenging task lacking in all previous studies. In this paper, we propose a Sybil attack detection scheme for a cluster-based hierarchical network mainly deployed to monitor forest wildfire. We propose a two-tier detection scheme. Initially, Sybil nodes and their forged identities are detected by high-energy nodes. However, if one or more identities of a Sybil node sneak through the detection process, they are ultimately detected by the two base stations. After Sybil attack detection, an optimal percentage of cluster heads are elected and each one is informed using nomination packets. Each nomination packet contains the identity of an elected cluster head and an end user’s specific query for data collection within a cluster. These queries are user-centric, on-demand and adaptive to an end user requirement. The undetected identities of Sybil nodes reside in one or more clusters. Their goal is to transmit high false-negative alerts to an end user for diverting attention to those geographical regions which are less vulnerable to a wildfire. Our proposed approach has better network lifetime due to efficient sleep–awake scheduling, higher detection rate and low false-negative rate.
Jan, MA, Tan, Z, He, X & Ni, W 2018, 'Moving towards highly reliable and effective sensor networks', Ad-Hoc and Sensor Wireless Networks, vol. 40, no. 3-4, pp. 163-168.
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Wireless Sensor Networks (WSNs) have been the preferred choice for the
design and deployment of next generation monitoring and control systems
[1]. In these networks, the sensor nodes forward their sensed data towards a
centralized base station. The neighboring nodes frequently sense correlated
data and forward towards the base station, using disjoints multiple paths [2].
As a result, the area around the base station becomes congested with all the
traffic converging towards it. Apart from packet lost due to congestion, a
significant number of packets are lost due to interference, packet collision,
node failure and transmission errors [3]. For a successful monitoring of the
deployed environment, the critical data collected by the sensor nodes need to
be reliably and effectively delivered to the base station. Given the error-prone
nature of the wireless links, ensuring reliable transmission of data from
resource-constrained sensor nodes towards the base station continues to be
one of the major challenges in the field of WSNs [4]. Retransmission and
redundancy are classified as the two main approaches to achieve data transmission reliability in WSNs. However, retransmission and redundancy techniques perform better when using hop-by-hop transmission approach as
compared to end-to-end transmission. Using hop-by-hop approach introduces
in-node processing overhead and incurs high overall latency in reporting data
to the base station. As a result, hybrid approaches need to be adopted to ensure highly reliable and effective data transmission towards the base stations in WSNs.
The specific objective of this special issue is to collect high quality research
articles with solid background in both theoretical and practical aspects of reliability and effectiveness for WSNs. This special issue focuses on various
topics pertaining to reliable and effective communication such as, fault-tolerance, energy-efficiency, topology control, load-balancing, propagation pathloss, co-channe...
Jayamali, KVSD, Nawagamuwa, UP & Indraratna, B 2018, 'Estimation of four-day soaked CBR using index properties', Australian Geomechanics Journal, vol. 53, no. 4, pp. 149-158.
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California Bearing Ratio (CBR) is an important parameter used to evaluate the strength of subgrade and sub-base soils for design of flexible pavements and hence it plays a significant role in road and highway constructions. Obtaining CBR is heavily time consuming and it is difficult to acquire a representative CBR value. Therefore, many correlations have been developed by various researchers worldwide to predict the CBR. Due to differences in soil formations in the tropical environment, these existing global correlations found to be not satisfactory with local soils in Sri Lanka. Hence, this study was carried out to develop empirical correlations between CBR and index properties those best suit for local soils, using the data obtained from Atterberg limits and sieve analysis tests together with compaction tests. The new correlations were established using the method of regression analysis in the form of empirical equations representing the role of index properties. Robust regression by the method of least absolute residuals using MATLAB was considered in the analysis to reduce the impact of outliers along with traditional multiple regression using Microsoft Excel. As a final verification, several laboratory tests were conducted to compare the results with proposed regression equations.
Jayawickrama, BA, He, Y, Dutkiewicz, E & Mueck, MD 2018, 'Scalable Spectrum Access System for Massive Machine Type Communication', IEEE Network, vol. 32, no. 3, pp. 154-160.
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© 1986-2012 IEEE. Future 5G networks aspire to enable new services with vastly different data rate, latency and scalability requirements. The consensus is that these new services will fall into three categories: eMBB, URLLC, and mMTC. Due to unique characteristics of these services and the limited availability of finite spectrum resources, 5G will need to carefully map appropriate bands and spectrum usage models for each service. The SAS is an emerging spectrum sharing model that is gaining momentum in the U.S. SAS presents an opportunity for operators to access the 3.5 GHz military radar band for commercial use. This article discusses the feasibility of the current SAS model in the context of mMTC. We propose a scalable SAS framework that can manage the mMTC uplink interference to the incumbent with less overhead. The simulation setup models the interference levels in New York City and its surrounding counties. The results show that mMTC uplink transmission can be enabled using our framework even on the coast of New York, where mMTC density is high, without causing a harmful level of interference to the incumbent.
Jhang, J-Y, Lin, C-J, Lin, C-T & Young, K-Y 2018, 'Navigation Control of Mobile Robots Using an Interval Type-2 Fuzzy Controller Based on Dynamic-group Particle Swarm Optimization', International Journal of Control, Automation and Systems, vol. 16, no. 5, pp. 2446-2457.
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© 2018, Institute of Control, Robotics and Systems and The Korean Institute of Electrical Engineers and Springer-Verlag GmbH Germany, part of Springer Nature. This paper presents an effective navigation control method for mobile robots in an unknown environment. The proposed behavior manager (BM) switches between two behavioral control patterns, wall-following behavior (WFB) and toward-goal behavior (TGB), based on the relationship between the mobile robot and the unknown environment. An interval type-2 fuzzy neural controller with a dynamic-group particle swarm optimization (DGPSO) algorithm is proposed to provide WFB control and obstacle avoidance for mobile robots. In the WFB learning process, the input signal of a controller is the distance between the wall and the sonar sensors, and its output signal is the speed of two wheels of a mobile robot. A fitness function, which operates on the total distance traveled by the mobile robot, distance from the side wall, angle to the side wall, and moving speed, evaluates the WFB performance of the mobile robot. In addition, an escape mechanism is proposed to avoid a dead cycle. Experimental results reveal that the proposed DGPSO is superior to other methods in WFB and navigation control.
Ji, K, Chen, Z, Sun, R, Ma, K, Yuan, Z & Xu, G 2018, 'GIST: A generative model with individual and subgroup-based topics for group recommendation', Expert Systems with Applications, vol. 94, pp. 81-93.
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© 2017 Elsevier Ltd In this paper, a Topic-based probabilistic model named GIST is proposed to infer group activities, and make group recommendations. Compared with existing individual-based aggregation methods, it not only considers individual members’ interest, but also consider some subgroups’ interest. Intuition might seem that when a group of users want to take part in an activity, not every group member is decisive, instead, more likely the subgroups of members having close relationships lead to the final activity decision. That motivates our study on jointly considering individual members’ choices and subgroups’ choices for group recommendations. Based on this, our model uses two kinds of unshared topics to model individual members’ interest and subgroups’ interest separately, and then make final recommendations according to the choices from the two aspects with a weight-based scheme. Moreover, the link information in the graph topology of the groups can be used to optimize the weights of our model. The experimental results on real-life data show that the recommendation accuracy is significantly improved by GIST comparing with the state-of-the-art methods.
Ji, L-Y, Qin, P-Y & Guo, YJ 2018, 'Wideband Fabry-Perot Cavity Antenna With a Shaped Ground Plane', IEEE Access, vol. 6, pp. 2291-2297.
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© 2013 IEEE. This paper proposes a novel approach to broaden the 3-dB gain bandwidth of Fabry-Perot cavity (FPC) antennas by utilizing a shaped ground plane. The shaped ground plane is flat in the middle to accommodate the source antenna, and then angled up in the shape of trapezoids. Compared with an FPC antenna with a traditional flat ground plane, the 3-dB gain bandwidth of the one with a shaped ground plane is improved from 11% to 20.2% with the maximum realized gain and the 10-dB impedance bandwidth almost unchanged. To validate the feasibility of the proposed approach, an FPC antenna prototype has been designed, fabricated, and measured. It consists of a U-slot rectangular microstrip patch antenna as the source, a Rogers RT6006 superstrate as the partially reflective surface, and the proposed shaped ground plane. Measured results on input reflection coefficients and radiation patterns agree well with simulated ones. Therefore, this new approach can be an effective way to enhance the gain bandwidth without increasing the cavity profile or using multi-layer superstrate structures.
Ji, S, Yu, CP, Fung, S-F, Pan, S & Long, G 2018, 'Supervised Learning for Suicidal Ideation Detection in Online User Content', Complexity, vol. 2018, no. 1, pp. 1-10.
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Early detection and treatment are regarded as the most effective ways to prevent suicidal ideation and potential suicide attempts—two critical risk factors resulting in successful suicides. Online communication channels are becoming a new way for people to express their suicidal tendencies. This paper presents an approach to understand suicidal ideation through online user‐generated content with the goal of early detection via supervised learning. Analysing users’ language preferences and topic descriptions reveals rich knowledge that can be used as an early warning system for detecting suicidal tendencies. Suicidal individuals express strong negative feelings, anxiety, and hopelessness. Suicidal thoughts may involve family and friends. And topics they discuss cover both personal and social issues. To detect suicidal ideation, we extract several informative sets of features, including statistical, syntactic, linguistic, word embedding, and topic features, and we compare six classifiers, including four traditional supervised classifiers and two neural network models. An experimental study demonstrates the feasibility and practicability of the approach and provides benchmarks for the suicidal ideation detection on the active online platforms: Reddit SuicideWatch and Twitter.
Jia, H, Liu, W, Wang, J, Ngo, H-H, Guo, W & Zhang, H 2018, 'Optimization of sensing performance in an integrated dual sensors system combining microbial fuel cells and upflow anaerobic sludge bed reactor', Chemosphere, vol. 210, pp. 931-940.
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Jian, S, Cao, L, Lu, K & Gao, H 2018, 'Unsupervised Coupled Metric Similarity for Non-IID Categorical Data', IEEE Transactions on Knowledge and Data Engineering, vol. 30, no. 9, pp. 1810-1823.
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© 1989-2012 IEEE. Appropriate similarity measures always play a critical role in data analytics, learning, and processing. Measuring the intrinsic similarity of categorical data for unsupervised learning has not been substantially addressed, and even less effort has been made for the similarity analysis of categorical data that is not independent and identically distributed (non-IID). In this work, a Coupled Metric Similarity (CMS) is defined for unsupervised learning which flexibly captures the value-to-attribute-to-object heterogeneous coupling relationships. CMS learns the similarities in terms of intrinsic heterogeneous intra-and inter-attribute couplings and attribute-to-object couplings in categorical data. The CMS validity is guaranteed by satisfying metric properties and conditions, and CMS can flexibly adapt to IID to non-IID data. CMS is incorporated into spectral clustering and k-modes clustering and compared with relevant state-of-the-art similarity measures that are not necessarily metrics. The experimental results and theoretical analysis show the CMS effectiveness of capturing independent and coupled data characteristics, which significantly outperforms other similarity measures on most datasets.
Jiang, J, Wen, S, Yu, S, Xiang, Y & Zhou, W 2018, 'Rumor Source Identification in Social Networks with Time-Varying Topology', IEEE Transactions on Dependable and Secure Computing, vol. 15, no. 1, pp. 166-179.
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© 2004-2012 IEEE. Identifying rumor sources in social networks plays a critical role in limiting the damage caused by them through the timely quarantine of the sources. However, the temporal variation in the topology of social networks and the ongoing dynamic processes challenge our traditional source identification techniques that are considered in static networks. In this paper, we borrow an idea from criminology and propose a novel method to overcome the challenges. First, we reduce the time-varying networks to a series of static networks by introducing a time-integrating window. Second, instead of inspecting every individual in traditional techniques, we adopt a reverse dissemination strategy to specify a set of suspects of the real rumor source. This process addresses the scalability issue of source identification problems, and therefore dramatically promotes the efficiency of rumor source identification. Third, to determine the real source from the suspects, we employ a novel microscopic rumor spreading model to calculate the maximum likelihood (ML) for each suspect. The one who can provide the largest ML estimate is considered as the real source. The evaluations are carried out on real social networks with time-varying topology. The experiment results show that our method can reduce 60 - 90 percent of the source seeking area in various time-varying social networks. The results further indicate that our method can accurately identify the real source, or an individual who is very close to the real source. To the best of our knowledge, the proposed method is the first that can be used to identify rumor sources in time-varying social networks.
Jiang, Q, Ngo, HH, Nghiem, LD, Hai, FI, Price, WE, Zhang, J, Liang, S, Deng, L & Guo, W 2018, 'Effect of hydraulic retention time on the performance of a hybrid moving bed biofilm reactor-membrane bioreactor system for micropollutants removal from municipal wastewater', Bioresource Technology, vol. 247, pp. 1228-1232.
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© 2017 Elsevier Ltd This study evaluated micropollutants removal and membrane fouling behaviour of a hybrid moving bed biofilm reactor-membrane bioreactor (MBBR-MBR) system at four different hydraulic retention times (HRTs) (24, 18, 12 and 6 h). The results revealed that HRT of 18 h was the optimal condition regarding the removal of most selected micropollutants. As the primary removal mechanism in the hybrid system was biodegradation, the attached growth pattern was desirable for enriching slow growing bacteria and developing a diversity of biocoenosis. Thus, the efficient removal of micropollutants was obtained. In terms of membrane fouling propensity analysis, a longer HRT (e.g. HRTs of 24 and 18 h) could significantly mitigate membrane fouling when compared with the shortest HRT of 6 h. Hence, enhanced system performance could be achieved when the MBBR-MBR system was operated at HRT of 18 h.
Jing, D, Huang, Y, Liu, X, Sia, KCS, Zhang, JC, Tai, X, Wang, M, Toscan, CE, McCalmont, H, Evans, K, Mayoh, C, Poulos, RC, Span, M, Mi, J, Zhang, C, Wong, JWH, Beck, D, Pimanda, JE & Lock, RB 2018, 'Lymphocyte-Specific Chromatin Accessibility Pre-determines Glucocorticoid Resistance in Acute Lymphoblastic Leukemia', Cancer Cell, vol. 34, no. 6, pp. 906-921.e8.
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© 2018 Elsevier Inc. Glucocorticoids play a critical role in the treatment of lymphoid malignancies. While glucocorticoid efficacy can be largely attributed to lymphocyte-specific apoptosis, its molecular basis remains elusive. Here, we studied genome-wide lymphocyte-specific open chromatin domains (LSOs), and integrated LSOs with glucocorticoid-induced RNA transcription and chromatin modulation using an in vivo patient-derived xenograft model of acute lymphoblastic leukemia (ALL). This led to the identification of LSOs critical for glucocorticoid-induced apoptosis. Glucocorticoid receptor cooperated with CTCF at these LSOs to mediate DNA looping, which was inhibited by increased DNA methylation in glucocorticoid-resistant ALL and non-lymphoid cell types. Our study demonstrates that lymphocyte-specific epigenetic modifications pre-determine glucocorticoid resistance in ALL and may account for the lack of glucocorticoid sensitivity in other cell types. Jing et al. identified lymphocyte-specific open chromatin domains (LSOs) critical for glucocorticoid (GC)-induced acute lymphoblastic leukemia (ALL) apoptosis. GC receptor cooperated with CTCF at these LSOs to mediate DNA looping, which was inhibited by DNA methylation in GC-resistant ALL and non-lymphoid cell types.
Jing, N, Jiang, T, Du, J & Sugumaran, V 2018, 'Personalized recommendation based on customer preference mining and sentiment assessment from a Chinese e-commerce website', Electronic Commerce Research, vol. 18, no. 1, pp. 159-179.
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Jonasson, OJ & Kandasamy, J 2018, 'Decentralised water reuse in Sydney, Australia: drivers for implementation and energy consumption', Journal of Environmental Engineering and Science, vol. 13, no. 1, pp. 2-7.
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Water recycling and reuse is becoming increasingly common throughout the world. The objective of this study was to compare five decentralised water recycling and reuse systems in Sydney, Australia, in terms of the drivers for their implementation and their ongoing energy consumption, allowing comparison to conventional water sources. The security of supply was found to be the main driver for four out of the five schemes. For the fifth scheme, the driver was to obtain a high environmental rating for the building it is located in. The analysis shows that water reuse can provide water at the same or less energy consumption compared to water supplied through the mains network. However, where the water recycling ethos of ‘fit for purpose’ is not considered, this can often lead to a significant overall increase in power consumption. This study highlights the need for regulatory bodies to consider a wider range of impacts when preparing guidelines and incentive schemes for water reuse. When the focus is too narrow, there is a risk that unintentional negative impacts such as increased power consumption and potential carbon dioxide emissions are the outcomes.
Jordaan, J, Punzet, S, Melnikov, A, Sanches, A, Oberst, S, Marburg, S & Powell, DA 2018, 'Measuring monopole and dipole polarizability of acoustic meta-atoms', Applied Physics Letters, vol. 113, no. 22, pp. 224102-224102.
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We present a method to extract monopole and dipole polarizability from experimental measurements of two-dimensional acoustic meta-atoms. In contrast to extraction from numerical results, this enables all second-order effects and uncertainties in material properties to be accounted for. We apply the technique to 3D-printed labyrinthine meta-atoms of a variety of geometries. We show that the polarizability of structures with a shorter acoustic path length agrees well with numerical results. However, those with longer path lengths suffer strong additional damping, which we attribute to the strong viscous and thermal losses in narrow channels.
Jordan, R, Gray, S, Zellner, M, Glynn, PD, Voinov, A, Hedelin, B, Sterling, EJ, Leong, K, Olabisi, LS, Hubacek, K, Bommel, P, BenDor, TK, Jetter, AJ, Laursen, B, Singer, A, Giabbanelli, PJ, Kolagani, N, Carrera, LB, Jenni, K & Prell, C 2018, 'Twelve Questions for the Participatory Modeling Community', Earth's Future, vol. 6, no. 8, pp. 1046-1057.
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AbstractParticipatory modeling engages the implicit and explicit knowledge of stakeholders to create formalized and shared representations of reality and has evolved into a field of study as well as a practice. Participatory modeling researchers and practitioners who focus specifically on environmental resources met at the National Socio‐Environmental Synthesis Center (SESYNC) in Annapolis, Maryland, over the course of 2 years to discuss the state of the field and future directions for participatory modeling. What follows is a description of 12 overarching groups of questions that could guide future inquiry.
Ju, M, Ding, C, Zhang, D & Guo, YJ 2018, 'Gamma-Correction-Based Visibility Restoration for Single Hazy Images', IEEE Signal Processing Letters, vol. 25, no. 7, pp. 1084-1088.
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© 1994-2012 IEEE. In this letter, a concise gamma-correction-based dehazing model (GDM) is proposed. This GDM explicitly describes the inner relationship between the gamma correction (GC) and the traditional scattering model. Combined with the existing priori constraints, GDM is further approximated into a one-dimensional (1-D) function to seek the only unknown constant that is used for haze removal. Using the determined constant, the scene albedo can be recovered, eliminating the haze from single hazy images. The proposed GDM is able to suppress the halo/blocking artifacts in the recovered results due to the scene albedo, which is less sensitive to the determined constant. Simulation results on different types of benchmark images verify that the proposed technique outperforms state-of-the-art methods in terms of both recovery, quality, and real-time performance.
Jumaah, HJ, Mansor, S, Pradhan, B & Adam, SN 2018, 'UAV-based PM2.5 monitoring for small-scale urban areas', International Journal of Geoinformatics, vol. 14, no. 4, pp. 61-69.
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Air quality data such as Particulate Matter PM2.5 collection near the ground is difficult, particularly in small complex regions. This study aims to introduce a PM2.5 prediction algorithm based on measurements from Unmanned Arial Vehicle (UAV)-based sensing system and validate the model at a specified low altitude. Observations were applied around 1.6 km2 area in University Putra Malaysia. This study uses an empirical method via applying amassed records of PM2.5 and meteorological parameters to produce a predictive Geographically Weighted Regression (GWR) model. An accuracy value is computed from the probability value given by the regression analysis model. To validate this approach, we have utilized training and testing data. To evaluate and validate the suggested model, we applied the model to the training set. The obtained result indicated that there is a good statistical correlation, and demonstrated that the characteristics obtained by analysis are able to predict the concentration of PM2.5.
Jupp, JR, Rivest, L, Forgues, D & Boton, C 2018, 'Comparison of shipbuilding and construction industries from the product structure standpoint', International Journal of Product Lifecycle Management, vol. 11, no. 3, pp. 191-191.
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Kaiwartya, O, Abdullah, AH, Cao, Y, Lloret, J, Kumar, S, Shah, RR, Prasad, M & Prakash, S 2018, 'Virtualization in Wireless Sensor Networks: Fault Tolerant Embedding for Internet of Things', IEEE Internet of Things Journal, vol. 5, no. 2, pp. 571-580.
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© 2017 IEEE. Recently, virtualization in wireless sensor networks (WSNs) has witnessed significant attention due to the growing service domain for Internet of Things (IoT). Related literature on virtualization in WSNs explored resource optimization without considering communication failure in WSNs environments. The failure of a communication link in WSNs impacts many virtual networks running IoT services. In this context, this paper proposes a framework for optimizing fault tolerance (FT) in virtualization in WSNs, focusing on heterogeneous networks for service-oriented IoT applications. An optimization problem is formulated considering FT and communication delay as two conflicting objectives. An adapted nondominated sorting-based genetic algorithm (A-NSGA) is developed to solve the optimization problem. The major components of A-NSGA include chromosome representation, FT and delay computation, crossover and mutation, and nondominance-based sorting. Analytical and simulation-based comparative performance evaluation has been carried out. From the analysis of results, it is evident that the framework effectively optimizes FT for virtualization in WSNs.
Kalantar, B, Pradhan, B, Naghibi, SA, Motevalli, A & Mansor, S 2018, 'Assessment of the effects of training data selection on the landslide susceptibility mapping: a comparison between support vector machine (SVM), logistic regression (LR) and artificial neural networks (ANN)', Geomatics, Natural Hazards and Risk, vol. 9, no. 1, pp. 49-69.
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© 2017 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. All rights reserved. Landslide is a natural hazard that results in many economic damages and human losses every year. Numerous researchers have studied landslide susceptibility mapping (LSM), each attempting to improve the accuracy of the final outputs. However, few studies have been published on the training data selection effects on the LSM. Thus, this study assesses the training landslides random selection effects on support vector machine (SVM) accuracy, logistic regression (LR) and artificial neural networks (ANN) models for LSM in a catchment at the Dodangeh watershed, Mazandaran province, Iran. A 160 landslide locations inventory was collected by Geological Survey of Iran for this investigation. Different methods were implemented to define the landslide locations, such as inventory reports, satellite images and field survey. Moreover, 14 landslide conditioning factors were considered in the analysis of landslide susceptibility. These factors include curvature, plan curvature, profile curvature, altitude, slope angle, slope aspect, distance to faults, distance to stream, topographic wetness index, stream power index, terrain roughness index, sediment transport index, lithology and land use. The results show that the random landslide training data selection affected the parameter estimations of the SVM, LR and ANN algorithms. The results also show that the training samples selection had an effect on the accuracy of the susceptibility model because landslide conditioning factors vary according to the geographic locations in the study area. The LR model was found to be less sensitive than the SVM and ANN models to the training samples selection. Validation results showed that SVM and LR models outperformed the ANN model for all scenarios. The average overall accuracy of LR, SVM and ANN models are 81.42%, 79.82% and 70.2%, respectively.
Kalaruban, M, Loganathan, P, Kandasamy, J & Vigneswaran, S 2018, 'Submerged membrane adsorption hybrid system using four adsorbents to remove nitrate from water', Environmental Science and Pollution Research, vol. 25, no. 21, pp. 20328-20335.
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© 2017, Springer-Verlag Berlin Heidelberg. Nitrate contamination of ground and surface waters causes environmental pollution and human health problems in many parts of the world. This study tests the nitrate removal efficiencies of two ion exchange resins (Dowex 21K XLT and iron-modified Dowex 21K XLT (Dowex-Fe)) and two chemically modified bio-adsorbents (amine-grafted corn cob (AG corn cob) and amine-grafted coconut copra (AG coconut copra)) using a dynamic adsorption treatment system. A submerged membrane (microfiltration) adsorption hybrid system (SMAHS) was used for the continuous removal of nitrate with a minimal amount of adsorbents. The efficiency of membrane filtration flux and replacement rate of adsorbent were studied to determine suitable operating conditions to maintain the effluent nitrate concentration below the WHO drinking standard limit of 11.3 mg N/L. The volume of water treated and the amount of nitrate adsorbed per gramme of adsorbent for all four flux tested were in the order Dowex-Fe > Dowex > AG coconut copra > AG corn cob. The volumes of water treated (L/g adsorbent) were 0.91 and 1.85, and the amount of nitrate removed (mg N/g adsorbent) were 9.8 and 22.2 for AG corn cob and Dowex-Fe, respectively, at a flux of 15 L/(m2/h).
Kalaruban, M, Loganathan, P, Shim, W, Kandasamy, J & Vigneswaran, S 2018, 'Mathematical Modelling of Nitrate Removal from Water Using a Submerged Membrane Adsorption Hybrid System with Four Adsorbents', Applied Sciences, vol. 8, no. 2, pp. 194-194.
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Excessive concentrations of nitrate in ground water are known to cause human health hazards. A submerged membrane adsorption hybrid system that includes a microfilter membrane and four different adsorbents (Dowex 21K XLT ion exchange resin (Dowex), Fe-coated Dowex, amine-grafted (AG) corn cob and AG coconut copra) operated at four different fluxes was used to continuously remove nitrate. The experimental data obtained in this study was simulated mathematically with a homogeneous surface diffusion model that incorporated membrane packing density and membrane correlation coefficient, and applied the concept of continuous flow stirred tank reactor. The model fit with experimental data was good. The surface diffusion coefficient was constant for all adsorbents and for all fluxes. The mass transfer coefficient increased with flux for all adsorbents and generally increased with the adsorption capacity of the adsorbents.
Kalhori, H, Alamdari, MM & Ye, L 2018, 'Automated algorithm for impact force identification using cosine similarity searching', Measurement, vol. 122, pp. 648-657.
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Kalhori, H, Makki Alamdari, M, Zhu, X & Samali, B 2018, 'Nothing-on-Road Axle Detection Strategies in Bridge-Weigh-in-Motion for a Cable-Stayed Bridge: Case Study', Journal of Bridge Engineering, vol. 23, no. 8, pp. 05018006-05018006.
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© 2018 American Society of Civil Engineers. This case-study article aims to share the field-test observations of a real-world cable-stayed bridge with the research community of bridge-weigh-in-motion to address the challenges of axle identification. Various structural members of the bridge, including cables, girders, and the deck, were instrumented with strain gauges at different locations to measure the axial, bending, or shear strain responses. Numerous field tests were conducted by running light and heavy vehicles traveling at different speeds, in different traffic directions, and in different lateral locations on the bridge. Because the identification of closely spaced axles is important to ensuring true classification of the vehicles, vehicles with tandem- and tridem-axle configurations were adopted in the field test. The study aimed to identify the sensor arrangement through which the closely spaced axles can be reliably detected regardless of the speed, traveling direction, and lateral location of the vehicle on the bridge. It was found that the axial strains on the cables and bending strains in the girders provided the global response of the structure; hence, they were unable to identify the closely spaced axles. In contrast, it was observed that the longitudinal strains under the deck were able to identify the closely spaced axles, provided they were positioned as closely as possible to the wheel path. Finally, the shear responses at the end of the span were able to identify the closely spaced axles irrespective of the traveling direction and lateral location of the vehicle. In this study, due to the testing limitations, including the short span of the bridge and the presence of a roundabout at one end of the bridge, it was not feasible to maintain a constant speed; therefore, identification of axle weight and axle spacing, which requires a constant-speed assumption, is not discussed.
Kamal, MS, Trivdedi, MC, Alam, JB, Dey, N, Ashour, AS, Shi, F & Tavares, JMRS 2018, 'Big DNA datasets analysis under push down automata', Journal of Intelligent & Fuzzy Systems, vol. 35, no. 2, pp. 1555-1565.
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Kamal, S, Dey, N, Nimmy, SF, Ripon, SH, Ali, NY, Ashour, AS, Karaa, WBA, Nguyen, GN & Shi, F 2018, 'Evolutionary framework for coding area selection from cancer data', Neural Computing and Applications, vol. 29, no. 4, pp. 1015-1037.
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Kamyabniya, A, Lotfi, MM, Naderpour, M & Yih, Y 2018, 'Robust Platelet Logistics Planning in Disaster Relief Operations Under Uncertainty: a Coordinated Approach', Information Systems Frontiers, vol. 20, no. 4, pp. 759-782.
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© 2017, Springer Science+Business Media, LLC. Resource sharing, as a coordination mechanism, can mitigate disruptions in supply and changes in demand. It is particularly crucial for platelets because they have a short lifespan and need to be transferred and allocated within a limited time to prevent waste or shortages. Thus, a coordinated model comprised of a mixed vertical-horizontal structure, for the logistics of platelets, is proposed for disaster relief operations in the response phase. The aim of this research is to reduce the wastage and shortage of platelets due to their critical role in wound healing. We present a bi-objective location-allocation robust possibilistic programming model for designing a two-layer coordinated organization strategy for multi-type blood-derived platelets under demand uncertainty. Computational results, derived using a heuristic ε-constraint algorithm, are reported and discussed to show the applicability of the proposed model. The experimental results indicate that surpluses and shortages in platelets remarkably declined following instigation of a coordinated disaster relief operation.
Kang, G, Li, J & Tao, D 2018, 'Shakeout: A New Approach to Regularized Deep Neural Network Training', IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 40, no. 5, pp. 1245-1258.
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© 1979-2012 IEEE. Recent years have witnessed the success of deep neural networks in dealing with a plenty of practical problems. Dropout has played an essential role in many successful deep neural networks, by inducing regularization in the model training. In this paper, we present a new regularized training approach: Shakeout. Instead of randomly discarding units as Dropout does at the training stage, Shakeout randomly chooses to enhance or reverse each unit's contribution to the next layer. This minor modification of Dropout has the statistical trait: the regularizer induced by Shakeout adaptively combines L-{0} , L-{1} and L-{2} regularization terms. Our classification experiments with representative deep architectures on image datasets MNIST, CIFAR-10 and ImageNet show that Shakeout deals with over-fitting effectively and outperforms Dropout. We empirically demonstrate that Shakeout leads to sparser weights under both unsupervised and supervised settings. Shakeout also leads to the grouping effect of the input units in a layer. Considering the weights in reflecting the importance of connections, Shakeout is superior to Dropout, which is valuable for the deep model compression. Moreover, we demonstrate that Shakeout can effectively reduce the instability of the training process of the deep architecture.
Kang, Y, Zhang, J, Li, B, Zhang, Y, Sun, H, Hao Ngo, H, Guo, W, Xie, H, Hu, Z & Zhao, C 2018, 'Improvement of bioavailable carbon source and microbial structure toward enhanced nitrate removal by Tubifex tubifex', Chemical Engineering Journal, vol. 353, pp. 699-707.
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Kani, K, Malgras, V, Jiang, B, Hossain, MSA, Alshehri, SM, Ahamad, T, Salunkhe, RR, Huang, Z & Yamauchi, Y 2018, 'Periodically Arranged Arrays of Dendritic Pt Nanospheres Using Cage‐Type Mesoporous Silica as a Hard Template', Chemistry – An Asian Journal, vol. 13, no. 1, pp. 106-110.
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AbstractDendritic Pt nanospheres of 20 nm diameter are synthesized by using a highly concentrated surfactant assembly within the large‐sized cage‐type mesopores of mesoporous silica (LP‐FDU‐12). After diluting the surfactant solution with ethanol, the lower viscosity leads to an improved penetration inside the mesopores. After Pt deposition followed by template removal, the arrangement of the Pt nanospheres is a replication from that of the mesopores in the original LP‐FDU‐12 template. Although it is well known that ordered LLCs can form on flat substrates, the confined space inside the mesopores hinders surfactant self‐organization. Therefore, the Pt nanospheres possess a dendritic porous structure over the entire area. The distortion observed in some nanospheres is attributed to the close proximity existing between neighboring cage‐type mesopores. This new type of nanoporous metal with a hierarchical architecture holds potential to enhance substance diffusivity/accessibility for further improvement of catalytic activity.
Kapeleris, J, Kulasinghe, A, Warkiani, ME, Vela, I, Kenny, L, O'Byrne, K & Punyadeera, C 2018, 'The Prognostic Role of Circulating Tumor Cells (CTCs) in Lung Cancer', Frontiers in Oncology, vol. 8, no. AUG.
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© 2018 Kapeleris, Kulasinghe, Warkiani, Vela, Kenny, O'Byrne and Punyadeera. Lung cancer affects over 1. 8 million people worldwide and is the leading cause of cancer related mortality globally. Currently, diagnosis of lung cancer involves a combination of imaging and invasive biopsies to confirm histopathology. Non-invasive diagnostic techniques under investigation include 'liquid biopsies' through a simple blood draw to develop predictive and prognostic biomarkers. A better understanding of circulating tumor cell (CTC) dissemination mechanisms offers promising potential for the development of techniques to assist in the diagnosis of lung cancer. Enumeration and characterization of CTCs has the potential to act as a prognostic biomarker and to identify novel drug targets for a precision medicine approach to lung cancer care. This review will focus on the current status of CTCs and their potential diagnostic and prognostic utility in this setting.
Karamanakos, P, Geyer, T & Aguilera, RP 2018, 'Long-Horizon Direct Model Predictive Control: Modified Sphere Decoding for Transient Operation', IEEE Transactions on Industry Applications, vol. 54, no. 6, pp. 6060-6070.
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© 1972-2012 IEEE. In this paper, we present modifications to the sphere decoder initially introduced in the work of Geyer and Quevedo and modified in the work of Karamanakos et al. that significantly reduce the computation times during transients. The relative position of the unconstrained solution of the integer quadratic program underlying model predictive control (MPC) with respect to the convex hull of the (truncated) lattice of integer points is examined. If it is found that the unconstrained solution does not lie within the convex hull - a phenomenon that is observed mostly during transients - then a projection is performed onto the convex hull. By doing so, a new sphere that guarantees feasibility and includes a significant smaller number of candidate solutions is computed. This reduces the computation time by up to three orders of magnitude when solving the optimization problem at hand. Nonetheless, the reduction of the computational burden comes at a cost of (mild) suboptimal results. The effectiveness of the proposed algorithm is tested with a variable speed drive system consisting of a three-level neutral point clamped voltage source inverter and a medium-voltage induction machine. Based on the presented results, the sphere decoding algorithm with the proposed refinements maintains the very fast transient responses inherent to direct MPC. Moreover, it is observed that the occasional implementation of suboptimal solutions does not lead to a deterioration of the system performance.
Karimi, F & Matous, P 2018, 'Mapping diversity and inclusion in student societies: A social network perspective', Computers in Human Behavior, vol. 88, pp. 184-194.
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Karmokar, DK, Guo, YJ, Qin, P-Y, Chen, S-L & Bird, TS 2018, 'Substrate Integrated Waveguide-Based Periodic Backward-to-Forward Scanning Leaky-Wave Antenna With Low Cross-Polarization', IEEE Transactions on Antennas and Propagation, vol. 66, no. 8, pp. 3846-3856.
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© 1963-2012 IEEE. For many leaky-wave antennas (LWAs), it is challenging to realize beam scanning through broadside. A problem is the presence of an open stopband (OSB), which restricts radiation in the broadside direction. In this paper, a novel substrate integrated waveguide (SIW)-based LWA is described to overcome the OSB problem and provide beam scanning continuously from the backward to the forward direction from a conventional periodic LWA. It is demonstrated that the n =-1 spatial harmonic can be excited efficiently from an SIW LWA and enables broadside radiation. However, it was found in our initial design that when the beam scans through the broadside, the cross-polarization level increases significantly compared to the beam close to the backfire direction. A technique is developed to reduce the cross-polarization level. As a result, a new antenna configuration is created. The antenna design has been realized and measured to validate the concept. The measured beam scanning range of the prototype is from -74° to +45° (119° of beam scanning) when the frequency sweeps from 7.625 to 11 GHz, and the measured cross-polarization level is 20.8 dB low at the main beam direction for the broadside beam.
Kashif, M, Hossain, MJ, Zhuo, F & Gautam, S 2018, 'Design and implementation of a three-level active power filter for harmonic and reactive power compensation', Electric Power Systems Research, vol. 165, pp. 144-156.
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Katalo, R, Okuda, T, Nghiem, LD & Fujioka, T 2018, 'Moringa oleifera coagulation as pretreatment prior to microfiltration for membrane fouling mitigation', Environmental Science: Water Research & Technology, vol. 4, no. 10, pp. 1604-1611.
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Coagulation pretreatment using Moringa oleifera in the microfiltration of river water achieved membrane fouling mitigation and filtered water quality improvement.
Ke, G, Li, W, Li, R, Li, Y & Wang, G 2018, 'Mitigation Effect of Waste Glass Powders on Alkali–Silica Reaction (ASR) Expansion in Cementitious Composite', International Journal of Concrete Structures and Materials, vol. 12, no. 1.
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© 2018, The Author(s). The effects of different contents and particle sizes of waste glass powder on alkali–silica reaction (ASR) expansion of cementitious composite bar were investigated in this study. Waste glass powder with particle size less than 300 μm exhibits an excellent mitigation effect on ASR expansion. With larger content and smaller particle size, the mitigation effect of waste glass powder on ASR expansion gradually increases. The mitigation effect of waste glass powder with particle size ranging from 38 to 53 μm and 20% by weight of cement seems relatively better than that of fly ash. When the waste glass powder content reaches 30%, the mitigation effect is still effective and almost the same as that of fly ash. However, the waste glass powder with particle size larger than 300 μm presents negative mitigation effect on ASR expansion when the replacement rate is larger than 30%. On the other hand, the waste glass powder and calcium hydroxide (CH) further react, and produce more calcium–silicate–hydrate gels, which apparently reduce the amount of CH. Moreover, the increasing content of waste glass powder results in a lower pH value in the pore solution of cementitious composite.
Keesstra, S, Nunes, JP, Saco, P, Parsons, T, Poeppl, R, Masselink, R & Cerdà, A 2018, 'The way forward: Can connectivity be useful to design better measuring and modelling schemes for water and sediment dynamics?', Science of The Total Environment, vol. 644, pp. 1557-1572.
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Kendrick, L, Musial, K & Gabrys, B 2018, 'Change point detection in social networks—Critical review with experiments', Computer Science Review, vol. 29, pp. 1-13.
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© 2018 Elsevier Inc. Change point detection in social networks is an important element in developing the understanding of dynamic systems. This complex and growing area of research has no clear guidelines on what methods to use or in which circumstances. This paper critically discusses several possible network metrics to be used for a change point detection problem and conducts an experimental, comparative analysis using the Enron and MIT networks. Bayesian change point detection analysis is conducted on different global graph metrics (Size, Density, Average Clustering Coefficient, Average Shortest Path) as well as metrics derived from the Hierarchical and Block models (Entropy, Edge Probability, No. of Communities, Hierarchy Level Membership). The results produced the posterior probability of a change point at weekly time intervals that were analysed against ground truth change points using precision and recall measures. Results suggest that computationally heavy generative models offer only slightly better results compared to some of the global graph metrics. The simplest metrics used in the experiments, i.e. nodes and links numbers, are the recommended choice for detecting overall structural changes.
Kennedy, P, Wagner, M, Castéra, L, Hong, CW, Johnson, CL, Sirlin, CB & Taouli, B 2018, 'Quantitative Elastography Methods in Liver Disease: Current Evidence and Future Directions', Radiology, vol. 286, no. 3, pp. 738-763.
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Keshavarzi, A, Shrestha, CK, Melville, B, Khabbaz, H, Ranjbar-Zahedani, M & Ball, J 2018, 'Estimation of maximum scour depths at upstream of front and rear piers for two in-line circular columns', Environmental Fluid Mechanics, vol. 18, no. 2, pp. 537-550.
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© 2018, Springer Science+Business Media B.V., part of Springer Nature. Previous investigations indicate that scour around bridge piers is one of the most important factors for the failure of waterway bridges. Hence, it is essential to determine the accurate scour depth around the bridge piers. Most of the previous studies were based on scour around a single pier; however, in practice, new bridges are usually wide and then piers comprise two circular piers aligned in the flow direction that together support the loading of the structure. In this study, the effect on maximum scour depth of the spacing between two piers aligned in the flow direction was investigated experimentally under clear water scour conditions. The results show that the maximum scour depth at upstream of the front pier occurs when the spacing between the two piers is 2.5 times the diameter of the pier. Two semi empirical equations have been developed to predict the maximum scour depth at upstream of both front and rear piers as a function of the spacing between the piers, in terms of a pier-spacing factor. If the new equations for the pier-spacing factor are used with some of the existing equations for scour at a single pier, the predicted scouring depths are in good agreement with observed results. The S/M equation exhibited the best performance among the various equations tested and was recommended for use in prediction of the equilibrium scour depth. The findings of this study can be used to facilitate the positioning of piers when scouring is a design concern.
Keshavarzi, A, Shrestha, CK, Zahedani, MR, Ball, J & Khabbaz, H 2018, 'Experimental study of flow structure around two in-line bridge piers', Proceedings of the Institution of Civil Engineers - Water Management, vol. 171, no. 6, pp. 311-327.
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Previous investigations indicate that local scouring is one of the most common causes of waterway bridge failure. The scour mechanism around bridge piers is complicated by the interaction of flow and structure. To explore the local scouring process, it is therefore essential to study the flow–structure interaction around bridge piers. Most previous studies have been based on this interaction around a single pier; however, in practice, many bridges are wide and comprise a number of piers aligned in the flow direction that together support the loading. In this study, a particle image velocimetry technique was used to investigate two-dimensional flow–structure interaction around two in-line bridge piers with different spacings. Various influencing flow characteristics including turbulence intensity, turbulent kinetic energy and Reynolds stresses were calculated in different vertical planes around the bridge piers. Results indicated that the flow characteristics around two in-line bridge piers are very different than for a single pier and the spacing between two in-line piers significantly influences the flow characteristics, particularly in the rear of the piers. Furthermore, for spacing in the range of 2 ≤ L/D ≤ 3, stronger turbulence structures occurred behind pier 1 and, as a result, a higher scour depth can be expected around pier 1.
Khalid, M, Aguilera, RP, Savkin, AV & Agelidis, VG 2018, 'A market‐oriented wind power dispatch strategy using adaptive price thresholds and battery energy storage', Wind Energy, vol. 21, no. 4, pp. 242-254.
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AbstractIn this paper, an adaptive dispatch strategy is presented to maximize the revenue for grid‐tied wind power plant coupled with a battery energy storage system (BESS). The proposed idea is mainly based on time‐varying market‐price thresholds, which are varied according to the proposed algorithm in an adaptive manner. The variable nature of wind power and market price signals leads to the idea of storing energy at low price periods and consequently selling it at high prices. In fact, the wind farm operators can take advantage of the price variability to earn additional income and to maximize the operational profit based on the choice of best price thresholds at each instant of time. This research study proposes an efficient strategy for intermittent power dispatch along with the optimal operation of a BESS in the presence of physical limits and constraints. The strategy is tested and validated with different BESSs, and the percentage improvement of income is calculated. The simulation results, based on actual wind farm and market‐price data, depict the proficiency of the proposed methodology over standard linear programming methods.
Khalid, M, Aguilera, RP, Savkin, AV & Agelidis, VG 2018, 'On maximizing profit of wind-battery supported power station based on wind power and energy price forecasting', Applied Energy, vol. 211, pp. 764-773.
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© 2017 Elsevier Ltd This paper proposes a framework to develop an optimal power dispatch strategy for grid-connected wind power plants containing a Battery Energy Storage System (BESS). Considering the intermittent nature of wind power and rapidly varying electricity market price, short-term forecasting of these variables is used for efficient energy management. The predicted variability trends in market price assist in earning additional income which subsequently increase the operational profit. Then on the basis of income improvement, optimal capacity of the BESS can be determined. The proposed framework utilizes Dynamic Programming tool which can incorporate the predictions of both wind power and market price simultaneously as inputs in a receding horizon approach. The proposed strategy is validated using real electricity market price and wind power data in different scenarios of BESS power and capacity. The obtained results depict the effectiveness of the strategy to help power system operators in ensuring economically optimal energy dispatch. Moreover, the results can aid power system planners in the selection of optimal BESS capacity for given power ratings in order to maximize their operational profits.
Khalid, M, AlMuhaini, M, Aguilera, RP & Savkin, AV 2018, 'Method for planning a wind–solar–battery hybrid power plant with optimal generation‐demand matching', IET Renewable Power Generation, vol. 12, no. 15, pp. 1800-1806.
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© 2018 The Institution of Engineering and Technology. This study aims to propose a methodology for a hybrid wind-solar power plant with the optimal contribution of renewable energy resources supported by battery energy storage technology. The motivating factor behind the hybrid solar-wind power system design is the fact that both solar and wind power exhibit complementary power profiles. Advantageous combination of wind and solar with optimal ratio will lead to clear benefits for hybrid wind-solar power plants such as smoothing of intermittent power, higher reliability, and availability. However, the potential challenges for its integration into electricity grids cannot be neglected. A potential solution is to utilise one of the energy storage technologies, though all of them are still very expensive for such applications, especially at large scale. Therefore, optimal capacity calculations for energy storage system are also vital to realise full benefits. Currently, battery energy storage technology is considered as one of the most promising choices for renewable power applications. This research targets at battery storage technology and proposes a generic methodology for optimal capacity calculations for the proposed hybrid wind-solar power system.
Khan, AA, Abolhasan, M & Ni, W 2018, 'An Evolutionary Game Theoretic Approach for Stable and Optimized Clustering in VANETs', IEEE Transactions on Vehicular Technology, vol. 67, no. 5, pp. 4501-4513.
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© 1967-2012 IEEE. Discovering and maintaining efficient routes for data dissemination in vehicular ad hoc networks (VANETs) has proven to be a very challenging problem. Clustering is one of the control protocols used to provide efficient and stable routes for data dissemination. However, the rapid changes in network topology in VANETs creates frequent cluster reformation, which can seriously affect route stability. We propose a novel evolutionary game theoretic (EGT) framework to automate the clustering of nodes and nominations of cluster heads, to achieve cluster stability in VANETs. The equilibrium point is proven analytically and the stability is also tested using Lyapunov function. The performance of the proposed evolutionary game is empirically investigated with different cost functions using static and mobile scenarios. The simulation results demonstrate the effectiveness and robustness of our proposed EGT approach for different populations and speeds, thus reducing the overhead of frequent cluster reformation in VANETs.
Khan, H, Razmjou, A, Ebrahimi Warkiani, M, Kottapalli, A & Asadnia, M 2018, 'Sensitive and Flexible Polymeric Strain Sensor for Accurate Human Motion Monitoring', Sensors, vol. 18, no. 2, pp. 418-418.
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Flexible electronic devices offer the capability to integrate and adapt with human body. These devices are mountable on surfaces with various shapes, which allow us to attach them to clothes or directly onto the body. This paper suggests a facile fabrication strategy via electrospinning to develop a stretchable, and sensitive poly (vinylidene fluoride) nanofibrous strain sensor for human motion monitoring. A complete characterization on the single PVDF nano fiber has been performed. The charge generated by PVDF electrospun strain sensor changes was employed as a parameter to control the finger motion of the robotic arm. As a proof of concept, we developed a smart glove with five sensors integrated into it to detect the fingers motion and transfer it to a robotic hand. Our results shows that the proposed strain sensors are able to detect tiny motion of fingers and successfully run the robotic hand.
Khan, HA, Khan, MSH, Castel, A & Sunarho, J 2018, 'Deterioration of alkali-activated mortars exposed to natural aggressive sewer environment', Construction and Building Materials, vol. 186, pp. 577-597.
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Khan, MA, Ngo, HH, Guo, W, Liu, Y, Chang, SW, Nguyen, DD, Nghiem, LD & Liang, H 2018, 'Can membrane bioreactor be a smart option for water treatment?', Bioresource Technology Reports, vol. 4, pp. 80-87.
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The gradual increase of organic and inorganic micropollutants in natural and drinking watercourses has posed a greater challenge for current water treatment technologies. Currently established water treatment processes such as activated sludge, microfiltration, reverse osmosis, adsorption, carbon nanotube etc. have a limited range of application, low energy recovery, and cost-intensive operation. Membrane bioreactor has already been utilized as a useful option to remove soluble organics, nutrients, and micropollutants from wastewater. Although currently established Membrane Bioreactors have few limitations, recent developments on this technology have improved its energy efficiency and reduced the operating and maintenance cost. Implementing these research findings in full-scale operation can make this process a favorable option in industrial wastewater treatment.
Khan, MA, Ngo, HH, Guo, W, Liu, Y, Zhang, X, Guo, J, Chang, SW, Nguyen, DD & Wang, J 2018, 'Biohydrogen production from anaerobic digestion and its potential as renewable energy', Renewable Energy, vol. 129, pp. 754-768.
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© 2017. The current demand-supply scenario for fossil fuels requires an alternative energy source with cleaner combustion products whilst production of hydrogen from anaerobic digestion involves the utilization of waste materials and zero emission of greenhouse gasses. However, large scale industrial application has yet not been implemented due to numerous challenges in its production, storage, and transportation. This review study demonstrates that production of hydrogen from anaerobic digestion is potentially a worthy alternative regarding energy density, environmental impact, and cost. Moreover, dependence on fossil fuel systems in the future could be minimized when biohydrogen production is feasible from renewable energy sources.
Khan, MA, Umer, T, Khan, SU, Yu, S & Rachedi, A 2018, 'IEEE Access Special Section Editorial: Green Cloud and Fog Computing: Energy Efficiency and Sustainability Aware Infrastructures, Protocols, and Applications', IEEE Access, vol. 6, pp. 12280-12283.
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Khan, MSH & Castel, A 2018, 'Effect of MgO and Na2SiO3 on the carbonation resistance of alkali activated slag concrete', Magazine of Concrete Research, vol. 70, no. 13, pp. 685-692.
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This paper investigates the effect of magnesium oxide (MgO) on the carbonation resistance of alkali-activated slag–fly ash blend containing 75% ground granulated blast furnace slag (GGBS) and 25% low-calcium fly ash. Two types of GGBS were used with different magnesium oxide content. Phenolphthalein indicator and pH profiles showed that the GGBS with higher levels of magnesium oxide offered no significant improvement in resistance against natural and 1% accelerated carbonation. X-ray diffraction confirmed no hydrotalcite formation, although the magnesium oxide content was 9·1%. A very small amount of free magnesium ions (Mg2+) was available in the pore solution, which was deemed insufficient to form hydrotalcite. Lack of its formation was the major reason for the lower carbonation resistance. Excessive silicate in the system reduces the calcium oxide/silicon dioxide ratio, which leads to the incorporation of magnesium ions in the calcium silicate hydrate structure. Hydrotalcite was observed when the activator concentration was reduced. The results suggest that in addition to magnesium and aluminium ion (Al3+) availability, silicate concentration also plays a strong role in deciding the hydrotalcite formation in alkali-activated GGBS concrete.
Khokle, RP, Esselle, KP & Bokor, DJ 2018, 'Design, Modeling, and Evaluation of the Eddy Current Sensor Deeply Implanted in the Human Body', Sensors, vol. 18, no. 11, pp. 3888-3888.
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Joint replacement surgeries have enabled motion for millions of people suffering from arthritis or grave injuries. However, over 10% of these surgeries are revision surgeries. We have first analyzed the data from the worldwide orthopedic registers and concluded that the micromotion of orthopedic implants is the major reason for revisions. Then, we propose the use of inductive eddy current sensors for in vivo micromotion detection of the order of tens of μ m. To design and evaluate its characteristics, we have developed efficient strategies for the accurate numerical simulation of eddy current sensors implanted in the human body. We present the response of the eddy current sensor as a function of its frequency and position based on the robust curve fit analysis. Sensitivity and Sensitivity Range parameters are defined for the present context and are evaluated. The proposed sensors are fabricated and tested in the bovine leg.
Khosrokhani, M, Khairunniza-Bejo, S & Pradhan, B 2018, 'Geospatial technologies for detection and monitoring of Ganoderma basal stem rot infection in oil palm plantations: a review on sensors and techniques', Geocarto International, vol. 33, no. 3, pp. 260-276.
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Khuat, TT & Le, MH 2018, 'A Novel Hybrid ABC-PSO Algorithm for Effort Estimation of Software Projects Using Agile Methodologies', Journal of Intelligent Systems, vol. 27, no. 3, pp. 489-506.
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AbstractIn modern software development processes, software effort estimation plays a crucial role. The success or failure of projects depends greatly on the accuracy of effort estimation and schedule results. Many studies focused on proposing novel models to enhance the accuracy of predicted results; however, the question of accurate estimation of effort has been a challenging issue with regards to researchers and practitioners, especially when it comes to projects using agile methodologies. This study aims at introducing a novel formula based on team velocity and story point factors. The parameters of this formula are then optimized by employing swarm optimization algorithms. We also propose an improved algorithm combining the advantages of the artificial bee colony and particle swarm optimization algorithms. The experimental results indicated that our approaches outperformed methods in other studies in terms of the accuracy of predicted results.
Kieu, LM, Ou, Y & Cai, C 2018, 'Large-scale transit market segmentation with spatial-behavioural features', Transportation Research Part C: Emerging Technologies, vol. 90, pp. 97-113.
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Transit market segmentation enables transit providers to comprehend the commonalities and heterogeneities among different groups of passengers, so that they can cater for individual transit riders’ mobility needs. The problem has recently been attracting a great interest with the proliferation of automated data collection systems such as Smart Card Automated Fare Collection (AFC), which allow researchers to observe individual travel behaviours over a long time period. However, there is a need for an integrated market segmentation method that incorporating both spatial and behavioural features of individual transit passengers. This algorithm also needs to be efficient for large-scale implementation. This paper proposes a new algorithm named Spatial Affinity Propagation (SAP) based on the classical Affinity Propagation algorithm (AP) to enable large-scale spatial transit market segmentation with spatial-behavioural features. SAP segments transit passengers using spatial geodetic coordinates, where passengers from the same segment are located within immediate walking distance; and using behavioural features mined from AFC data. The comparison with AP and popular algorithms in literature shows that SAP provides nearly as good clustering performance as AP while being 52% more efficient in computation time. This efficient framework would enable transit operators to leverage the availability of AFC data to understand the commonalities and heterogeneities among different groups of passengers.
Kim, DI, Gwak, G, Dorji, P, He, D, Phuntsho, S, Hong, S & Shon, H 2018, 'Palladium Recovery through Membrane Capacitive Deionization from Metal Plating Wastewater', ACS Sustainable Chemistry & Engineering, vol. 6, no. 2, pp. 1692-1701.
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© 2017 American Chemical Society. The potential application of membrane capacitive deionization (MCDI) for recovery of palladium (Pd) ions from catalyst solution wastewater generated from the plating industry was investigated in this study. Several major issues were explored in this work to verify the suitability of MCDI for Pd recovery from a practical perspective: adsorption and desorption efficiencies, desorption mechanisms into high concentration of Pd concentrate, and its sustainability in long-term operation. The lab-scale MCDI operation achieved satisfactory and highly competitive Pd removal (99.07-99.94% removal with 1.42-1.52 of Pd selectivity over ammonium ions) showing that Pd can be effectively collected from plating industry wastewater. A high concentration of Pd concentrate (64.77 and 919.44 mg/L of Pd from the 10 and 100 mg/L Pd containing catalyst solution, respectively) was obtained through successive five operation cycles of adsorption/desorption phases. However, it is significant to note that the desorption efficiency was inversely proportional to the concentration of Pd concentrate which is likely due to the Pd ions discharged from carbon electrode toward Pd solution against the enhanced concentration gradient. The long-term operation results suggest that scaling could reduce the MCDI efficiency during Pd recovery (0.17% decrease in Pd removal for every cycle on average) and hence may require an adequate electrode cleaning regime.
Kim, J 2018, 'Robot Navigation and SLAM', Robots and Human: Special Issue on Robot Navigation and SLAM Technology, vol. 15.
Kim, JE, Phuntsho, S, Ali, SM, Choi, JY & Shon, HK 2018, 'Forward osmosis membrane modular configurations for osmotic dilution of seawater by forward osmosis and reverse osmosis hybrid system', Water Research, vol. 128, pp. 183-192.
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© 2017 Elsevier Ltd This study evaluates various options for full-scale modular configuration of forward osmosis (FO) process for osmotic dilution of seawater using wastewater for simultaneous desalination and water reuse through FO-reverse osmosis (RO) hybrid system. Empirical relationship obtained from one FO membrane element operation was used to simulate the operational performances of different FO module configurations. The main limiting criteria for module operation is to always maintain the feed pressure higher than the draw pressure throughout the housing module for safe operation without affecting membrane integrity. Experimental studies under the conditions tested in this study show that a single membrane housing cannot accommodate more than four elements as the draw pressure exceeds the feed pressure. This then indicates that a single stage housing with eight elements is not likely to be practical for safe FO operation. Hence, six different FO modular configurations were proposed and simulated. A two-stage FO configuration with multiple housings (in parallel) in the second stage using same or larger spacer thickness reduces draw pressure build-up as the draw flow rates are reduced to half in the second stage thereby allowing more than four elements in the second stage housing. The loss of feed pressure (pressure drop) and osmotic driving force in the second stage are compensated by operating under the pressure assisted osmosis (PAO) mode, which helps enhance permeate flux and maintains positive pressure differences between the feed and draw chamber. The PAO energy penalty is compensated by enhanced permeate throughput, reduced membrane area, and plant footprint. The contribution of FO/PAO to total energy consumption was not significant compared to post RO desalination (90%) indicating that the proposed two-stage FO modular configuration is one way of making the FO full-scale operation practical for FO-RO hybrid system.
Kim, JE, Phuntsho, S, Chekli, L, Choi, JY & Shon, HK 2018, 'Environmental and economic assessment of hybrid FO-RO/NF system with selected inorganic draw solutes for the treatment of mine impaired water', Desalination, vol. 429, pp. 96-104.
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© 2017 Elsevier B.V. A hybrid forward osmosis (FO) and reverse osmosis (RO)/nanofiltration (NF) system in a closed-loop operation with selected draw solutes was evaluated to treat coal mine impaired water. This study provides an insight of selecting the most suitable draw solution (DS) by conducting environmental and economic life cycle assessment (LCA). Baseline environmental LCA showed that the dominant components to energy use and global warming are the DS recovery processes (i.e. RO or NF processes) and FO membrane materials, respectively. When considering the DS replenishment in FO, the contribution of chemical use to the overall global warming impact was significant for all hybrid systems. Furthermore, from an environmental perspective, the FO-NF hybrid system with Na2SO4 shows the lowest energy consumption and global warming with additional considerations of final product water quality and FO brine disposal. From an economic perspective, the FO-NF with Na2SO4 showed the lowest total operating cost due to its lower DS loss and relatively low solute cost. In a closed-loop system, FO-NF with NaCl and Na2SO4 had the lowest total water cost at optimum NF recovery rates of 90 and 95%, respectively. FO-NF with Na2SO4 had the lowest environmental and economic impacts. Overall, draw solute performances and cost in FO and recovery rate in RO/NF play a crucial role in determining the total water cost and environmental impact of FO hybrid systems in a closed-loop operation.
Kim, S, Piao, G, Han, DS, Shon, HK & Park, H 2018, 'Solar desalination coupled with water remediation and molecular hydrogen production: a novel solar water-energy nexus', Energy & Environmental Science, vol. 11, no. 2, pp. 344-353.
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A novel solar water-energy nexus technology is presented that combines the solar desalination of saline water and desalination-driven wastewater remediation coupled with the production of H2.
Kim, T, Sotirova, E, Shannon, A, Atanassova, V, Atanassov, K & Jang, L-C 2018, 'Interval Valued Intuitionistic Fuzzy Evaluations for Analysis of a Student’s Knowledge in University e-Learning Courses', INTERNATIONAL JOURNAL of FUZZY LOGIC and INTELLIGENT SYSTEMS, vol. 18, no. 3, pp. 190-195.
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© The Korean Institute of Intelligent Systems. In the paper a method is proposed for evaluation of the students' knowledge obtained in the university e-learning courses and an evaluation of the whole student class. For the assessment of the student's solution of the respective assessment units the theory of intuitionistic fuzzy sets is used, while for the class evaluation, interval valued intuitionistic fuzzy sets is used. The obtained intuitionistic fuzzy estimations reflect the degree of each student's good or poor performances, for each assessment unit. The interval valued intuitionistic fuzzy evaluations are based on the separate student's evaluations. We also consider a degree of uncertainty that represents such cases wherein the student is currently unable to solve the problem. The method presented here provides the possibility for the algorithmization of the process of forming the student's evaluations.
Kok, VC, Zhang, H-W, Lin, C-T, Huang, S-C & Wu, M-F 2018, 'Positive association between hypertension and urinary bladder cancer: epidemiologic evidence involving 79,236 propensity score-matched individuals', Upsala Journal of Medical Sciences, vol. 123, no. 2, pp. 109-115.
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INTRODUCTION: We hypothesized that hypertensive patients harbor a higher risk of urinary bladder (UB) cancer. MATERIAL AND METHODS: We performed a population-based cohort study on adults using a National Health Insurance Research Database (NHIRD) dataset. Hypertension and comparison non-hypertensive (COMP) groups comprising 39,618 patients each were propensity score-matched by age, sex, index date, and medical comorbidities. The outcome was incident UB cancer validated using procedure codes. We constructed multivariable Cox models to derive adjusted hazard ratios (aHRs) and 95% confidence intervals (CIs). Cumulative incidence was compared using a log-rank test. RESULTS: During a total follow-up duration of 380,525 and 372,020 person-years in the hypertension and COMP groups, 248 and 186 patients developed UB cancer, respectively, representing a 32% increase in the risk (aHR, 1.32; 95% CI, 1.09-1.60). Hypertensive women harbored a significantly increased risk of UB cancer (aHR, 1.55; 95% CI, 1.12-2.13) compared with non-hypertensive women, whereas men with hypertension had a statistically non-significant increased risk (aHR, 1.22; 95% CI, 0.96-1.55). The sensitivity analysis demonstrated that the increased risk was sustained throughout different follow-up durations for the entire cohort; a statistical increase in the risk was also noted among hypertensive men. CONCLUSION: This nationwide population-based propensity score-matched cohort study supports a positive association between hypertension and subsequent UB cancer development.
Kong, F, Sun, X, Guo, YJ, Leung, VCM, Zhu, Q & Zhu, H 2018, 'Queue-Aware Power Consumption Minimization in Two-Tier Heterogeneous Networks', IEEE Transactions on Vehicular Technology, vol. 67, no. 9, pp. 8875-8889.
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© 1967-2012 IEEE. In this paper, we study the network average power consumption minimization problem in a two-tier heterogeneous network by optimally tuning the activation ratio of micro base stations (BSs) under the quality of service (QoS) constraints of the network mean queueing delay and the network signal-to-interference ratio (SIR) coverage. With the consideration of dynamic packets arrivals, each BS can either be busy or be idle depending on its queueing status. The network performance is thus critically determined by the traffic intensity of each BS. With the assumption of universal frequency reuse, the average traffic intensity of each tier is characterized by a set of fixed-point equations, which can be solved by a proposed iterative method. By using the approximation that BSs of the same tier have the same SIR coverage, the cumulative distribution function of the traffic intensity of each tier is further obtained. On that basis, the network average power consumption per area, the network mean queueing delay, and the network SIR coverage are characterized. Numerical results demonstrate that if the idle power coefficient is below a certain threshold, then the optimal activation ratio equals the one to minimize the network average power consumption per area; otherwise, the optimal activation ratio can be obtained according to the QoS constraints. It is further shown that universal frequency reuse outperforms spectrum partitioning in terms of both the network average power consumption and the network SIR coverage in the considered scenario.
Kong, S-H, Kim, M, Hoang, LM & Kim, E 2018, 'Automatic LPI Radar Waveform Recognition Using CNN', IEEE Access, vol. 6, pp. 4207-4219.
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Kook, S, Lee, C, Nguyen, TT, Lee, J, Shon, HK & Kim, IS 2018, 'Serially connected forward osmosis membrane elements of pressure-assisted forward osmosis-reverse osmosis hybrid system: Process performance and economic analysis', Desalination, vol. 448, pp. 1-12.
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© 2018 Elsevier B.V. Due to the improved dilution of draw streams, employing pressure-assisted forward osmosis (PAFO) to the hybrid system of forward osmosis (FO) followed by reverse osmosis (RO) for seawater desalination has been expected to reduce the overall economics. However, replacing FO with PAFO causes an additional energy cost in the seawater dilution step which inevitably leads to a question that PAFO-RO hybrid is truly an economically beneficial option. More importantly, though serial connection of FO elements improves the dilution of initial draw water, this economic benefit is also compensated with the additional membrane. To rationalize its overall performance and economic benefit, thorough performance and economic evaluations were conducted based on actual pilot-scale PAFO operations for serial connection of up to three 8040 FO elements. The results showed the FO-RO hybrid is not an economically feasible option unless a significant unit FO element cost cut-down is guaranteed. Meanwhile, PAFO-RO showed benefits with regards to target RO recovery and unit FO element cost, particularly when two FO elements are serially connected (SE2). It was found that PAFO-RO, indeed, has higher economic potential than FO-RO. A graphical overlapping method suggested in this work can help determine optimal serial configuration and operating conditions of PAFO-RO.
Korzekwa, K, Chubb, CT & Tomamichel, M 2018, 'Avoiding irreversibility: engineering resonant conversions of quantum resources', Phys. Rev. Lett., vol. 122, no. 11, p. 110403.
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We identify and explore the intriguing property of resource resonance arisingwithin resource theories of entanglement, coherence and thermodynamics. Whilethe theories considered are reversible asymptotically, the same is generallynot true in realistic scenarios where the available resources are bounded. Thefinite-size effects responsible for this irreversibility could potentiallyprohibit small quantum information processors or thermal machines fromachieving their full potential. Nevertheless, we show here that by carefullyengineering the resource interconversion process any such losses can be greatlysuppressed. Our results are predicted by higher order expansions of thetrade-off between the rate of resource interconversion and the achievedfidelity, and are verified by exact numerical optimizations of appropriateapproximate majorization conditions.
Kulasinghe, A, Schmidt, H, Perry, C, Whitfield, B, Kenny, L, Nelson, C, Warkiani, ME & Punyadeera, C 2018, 'A Collective Route to Head and Neck Cancer Metastasis', Scientific Reports, vol. 8, no. 1.
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AbstractDistant metastasis (DM) from head and neck cancers (HNC) portends a poor patient prognosis. Despite its important biological role, little is known about the cells which seed these DM. Circulating tumour cells (CTCs) represent a transient cancer cell population, which circulate in HNC patients’ peripheral blood and seed at distant sites. Capture and analysis of CTCs offers insights into tumour metastasis and can facilitate treatment strategies. Whilst the data on singular CTCs have shown clinical significance, the role of CTC clusters in metastasis remains limited. In this pilot study, we assessed 60 treatment naïve HNC patients for CTCs with disease ranging from early to advanced stages, for CTC clusters utilizing spiral CTC enrichment technology. Single CTCs were isolated in 18/60–30% (Ranging from Stage I-IV),