Ahad, MT, Dyson, LE & Gay, VC 2012, 'An Empirical Study of Factors Influencing the SME's Intention to Adopt m-Banking in Rural Bangladesh', Journal of Mobile Technologies, Knowledge and Society, vol. 2012, pp. 1-16.
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This research empirically studies the factors that influence the intention of SME owners and managers to adopt m-banking in rural Bangladesh. The study specifically focuses on business oriented m-banking, such as paying suppliers or receiving payments from customers, and on person-to-person use of m-banking. Although over the last ten years a wide spectrum of mbanking frameworks has emerged in various countries, very few research have focused on SMEs m-banking adoption and acceptance of the service. Another rationale for undertaking such a study is that m-banking has not yet been extended to rural Bangladesh. To fill the gap this research surveyed 550 SMEs owners/managers in four (4) rural villages. The survey indicates that poor banking facilities, cost, credibility, gender, education and SME business type are the main factors that significantly influence the intention to adopt m-banking. The analysis focuses on the three factors that have been largely overlooked in prior literature, that are banking satisfaction, m-banking advantages for SMEs, and SME business type. The study broadens our understanding of m-banking and provides insights into developing m-banking strategies in Bangladesh. This research will be of potential value in accelerating the development of m-banking in Bangladesh.
Arefin, AS, Mathieson, L, Johnstone, D, Berretta, R & Moscato, P 2012, 'Unveiling Clusters of RNA Transcript Pairs Associated with Markers of Alzheimer's Disease Progression', PLOS ONE, vol. 7, no. 9.
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Arif, M, Saqib, M, Basalamah, S & Naeem, A 2012, 'Counting of moving people in the video using neural network system', Life Science Journal, vol. 9, no. 3, pp. 1384-1392.
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Automatic counting of people in the crowd using surveillance visual camera is very useful in effective crowd management, security surveillance, and many more applications. In this paper, we have proposed an intelligent framework to automate the process of people counting in the surveillance video. Foreground (moving people) segmentation from the video is done by combination of different foreground estimation techniques. Texture analysis and foreground pixel area for different segmentation techniques are used to extract the useful features. Neural Network is trained on these features and people counting accuracy of more than 96% is achieved on a benchmark video.
Ariffin, SA, Dyson, LE & Hoskins-McKenzie, D 2012, 'Content is king: Malaysian industry experts' point of view on local content for mobile phones', Journal of Mobile Technologies, Knowledge and Society, vol. 2012, no. 2012, pp. 1-9.
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Content is the most prominent aspect of the medium for communication. The trends of the content nowadays, especially in Malaysia, have shown the lack of local content in, for example, television, radio, films, the Internet and, in more recent years, mobile phones. In order to understand the situation in Malaysia with regards to local content for mobile phones, meetings were carried out with Malaysian mobile technology specialists. Given their extensive experience in this industry, they are knowledgeable regarding mobile users needs. The findings show that there is limited local content. On the other hand, the Malaysian government has adopted a pro-active attitude to launch activities to motivate students in the universities to produce more local mobile content. Problems that need to be addressed include: low numbers of mobile content developers; lack of standardization of mobile phones; a limited business for Malaysian mobile content and limitation of bandwidth coverage in rural areas. The content on the mobile phone is also crucially important for the positioning of Malaysian local culture on the world map. One of the areas identified of importance for understanding use of mobile content is at the local institutions of higher learning. Thus, it is suggested to investigate mobile content for students and educators further on how it could benefit those participants.
Bakker, S, Antle, A & van den Hoven, E 2012, 'Embodied Metaphors in Tangible Interaction Design', Personal and Ubiquitous Computing, vol. 16, pp. 433-449.
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For centuries, learning and development has been supported by physical activity and manipulating physical objects. With the introduction of embedded technologies, opportunities for employing tangible or embodied interaction for learning and development have emerged. As a result of previous research, we have seen that interaction models based on embodied knowledge (through embodied metaphors) can support children's learning in abstract domains. Although metaphorical mappings are promoted in tangible and embodied interaction research, little is known about how to identify embodied metaphors, or how to implement them effectively into interaction models. In this paper, we introduce a people centered, iterative approach to the design of tangible learning systems with embodied metaphor-based mappings. As a design case, we imple- mented our approach to the design of Moving Sounds (MoSo) Tangibles; a tangible system for learning abstract sound concepts. The system consists of a set of interactive tangibles with which children can manipulate pitch, volume, and tempo of ongoing tones. In a user study with 39 participants, we found that all children were able to reproduce sound samples with MoSo Tangibles.
Bakker, S, van den Hoven, E & Eggen, B 2012, 'Acting by hand: Informing interaction design for the periphery of people's attention', Interacting With Computers, vol. 24, no. -, pp. 119-130.
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Interactions in and with the physical world have enabled us to perform everyday activities in the periphery of our attention. Even though digital technologies are becoming increasingly present in the everyday environment, interaction with these technologies usually requires people's focused attention. In the realm of the vision of calm technology, we think that designing interactions with the digital world inspired by our peripheral interaction with the physical world, will enable digital technologies to better blend into our everyday lives. However, for such interaction design to be effective, a detailed understanding of the everyday periphery is required. In this paper, we therefore present a qualitative study on every- day activities that may take place in the periphery of the attention. We provide a broad range of examples of such everyday activities and cluster them to present the conditions under which they may be performed peripherally. Furthermore, we discuss how our findings may be relevant for the design of peripheral interactions with digital technologies, and present two conceptual designs that are based on our findings.
Bakker, S, van den Hoven, E & Eggen, B 2012, 'Knowing by ear: leveraging human attention abilities in interaction design', Journal on Multimodal User Interfaces, vol. 5, no. 3, pp. 197-209.
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In a world in which intelligent technologies are integrated in everyday objects and environments, users are at risk of being overburdened with information and interac- tion possibilities. Calm technology therefore aims at design- ing interactions that may reside in the periphery of the userâs attention and only shift to the center of the attention when re- quired. However, for such designs to be effective, a detailed understanding of human attention abilities is needed. In this paper, we therefore present a qualitative study on the every- day periphery of the attention. As we expected, we found that sound plays a major role in this, which supports our ap- proach to use interactive sonification as an interaction style for peripheral interaction. We present a range of rich exam- ples of everyday situations that lay out the design space for peripheral interaction and support these findings by describ- ing three initial designs that use interactive sonification for peripheral interaction.
Balsys, RJ, Harbinson, D & Suffern, KG 2012, 'Visualizing Nonmanifold and Singular Implicit Surfaces with Point Clouds', IEEE Transactions on Visualization and Computer Graphics, vol. 18, no. 2, pp. 188-201.
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We use octree spatial subdivision to generate point clouds on complex nonmanifold implicit surfaces in order to visualize them. The new spatial subdivision scheme only uses point sampling and an interval exclusion test. The algorithm includes a test for pruning the resulting plotting nodes so that only points in the closest nodes to the surface are used in rendering. This algorithm results in improved image quality compared to the naive use of intervals or affine arithmetic when rendering implicit surfaces, particularly in regions of high curvature. We discuss and compare CPU and GPU versions of the algorithm. We can now render nonmanifold features such as rays, ray-like tubes, cusps, ridges, thin sections that are at arbitrary angles to the octree node edges, and singular points located within plot nodes, all without artifacts. Our previous algorithm could not render these without severe aliasing. The algorithm can render the self-intersection curves of implicit surfaces by exploiting the fact that surfaces are singular where they self-intersect. It can also render the intersection curves of two implicit surfaces. We present new image space and object space algorithms for rendering these intersection curves as contours on one of the surfaces. These algorithms are better at rendering high curvature contours than our previous algorithms. To demonstrate the robustness of the node pruning algorithm we render a number of complex implicit surfaces such as high order polynomial surfaces and Gaussian curvature surfaces. We also compare the algorithm with ray casting in terms of speed and image quality. For the surfaces presented here, the point clouds can be computed in seconds to minutes on a typical Intel based PC. Once this is done, the surfaces can be rendered at much higher frame rates to allow some degree of interactive visualization.
Bian, W & Tao, D 2012, 'Constrained Empirical Risk Minimization Framework For Distance Metric Learning', IEEE Transactions On Neural Networks And Learning Systems, vol. 23, no. 8, pp. 1194-1205.
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Distance metric learning (DML) has received increasing attention in recent years. In this paper, we propose a constrained empirical risk minimization framework for DML. This framework enriches the state-of-the-art studies on both theoretic and algorithmi
Bian, W, Tao, D & Rui, Y 2012, 'Cross-Domain Human Action Recognition', Ieee Transactions On Systems Man And Cybernetics Part B-Cybernetics, vol. 42, no. 2, pp. 298-307.
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Conventional human action recognition algorithms cannot work well when the amount of training videos is insufficient. We solve this problem by proposing a transfer topic model (TTM), which utilizes information extracted from videos in the auxiliary domai
Bogdanov, A & Qiao, Y 2012, 'On the security of Goldreich's one-way function', Computational Complexity, vol. 21, no. 1, pp. 83-127.
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Goldreich (ECCC 2000) suggested a simple construction of a candidate one-way function f : {0, 1} n ? {0, 1} m where each bit of output is a fixed predicate P of a constant number d of (random) input bits. We investigate the security of this construction in the regime m = Dn, where D(d) is a sufficiently large constant. We prove that for any predicate P that correlates with either one or two of its inputs, f can be inverted with high probability.
Bommes, D, Lévy, B, Pietroni, N, Silva, C, Tarini, M & Zorin, D 2012, 'State of the art in quad meshing'.
Bressan, N, McGregor, C, Blount, M, Ebling, M, Sow, D & James, A 2012, '1618 Identification of Noxious Events for Newborn Infants with a Neural Network', Archives of Disease in Childhood, vol. 97, no. Suppl 2, pp. A458-A458.
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Brodka, P, Kazienko, P, Musial, K & Skibicki, K 2012, 'Analysis of Neighbourhoods in Multi-layered Dynamic Social Networks', INTERNATIONAL JOURNAL OF COMPUTATIONAL INTELLIGENCE SYSTEMS, vol. 5, no. 3, pp. 582-596.
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Chang, Y-J, Liao, L-D, Lin, C-T, Lai, H-Y, Chen, J-L, Yang, Y-T, Ting, Y-C, Huang, Y-P, Wu, R, Thakor, NV & Chen, Y-Y 2012, 'A Low-Cost Multi-Electrode Array System for the Simultaneous Acquisition of Electrophysiological Signal and Cellular Morphology', Journal of neuroscience and neuroengineering, vol. 1, no. 2, pp. 131-142.
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This study aimed to develop a low-cost multichannel neural recording system and multi-electrode array (MEA) chip for a number of research laboratories. Because these elaborate systems may be cost-prohibitive for many laboratories, the simple fabrication of the MEA chip and the construction of the low-cost recording system with cellular image acquisition is presented in this study. The MEA chip is a polyimide-based microelectrode array with 60 electrodes (5 μm thick, 30 μm in radius and with 200 μm spacing) and is based on the semiconductor process and advanced microelectro-mechanical system (MEMS) technology. The three-dimensional (3D) structure of the electrodes is fabricated by electroplating, which produces rough textures that increased the effective surface area. The in vitro impedance of the electrodes on the MEA chip is 0.43±0.024 MΩ at 1 kHz, which is sufficiently low for obtaining high-quality neural recordings. A self-built amplifier (79 dB) and filter (100 Hz∼5 kHz) were implemented for signal conditioning. Furthermore, with the help of the National Instruments system and LabVIEW graphic interface, multichannel neural signals and cellular images can be simultaneously acquired using this low-cost neural recording system. With good biocompatibility, a high and stable SNR for neural recording, and a high tolerance for chemical and electrolytic erosion, the laboratory-designed MEA-based recording can serve as a useful device in neuroscience research.
Cheema, MA, Zhang, W, Lin, X & Zhang, Y 2012, 'Efficiently processing snapshot and continuous reverse k nearest neighbors queries', VLDB Journal, vol. 21, no. 5, pp. 702-728.
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Given a set of objects and a query q, a point p is called the reverse k nearest neighbor (RkNN) of q if q is one of the k closest objects of p. In this paper, we introduce the concept of influence zone that is the area such that every point inside this area is the RkNN of q and every point outside this area is not the RkNN. The influence zone has several applications in location-based services, marketing and decision support systems. It can also be used to efficiently process RkNN queries. First, we present efficient algorithm to compute the influence zone. Then, based on the influence zone, we present efficient algorithms to process RkNN queries that significantly outperform existing best-known techniques for both the snapshot and continuous RkNN queries. We also present a detailed theoretical analysis to analyze the area of the influence zone and IO costs of our RkNN processing algorithms. Our experiments demonstrate the accuracy of our theoretical analysis. This paper is an extended version of our previous work (Cheema et al. in Proceedings of ICDE, pp. 577---588, 2011). We make the following new contributions in this extended version: (1) we conduct a rigorous complexity analysis and show that the complexity of one of our proposed algorithms in Cheema et al. (Proceedings of ICDE, pp. 577---588, 2011) can be reduced from O(m 2) to O( km) where m > k is the number of objects used to compute the influence zone, (2) we show that our techniques can be applied to dimensionality higher than two, and (3) we present efficient techniques to handle data updates.
Cheema, MA, Zhang, W, Lin, X, Zhang, Y & Li, X 2012, 'Continuous reverse k nearest neighbors queries in Euclidean space and in spatial networks', VLDB Journal, vol. 21, no. 1, pp. 69-95.
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In this paper, we study the problem of continuous monitoring of reverse k nearest neighbors queries in Euclidean space as well as in spatial networks. Existing techniques are sensitive toward objects and queries movement. For example, the results of a query are to be recomputed whenever the query changes its location. We present a framework for continuous reverse k nearest neighbor (RkNN) queries by assigning each object and query with a safe region such that the expensive recomputation is not required as long as the query and objects remain in their respective safe regions. This significantly improves the computation cost. As a byproduct, our framework also reduces the communication cost in client---server architectures because an object does not report its location to the server unless it leaves its safe region or the server sends a location update request. We also conduct a rigid cost analysis for our Euclidean space RkNN algorithm. We show that our techniques can also be applied to answer bichromatic RkNN queries in Euclidean space as well as in spatial networks. Furthermore, we show that our techniques can be extended for the spatial networks that are represented by directed graphs. The extensive experiments demonstrate that our techniques outperform the existing techniques by an order of magnitude in terms of computation cost and communication cost.
Cheng, J, Xie, C, Bian, W & Tao, D 2012, 'Feature fusion for 3D hand gesture recognition by learning a shared hidden space', Pattern Recognition Letters, vol. 33, no. 4, pp. 476-484.
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Hand gesture recognition has been intensively applied in various humancomputer interaction (HCI) systems. Different hand gesture recognition methods were developed based on particular features, e.g., gesture trajectories and acceleration signals. However, it has been noticed that the limitation of either features can lead to flaws of a HCI system. In this paper, to overcome the limitations but combine the merits of both features, we propose a novel feature fusion approach for 3D hand gesture recognition. In our approach, gesture trajectories are represented by the intersection numbers with randomly generated line segments on their 2D principal planes, acceleration signals are represented by the coefficients of discrete cosine transformation (DCT). Then, a hidden space shared by the two features is learned by using penalized maximum likelihood estimation (MLE). An iterative algorithm, composed of two steps per iteration, is derived to for this penalized MLE, in which the first step is to solve a standard least square problem and the second step is to solve a Sylvester equation. We tested our hand gesture recognition approach on different hand gesture sets. Results confirm the effectiveness of the feature fusion method.
Chiu, T-C, Gramann, K, Ko, L-W, Duann, J-R, Jung, T-P & Lin, C-T 2012, 'Alpha modulation in parietal and retrosplenial cortex correlates with navigation performance', PSYCHOPHYSIOLOGY, vol. 49, no. 1, pp. 43-55.
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Chuang, S-W, Ko, L-W, Lin, Y-P, Huang, R-S, Jung, T-P & Lin, C-T 2012, 'Co-modulatory spectral changes in independent brain processes are correlated with task performance', NEUROIMAGE, vol. 62, no. 3, pp. 1469-1477.
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Dengler, KA, Wilson, V, Redshaw, S & Scarfe, G 2012, 'Appreciation of a Child's Journey: Implementation of a Cardiac Action Research Project.', Nursing Research and Practice, vol. 2012, pp. 1-7.
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The aim of this paper is to provide an overview of the phases of the action research process involved in developing, implementing, and evaluating the Heart Beads program. The aim of the project is to enrich the hospital experience of children with cardiac conditions. Heart Beads involves children receiving unique beads specific to each cardiac treatment, procedure or event in recognition of their experiences, and endurance. An action research approach, involving a partnership between clinicians and researchers and emphasising the involvement of patients and their families, was used to guide the Heart Beads program. The project followed the five phases of action research: identification, investigation, program development, implementation, and evaluation. Heart Beads began as a small project which continues to grow in popularity and significance with children at a tertiary paediatric hospital in Sydney, Australia. The program is now being implemented nationwide with the vision that all Australian children hospitalised with cardiac conditions can benefit from Heart Beads.
Doss, R, Zhou, W, Sundaresan, S, Yu, S & Gao, L 2012, 'A minimum disclosure approach to authentication and privacy in RFID systems', Computer Networks, vol. 56, no. 15, pp. 3401-3416.
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In this paper we present a novel approach to authentication and privacy in RFID systems based on the minimum disclosure property and in conformance to EPC Class-1 Gen-2 specifications. We present two security schemes that are suitable for both fixed reader and mobile/wireless reader environments, the mutual authentication and the collaborative authentication schemes respectively. Both schemes are suited to the computational constraints of EPC Class-1 Gen-2 passive RFID tags as only the cyclic redundancy check (CRC) and pseudo random number generator (PRNG) functions that passive RFID tags are capable of are used. Detailed security analysis of both our schemes show that they offer robust security properties in terms of tag anonymity, tag untraceability and reader privacy while at the same time being robust to replay, tag impersonation and desynchronisation attacks. Simulations results are also presented to study the scalability of the schemes and its impact on authentication delay. In addition, Yeh et al. (2010) [20] proposed a security scheme for EPC Class-1 Gen-2 based mobile/wireless RFID systems. We show that this scheme has a security vulnerability and is not suitable for mobile/wireless RFID systems. © 2012 Elsevier B.V. All rights reserved.
Dyson, LE 2012, 'Student-Generated Mobile Learning: A Shift in the Educational Paradigm for the 21st Century', anzMLearn Transactions on Mobile Learning, vol. 1, no. 1, pp. 15-19.
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User-generated content represents a major shift in the way that people are engaging with technology in the twenty-first century and this change has its educational parallel in student -generated content. Though student-generated content can be produced on a desktop computer, there are a number of characteristics of mobile devices, in particular, that lend themselves to this approach, namely convergence, portability, the digital and networked nature of devices, and their affordability. By exploiting these characteristics mobile learning can support a paradigm shift in learning to suit the needs of our students, moving away from more passive learning approaches, as exemplified by the traditional lecture, to active, learner-centred modes in which students produce their own knowledge. Three examples of student-generated mobile learning are presented and their advantages discussed. Affordances of this approach which contribute to a good learning experience and outcome include the high levels of engagement and motivation, the contextualization of learning, and the support that multimedia presentations provide for learning conversations, peer learning and multiple meaningmaking.
Ellis, JT, Goodswen, SJ, Kennedy, PJ & Bush, SA 2012, 'The Core Mouse Response to Infection by Neospora Caninum Defined by Gene Set Enrichment Analyses', Bioinformatics and Biology Insights, vol. 6, pp. 187-202.
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.In this study, the BALB/c and Qs mouse responses to infection by the parasite Neospora caninum were investigated in order to identify host response mechanisms. Investigation was done using gene set (enrichment) analyses of microarray data. GSEA, MANOVA, Romer, subGSE and SAM-GS were used to study the contrasts Neospora strain type, Mouse type (BALB/c and Qs) and time post infection (6 hours post infection and 10 days post infection). The analyses show that the major signal in the core mouse response to infection is from time post infection and can be defined by gene ontology terms Protein Kinase Activity, Cell Proliferation and Transcription Initiation. Several terms linked to signaling, morphogenesis, response and fat metabolism were also identified. At 10 days post infection, genes associated with fatty acid metabolism were identified as up regulated in expression. The value of gene set (enrichment) analyses in the analysis of microarray data is discussed.
Faber, J & van den Hoven, E 2012, 'MARBOWL: Increasing the Fun Experience of Shooting Marbles', Personal and Ubiquitous Computing, vol. 16, no. 4, pp. 391-404.
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This paper focuses on the old school game of shooting marbles. We investigate which aspects of this tangible game make it popular and show how experienced fun can increase by elaborating such aspects through an iterative design process. A questionnaire and field study, tailored to the user group of primary school children aged 9-12 years old, revealed that aspects within areas of physical control, surface of the playground, opponent, and stakes of the game had the biggest influence on the fun experience of shooting marbles. A gameflow model and fun toolkit were used to improve the game in these respective areas. This resulted in a moving marble hole entitled Marbowl: a tangible marble game that augments existing game aspects such as timing, distance, surface, and other physical and environmental influences. A working prototype was field tested with 24 children at a primary school. Results show that different gameflow areas like concentration needed, playability, difficulty to win the game, and amount of challenge, increased in a positive way. Together these findings concluded that compared with the original marble game, children experienced a higher level of fun while playing with Marbowl.
Fachrunnisa, O & Hussain, FK 2012, 'A methodology for modelling temporal nature of trust in trust maintenance for digital enterprise', International Journal of Computer Systems Science And Engineering, vol. 27, no. 3, pp. 219-233.
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Trust is the foundation for the success of Digital Enterprise. However, in a trust-based relationship, trust has distinct life cycle phases. These phases are: building, maintenance and dissolution. A positive trust value between trusting agent and trusted agent results from the activity of successful trust building. However, the next important step in the relationship is to maintain this positive trust level which has been established. In the trust maintenance phase, the initial trust value that that has already been established in the trust building phase needs to be re-calibrated. In this paper, we present a methodology for calculating the final trust during the trust maintenance phase. Continuous performance monitoring employed during trust maintenance results in multiple intermediate trust values. This intermediate trust value takes into account the dynamic nature of trust in an interaction. We present a framework for using our proposed metrics to calculate final trust values in a real world situation and demonstrate the validity of the metrics with a case study and simulations
Ferguson, S, Beilharz, KA & Calo, CA 2012, 'Navigation of interactive sonifications and visualisations of time-series data using multi-touch computing', Journal on Multimodal User Interfaces, vol. 5, no. 3-4, pp. 97-109.
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This paper discusses interaction design for inter- active sonification and visualisation of data in multi-touch contexts. Interaction design for data analysis is becoming increasingly important as data becomes more openly avail- able. We discuss how navigation issues such as zooming, se- lection, arrangement and playback of data relate to both the auditory and visual modality in different ways, and how they may be linked through the modality of touch and gestural in- teraction. For this purpose we introduce a user interface for exploring and interacting with representations of time-series data simultaneously in both the visual and auditory modali- ties.
Gao, L, Li, M, Bonti, A, Zhou, W & Yu, S 2012, 'M-Dimension: Multi-characteristics based routing protocol in human associated delay-tolerant networks with improved performance over one dimensional classic models', Journal of Network and Computer Applications, vol. 35, no. 4, pp. 1285-1296.
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Human associated delay-tolerant network (HDTN) is a new delay-tolerant network where mobile devices are associated with humans. It can be viewed from both their geographic and social dimensions. The combination of these different dimensions can enable us to more accurately comprehend a delay-tolerant network and consequently use this multi-dimensional information to improve overall network efficiency. Alongside the geographic dimension of the network which is concerned with geographic topology of routing, social dimensions such as social hierarchy can be used to guide the routing message to improve not only the routing efficiency for individual nodes, but also efficiency for the entire network. We propose a multi-dimensional routing protocol (M-Dimension) for the human associated delay-tolerant network which uses the local information derived from multiple dimensions to identify a mobile node more accurately. Each dimension has a weight factor and is organized by the Distance Function to select an intermediary and applies multi-cast routing. We compare M-Dimension to existing benchmark routing protocols using the MIT Reality Dataset, a well-known benchmark dataset based on a human associated mobile network trace file. The results of our simulations show that M-Dimension has a significant increase in the average success ratio and is very competitive when End-to-End Delay of packet delivery is used in comparison to other multi-cast DTN routing protocols. © 2011 Elsevier Ltd. All rights reserved.
Garcia Marin, JA, Navarro, KF, Schoene, D, Smith, S & Pisan, Y 2012, 'Exergames for the elderly: towards an embedded Kinect-based clinical test of falls risk', Studies in Health Technology and Informatics, vol. 178, no. 1, pp. 51-57.
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Falls are the leading cause of disability, injuries or even death among older adults. Exercise programmes that include a balance component reduce the risk of falling by 40%. However, such interventions are often perceived as boring and drop-out rates are high. The characteristics of videogames may overcome this weakness and increase exercise adherence. The use of modern input devices, such as the Microsoft Kinect, enables quantification of player performance in terms of motor function while engaging with games. This capability has just started to be explored. The work presented in this paper focuses on the development of a Kinect-based system to deliver step training while simultaneously measuring parameters of stepping performance that have shown to predict falls in older people.
Golsteijn, C & van den Hoven, E 2012, 'Cueb', interactions, vol. Mar/Apr, pp. 9-9.
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Cueb is a set of interactive photo cubes that aims to encourage parents and teenagers to explore digital photos of their individual and shared experiences, reminisce, and exchange stories. Family members each have their own cube with photos of their individual experiences. Shaking a cube will randomly display photos on six sides. Connecting cubes by holding them together will display photos of the family membersâ shared experiences. Photos can be transferred between cubes and locked for use as a selection filter to find related photos. This generates surprising photo results and allows parents and teenagers to compare their experiences.
Goodswen, SJ, Kennedy, PJ & Ellis, JT 2012, 'Evaluating High-Throughput Ab Initio Gene Finders to Discover Proteins Encoded in Eukaryotic Pathogen Genomes Missed by Laboratory Techniques', PLOS ONE, vol. 7, no. 11.
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Goyal, M & Ma, J 2012, 'A fuzzy attitude based bidding strategy in continuous double auctions', Web Intelligence and Agent Systems, vol. 10, no. 1, pp. 65-74.
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To be successful in Continuous Double Auctions, agents must be capable of adapting to continuously changing bidding prices. This paper presents a novel fuzzy attitude-based bidding strategy (FA-Bid), which employs a dual assessment technique i.e. the assessment of multiple attributes of the goods as well as the assessment of the agent's attitude (eagerness) to procure an item in an automated auction. The assessment of attributes adopts the fuzzy sets technique to handle the uncertainty of the bidding process, as well as using the heuristic rules to determine the attitudes of bidding agents in simulated auctions to procure goods. The overall assessment is used to determine a price range from which the best one is selected as the new bid.
Guo, Y, Zhu, J, Lu, H, Lin, Z & Li, Y 2012, 'Core Loss Calculation for Soft Magnetic Composite Electrical Machines', IEEE Transactions On Magnetics, vol. 48, no. 11, pp. 3112-3115.
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Soft magnetic composite (SMC) materials are especially suitable for developing electrical machines with complex structure and three-dimensional (3-D) magnetic flux path. In these SMC machines, the magnetic field is in general 3-D and rotational, so the mechanism and calculation of core loss may be quite different from that in traditional electrical machines with laminated steels in which the magnetic field is restrained. This paper investigates the calculation of core loss in a permanent magnet claw pole motor with SMC stator core. First, core loss models are developed based on the experimental data on SMC samples by using a 3-D magnetic property tester. Then, 3-D magnetic time-stepping field finite element analysis (FEA) is conducted to find the flux density locus in each element when the rotor rotates. The core loss is computed based on the magnetic field FEA results by using the developed core loss models. The calculations agree well with the experimental measurements on the SMC motor prototype.
Guo, Z, Zhao, W, Lu, H & Wang, J 2012, 'Multi-step forecasting for wind speed using a modified EMD-based artificial neural network model', Renewable Energy, vol. 37, no. 1, pp. 241-249.
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In this paper, a modified EMD-FNN model (empirical mode decomposition (EMD) based feed-forward neural network (FNN) ensemble learning paradigm) is proposed for wind speed forecasting. The nonlinear and non-stationary original wind speed series is first decomposed into a finite and often small number of intrinsic mode functions (IMFs) and one residual series using EMD technique for a deep insight into the data structure. Then these sub-series except the high frequency are forecasted respectively by FNN whose input variables are selected by using partial autocorrelation function (PACF). Finally, the prediction results of the modeled IMFs and residual series are summed to formulate an ensemble forecast for the original wind speed series. Further more, the developed model shows the best accuracy comparing with basic FNN and unmodified EMD-based FNN through multi-step forecasting the mean monthly and daily wind speed in Zhangye of China.
Henderson-Sellers, B, Qureshi, M & Gonzalez-Perez, C 2012, 'Towards an interoperable metamodel suite: size assessment as one input', International Journal of Software and Informatics, vol. 6, no. 2, pp. 1-14.
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In recent years, many metamodels have been introduced in the software engi- neering literature and standards. These metamodels vary in their focus across, for example, process, product, organizational and measurement aspects of software development and have typically been developed independently of each other with shared concepts being only accidental. There is thus an increasing concern in the standards communities that possible conicts of structure and semantics between these various metamodels will hinder their widespread adoption. The complexity of these metamodels has also increased significantly and is another barrier in their appreciation. This complexity is compounded when more than one metamodel is used in the lifecycle of a software project. Therefore there is a need to have interoperable metamodels. As a first step towards engendering interoperability and/or possible mergers between metamodels, we examine the size and complexity of various meta- models. To do this, we have used the Rossi and Brinkkemper metrics-based approach to evaluate the size and complexity of several standard metamodels including UML 2.3, BPMN 2.0, ODM, SMM and OSM. The size and complexity of these metamodels is also compared with the previous version of UML, BPMN and Activity diagrams. The comparatively large sizes of BPMN 2.0 and UML 2.3 suggest that future integration with these metamodels might be more difficult than with the other metamodels under study (especially ODM, SSM and OSM).
Hu, J, Xiang, Y & Zhou, W 2012, 'Advances in network and system security: Editorial statement', Computer Journal, vol. 55, no. 4, pp. 382-383.
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Hussain, O, Dillon, T, Hussain, FK & Chang, E 2012, 'Probabilistic assessment of loss in revenue generation in demand-driven production', Journal of Intelligent Manufacturing, vol. 23, no. 3, pp. 2069-2084.
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In Demand-driven Production with Just-in-Time inputs, there are several sources of uncertainty which impact on themanufacturers ability to meet the required customers demand within the given time frame. This can result in a loss of revenue and customers, which will have undesirable impacts on the financial aspects and on the viability of the manufacturer.Hence, a key concern for manufacturers in justin- time production is to determine whether they can meet a specific level of demand within a given time frame, to meet the customers orders and also to achieve the required revenue target for that period of time. In this paper, we propose a methodology by which a manufacturer can ascertain the probability of not meeting the required demand within a given period by considering the uncertainties in the availability of production units and raw materials, and the loss of financial revenue that it would experience as a result.
Huy, QV, Li, G, Sukhorukova, NS, Beliakov, G, Liu, S, Philippe, C, Amiel, H & Ugon, A 2012, 'K-Complex Detection Using a Hybrid-Synergic Machine Learning Method', IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART C-APPLICATIONS AND REVIEWS, vol. 42, no. 6, pp. 1478-1490.
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Iversen, OS, Halskov, K & Leong, T 2012, 'Values-led Participatory Design', CoDesign: International Journal of CoCreation in Design and the Arts, vol. 8, no. 2-3, pp. 87-103.
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The widespread use of participatory design (PD) has meant that different approaches and conceptualisations exist in this field today. In this article, it is argued that one fruitful approach is to rekindle a concern for values in design, focusing upon values as the engine that drives activities in PD. Drawing from the authors` own PD projects, this article shows how this can be accomplished: through designers enacting their appreciative judgement of values by engaging in a dynamic and dialogical process of cultivating the emergence of values, developing them and supporting their grounding.
Janjua, NK & Hussain, FK 2012, 'Web@IDSS - Argumentation-enabled Web-based IDSS for reasoning over incomplete and conflicting information', Knowledge-Based Systems, vol. 32, no. 1, pp. 9-27.
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Over the past few decades, there has been a resurgence of interest in using high-level software intelligence for business intelligence (BI). The objective is to produce actionable information that is delivered at the right time, easily comprehendible and exportable to other software to assist business decision-making processes. Although the design and development of decision support systems (DSS) has been carried out for over 40 years, DSS still suffer from many limitations such as poor maintainability, poor flexibility and less reusability. The development of the Internet and WWW has helped information systems to overcome those limitations and Web DSS is now an active area of research in business intelligence, impacting significantly on the way information is exchanged and businesses are conducted. However, to remain competitive, companies rely on business intelligence (BI) to continually monitor and analyze the operating environment (both internal and external), to identify potential risks, and to devise competitive business strategies. However, the current Web DSS applications are not able to reason over information present across organizational boundaries which could be incomplete and conflicting. The use of an argumentation-based mechanism has not been explored to address such shortcomings in Web DSS. Argumentation is a kind of commonsense reasoning used by human beings to reach a justifiable conclusion when available information is incomplete and/or inconsistent among participants. In this paper, we propose and elaborate in detail a conceptual framework and formal argumentation-based semantics for Web enabled Intelligent DSS (Web@IDSS). We evaluate the use of argumentative reasoning in Web DSS with the help of a case study, prototype development and future directions. Applications built according to the proposed framework will provide more practical, understandable results to decision makers.
Kamaleswaran, R & McGregor, C 2012, 'Integrating Complex Business Processes for Knowledge-driven Clinical Decision Support Systems', 2012 ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC), pp. 1306-1309.
Kaur, P, Goyal, M & Lu, J 2012, 'An Integrated Model for a Price Forecasting Agent in Online Auctions', Journal of Internet Commerce, vol. 11, no. 3, pp. 208-225.
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In an environment of multiple online auctions for same or similar items, the biggest challenge faced by the participants is opting for the best bidding strategies. Deciding which auction to participate in, whether to bid early or late, and how much to bid is very complicated for the bidders. This article presents the design of a data mining–based price forecasting agent (PFA) that makes these decisions on behalf of the bidders. The agent selects an auction to participate in and then predicts its end price for the late bidders based on a clustering, and a bid mapping and selection approach. The experimental results demonstrated improved end price prediction outcomes.
Kieferova, M & Nagaj, D 2012, 'Quantum Walks on Necklaces and Mixing'.
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We analyze continuous-time quantum walks on necklace graphs - cyclical graphs
consisting of many copies of a smaller graph (pearl). Using a Bloch-type ansatz
for the eigenfunctions, we block-diagonalize the Hamiltonian, reducing the
effective size of the problem to the size of a single pearl. We then present a
general approach for showing that the mixing time scales (with growing size of
the necklace) similarly to that of a simple walk on a cycle. Finally, we
present results for mixing on several necklace graphs.
Lai, H-Y, Liao, L-D, Lin, C-T, Hsu, J-H, He, X, Chen, Y-Y, Chang, J-Y, Chen, H-F, Tsang, S & Shih, Y-YI 2012, 'Design, simulation and experimental validation of a novel flexible neural probe for deep brain stimulation and multichannel recording', JOURNAL OF NEURAL ENGINEERING, vol. 9, no. 3.
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Lambert, M & Kennedy, PJ 2012, 'Using Artificial Intelligence to Build with Unprocessed Rock', Key Engineering Materials, vol. 517, pp. 939-945.
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Unprocessed rock is a massive resource of very cheap building material with very low embodied energy. However, it is highly underutilised due to the difficulty of dealing with irregular shaped blocks. We have developed a novel software application using the artificial intelligence methods of search and optimisation to simulate building three-dimensional structures in a virtual world. The aim of our software is to help builders solve the 3-dimensional jigsaw puzzle of building with rock rubble with an emphasis on its potential use for building sustainable housing and infrastructure. This paper describes our approach and the design of our software including an overview of the rock digitising, optimisation software and building methods. We present simulation results of building and testing several small drystone structures using the prototype software
Lee, C-Y, Lin, C-T, Hong, C-T & Su, M-T 2012, 'SMOKE DETECTION USING SPATIAL AND TEMPORAL ANALYSES', INTERNATIONAL JOURNAL OF INNOVATIVE COMPUTING INFORMATION AND CONTROL, vol. 8, no. 7A, pp. 4749-4770.
Leong, TW, Vetere, F & Howard, S 2012, 'Experiencing coincidence during digital music listening', ACM Transactions on Computer-Human Interaction, vol. 19, no. 1, pp. 1-19.
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People have reported encountering coincidences when using particular technologies to interact with personal digital content. However, to date, there is a paucity of research to understand these experiences. This article applies McCarthy and Wright's [2004; 2005] experiential framework to analyze these kinds of technologymediated coincidences. By focusing upon encounters of coincidence during people's digitalmusic listening, we identified the elements at play, elucidated the properties of the individual elements, their inter-relationships, and an understanding of how coincidences can arise. We also reveal how, under particular conditions, such elements provide people with opportunities to encounter coincidence. This understanding of coincidence demonstrates how McCarthy and Wright's [2004; 2005] framework can be usefully applied to an empirical investigation of user experience. © 2012 ACM.
Li, C-H, Ho, H-H, Liu, Y-L, Lin, C-T, Kuo, B-C & Taur, J-S 2012, 'An Automatic Method for Selecting the Parameter of the Normalized Kernel Function to Support Vector Machines', JOURNAL OF INFORMATION SCIENCE AND ENGINEERING, vol. 28, no. 1, pp. 1-15.
Li, CH, Kuo, BC, Lin, CT & Huang, CS 2012, 'A Spatial-Contextual Support Vector Machine for Remotely Sensed Image Classification', IEEE Transactions on Geoscience and Remote Sensing.
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Recent studies show that hyperspectral image classification techniques that use both spectral and spatial information are more suitable, effective, and robust than those that use only spectral information. Using a spatial-contextual term, this study modifies the decision function and constraints of a support vector machine (SVM) and proposes two kinds of spatial-contextual SVMs for hyperspectral image classification. One machine, which is based on the concept of Markov random fields (MRFs), uses the spatial information in the original space (SCSVM). The other machine uses the spatial information in the feature space (SCSVMF), i.e., the nearest neighbors in the feature space. The SCSVM is better able to classify pixels of different class labels with similar spectral values and deal with data that have no clear numerical interpretation. To evaluate the effectiveness of SCSVM, the experiments in this study compare the performances of other classifiers: an SVM, a context-sensitive semisupervised SVM, a maximum likelihood (ML) classifier, a Bayesian contextual classifier based on MRFs (ML_MRF), and k nearest neighbor classifier. Experimental results show that the proposed method achieves good classification performance on famous hyperspectral images (the Indian Pine site (IPS) and the Washington, DC mall data sets). The overall classification accuracy of the hyperspectral image of the IPS data set with 16 classes is 95.5%. The kappa accuracy is up to 94.9%, and the average accuracy of each class is up to 94.2%.
Li, D-L, Prasad, M, Hsu, S-C, Hong, C-T & Lin, C-T 2012, 'Face recognition using nonparametric-weighted Fisherfaces', EURASIP JOURNAL ON ADVANCES IN SIGNAL PROCESSING.
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Li, J & Tao, D 2012, 'On Preserving Original Variables in Bayesian PCA with Application to Image Analysis', IEEE Transactions On Image Processing, vol. 21, no. 12, pp. 4830-4843.
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Principal component analysis (PCA) computes a succinct data representation by converting the data to a few new variables while retaining maximum variation. However, the new variables are dif?cult to interpret, because each one is combined with all of the original input variables and has obscure semantics. Under the umbrella of Bayesian data analysis, this paper presents a new prior to explicitly regularize combinations of input variables. In particular, the prior penalizes pair-wise products of the coef?cients of PCA and encourages a sparse model. Compared to the commonly used 1 -regularizer, the proposed prior encourages the sparsity pattern in the resultant coef?cients to be consistent with the intrinsic groups in the original input variables. Moreover, the proposed prior can be explained as recovering a robust estimation of the covariance matrix for PCA. The proposed model is suited for analyzing visual data, where it encourages the output variables to correspond to meaningful parts in the data. We demonstrate the characteristics and effectiveness of the proposed technique through experiments on both synthetic and real data.
Li, J, Tao, D & Li, X 2012, 'A probabilistic model for image representation via multiple patterns', Pattern Recognition, vol. 45, no. 11, pp. 4044-4053.
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For image analysis, an important extension to principal component analysis (PCA) is to treat an image as multiple samples, which helps alleviate the small sample size problem. Various schemes of transforming an image to multiple samples have been proposed. Although having been shown effective in practice, the schemes are mainly based on heuristics and experience. In this paper, we propose a probabilistic PCA model, in which we explicitly represent the transformation scheme and incorporate the scheme as a stochastic component of the model. Therefore fitting the model automatically learns the transformation. Moreover, the learned model allows us to distinguish regions that can be well described by the PCA model from those that need further treatment. Experiments on synthetic images and face data sets demonstrate the properties and utility of the proposed model
Li, L, Zhong, L, Xu, G & Kitsuregawa, M 2012, 'A feature-free search query classification approach using semantic distance', Expert Systems with Applications, vol. 39, no. 12, pp. 10739-10748.
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When classifying search queries into a set of target categories, machine learning based conventional approaches usually make use of external sources of information to obtain additional features for search queries and training data for target categories. Unfortunately, these approaches rely on large amount of training data for high classification precision. Moreover, they are known to suffer from inability to adapt to different target categories which may be caused by the dynamic changes observed in both Web topic taxonomy and Web content. In this paper, we propose a feature-free classification approach using semantic distance. We analyze queries and categories themselves and utilizes the number of Web pages containing both a query and a category as a semantic distance to determine their similarity. The most attractive feature of our approach is that it only utilizes the Web page counts estimated by a search engine to provide the search query classification with respectable accuracy. In addition, it can be easily adaptive to the changes in the target categories, since machine learning based approaches require extensive updating process, e.g., re-labeling outdated training data, re-training classifiers, to name a few, which is time consuming and high-cost. We conduct experimental study on the effectiveness of our approach using a set of rank measures and show that our approach performs competitively to some popular state-of-the-art solutions which, however, frequently use external sources and are inherently insufficient in flexibility.
Li, S-Y, Yang, C-H, Lin, C-T, Ko, L-W & Chiu, T-T 2012, 'Adaptive synchronization of chaotic systems with unknown parameters via new backstepping strategy', NONLINEAR DYNAMICS, vol. 70, no. 3, pp. 2129-2143.
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Li, Y, Geng, B, Yang, L, Xu, C & Bian, W 2012, 'Query Difficulty Estimation For Image Retrieval', Neurocomputing, vol. 95, pp. 48-53.
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Query difficulty estimation predicts the performance of the search result of the given query. It is a powerful tool for multimedia retrieval and receives increasing attention. It can guide the pseudo relevance feedback to rerank the image search results
Liao, L-D & Lin, C-T 2012, 'Novel Trends in Biosensors Used for Electroencephalography Measurements in Neurocognitive Engineering Applications', Journal of neuroscience and neuroengineering, vol. 1, no. 1, pp. 32-41.
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The measurement of human brain function via the Electroencephalography (EEG)-based augmented brain-computer interface (ABCI) system is an important research topic in the neurocognitive field. The ABCI provides a direct pathway for communication between the human brain and the external world. Conventionally, wet sensors have been commonly used to perform cognitive experiments with EEG-based ABCIs. The wet sensors provide measurable results, showing that high temporal resolution of brain activity can be reliably achieved, but only in limited laboratory experiments. Brain function in real-world conditions still needs to be further studied. Currently, many types of biosensors are proposed to be lightweight and provide a rapid and comfortable response. Here, we present an overview of the wide range of biosensors used for measuring brain activity in cognitive neuroscience applications, including multi-modality biosensors. This review provides novel insights into the development trends of biosensors in the cognitive neuroscience field, especially in real-world applications
Liao, L-D, Chen, C-Y, Wang, I-J, Chen, S-F, Li, S-Y, Chen, B-W, Chang, J-Y & Lin, C-T 2012, 'Gaming control using a wearable and wireless EEG-based brain-computer interface device with novel dry foam-based sensors.', Journal of NeuroEngineering and Rehabilitation, vol. 9, pp. 1-12.
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A brain-computer interface (BCI) is a communication system that can help users interact with the outside environment by translating brain signals into machine commands. The use of electroencephalographic (EEG) signals has become the most common approach for a BCI because of their usability and strong reliability. Many EEG-based BCI devices have been developed with traditional wet- or micro-electro-mechanical-system (MEMS)-type EEG sensors. However, those traditional sensors have uncomfortable disadvantage and require conductive gel and skin preparation on the part of the user. Therefore, acquiring the EEG signals in a comfortable and convenient manner is an important factor that should be incorporated into a novel BCI device. In the present study, a wearable, wireless and portable EEG-based BCI device with dry foam-based EEG sensors was developed and was demonstrated using a gaming control application. The dry EEG sensors operated without conductive gel; however, they were able to provide good conductivity and were able to acquire EEG signals effectively by adapting to irregular skin surfaces and by maintaining proper skin-sensor impedance on the forehead site. We have also demonstrated a real-time cognitive stage detection application of gaming control using the proposed portable device. The results of the present study indicate that using this portable EEG-based BCI device to conveniently and effectively control the outside world provides an approach for researching rehabilitation engineering.
Liao, LD, Lin, CT, McDowell, K, Wickenden, AE, Gramann, K, Jung, TP, Ko, LW & Chang, JY 2012, 'Biosensor technologies for augmented brain-computer interfaces in the next decades', Proceedings of the IEEE, vol. 100, no. SPL CONTENT, pp. 1553-1566.
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The study of brain-computer interfaces (BCIs) has undergone 30 years of intense development and has grown into a rich and diverse field. BCIs are technologies that enable direct communication between the human brain and external devices. Conventionally, wet electrodes have been employed to obtain unprecedented sensitivity to high-temporal-resolution brain activity; recently, the growing availability of various sensors that can be used to detect high-quality brain signals in a wide range of clinical and everyday environments is being exploited. This development of biosensing neurotechnologies and the desire to implement them in real-world applications have led to the opportunity to develop augmented BCIs (ABCIs) in the upcoming decades. An ABCI is similar to a BCI in that it relies on biosensors that record signals from the brain in everyday environments; the signals are then processed in real time to monitor the behavior of the human. To use an ABCI as a mobile brain imaging technique for everyday, real-life applications, the sensors and the corresponding device must be lightweight and the equipment response time must be short. This study presents an overview of the wide range of biosensor approaches currently being applied to ABCIs, from their use in the laboratory to their application in clinical and everyday use. The basic principles of each technique are described along with examples of current applications of cutting-edge neuroscience research. In summary, we show that ABCI techniques continue to grow and evolve, incorporating new technologies and advances to address ever more complex and important neuroscience issues, with advancements that are envisioned to lead to a wide range of real-life applications. © 2012 IEEE.
Liao, L-D, Lin, C-T, Shih, Y-YI, Duong, TQ, Lai, H-Y, Wang, P-H, Wu, R, Tsang, S, Chang, J-Y, Li, M-L & Chen, Y-Y 2012, 'Transcranial imaging of functional cerebral hemodynamic changes in single blood vessels using in vivo photoacoustic microscopy', JOURNAL OF CEREBRAL BLOOD FLOW AND METABOLISM, vol. 32, no. 6, pp. 938-951.
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Liao, L-D, Lin, C-T, Shih, Y-YI, Lai, H-Y, Zhao, W-T, Duong, TQ, Chang, J-Y, Chen, Y-Y & Li, M-L 2012, 'Investigation of the cerebral hemodynamic response function in single blood vessels by functional photoacoustic microscopy', JOURNAL OF BIOMEDICAL OPTICS, vol. 17, no. 6.
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Lin, CC, Lin, CL, Shyu, JZ & Lin, C 2012, 'The ANFIS system for nonlinear combined fore-casts in the telecommunications industry', International Journal of Computers and Applications, vol. 37, no. 12, pp. 30-35.
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The Adaptive Network-Based Fuzzy Inference System (ANFIS) has been proven to be efficient for forecasting. To address this concern, this research develops a nonlinear combined forecasting system by ANFIS for predicting the demand of telecommu-nication technology. We investigate the weights assigned to the combined forecast using two linear methods (the Least squares analysis and the Logistic model), as well as one nonlinear me-thods (the Bass model). An empirical data set from 3G technol-ogy development in Taiwan is used to demonstrate the application of the proposed methodology. These results show that the ANFIS method outperforms other individual methods. Also, this proposed work also provides the user with a user interface in which user can fill the query and find the desired forecasting results.
Lin, C-L, Lin, C-C, Z. Shyu, J & Lin, C-T 2012, 'A Rule-based Forecasting System Integrating combining and Single Forecast for Decision Making', International Journal of Computers and Applications, vol. 39, no. 14, pp. 1-6.
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Many studies demonstrated that combining forecasts produces
consistent but modest gains in accuracy. However, little
researches define well the conditions under neither which
combining is most effective nor how methods should be
combined in each situation. In this paper, a rule-based
forecasting system industry is proposed in order to compare
forecast performance between combining forecasts and single
forecasts, then define these conditions and to specify more
effective combinations, finally suggest the best methods. Two
comparative case studies for the telecommunications and
TFT-LCD industry are proposed to examine the performance
of the proposed system. Results from this study indicate that
combining forecasts outperform single forecasts only when
data set is data have various nonlinear characteristics. In this
research, empirical evidence shows that rules based on causal
forces improved the selection of forecasting methods, the
structuring of time series, and the assessment of prediction
intervals.
Lin, C-L, Shaw, F-Z, Young, K-Y, Lin, C-T & Jung, T-P 2012, 'EEG correlates of haptic feedback in a visuomotor tracking task', NEUROIMAGE, vol. 60, no. 4, pp. 2258-2273.
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Lin, C-T & McDowell, K 2012, 'Prolog to the Section on Neurotechnological Systems: The Brain-Computer Interface', PROCEEDINGS OF THE IEEE, vol. 100, pp. 1551-1552.
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Lin, C-T, Chuang, C-H, Wang, Y-K, Tsai, S-F, Chiu, T-C & Ko, L-W 2012, 'Neurocognitive Characteristics of the Driver: A Review on Drowsiness, Distraction, Navigation, and Motion Sickness', Journal of neuroscience and neuroengineering, vol. 1, no. 1, pp. 61-81.
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Within the past few decades, neuroscientists have designed various experimental paradigms and driving environments. Using well-established neurotechnologies, such as functional magnetic resonance imaging (fMRI), positron emission tomography (PET), and electroencephalography (EEG), they have gained insight into the brain activity involved in the processing of driving cognition and behaviors. Moreover, neuroengineers have developed computational intelligent technologies to model these brain-behavioral relationships for real-life applications. With the advance of neurotechnology and the understanding of driving cognition, it is thought that an in-vehicle brain-computer interface will be implemented in the near future. In this review, we discuss four major issues prominent in driving cognitive research, including drowsiness, distraction, navigation, and motion sickness. We provide four summary tables that list nearly 60 references from the fields of neuroscience and neuroengineering to briefly present experimental materials, brain imaging modalities, and major findings of the brain in response to specific driving cognitive states. In addition, driving experiments conducted in a virtual-realistic driving environment and studies examining the power spectral characteristics of brain dynamics using independent component analysis, which eliminates artifacts and extracts the independent component processes, are also described.
Lin, C-T, Huang, T-Y, Lin, W-J, Chang, S-Y, Lin, Y-H, Ko, L-W, Hung, DL & Chang, EC 2012, 'Gender differences in wayfinding in virtual environments with global or local landmarks', JOURNAL OF ENVIRONMENTAL PSYCHOLOGY, vol. 32, no. 2, pp. 89-96.
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Lin, C-T, Li, D-L, Lai, J-H, Han, M-F & Chang, J-Y 2012, 'Automatic Age Estimation System for Face Images Regular Paper', INTERNATIONAL JOURNAL OF ADVANCED ROBOTIC SYSTEMS, vol. 9.
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Lin, F-C, Ko, L-W, Chuang, C-H, Su, T-P & Lin, C-T 2012, 'Generalized EEG-Based Drowsiness Prediction System by Using a Self-Organizing Neural Fuzzy System', IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-REGULAR PAPERS, vol. 59, no. 9, pp. 2044-2055.
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Lin, WY, Lin, CT, Wang, YH & Chen, RT 2012, 'The transformation of users in living lab construction: The case of Eco-City living lab', International Journal of Automation and Smart Technology, vol. 2, no. 3, pp. 231-240.
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To promote the development of user-oriented technology, different approaches are explored, with living labs being one of the most promising. This paper introduces the strategies in making of a community-based living lab with a specific focus on the users. We introduce the practical mechanisms built in a community environment and the methods to facilitate user innovation. We also report a case study of the users' response to a health care technology, finding out that most of the users did not change their opinion after a year's use. The major finding is on the dynamics between living lab construction and the transformation of the users. We reflect on the phenomenon of a living lab itself transforming the users and making it difficult for them to provide specific opinions of the technology. © 2012 International Journal of Automation and Smart Technology.
Lister, RF 2012, 'A variation on Kvale's one thousand page question', ACM Inroads, vol. 3, no. 3, pp. 24-25.
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This is a regular invited column I write for this journal.
Lister, RF 2012, 'Rare research: why is research uncommon in the computing education universe?', ACM Inroads, vol. 3, no. 4, pp. 16-17.
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This is a regular invited column I write for this journal.
Lister, RF 2012, 'Teaching-Oriented Faculty and Computing Education Research', ACM Inroads, vol. 3, no. 1, pp. 22-23.
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This is a regular invited column I write for this journal.
Lister, RF 2012, 'The CC2013 Strawman and Bloom's Taxonomy', ACM Inroads, vol. 3, no. 2, pp. 12-13.
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This is a regular column that I write for this journal.
Lu, J, Zhang, G & Jain, LC 2012, 'Handbook on Decision Making', Intelligent Systems Reference Library, vol. 33.
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Lu, J, Zhang, G, Montero, J & Garmendia, L 2012, 'Multifollower Trilevel Decision Making Models And System', IEEE Transactions On Industrial Informatics, vol. 8, no. 4, pp. 974-985.
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In a trilevel hierarchical decision problem, the objectives and variables of each decision entity at one level are controlled, in part, by the decision entities at other levels. The choice of values for the decision variables at each level may influence
Ma, J, Zhang, G & Lu, J 2012, 'A Method For Multiple Periodic Factor Prediction Problems Using Complex Fuzzy Sets', Ieee Transactions On Fuzzy Systems, vol. 20, no. 1, pp. 32-45.
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Multiple periodic factor prediction (MPFP) problems exist widely in multisensor data fusion applications. Development of an effective prediction method should integrate information for multiple periodically changing factors. Because the uncertainty and p
Marynowsky, W 2012, 'THE UNCANNY AUTOMATON', LEONARDO, vol. 45, no. 5, pp. 482-483.
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Mathieson, L & Szeider, S 2012, 'Editing graphs to satisfy degree constraints: A parameterized approach', JOURNAL OF COMPUTER AND SYSTEM SCIENCES, vol. 78, no. 1, pp. 179-191.
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Mirtalaei, MS, Saberi, M, Hussain, OK, Ashjari, B & Hussain, FK 2012, 'A trust-based bio-inspired approach for credit lending decisions', Computing, vol. 94, no. 7, pp. 541-577.
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Credit scoring computation essentially involves taking into account various financial factors and the previous behavior of the credit requesting person. There is a strong degree of correlation between the compliance level and the credit score of a given entity. The concept of trust has been widely used and applied in the existing literature to determine the compliance level of an entity. However it has not been studied in the context of credit scoring literature. In order to address this shortcoming, in this paper we propose a six-step bio-inspired methodology for trust-based credit lending decisions by credit institutions. The proposed methodology makes use of an artificial neural network-based model to classify the (potential) customers into various categories. To show the applicability and superiority of the proposed algorithm, it is applied to a credit-card dataset obtained from the UCI repository. Due to the varying spectrum of trust levels, we are able to solve the problem of binary credit lending decisions. A trust-based credit scoring approach allows the financial institutions to grant credit-based on the level of trust in potential customers.
Natgunanathan, I, Xiang, Y, Rong, Y, Zhou, W & Guo, S 2012, 'Robust patchwork-based embedding and decoding scheme for digital audio watermarking', IEEE Transactions on Audio, Speech and Language Processing, vol. 20, no. 8, pp. 2232-2239.
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This paper presents a novel patchwork-based embedding and decoding scheme for digital audio watermarking. At the embedding stage, an audio segment is divided into two subsegments and the discrete cosine transform (DCT) coefficients of the subsegments are computed. The DCT coefficients related to a specified frequency region are then partitioned into a number of frame pairs. The DCT frame pairs suitable for watermark embedding are chosen by a selection criterion and watermarks are embedded into the selected DCT frame pairs by modifying their coefficients, controlled by a secret key. The modifications are conducted in such a way that the selection criterion used at the embedding stage can be applied at the decoding stage to identify the watermarked DCT frame pairs. At the decoding stage, the secret key is utilized to extract watermarks from the watermarked DCT frame pairs. Compared with existing patchwork watermarking methods, the proposed scheme does not require information of which frame pairs of the watermarked audio signal enclose watermarks and is more robust to conventional attacks. © 2012 IEEE.
Nguyen, TTS, Lu, H, Tran, TP & Lu, J 2012, 'Investigation of sequential pattern mining techniques for web recommendation', International Journal of Information and Decision Sciences, vol. 4, no. 4, pp. 293-312.
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Increased application of sequence mining in web recommender systems (WRS) requires a better understanding of the performance and a clear identification of the strengths and weaknesses of existing algorithms. Among the commonly used sequence mining methods, the tree-based approach, such as pre-order linked WAP-tree mining algorithm (PLWAP-Mine) and conditional sequence mining algorithm (CS-Mine), has demonstrated high performance in web mining applications. However, its advantages over other mining methods are not well explained and understood in the context of WRS. This paper firstly reviews the existing sequence mining algorithms, and then studies the performance of two outstanding algorithms, i.e., the PLWAP-Mine and CS-Mine algorithms, with respect to their sensitivity to the dataset variability, and their practicality for web recommendation. The results show that CS-Mine performs faster than PLWAP-Mine, but the frequent patterns generated by PLWAP-Mine are more effective than CS-Mine when applied in web recommendations. These results are useful to WRS developers for the selection of appropriate sequence mining algorithms. © 2012 Inderscience Enterprises Ltd.
O'Hara, K, Helmes, J, Sellen, A, Harper, R, Bhoemer, M & van, DHE 2012, 'Food for Talk: Phototalk in the Context of Sharing a Meal', Human-Computer Interaction, vol. 27, no. 1-2, pp. 124-150.
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Photographic mementos are important signifiers of our personal memories. Rather than simply passive representations of memories to "preserve" the past, these photos are actively displayed and consumed in the context of everyday behavior and social practices. Within the context of these settings, these mementos are invoked in particular ways to mobilize particular social relations in the present. Taking this perspective, we explore how photo mementos come to be used in the everyday social setting of sharing meal. Rather than a simple concern with nutritional consumption, the shared meal is a social event and impor- tant cultural site in the organization of family and social life with culturally specific rhythms, norms, rights, and responsibilities. We present a system-4 Photos-that situates photo mementos within the social concerns of these settings. The system collates photo mementos from those attending the meal and displays them at the dining table to be interacted with by all. Through a real-world deployment of the system, we explore the social work performed by invoking these personal memory resources in the context of real-world settings of shared eating. We highlight particular features of the system that enable this social work to be achieved.
Pal, U, Jayadevan, R & Sharma, N 2012, 'Handwriting recognition in indian regional scripts: A survey of offline techniques', ACM Transactions on Asian Language Information Processing, vol. 11, no. 1.
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Offline handwriting recognition in Indian regional scripts is an interesting area of research as almost 460 million people in India use regional scripts. The nine major Indian regional scripts are Bangla (for Bengali and Assamese languages), Gujarati, Kannada, Malayalam, Oriya, Gurumukhi (for Punjabi language), Tamil, Telugu, and Nastaliq (for Urdu language). A state-of-the-art survey about the techniques available in the area of offline handwriting recognition (OHR) in Indian regional scripts will be of a great aid to the researchers in the subcontinent and hence a sincere attempt is made in this article to discuss the advancements reported in this regard during the last few decades. The survey is organized into different sections. A brief introduction is given initially about automatic recognition of handwriting and official regional scripts in India. The nine regional scripts are then categorized into four subgroups based on their similarity and evolution information. The first group contains Bangla, Oriya, Gujarati and Gurumukhi scripts. The second group contains Kannada and Telugu scripts and the third group contains Tamil and Malayalam scripts. The fourth group contains only Nastaliq script (Perso-Arabic script for Urdu), which is not an Indo-Aryan script. Various feature extraction and classification techniques associated with the offline handwriting recognition of the regional scripts are discussed in this survey. As it is important to identify the script before the recognition step, a section is dedicated to handwritten script identification techniques. A benchmarking database is very important for any pattern recognition related research. The details of the datasets available in different Indian regional scripts are also mentioned in the article. A separate section is dedicated to the observations made, future scope, and existing difficulties related to handwriting recognition in Indian regional scripts. We hope that this survey will serve as a compendi...
Palmas, G, Pietroni, N, Cignoni, P & Scopigno, R 2012, 'A practical framework for assembling fragmented objects', paper submitted to IEEE Computer Graphics and Applications on August.
Parvin, S, Hussain, FK & Ali, S 2012, 'A Methodology To Counter DoS Attacks In Mobile IP Communication', Mobile Information Systems, vol. 8, no. 2, pp. 127-152.
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Similar to wired communication, Mobile IP communication is susceptible to various kinds of attacks. Of these attacks, Denial of Service (DoS) attack is considered as a great threat to mobile IP communication. The number of approaches hitherto proposed to
Parvin, S, Hussain, FK, Hussain, OK & Faruque, MA 2012, 'Trust-based Throughput in Cognitive Radio Networks', Procedia Computer Science, vol. 10, pp. 713-720.
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Cognitive Radio Networks (CRNs) deal with opportunistic spectrum access in order to fully utilize the scarce of spectrum resources, with the development of cognitive radio technologies to greater utilization of the spectrum. Nowa-days Cognitive Radio (CR) is a promising concept for improving the utilization of limited radio spectrum resources for future wireless communications and mobile computing. In this paper, we propose two approaches. At first we propose a trust aware model to authenticate the secondary users (SUs) in CRNs which provides a reliable technique to establish trust for CRNs. Secondly, we propose trust throughput mechanism to measure throughput in CRNs.
Parvin, S, Hussain, FK, Hussain, OK, Han, S, Tian, B & Chang, E 2012, 'Cognitive radio network security: A survey', Journal of Network and Computer Applications, vol. 35, no. 6, pp. 1691-1708.
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Recent advancements in wireless communication are creating a spectrum shortage problem on a daily basis. Recently, Cognitive Radio (CR), a novel technology, has attempted to minimize this problem by dynamically using the free spectrum in wireless communications and mobile computing. Cognitive radio networks (CRNs) can be formed using cognitive radios by extending the radio link features to network layer functions. The objective of CRN architecture is to improve the whole network operation to fulfil the userâs demands anytime and anywhere, through accessing CRNs in a more efficient way, rather than by just linking spectral efficiency. CRNs are more flexible and exposed to wireless networks compared with other traditional radio networks. Hence, there are many security threats to CRNs, more so than other traditional radio environments. The unique characteristics of CRNs make security more challenging. Several crucial issues have not yet been investigated in the area of security for CRNs. A typical public key infrastructure (PKI) scheme which achieves secure routing and other purposes in typical ad hoc networks is not enough to guarantee the security of CRNs under limited communication and computation resources. However, there has been increasing research attention on security threats caused specifically by CR techniques and special characteristics of CR in CRNs. Therefore, in this research, a survey of CRNs and their architectures and security issues has been carried out in a broad way in this paper.
Parvin, S, Hussain, FK, Park, JS & Kim, DS 2012, 'A Survivability Model In Wireless Sensor Networks', Computers & Mathematics With Applications, vol. 64, no. 12, pp. 3666-3682.
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In this paper, we present a survivability evaluation model and analyze the performance of Wireless Sensor Networks (WSNs) under attack and key compromise. First, we present a survivability evaluation model of WSNs by representing the states of WSNs under
Peppas, P, Koutras, CD & Williams, M 2012, 'Maps In Multiple Belief Change', Acm Transactions On Computational Logic, vol. 13, no. 4, pp. 1-23.
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Multiple Belief Change extends the classical AGM framework for Belief Revision introduced by Alchourron, Gardenfors, and Makinson in the early '80s. The extended framework includes epistemic input represented as a (possibly infinite) set of sentences, as
Phithakkitnukoon, S, Leong, T, Smoreda, Z & Olivier, P 2012, 'Weather Effects in Mobile Social Interaction: A Case Study of Mobile Phone Users in Lisbon, Portugal', PLoS One, vol. 7, no. 10, pp. 1-13.
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Purba, J, Lu, J, Zhang, G & Ruan, D 2012, 'An Area Defuzzification Technique to Assess Nuclear Event Reliability Data from Failure Possibilities', International Journal of Computational Intelligence and Applications, vol. 11, no. 4, pp. 1-16.
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Reliability data is essential for a nuclear power plant probabilistic safety assessment by fault tree analysis to assess the performance of the safety-related systems. The limitation of conventional reliability data arises from insufficient historical data for probabilistic calculation. This study describes a new approach to calculate nuclear event reliability data by utilizing the concept of failure possibilities, which are expressed in qualitative natural languages, mathematically represented by membership functions of fuzzy numbers, and subjectively justified by a group of experts based on their working experience and expertise. We also propose an area defuzzification technique to convert the membership function into nuclear event reliability data. The actual event reliability data, which are collected from the operational experiences of the reactor protection system in Babcock & Wilcox pressurized water reactor between 1984 and 1998, are then compared with the reliability data calculated from the new approach. The results show that fuzzy failure rates can be used as alternatives for probabilistic failure rates when nuclear event historical data are insufficient or unavailable for probabilistic calculation. This study also confirms that our proposed area defuzzification technique is a suitable technique to defuzzify failure possibilities into nuclear event reliability data
Qiao, Y, Sarma, MNJ & Tang, B 2012, 'On Isomorphism Testing of Groups with Normal Hall Subgroups', Journal Of Computer Science And Technology, vol. 27, no. 4, pp. 687-701.
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A normal Hall subgroup N of a group G is a normal subgroup with its order coprime with its index. Schur-Zassenhaus theorem states that every normal Hall subgroup has a complement subgroup, that is a set of coset representatives H which also forms a subgroup of G. In this paper, we present a framework to test isomorphism of groups with at least one normal Hall subgroup, when groups are given as multiplication tables. To establish the framework, we first observe that a proof of Schur-Zassenhaus theorem is constructive, and formulate a necessary and sufficient condition for testing isomorphism in terms of the associated actions of the semidirect products, and isomorphisms of the normal parts and complement parts. We then focus on the case when the normal subgroup is abelian. Utilizing basic facts of representation theory of finite groups and a technique by Le Gall (STACS 2009), we first get an efficient isomorphism testing algorithm when the complement has bounded number of generators. For the case when the complement subgroup is elementary abelian, which does not necessarily have bounded number of generators, we obtain a polynomial time isomorphism testing algorithm by reducing to generalized code isomorphism problem, which asks whether two linear subspaces are the same up to permutation of coordinates. A solution to the latter can be obtained by a mild extension of the singly exponential (in the number of coordinates) time algorithm for code isomorphism problem developed recently by Babai et al. (SODA 2011). Enroute to obtaining the above reduction, we study the following computational problem in representation theory of finite groups: given two representations ? and t of a group H over
Qureshi, M 2012, 'Interoperability of Software Engineering Metamodels', Lecture Notes in Computer Science, vol. 7167, pp. 12-19.
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Several metamodels have been proposed in the software engineering literature recently. For practical usage, it is important to ensure that these metamodels can be used in an interoperable fashion. In this paper we present an approach as a part of our PhD research in the same direction. Our methodology is based on the study of analogous characteristics among metamodels, ontologies and schemas. We have adopted ontology merging and schema matching techniques and apply them to the domain of metamodels to assist in creating interoperable metamodels. This methodology is applied and presented here with an illustrative example in which we show the results of merging two of the OMG metamodels: the Organization Structure Metamodel (OSM) and the Business Process Modelling Notation (BPMN).
Raza, MR, Hussain, FK & Hussain, OK 2012, 'Neural Network-Based Approach for Predicting Trust Values Based on Non-uniform Input in Mobile Applications', Computer Journal, vol. 55, no. 3, pp. 347-378.
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Redshaw, S & Wilson, V 2012, 'Sibling involvement in childhood chronic heart disease through a bead program', Journal of Child Health Care, vol. 16, no. 1, pp. 53-61.
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In interviews with parents for the evaluation of a cardiac ward programme in a childrens hospital, a number of parents mentioned the role of the Heart Beads Program in including siblings in the hospitalisation of the child with congenital heart condition (CHD). Inclusion of siblings in the events surrounding the child with the cardiac condition was of two kinds: (a) touching and explaining about the beads and the childs condition and (b) involvement in collecting and threading the beads. Discussion of the needs of siblings suggests that inclusion of siblings in activities related to the care and understanding of the CHD child as well as the creation and shaping of the family narrative is important. These cases illustrate the different ways in which siblings are involved and acknowledged and how involvement can be facilitated by a programme like Heart Beads.
Scarfe, G, Redshaw, S, Wilson, V & Dengler, KA 2012, 'Heart to heart: a programme for children on a cardiac ward', British Journal of Nursing, vol. 21, no. 2, pp. 108-114.
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This paper presents three research case studies of children who have had surgery for a cardiac condition and discusses the experiences of the children and their families through their responses to the Heart Beads programme, as well as the insights gained by staff. The Children's Hospital at Westmead has a significant population of children with cardiac conditions. For many of these, diagnosis signals the beginning of a long, arduous journey with multiple procedures and admissions. The hospital has a family-centred care focus, and the cardiac ward undertook a project to implement and progress changes consistent with this approach. Staff developed the Heart Beads programme to enhance the care of children being treated for cardiac conditions. The programme involves children receiving distinct beads specific to each cardiac procedure, treatment, or event in recognition of their experience. A total of 7 staff members and 11 families were interviewed and particular stories were noted by staff. The case studies presented illustrated how nursing staff were able to recognize potential improvements to care and acknowledge the experiences of patients and families. Assumptions questioned as a result of the programme related to the complexity of the child's condition and gender. The death of a child and the acknowledgement of the child's life is also considered. Heart Beads allowed staff to reflect on the positive aspects of the care they provided
Somma, RD, Nagaj, D & Kieferová, M 2012, 'Quantum speedup by quantum annealing.', Physical review letters, vol. 109, no. 5, pp. 050501-050501.
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We study the glued-trees problem from A. M. Childs, R. Cleve, E. Deotto, E. Farhi, S. Gutmann, and D. Spielman, in Proceedings of the 35th Annual ACM Symposium on Theory of Computing (ACM, San Diego, CA, 2003), p. 59. in the adiabatic model of quantum computing and provide an annealing schedule to solve an oracular problem exponentially faster than classically possible. The Hamiltonians involved in the quantum annealing do not suffer from the so-called sign problem. Unlike the typical scenario, our schedule is efficient even though the minimum energy gap of the Hamiltonians is exponentially small in the problem size. We discuss generalizations based on initial-state randomization to avoid some slowdowns in adiabatic quantum computing due to small gaps.
Su, M-T, Lin, C-T & Hsu, K-W 2012, 'A NOVEL METHOD FOR LOCATING SOLDER JOINTS BASED ON MODIFIED BINARY POTENTIAL FUNCTION', INTERNATIONAL JOURNAL OF INNOVATIVE COMPUTING INFORMATION AND CONTROL, vol. 8, no. 1B, pp. 911-932.
Su, M-T, Lin, C-T, Hsu, S-C, Li, D-L, Lin, C-J & Chen, C-H 2012, 'Nonlinear System Control Using Functional-Link-Based Neuro-Fuzzy Network Model Embedded with Modified Particle Swarm Optimizer', INTERNATIONAL JOURNAL OF FUZZY SYSTEMS, vol. 14, no. 1, pp. 97-109.
Tao, W & Zhang, G 2012, 'Trusted interaction approach for dynamic service selection using a multi-criteria decision making technique', Knowledge-Based Systems, vol. 32, no. 1, pp. 116-122.
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Recent developments in information technology have shifted the computing paradigm in a more dynamic direction, and this has raised new challenges. In a dynamic computing environment, (1) the number of transacting entities is not fixed; (2) the relationship between these entities are very dynamic; (3) transacting entities may not necessarily have previous knowledge of each other; (4) the surrounding context may possibly constantly change; and, (5) it is possible that the transaction is conducted in fully a automatic approach. Based on these unique feature in a dynamic environment, we claim that two important challenges need to be resolved: one is transacting entities should be able to establish trusted interactions between each other, and another is transacting entities should be able to select the most suitable transacting entities by pre-programmed business rules and current context. Based on our previous research work on MobiPass, this paper proposes a technique which successfully solves the above two important research issues by using Multi Criteria Decision Making (MCDM) on top of the MobiPass framework, to help transacting entities select the most suitable transacting partners under a trusted interaction in dynamic environments in real time
van den Hoven, E, Sas, C & Whittaker, S 2012, 'Introduction to this Special Issue on Designing for Personal Memories: Past, Present, and Future', Human-Computer Interaction, vol. 27, no. 1-2, pp. 1-12.
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This special issue focuses on new uses of digital media to help people remember in everyday situations. We begin this introduction by describing the field's origins (personal memories past), using this to contextualise the papers presented here (personal memories present). We conclude by identifying a number of important research challenges that we feel must be addressed by future work in this area (personal memories future).
Verma, P, Singh, R & Kumar Singh, A 2012, 'A Framework for the Next Generation Screen Readers for Visually Impaired', International Journal of Computer Applications, vol. 47, no. 10, pp. 31-38.
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Despite shortcomings, Screen Readers have been the primary
tool for using internet by visually impaired. In this paper, we
present a framework for an advanced Screen Reader that aims
at eliminating the drawbacks that are associated with the
existing systems. The proposed framework makes the use of
informed search technique to enhance the usability and
navigability. Some of its features like background music to
appraise the layout structure of web page, mouse hovering to
speak out glimpses of the underlying text make the use of
image processing techniques. These features are implemented
independent of the rest development therefore they can also
be used to enhance any existing Screen Reader.
Vu, HQ, Liu, S, Yang, X, Li, Z & Ren, Y 2012, 'Identifying microphone from noisy recordings by using representative instance one class-classification approach', Journal of Networks, vol. 7, no. 6, pp. 908-917.
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Rapid growth of technical developments has created huge challenges for microphone forensics - a subcategory of audio forensic science, because of the availability of numerous digital recording devices and massive amount of recording data. Demand for fast and efficient methods to assure integrity and authenticity of information is becoming more and more important in criminal investigation nowadays. Machine learning has emerged as an important technique to support audio analysis processes of microphone forensic practitioners. However, its application to real life situations using supervised learning is still facing great challenges due to expensiveness in collecting data and updating system. In this paper, we introduce a new machine learning approach which is called One-class Classification (OCC) to be applied to microphone forensics; we demonstrate its capability on a corpus of audio samples collected from several microphones. In addition, we propose a representative instance classification framework (RICF) that can effectively improve performance of OCC algorithms for recording signal with noise. Experiment results and analysis indicate that OCC has the potential to benefit microphone forensic practitioners in developing new tools and techniques for effective and efficient analysis. © 2012 Academy Publisher.
Wang, J, Lu, H, Dong, Y & Chi, D 2012, 'The Model Of Chaotic Sequences Based On Adaptive Particle Swarm Optimization Arithmetic Combined With Seasonal Term', Applied Mathematical Modelling, vol. 36, no. 3, pp. 1184-1196.
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Within a competitive electric power market, electricity price is one of the core elements, which is crucial to all the market participants. Accurately forecasting of electricity price becomes highly desirable. This paper propose a forecasting model of el
Wang, X, Wang, Z & Xu, X 2012, 'Effective Service Composition in Large Scale Service Market: An Empirical Evidence Enhanced Approach', INTERNATIONAL JOURNAL OF WEB SERVICES RESEARCH, vol. 9, no. 1, pp. 74-94.
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Wang, Y, Xiang, Y, Zhou, W & Yu, S 2012, 'Generating regular expression signatures for network traffic classification in trusted network management', Journal of Network and Computer Applications, vol. 35, no. 3, pp. 992-1000.
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Network traffic classification is a critical foundation for trusted network management and security systems. Matching application signatures in traffic payload is widely considered to be the most reliable classifying method. However, deriving accurate and efficient signatures for various applications is not a trivial task, for which current practice is mostly manual thus error-prone and of low efficiency. In this paper, we tackle the problem of automatic signature generation. In particular, we focus on generating regular expression signatures with a certain subset of standard syntax rules, which are of sufficient expressive power and compatible with most practical systems. We propose a novel approach that takes as input a labeled training data set and produces a set of signatures for matching the application classes presented in the data. The approach involves four procedures: pre-processing to extract application session payload, tokenization to find common substrings and incorporate position constraints, multiple sequence alignment to find common subsequences, and signature construction to transform the results into regular expressions. A real life full payload traffic trace is used to evaluate the proposed system, and signatures for a range of applications are automatically derived. The results indicate that the signatures are of high quality, and exhibit low false negatives and false positives. © 2011 Elsevier Ltd. All rights reserved.
Wen, S, Zhou, W, Wang, Y, Zhou, W & Xiang, Y 2012, 'Locating defense positions for thwarting the propagation of topological worms', IEEE Communications Letters, vol. 16, no. 4, pp. 560-563.
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A common view for the preferable positions of thwarting worm propagation is at the highly connected nodes. However, in certain conditions, such as when some popular users (highly connected nodes in the network) have more vigilance on the malicious codes, this may not always be the truth. In this letter, we propose a measure of betweenness and closeness to locate the most suitable positions for slowing down the worm propagation. This work provides practical values to the defense of topological worms. © 1997-2012 IEEE.
Wen, S, Zhou, W, Xiang, Y & Zhou, W 2012, 'CAFS: A novel lightweight cache-based scheme for large-scale intrusion alert fusion', Concurrency Computation Practice and Experience, vol. 24, no. 10, pp. 1137-1153.
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In this paper, we present some practical experiences on implementing an alert fusion mechanism from our project. After investigation on most of the existing alert fusion systems, we found the current body of work alternatively weighed down in the mire of insecure design or rarely deployed because of their complexity. As confirmed by our experimental analysis, unsuitable mechanisms could easily be submerged by an abundance of useless alerts. Even with the use of methods that achieve a high fusion rate and low false positives, attack is also possible. To find the solution, we carried out analysis on a series of alerts generated by well-known datasets as well as realistic alerts from the Australian Honey-Pot. One important finding is that one alert has more than an 85% chance of being fused in the following five alerts. Of particular importance is our design of a novel lightweight Cache-based Alert Fusion Scheme, called CAFS. CAFS has the capacity to not only reduce the quantity of useless alerts generated by intrusion detection system, but also enhance the accuracy of alerts, therefore greatly reducing the cost of fusion processing. We also present reasonable and practical specifications for the target-oriented fusion policy that provides a quality guarantee on alert fusion, and as a result seamlessly satisfies the process of successive correlation. Our experiments compared CAFS with traditional centralized fusion. The results showed that the CAFS easily attained the desired level of simple, counter-escapable alert fusion design. Furthermore, as a lightweight scheme, CAFS can easily be deployed and excel in a large amount of alert fusions, which go towards improving the usability of system resources. To the best of our knowledge, our work is a practical exploration in addressing problems from the academic point of view. Copyright © 2011 John Wiley & Sons, Ltd.
Wu, Z, Xu, G, Zhang, Y, Cao, Z, Li, G & Hu, Z 2012, 'GMQL: A graphical multimedia query language', Knowledge-based Systems, vol. 26, pp. 135-143.
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The rapid increase of multimedia data makes multimedia query more and more important. To better satisfy users query requirements, developing a functional multimedia query language is becoming a promising and interesting task. In this paper, we propose a graphical multimedia query language called GMQL, which is developed based on a semi-structured data organization model. In GMQL, we combine the advantages of graphs and texts, making the query language much clear, easy to use and with powerful expressiveness. In this paper, we first present the notations and basic capabilities of GMQL by query examples. Second, we discuss the GMQL query processing techniques. Last, we evaluate and analyze our multimedia query language through the comparison with other existing multimedia query languages. The evaluation results show that, GMQL has powerful expressiveness, and thus is much applicable for multimedia information retrieval.
Wu, Z, Xu, G, Zhang, Y, Dolog, P & Lu, C 2012, 'An Improved Contextual Advertising Matching Approach Based On Wikipedia Knowledge', Computer Journal, vol. 55, no. 3, pp. 277-292.
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The current boom of the Web is associated with the revenues originated from Web advertising. As one prevalent type of Web advertising, contextual advertising refers to the placement of the most relevant commercial textual ads within the content of a Web
Wu, Z, Xu, G, Zong, Y, Yi, X, Chen, E & Zhang, Y 2012, 'Executing SQL queries over encrypted character strings in the Database-As-Service model', Knowledge-based Systems, vol. 35, pp. 332-348.
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Xiang, Y, Hu, J & Zhou, W 2012, 'Advances in network and system security', Concurrency Computation Practice and Experience, vol. 24, no. 10, pp. 1035-1036.
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Xiong, P & Zhu, T 2012, 'A data anonymization approach based on impurity gain and hierarchical clustering', Jisuanji Yanjiu yu Fazhan/Computer Research and Development, vol. 49, no. 7, pp. 1545-1552.
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Data anonymization is one of the important solutions to preserve privacy in data publishing. The basic concept of data anonymization and the application models are introduced, and the requirements that an anonymized dataset should meet are discussed. To resist the background knowledge attack, a new data anonymization approach based on impurity gain and hierarchical clustering is brought out. The impurity of a cluster is used to measure the randomicity of sensitive attributes, and the clusters' combination process is controlled by the restrictions that the information loss caused by generalization should be minimized and the impurity gain should be maximized. With the method, the anonymization results of a dataset can meet the requirements of k-anonymity model and l-diversity model, meanwhile, the information loss is minimized and the values of the sensitive attributes in each cluster has a uniform distribution. An evaluation method is provided in the experiment section, which compares anonymized dataset with the original one to evaluate the quality by calculating the average information loss and impurity. The experimental results validate the availability of the method.
Ye, D, Zhang, M & Sutanto, D 2012, 'Self-organization in an agent network: A mechanism and a potential application', Decision Support Systems, vol. 53, no. 3, pp. 406-417.
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Self-organization provides a suitable paradigm for developing self-managed complex computing systems, e.g., decision support systems. Towards this end, in this paper, a composite self-organization mechanism in an agent network is proposed. To intuitively elucidate this mechanism, a task allocation environment is simulated. Based on self-organization principles, this mechanism enables agents to dynamically adapt relations with other agents, i.e., to change the underlying network structure, so as to achieve efficient task allocation. The proposed mechanism utilizes a trust model to assist agents in reasoning with whom to adapt relations and employs a multi-agent Q-learning algorithm for agents to learn how to adapt relations. Moreover, in this mechanism, it is considered that the agents are connected by weighted relations, instead of crisp relations. The proposed mechanism is evaluated through a comparison with a centralized mechanism and the K-Adapt mechanism in both closed and open agent networks. Experimental results demonstrate the adequate performance of the proposed mechanism in terms of the entire network profit and time consumption. Additionally, a potential application scenario of this mechanism is also given, which exhibits the potential applicability of this mechanism in some real world cases. © 2012 Elsevier B.V. All rights reserved.
Yu, JX, Bian, W, Song, M, Cheng, JL & Tao, D 2012, 'Graph Based Transductive Learning For Cartoon Correspondence Construction', Neurocomputing, vol. 79, pp. 105-114.
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Correspondence construction of characters in key frames is the prerequisite for cartoon animations' automatic inbetweening and coloring. Since each frame of an animation consists of multiple layers, characters are complicated in terms of shape and struct
Yu, S, Zhou, W, Doss, R & Jia, W 2012, 'Traceback of DDoS attacks using entropy variations', IEEE Transactions on Parallel and Distributed Systems, vol. 23, no. 3, pp. 412-425.
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Distributed Denial-of-Service (DDoS) attacks are a critical threat to the Internet. However, the memoryless feature of the Internet routing mechanisms makes it extremely hard to trace back to the source of these attacks. As a result, there is no effective and efficient method to deal with this issue so far. In this paper, we propose a novel traceback method for DDoS attacks that is based on entropy variations between normal and DDoS attack traffic, which is fundamentally different from commonly used packet marking techniques. In comparison to the existing DDoS traceback methods, the proposed strategy possesses a number of advantagesit is memory nonintensive, efficiently scalable, robust against packet pollution, and independent of attack traffic patterns. The results of extensive experimental and simulation studies are presented to demonstrate the effectiveness and efficiency of the proposed method. Our experiments show that accurate traceback is possible within 20 seconds (approximately) in a large-scale attack network with thousands of zombies. © 2011 IEEE.
Yu, S, Zhou, W, Jia, W & Hu, J 2012, 'Attacking anonymous web browsing at local area networks through browsing dynamics', Computer Journal, vol. 55, no. 4, pp. 410-421.
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The majority of current anonymous systems focus on improving anonymity at the network and website level in order to defend against traffic analysis attacks. However, the vulnerability of the connections between end users and the anonymous network do not attract any attention yet. For the first time, we reveal an end user browsing dynamics based attack on anonymous browsing systems at the LAN where the victim locates. This new attack method is fundamentally different from existing attack methodologies. In general, web surfers browse the web following certain patterns, such as requesting a web page, viewing it and requesting another page. The browsing pattern of a victim can be clearly observed by a local adversary when the victim is viewing the web without protection. Unfortunately, browsing dynamics releases rich information for attacking even though the web page content is encrypted. In order to show how a local eavesdropper can decipher which pages have been viewed with the knowledge of user browsing dynamics and the public information of a given website, we established a specific hidden Markov model to represent browsing dynamics for the website. By using this model, we can then identify the optimal of the accessed pages using the Viterbi algorithm. In order to confirm the effectiveness of the revealed attack method, we have conducted extensive experiments on a real data set. The results demonstrated that the attack accuracy can be more than 80. A few possible counter-attack strategies are discussed at the end of the paper. © 2011 The Author. Published by Oxford University Press on behalf of The British Computer Society. All rights reserved.
Yu, S, Zhou, W, Jia, W, Guo, S, Xiang, Y & Tang, F 2012, 'Discriminating DDoS attacks from flash crowds using flow correlation coefficient', IEEE Transactions on Parallel and Distributed Systems, vol. 23, no. 6, pp. 1073-1080.
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Distributed Denial of Service (DDoS) attack is a critical threat to the Internet, and botnets are usually the engines behind them. Sophisticated botmasters attempt to disable detectors by mimicking the traffic patterns of flash crowds. This poses a critical challenge to those who defend against DDoS attacks. In our deep study of the size and organization of current botnets, we found that the current attack flows are usually more similar to each other compared to the flows of flash crowds. Based on this, we proposed a discrimination algorithm using the flow correlation coefficient as a similarity metric among suspicious flows. We formulated the problem, and presented theoretical proofs for the feasibility of the proposed discrimination method in theory. Our extensive experiments confirmed the theoretical analysis and demonstrated the effectiveness of the proposed method in practice. © 1990-2012 IEEE.
Yu, Y, Li, K, Zhou, W & Li, P 2012, 'Trust mechanisms in wireless sensor networks: Attack analysis and countermeasures', Journal of Network and Computer Applications, vol. 35, no. 3, pp. 867-880.
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As the trust issue in wireless sensor networks is emerging as one important factor in security schemes, it is necessary to analyze how to resist attacks with a trust scheme. In this paper we categorize various types of attacks and countermeasures related to trust schemes in WSNs. Furthermore, we provide the development of trust mechanisms, give a short summarization of classical trust methodologies and emphasize the challenges of trust scheme in WSNs. An extensive literature survey is presented by summarizing state-of-the-art trust mechanisms in two categories: secure routing and secure data. Based on the analysis of attacks and the existing research, an open field and future direction with trust mechanisms in WSNs is provided. © 2011 Elsevier Ltd. All rights reserved.
Zhang, C, Bian, W, Tao, D & Weisi, L 2012, 'Discretized-Vapnik-Chervonenkis Dimension For Analyzing Complexity Of Real Function Classes', IEEE Transactions On Neural Networks And Learning Systems, vol. 23, no. 9, pp. 1461-1472.
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In this paper, we introduce the discretized-Vapnik-Chervonenkis (VC) dimension for studying the complexity of a real function class, and then analyze properties of real function classes and neural networks. We first prove that a countable traversal set i
Zhang, G, Xu, Y & Li, T 2012, 'A special issue on new trends in Intelligent Decision Support Systems', KNOWLEDGE-BASED SYSTEMS, vol. 32, pp. 1-2.
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Zhang, G, Yang, YL & Chen, JF 2012, 'A Historical Probability Based Noise Generation Strategy For Privacy Protection In Cloud Computing', Journal of Computer and System Sciences, vol. 78, no. 5, pp. 1374-1381.
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Cloud computing promises an open environment where customers can deploy IT services in pay-as-you-go fashion while saving huge capital investment in their own IT infrastructure. Due to the openness, various malicious service providers can exist. Such ser
Zhang, J, Chen, C, Xiang, Y & Zhou, W 2012, 'Semi-supervised and compound classification of network traffic', International Journal of Security and Networks, vol. 7, no. 4, pp. 252-261.
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This paper presents a new semi-supervised method to effectively improve traffic classification performance when very few supervised training data are available. Existing semisupervised methods label a large proportion of testing flows as unknown flows due to limited supervised information, which severely affects the classification performance. To address this problem, we propose to incorporate flow correlation into both training and testing stages. At the training stage, we make use of flow correlation to extend the supervised data set by automatically labelling unlabelled flows according to their correlation to the pre-labelled flows. Consequently, a traffic classifier achieves excellent performance because of the enhanced training data set. At the testing stage, the correlated flows are identified and classified jointly by combining their individual predictions, so as to further boost the classification accuracy. The empirical study on the real-world network traffic shows that the proposed method significantly outperforms the state-of-the-art flow statistical feature based classification methods. Copyright © 2012 Inderscience Enterprises Ltd.
Zhang, TT, Zhang, G, Lu, J, Feng, X & Yang, W 2012, 'A New Index And Classification Approach For Load Pattern Analysis Of Large Electricity Customers', IEEE Transactions on Power Systems, vol. 27, no. 1, pp. 153-160.
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Conducting load pattern analysis is an important task in obtaining typical load profiles (TLPs) of customers and grouping them into classes according to their load characteristics. When using clustering techniques to obtain the load patterns of electrici
Zhang, W, Lin, X, Zhang, Y, Cheema, MA & Zhang, Q 2012, 'Stochastic Skylines', ACM Transactions on Database Systems, vol. 37, no. 2, pp. 1-34.
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In many applications involving multiple criteria optimal decision making, users may often want to make a personal trade-off among all optimal solutions for selecting one object that fits best their personal needs. As a key feature, the skyline in a multidimensional space provides the minimum set of candidates for such purposes by removing all points not preferred by any (monotonic) utility/scoring functions; that is, the skyline removes all objects not preferred by any user no matter how their preferences vary. Driven by many recent applications with uncertain data, the probabilistic skyline model is proposed to retrieve uncertain objects based on skyline probabilities. Nevertheless, skyline probabilities cannot capture the preferences of monotonic utility functions. Motivated by this, in this article we propose a novel skyline operator, namely stochastic skylines. In the light of the expected utility principle, stochastic skylines guarantee to provide the minimum set of candidates to optimal solutions over a family of utility functions. We first propose the lskyline operator based on the lower orthant orders. lskyline guarantees to provide the minimum set of candidates to the optimal solutions for the family of monotonic multiplicative utility functions. While lskyline works very effectively for the family of multiplicative functions, it may miss optimal solutions for other utility /scoring functions (e.g., linear functions). To resolve this, we also propose a general stochastic skyline operator, gskyline, based on the usual orders. gskyline provides the minimum candidate set to the optimal solutions for all monotonic functions.
Zhang, Y, Lin, X, Tao, Y, Zhang, W & Wang, H 2012, 'Efficient Computation of Range Aggregates against Uncertain Location-Based Queries', IEEE Transactions On Knowledge And Data Engineering, vol. 24, no. 7, pp. 1244-1258.
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In many applications, including location-based services, queries may not be precise. In this paper, we study the problem of efficiently computing range aggregates in a multidimensional space when the query location is uncertain. Specifically, for a query point Q whose location is uncertain and a set S of points in a multidimensional space, we want to calculate the aggregate (e.g., count, average and sum) over the subset S' of S such that for each p ? S', Q has at least probability ? within the distance ? to p. We propose novel, efficient techniques to solve the problem following the filtering-and-verification paradigm. In particular, two novel filtering techniques are proposed to effectively and efficiently remove data points from verification. Our comprehensive experiments based on both real and synthetic data demonstrate the efficiency and scalability of our techniques.
Zhang, Z, Cheng, J, Li, J, Bian, W & Tao, D 2012, 'Segment-Based Features for Time Series Classification', Computer Journal, vol. 55, no. 9, pp. 1088-1102.
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In this paper, we propose an approach termed segment-based features (SBFs) to classify time series. The approach is inspired by the success of the component- or part-based methods of object recognition in computer vision, in which a visual object is described as a number of characteristic parts and the relations among the parts. Utilizing this idea in the problem of time series classification, a time series is represented as a set of segments and the corresponding temporal relations. First, a number of interest segments are extracted by interest point detection with automatic scale selection. Then, a number of feature prototypes are collected by random sampling from the segment set, where each feature prototype may include single segment or multiple ordered segments. Subsequently, each time series is transformed to a standard feature vector, i.e. SBF, where each entry in the SBF is calculated as the maximum response (maximum similarity) of the corresponding feature prototype to the segment set of the time series.
Agmon, N, Agrawal, V, Aha, DW, Aloimonos, Y, Buckley, D, Doshi, P, Geib, C, Grasso, F, Green, N, Johnston, B, Kaliski, B, Kiekintveld, C, Law, E, Lieberman, H, Mengshoel, OJ, Metzler, T, Modayil, J, Oard, DW, Onder, N, O'Sullivan, B, Pastra, K, Precup, D, Ramachandran, S, Reed, C, Sariel-Talay, S, Selker, T, Shastri, L, Singh, S, Smith, SF, Srivastava, S, Sukthankar, G, Uthus, DC & Williams, MA 2012, 'Reports of the AAAI 2011 conference workshops', AI Magazine, pp. 57-70.
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The AAAI-11 workshop program was held Sunday and Monday, August 7-18, 2011, at the Hyatt Regency San Francisco in San Francisco, California USA. The AAAI-11 workshop program included 15 workshops covering a wide range of topics in artificial intelligence. The titles of the workshops were Activity Context Representation: Techniques and Languages; Analyzing Microtext; Applied Adversarial Reasoning and Risk Modeling; Artificial Intelligence and Smarter Living: The Conquest of Complexity; Artifiicial Intelligence for Data Center Management and Cloud Computing; Automated Action Planning for Autonomous Mobile Robots; Computational Models of Natural Argument; Generalized Planning; Human Computation; Human-Robot Interaction in Elder Care; Interactive Decision Theory and Game Theory, 2010; Language-Action Tools for Cognitive Artificial Agents: Integrating Vision, Action, and Language; Lifelong Learning from Sensorimotor Experience; Plan, Activity, and Intent Recognition; and Scalable Integration of Analytics and Visualization. This article presents short summaries of those events. Copyright © 2012, Association for the Advancement of Artificial Intelligence. All rights reserved.
Ahad, MT, Dyson, LE & Gay, VC 2012, 'Towards an M-banking Framework for Rural SMEs in Bangladesh', Proceedings of the 19th IBIMA Conference on Innovation Vision 2020, International Business Information Management, International Business Information Management Association, Barcelona, Spain, pp. 1153-1164.
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This research aims at discovering factors which impact on the intention of rural SME owners and managers to adopt m-banking in Bangladesh. Over the last ten years, a wide spectrum of mbanking frameworks has emerged that offers new insights into the adoption and acceptance of mbanking. However, m-banking has still not been extended to rural Bangladesh. To fill the gap this research surveyed 550 SMEs owners/managers in four rural villages. The result indicates that poor banking facilities, cost, credibility, gender, education and SME category are the main factors that significantly influence the intention to adopt m-banking. The analysis introduces three factors which have been largely overlooked in prior literature. The study broadens our understanding of m-banking and provides insights into developing m-banking strategies in Bangladesh. This research will be of potential value in accelerating the development of m-banking in Bangladesh
An, H, Lu, J & Zhang, G 2012, 'A JUDGEMENT METHOD FOR EARTHQUAKE EARLY WARNING INFORMATION', The 10th International FLINS Conference on Uncertainty Modeling in Knowledge Engineering and Decision Making (FLINS 2012), International Fuzzy Logic and Intelligent technologies in Nuclear Science Conference, World Scientific, Istanbul, Turkey, pp. 333-338.
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Earthquake early warning (EEW) is very important to earthquake mitigation, but EEW information before an earthquake is usually ignored. China Public Safety Early Warning Information Systems (CPSEWIS) including EEW information before, amid and after an earthquake is introduced. More important is that a method is designed to judge credibility of EEW information and help people mitigate
Ariffin, SA & Dyson, LE 2012, 'Student perspectives on mLearning for local cultural studies in Malaysia', Proceedings for CATAC 2012 (Cultural Attitudes Towards Technology and Communications), Cultural Attitudes towards Technology and Communications, Murdoch University Australia, Aarhus, Denmark, pp. 135-145.
Babai, L & Qiao, Y 2012, 'Polynomial-time Isomorphism Test for Groups with Abelian Sylow Towers', 29th Symposium on Theoretical Aspects of Computer Science, Symposium on Theoretical Aspects of Computer Science, Dagstuhl Publishing, Paris, France, pp. 453-465.
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We consider the problem of testing isomorphism of groups of order n given by Cayley tables. The trivial n^{log n} bound on the time complexity for the general case has not been improved over the past four decades. Recently, Babai et al. (following Babai et al. in SODA 2011) presented a polynomial-time algorithm for groups without abelian normal subgroups, which suggests solvable groups as the hard case for group isomorphism problem. Extending recent work by Le Gall (STACS 2009) and Qiao et al. (STACS 2011), in this paper we design a polynomial-time algorithm to test isomorphism for the largest class of solvable groups yet, namely groups with abelian Sylow towers, defined as follows. A group G is said to possess a Sylow tower, if there exists a normal series where each quotient is isomorphic to Sylow subgroup of G. A group has an abelian Sylow tower if it has a Sylow tower and all its Sylow subgroups are abelian. In fact, we are able to compute the coset of isomorphisms of groups formed as coprime extensions of an abelian group, by a group whose automorphism group is known. The mathematical tools required include representation theory, Wedderburn's theorem on semisimple algebras, and M.E. Harris's 1980 work on p'-automorphisms of abelian p-groups. We use tools from the theory of permutation group algorithms, and develop an algorithm for a parameterized versin of the graph-isomorphism-hard setwise stabilizer problem, which may be of independent interest
Babai, L, Codenotti, P & Qiao, Y 2012, 'Polynomial-Time Isomorphism Test for Groups with No Abelian Normal Subgroups', LNCS - Automata, Languages, and Programming - Proceedings, Part I of the 39th International Colloquium on Automata, Languages and Programming, International Colloquium on Automata Languages and Programming, Springer, Warwick, UK, pp. 51-62.
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We consider the problem of testing isomorphism of groups of order n given by Cayley tables. The trivial n logn bound on the time complexity for the general case has not been improved upon over the past four decades. We demonstrate that the obstacle to efficient algorithms is the presence of abelian normal subgroups; we show this by giving a polynomial-time isomorphism test for groups without nontrivial abelian normal subgroups. This concludes a project started by the authors and J. A. Grochow (SODA 2011). Two key new ingredient are: (a) an algorithm to test permutational isomorphism of permutation groups in time, polynomial in the order and simply exponential in the degree; (b) the introduction of the twisted code equivalence problem, a generalization of the classical code equivalence problem by admitting a group action on the alphabet. Both of these problems are of independent interest
Bakker, S, van den Hoven, E & Eggen, B 2012, 'FireFlies: Supporting Primary School Teachers through Open-Ended Interaction Design', Proceedings of the 24th Australian Computer-Human Interaction Conference (OzCHI2012), Australian Computer Human Interaction Conference, ACM, Melbourne, pp. 26-29.
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Primary school teachers usually perform several tasks simultaneously. Many secondary tasks, such as giving turns or encouraging children to work silently, could be supported by interactive systems, which may lighten the teacher's busy everyday routine. Such systems however, should afford being interacted with while performing another primary task. We call this type of design peripheral interaction design. In this paper we present FireFlies, an open-ended peripheral interaction design developed for primary schools. Preliminary results of a six week deployment of FireFlies in four classrooms, reveal that teachers used FireFlies to perform secondary tasks and saw it as a valuable addition to the classroom. Though different interactions with FireFlies required different levels of effort, teachers could successfully interact with FireFlies during or in between other tasks.
Bakker, S, van den Hoven, E, Eggen, B & Overbeeke, K 2012, 'Exploring peripheral interaction design for primary school teachers', Proceedings of the Sixth International Conference on Tangible, Embedded and Embodied Interaction, Tangible, Embedded, and Embodied Interaction, ACM, Kingston, Canada, pp. 245-252.
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This paper explores the concept of peripheral interactions; interactions with technology that take place in the background or periphery of the attention. We present two designs for a classroom setting. CawClock makes selected time frames audible in order to provide teachers with awareness of time. NoteLet is designed to support the teacher in observing children's behavior, by enabling him or her to take pictures of the classroom through straightforward interactions on a bracelet. A qualitative, two-week exploration of both systems in a classroom revealed that the soundscapes of CawClock indeed shifted to the periphery of the attention and supported the teacher's time awareness. The actions with NoteLet did not shift to the periphery. However, the tangible aspects of NoteLet seemed to facilitate the interaction to be quick and simple, which may indicate that it could shift to the periphery with more practice. Tangible interaction therefore seems a promising interaction style for this purpose.
Bian, W, Xie, B & Tao, D 2012, 'CorrLog: Correlated Logistic Models for Joint Prediction of Multiple Labels', Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics, International Conference on Artificial Intelligence and Statistics, the MIT Press, La Palma, Canary Islands, pp. 109-117.
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In this paper, we present a simple but effective method for multi-label classification (MLC), termed Correlated Logistic Models (Corrlog), which extends multiple Independent Logistic Regressions (ILRs) by modeling the pairwise correlation between labels. Algorithmically, we propose an efficient method for learning parameters of Corrlog, which is based on regularized maximum pseudolikelihood estimation and has a linear computational complexity with respect to the number of labels. Theoretically, we show that Corrlog enjoys a satisfying generalization bound which is independent of the number of labels. The effectiveness of Corrlog on modeling label correlations is illustrated by a toy example, and further experiments on real data show that Corrlog achieves competitive performance compared with popular MLC algorithms.
Bogdanovych, A, Stanton, CJ, Wang, X & Williams, M 2012, 'Real-Time Human-Robot Interactive Coaching System with Full-Body Control Interface', Lecture Notes in Computer Science, RoboCup Symposium held in Conjunction with the RoboCup Competition, Springer, Istanbul, Turkey, pp. 562-573.
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The ambitious goal being pursued by researchers participating in the RoboCup challenge [8] is to develop a team of autonomous humanoid robots that is capable of winning against a team of human soccer players. An important step in this direction is to actively utilise human coaching to improve the skills of robots at both tactical and strategic levels. In this paper we explore the hypothesis that embedding a human into a robots body and allowing the robot to learn tactical decisions by imitating the human coach can be more efficient than programming the robot explicitly. To enable this, we have developed a sophisticated HRI system that allows a human to interact with, coach and control an Aldebaran Nao robot through the use of a motion capture suit, portable computing devices (iPhone and iPad), and a head mounted display (which allows the human controller to experience the robots visual perceptions of the world). This paper describes the HRI-Coaching system we have developed, detailing the underlying technologies and lessons learned from using it to control the robot. The system in its current stages shows high potential for human-robot coaching, but requires further calibration and development to allow a robot to learn by imitating the human coach.
Bommes, D, Lévy, B, Pietroni, N, Puppo, E, Silva, CT, Tarini, M & Zorin, D 2012, 'Quad Meshing.', Eurographics (STARs), pp. 159-182.
Bressan, N, James, A & McGregor, C 2012, 'Trends and opportunities for integrated real time neonatal clinical decision support', Proceedings - IEEE-EMBS International Conference on Biomedical and Health Informatics: Global Grand Challenge of Health Informatics, BHI 2012, pp. 687-690.
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Neonatal Intensive Care Unit maintain and support life during the critical period of premature development. This research presents the challenges, trends and opportunities for integrated real time neonatal clinical decision support. We demonstrated this potential using environment known as Artemis, a clinical decision support system. A review of the current devices in the intensive care unit and neonatal practice shows the current environment and our perspective for the future of the neonatal clinical decision support. The study demonstrates that Artemis will be able to incorporate new data streams from infusion pumps, EEG monitors and cerebral oxygenation monitors innovating the practice and improving the clinical support. © 2012 IEEE.
Budka, M, Musial, K & Juszczyszyn, K 2012, 'Predicting the evolution of social networks: Optimal time window size for increased accuracy', Proceedings - 2012 ASE/IEEE International Conference on Privacy, Security, Risk and Trust and 2012 ASE/IEEE International Conference on Social Computing, SocialCom/PASSAT 2012, pp. 21-30.
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This study investigates the data preparation process for predictive modelling of the evolution of complex networked systems, using an e - mail based social network as an example. In particular, we focus on the selection of optimal time window size for building a time series of network snapshots, which forms the input of chosen predictive models. We formulate this issue as a constrained multi - objective optimization problem, where the constraints are specific to a particular application and predictive algorithm used. The optimization process is guided by the proposed Windows Incoherence Measures, defined as averaged Jensen-Shannon divergences between distributions of a range of network characteristics for the individual time windows and the network covering the whole considered period of time. The experiments demonstrate that the informed choice of window size according to the proposed approach allows to boost the prediction accuracy of all examined prediction algorithms, and can also be used for optimally defining the prediction problems if some flexibility in their definition is allowed. © 2012 IEEE.
Cai, H, Liu, B, Gui, L & Wu, MY 2012, 'Neighbor discovery algorithms in wireless networks using directional antennas', IEEE International Conference on Communications, pp. 767-772.
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Directional antennas provide great performance improvement for wireless networks, such as increased network capacity and reduced energy consumption. Nonetheless new media access and routing protocols are required to control the directional antenna system. One of the most important protocols is neighbor discovery, which is aiming at setting up links between nodes and their neighbors. In the past few years, a number of algorithms have been proposed for neighbor discovery with directional antennas. However, most of them cannot work efficiently when taking into account the collision case that more than one node exist in one directional beam. For practical considerations, we propose a new neighbor discovery algorithm to overcome this shortcoming. Moreover, we present a novel and practical mathematical model to analyze the performance of neighbor discovery algorithms considering collision effects. Numerical results clearly show our new algorithm always requires less time to discover the whole neighbors than previous ones. To the best of our knowledge, it is the first complete, practical analytical model that incorporates directional neighbor discovery algorithms. © 2012 IEEE.
Chan, J, Liu, W, Leckie, C, Bailey, J & Ramamohanarao, K 2012, 'SeqiBloc: Mining multi-time spanning blockmodels in dynamic graphs', Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 651-659.
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Blockmodelling is an important technique for decomposing graphs into sets of roles. Vertices playing the same role have similar patterns of interactions with vertices in other roles. These roles, along with the role to role interactions, can succinctly summarise the underlying structure of the studied graphs. As the underlying graphs evolve with time, it is important to study how their blockmodels evolve too. This will enable us to detect role changes across time, detect different patterns of interactions, for example, weekday and weekend behaviour, and allow us to study how the structure in the underlying dynamic graph evolves. To date, there has been limited research on studying dynamic blockmodels. They focus on smoothing role changes between adjacent time instances. However, this approach can overfit during stationary periods where the underling structure does not change but there is random noise in the graph. Therefore, an approach to a) find blockmodels across spans of time and b) to find the stationary periods is needed. In this paper, we propose an information theoretic framework, SeqiBloc, combined with a change point detection approach to achieve a) and b). In addition, we propose new vertex equivalence definitions that include time, and show how they relate back to our information theoretic approach. We demonstrate their usefulness and superior accuracy over existing work on synthetic and real datasets. © 2012 ACM.
Chang, JY, Han, MF & Lin, CT 2012, 'Optimization of fuzzy systems using group-based evolutionary algorithm', Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), International Conference on Neural Information Processing, Springer, Doha, Qatar, pp. 291-298.
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This paper proposes a group-based evolutionary algorithm (GEA) for the fuzzy system (FS) optimization. Initially, we adopt an entropy measure method to determine the number of rules. Fuzzy rules are automatically generated from training data by entropy measure. Subsequently, the GEA is performed to optimize all the free parameters for the FS design. In the evolution process, a FS is coded as an individual. All individuals based on their performance are partitioned into a superior group and an inferior group. The superior group, which is composed of individuals with better performance, uses a global evolution operation to search potential individuals. In the inferior group, individuals with a worse performance employ the local evolution operation to search better individuals near the current best individual. Finally, the proposed FS with GEA model (FS-GEA) is applied to time series forecasting problem. Results show that the proposed FS-GEA model obtains better performance than other algorithm. © 2012 Springer-Verlag.
Chang, J-Y, Liao, S-H & Lin, C-T 2012, 'Adaptive Least Trimmed Squares Fuzzy Neural Network', 2012 INTERNATIONAL CONFERENCE ON FUZZY THEORY AND ITS APPLICATIONS (IFUZZY2012), International Conference on Fuzzy Theory and Its Applications (iFUZZY), IEEE, Natl Chung Hsing Univ, Taichung, TAIWAN, pp. 413-416.
Chen, S & Williams, M 2011, 'An ontological study of data purpose for privacy policy enforcement', The Third IEEE International Conference on Privacy, Security, Risk and Trust, IEEE International Conference on Privacy, Security, Risk and Trust, IEEE,CPS, Boston, MA, USA, pp. 1208-1213.
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Data purpose is a central concept in modeling privacy requirements. Existing purpose-based approaches for privacy protection have mainly focused on access control. The problem of ensuring the consistency between data purpose and data usage has been under-addressed. In an attempt to bridge this research gap, we develop a grounded understanding of data purpose and relevant key concepts that is fundamental to address the problem. We propose a Minimum Action Permission Principle as a basic guideline to establish a path to solutions to the consistency problem.
Chen, S & Williams, M 2012, 'Information Makes A Difference For Privacy Design', PACIS 2012 PROCEEDINGS, Pacific Asia Conference on Information Systems, PACIS, Ho Chi Minh City, pp. 1-13.
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In the current information age, information can make a difference to all aspects of ones life, emotionally, ethically, financially or societally. Information privacy plays a key role in enabling a difference in many dimensions such as trust, respect, reputation, security, resource, ability, employment, etc. The capability of information to make a difference to ones life is a fundamental factor; and privacy status of information is a key factor driving this difference. Understanding the impact of these two factors to ones life within an IS context is an important research gap in the discipline. This paper studies information + privacy, ontologically and integrally, in making a difference to ones life, within the IS context. In recognition of the importance of the Privacy-by- Design approach to IS development, a methodology is proposed to understand the grounds of information and model fundamental constructs for using Privacy-by-Design approach to develop robust privacy-friendly information systems
Chen, SH, Lin, CT & Fu, LC 2012, 'Second order sliding mode control on task-space of a 6-DOF Stewart platform', IECON Proceedings (Industrial Electronics Conference), Annual Conference of the IEEE Industrial Electronics Society, IEEE, Institute of Electrical and Electronics Engineers, Montreal, QC, Canada, pp. 2482-2487.
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In this paper, the second order sliding mode control strategy is applied on a 6-dof parallel manipulator, so-called Stewart platform. The advantages such as robustness and design simplicity of sliding mode control are the main reason that it was often used on robotic systems. However, the chattering phenomenon of conventional sliding mode control may cause unstability due to the practical implementations of the switching control. As a result of discontinuous control signal, the chattering phenomenon can be eliminated via designing a higher order control strategy. Once the switching signal is designed in higher order manifold, the real input will be smoothed because of the integration. The paper represents a robustness control method without chattering for Stewart platform which is a multi-input nonlinear system. The control performance of the second-order approach was compared to conventional sliding mode control in the simulation results. © 2012 IEEE.
Chen, X, Li, L, Xu, G, Yang, Z, Kitsuregawa, M & Xiao, H 2012, 'Recommending Related Microblogs: A Comparison Between Topic and WordNet based Approaches', Proceedings of the Twenty-Sixth AAAI Conference on Artificial Intelligence, AAAI Conference on Artificial Intelligence, AAAI Press, Toronto, pp. 2417-2418.
Chuang, CH, Huang, CS, Lin, CT, Ko, LW, Chang, JY & Yang, JM 2012, 'Mapping information flow of independent source to predict conscious level: A granger causality based brain-computer interface', Proceedings - 2012 International Symposium on Computer, Consumer and Control, IS3C 2012, pp. 813-816.
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Recent studies have shown that the various brain networks over different cognitive states. In contrast to measure a physiological change over a single region, the information flows between brain regions described by effective connectivity provides an informative dynamic over the whole brain. In this study, we proposed a source information flow network based on the combination of Granger causality and support vector regression to predict driver's conscious level. This work provides the first application of using brain network to develop a brain-computer interface and obtain a sound result of performance. © 2012 IEEE.
Corney, M, Teague, D, Ahadi, A & Lister, RF 2012, 'Some Empirical Results for Neo-Piagetian Reasoning in Novice Programmers and the Relationship to Code Explanation Questions', Fourteenth Australasian Computing Education Conference (ACE2012), Australasian Computing Education Conference, Australian Computer Society Inc, Melbourne, Australia, pp. 77-86.
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Abstract: Recent research on novice programmers has suggested that they pass through neo-Piagetian stages: sensorimotor, preoperational, and concrete operational stages, before eventually reaching programming competence at the formal operational stage. This paper presents empirical results in support of this neo-Piagetian perspective. The major novel contributions of this paper are empirical results for some exam questions aimed at testing novices for the concrete operational abilities to reason with quantities that are conserved, processes that are reversible, and properties that hold under transitive inference. While the questions we used had been proposed earlier by Lister, he did not present any data for how students performed on these questions. Our empirical results demonstrate that many students struggle to answer these problems, despite the apparent simplicity of these problems. We then compare student performance on these questions with their performance on six explain in plain English questions.
Demong, NA, Lu, J & Hussain, FK 2012, 'Multidimensional Analysis and Data Mining for Property Investment Risk Analysis', International Conference on Information Systems (ICIS 2012), International Conference on Information Systems, World Academy of Science, Engineering and Technology, Penang, Malaysia, pp. 118-123.
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Property investment in the real estate industry has a high risk due to the uncertainty factors that will affect the decisions made and high cost. Analytic hierarchy process has existed for some time in which referred to an expertâs opinion to measure the uncertainty of the risk factors for the risk analysis. Therefore, different level of expertsâ experiences will create different opinion and lead to the conflict among the experts in the field. The objective of this paper is to propose a new technique to measure the uncertainty of the risk factors based on multidimensional data model and data mining techniques as deterministic approach. The propose technique consist of a basic framework which includes four modules: user, technology, end-user access tools and applications. The property investment risk analysis defines as a micro level analysis as the features of the property will be considered in the analysis in this paper.
Di, P, Ye, D, Su, Y, Sui, Y & Xue, J 2012, 'Automatic parallelization of tiled loop nests with enhanced fine-grained parallelism on GPUs', Proceedings of the International Conference on Parallel Processing, pp. 350-359.
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Automatically parallelizing loop nests into CUDA kernels must exploit the full potential of GPUs to obtain high performance. One state-of-the-art approach makes use of the polyhedral model to extract parallelism from a loop nest by applying a sequence of affine transformations to the loop nest. However, how to automate this process to exploit both intra and inter-SM parallelism for GPUs remains a challenging problem. Presently, compilers may generate code significantly slower than hand-optimized code for certain applications. This paper describes a compiler framework for tiling and parallelizing loop nests with uniform dependences into CUDA code. We aim to improve two levels of wave front parallelism. We find tiling hyper planes by embedding parallelism enhancing constraints in the polyhedral model to maximize intra-tile, i.e., intra-SM parallelism. This improves the load balance among the SPs in an SM executing a wave front of loop iterations within a tile. We eliminate parallelism-hindering false dependences to maximize inter-tile, i.e., inter-SM parallelism. This improves the load balance among the SMs executing a wave front of tiles. Our approach has been implemented in PLUTO and validated using eight benchmarks on two different NVIDIA GPUs (C1060 and C2050). Compared to PLUTO, our approach achieves 2 - 5.5X speedups across the benchmarks. Compared to highly hand-optimized 1-D Jacobi (3 points), 2-D Jacobi (5 points), 3-D Jacobi (7 points) and 3-D Jacobi (27 points), our speedups, 1.17X, 1.41X, 0.97X and 0.87X with an average of 1.10X on C1060 and 1.24X, 1.20X, 0.86X and 0.95X with an average of 1.06X on C2050, are competitive. © 2012 IEEE.
Dong, H, Hussain, FK & Chang, E 2012, 'Ontology-Learning-Based Focused Crawling for Online Service Advertising Information Discovery and Classification', Proceedings of the 10th International Conference on Service-Oriented Computing, 10th International Conference on Service-Oriented Computing, Springer Verlag, Shanghai, China, pp. 591-598.
Dong, H, Hussain, FK & Chang, E 2012, 'Ontology-Learning-Based Focused Crawling for Online Service Advertising Information Discovery and Classification', Lecture Notes in Computer Science, International Conference on Service Oriented Computing, Springer-Verlag, Shanghai, China, pp. 591-598.
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Online advertising has become increasingly popular among SMEs in service industries, and thousands of service advertisements are published on the Internet every day. However, there is a huge barrier between service-provider-oriented service information publishing and service-customer-oriented service information discovery, which causes that service consumers hardly retrieve the published service advertising information from the Internet. This issue is partly resulted from the ubiquitous, heterogeneous, and ambiguous service advertising information and the open and shoreless Web environment. The existing research, nevertheless, rarely focuses on this research problem. In this paper, we propose an ontology-learning-based focused crawling approach, enabling Web-crawler-based online service advertising information discovery and classification in the Web environment, by taking into account the characteristics of service advertising information. This approach integrates an ontology-based focused crawling framework, a vocabulary-based ontology learning framework, and a hybrid mathematical model for service advertising information similarity computation.
Doss, R & Zhou, W 2012, 'A secure tag ownership transfer scheme in a closed loop RFID system', 2012 IEEE Wireless Communications and Networking Conference Workshops, WCNCW 2012, pp. 164-169.
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In this paper we propose a novel secure tag ownership transfer scheme for closed loop RFID systems. An important property of our method is that the ownership transfer is guaranteed to be atomic and the scheme is protected against desynchronisation leading to permanent DoS. Further, it is suited to the computational constraints of EPC Class-1 Gen-2 passive RFID tags as they only use the CRC and PRNG functions that passive RFID tags are capable of. We provide a detailed security analysis to show that our scheme satisfies the required security properties of tag anonymity, tag location privacy, forward secrecy, forward untraceability while being resistant to replay, desynchronisation and server impersonation attacks. Performance comparisons show that our scheme is practical and can be implemented on passive low-cost RFID tags. © 2012 IEEE.
Enokido, T & Hussain, F 2012, 'Message from the 3PGCIC 2012 Workshops Co-chairs', Proceedings - 2012 7th International Conference on P2P, Parallel, Grid, Cloud and Internet Computing, 3PGCIC 2012.
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Esfijani, A, Hussain, FK & Chang, E 2012, 'An Approach to University Social Responsibility Ontology Development through Text Analyses', Human System Interactions (HSI), 2012 5th International Conference on, International Conference on Human System Interactions (HSI), IEEE, Perth, WA, pp. 1-7.
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The main purpose of this paper is to propose a content analysis approach in order to develop an ontology of university social responsibility (USR). The proposed approach comprises four main phases in which two content analyses software have been utilized to extract the main USR components and to identify the domain of this concept. To achieve the goal, the existing body of knowledge of USR definitions and specifications - using a variety of terms - has been considered to identify the main notions of USR and their relationships. The developed ontology can be applied to define a formal, explicit description of the USR concept and to construct a more reliable basis for measurement purposes.
Esfijani, A, Hussain, FK & Chang, E 2012, 'Human motivation principles and human factors for virtual communities', Proceedings of the 4th International Conference on Computer Supported Education vol 1, International Conference on Computer Supported Education, Science and Technology Publications, Porto, Portugal, pp. 93-100.
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The main purpose of this study is to investigate, from a theoretical point of view, virtual universities in comparison with Social Networking Services (SNS). The theoretical framework constitutes of the Human Motivation Theory (HMT) and the Human Factors (HF) in which Facebook as the most popular SNS is compared with virtual university in general. The main features of these technologies were compared in order to consider whether they comply with mentioned theories. Using an exploratory research methodology, this study concludes that SNSs are more adopted with HMT than virtual university. In the other word, Facebook applications as the most popular virtual community with over 500,000,000 users worldwide, is more compliant with HMT to gratify users needs. Also, from the perspective of human factors, it is more successful than the virtual university
Ferguson, S, Johnston, AJ, Ballard, KJ, Tan, C & Perera-Schulz, D 2012, 'Visual feedback of acoustic data for speech therapy: model and design parameters', Proceedings of the 7th Audio Mostly Conference: A Conference on Interaction with Sound, Audio Mostly Conference: A Conference on Interaction with Sound, ACM, Corfu, Greece, pp. 135-140.
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Feedback, usually of a verbal nature, is important for speech therapy sessions. Some disadvantages exist however with traditional methods of speech therapy, and visual feedback of acoustic data is a useful alternative that can be used to complement typical clinical sessions. Visual feedback has been investigated before, and in this paper we propose sev- eral new prototypes. From these prototypes we develop an iterative model of analysing the design of feedback sys- tems by examining the feedback process. From this iterative model, we then extract methods to inform design of visual feedback systems for speech therapy
Fu, B, Wang, Z, Pan, R, Xu, G & Dolog, P 2012, 'An Integrated Pruning Criterion for Ensemble Learning Based on Classification Accuracy and Diversity', Proceedings of 7th International Conference on Knowledge Management in Organizations: Service and Cloud Computing, International Conference on Knowledge Management in Organizations: Service and Cloud Computing, Springer Berlin / Heidelberg, Salamanca, Spain, pp. 47-58.
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Fu, B, Wang, Z, Pan, R, Xu, G & Dolog, P 2012, 'Learning Tree Structure of Label Dependency for Multi-label Learning', Advances in Knowledge Discovery and Data Mining Lecture Notes in Computer Science, Pacific-Asia Conference on Knowledge Discovery and Data Mining, Springer Berlin / Heidelberg, Kuala Lumpur, Malaysia, pp. 159-170.
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There always exists some kind of label dependency in multi- label data. Learning and utilizing those dependencies could improve the learning performance further. Therefore, an approach for multi-label learning is proposed in this paper, which quantifies the dependencies of pairwise labels firstly, and then builds a tree structure of the labels to describe them. Thus the approach could find out potential strong la- bel dependencies and produce more generalized dependent relationships. The experimental results have validated that compared with other state- of-the-art algorithms, the method is not only a competitive alternative, but also has shown better performance after ensemble learning especially.
Furqan, F & Hoang, DB 2011, 'Analysis of Parameters Contributing Performance and Coverage of Mobile WiMAX with Mix Traffic', 2011 12th International Conference on Parallel and Distributed Computing, Applications and Technologies (PDCAT), International Conference on Parallel and Distributed Computing, Applications and Technologies, IEEE, Gwangju, China, pp. 313-318.
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With high data rate and mobility support wireless networks are becoming an essential access component and an integral part of the ubiquitous Internet. As the provision of wireless networks is cost effective, they are being adopted for broadband access in rural areas (e.g., the Australian National Broadband Network). In this paper we present a comprehensive study of the parameters that effect both the capacity and coverage of IEEE 802.16e WiMAX which will serve as a basis for designing an effective access network including network dimensioning and provisioning QoS for dynamic and mixed distribution of services. In particular, the effect of physical and MAC layer overhead is considered for capacity evaluation with a simple scheduler. The paper also discusses the usage of compressed MAPs with SUB-DL-UL-MAP to reduce overheads and increase network capacity. Different scenarios are presented to evaluate the effect of standard and compressed overhead on capacity and coverage
Gao, L, Li, M, Zhu, T, Bonti, A, Zhou, W & Yu, S 2012, 'AMDD: Exploring entropy based anonymous multi-dimensional data detection for network optimization in human associated DTNs', Proc. of the 11th IEEE Int. Conference on Trust, Security and Privacy in Computing and Communications, TrustCom-2012 - 11th IEEE Int. Conference on Ubiquitous Computing and Communications, IUCC-2012, pp. 1245-1250.
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Human associated delay-tolerant networks (HDTNs) are new networks where mobile devices are associated with humans and demonstrate social-related communication characteristics. Most of recent works use real social trace file to analyse its social characteristics, however social-related data is sensitive and has concern of privacy issues. In this paper, we propose an anonymous method that anonymize the original data by coding to preserve individual's privacy. The Shannon entropy is applied to the anonymous data to keep rich useful social characteristics for network optimization, e.g. routing optimization. We use an existing MIT reality dataset and Infocom 06 dataset, which are human associated mobile network trace files, to simulate our method. The results of our simulations show that this method can make data anonymously while achieving network optimization. © 2012 IEEE.
Gay, VC & Leijdekkers, P 2012, 'Personalised Mobile Health and Fitness Apps: Lessons learned from myFitnessCompanion', 9th International Conference on Wearable Micro and Nano Technologies for Personalized Health, 9th International Conference on Wearable Micro and Nano Technologies for Personalized Health, IOS Press Inc, Porto, Portugal, pp. 248-253.
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Smartphone and tablets are slowly but steadily changing the way we look after our health and fitness. Today, many high quality mobile apps are available for users and health professionals and cover the whole health care chain, i.e. information collection, prevention, diagnosis, treatment and monitoring. Our team has developed a mobile health and fitness app called myFitnessCompanion (R) which has been available via Android market since February 2011. The objective of this paper is to share our experience with rolling out a mobile health and fitness app. We discuss the acceptance of health apps by end-users and healthcare industry. We discuss the acceptance of health apps will be distributed in the near future, the use of Personal Health Record (PHR) systems such as Microsoft Health Vault and impact of regulations (FDA) on the future of mobile health apps. The paper is based on seven years of experience by the authors as mobile health and fitness application developers and we discuss the challenges and opportunities for app developers in the health industry.
Ghous, H, Kennedy, PJ, Ho, N & Catchpoole, DR 2012, 'Functional Visualisation of Genes using Singular Value Decomposition', Proceedings of the 10th Australasian Data Mining Conference, Australian Data Mining Conference, Australian Computer Society, Sydney, Australia, pp. 53-60.
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Progress in understanding core pathways and processes of cancer requires thorough analysis of many coding regions of the genome. New insights are hampered due to the lack of tools to make sense of large lists of genes identified using high throughput technology. Data mining, particularly visualisation that finds relationships between genes and the Gene Ontology (GO), has the potential to assist in functional understanding. This paper addresses the question of how well GO annotations can help in functional understanding of genes. We augment genes with associated GO terms and visualise with Singular Value Decomposition (SVD). Meaning of derived components is further interpreted using correlations to GO terms. The results demonstrate that SVD visualisation of GOaugmented genes matches the biological understanding expected in the simulated data and presents understanding of childhood cancer genes that aligns with published results
Gill, AQ & Bunker, D 2012, 'Crowd Sourcing Challenges Assessment Index for Disaster Management', AMCIS 2012 Proceedings, Americas Conference on Information Systems, AIS, Seattle, USA, pp. 1-11.
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Emergency agencies (EA) rely on inter-agency approaches to information management during disasters. EA have shown a significant interest in the use of cloud-based social media such as Twitter and Facebook for crowd-sourcing and distribution of disaster information. While the intentions are clear, the question of what are its major challenges are not. EA have a need to recognise the challenges in the use of social media under their local circumstances. This paper analysed the recent literature, 2010 Haiti earthquake and 2010-11 Queensland flood cases and developed a crowd sourcing challenges assessment index construct specific to EA areas of interest. We argue that, this assessment index, as a part of our large conceptual framework of context aware cloud adaptation (CACA), can be useful for the facilitation of citizens, NGOs and government agencies in a strategy for use of social media for crowd sourcing, in preventing, preparing for, responding to and recovering from disasters.
Gill, AQ, Bunker, D & Seltsikas, P 2012, 'Evaluating A Communication Technology Assessment Tool (CTAT): A Case Of A Cloud Based Communication Tool', Proceedings of Pacific Asia Conference on Information Systems 2012, Pacific Asia Conference on Information Systems, AIS, Ho Chi Min, Vietnam, pp. 1-13.
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A primary concern of distributed adaptive development environment (DADE) is that of human communication and knowledge sharing among geographically dispersed developers. Emerging cloud-based communication technologies claim to provide a support for communication and knowledge sharing among developers in a DADE. However, the challenge is how to enable developers to self assess and select appropriate cloud-based communication technologies for their DADE. Based on our recent empirical study, we have developed the construct of a practical communication technologies assessment tool (CTAT). We argue that, CTAT construct, as a part of our large conceptual framework of context aware cloud adaptation (CACA), can be useful to assist developers in the self assessment of appropriate cloud-based communication technologies for their DADE. This paper presents the evaluation of the CTAT by using it for the assessment of the Force.com cloud-based Chatter communication tool. The main objective of this evaluation is to determine to what extent CTAT construct is relevant, valuable and sufficient to achieve its purpose. The results of this evaluation indicate that CTAT seems useful when performing vendor independent assessment of communication technologies in order to make an informed decision about the selection of a communication tool for the DADE.
Gluga, R, Kay, J, Lister, RF & Lever, T 2012, 'A unified model for embedding learning standards into university curricula for effective accreditation and quality assurance', Proceedings of the 23rd Annual Conference of the Australasian Association for Engineering Education, AAEE - Annual Conference of Australasian Association for Engineering Education, The Engineering & Science Education Research (ESER) group, Melbourne, Australia, pp. 1-9.
Gluga, R, Kay, J, Lister, RF & Teague, D 2012, 'On the reliability of classifying programming tasks using a neo-piagetian theory of cognitive development', International computing education research, International Computing Education Research Conference, Association of Computing Machinery (ACM), Auckland, New Zealand, pp. 31-38.
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Abstract: Recent research has proposed Neo-Piagetian theory as a useful way of describing the cognitive development of novice programmers. Neo-Piagetian theory may also be a useful way to classify materials used in learning and assessment. If Neo-Piagetian coding of learning resources is to be useful then it is important that practitioners can learn it and apply it reliably. We describe the design of an interactive web-based tutorial for Neo-Piagetian categorization of assessment tasks. We also report an evaluation of the tutorial's effectiveness, in which twenty computer science educators participated. The average classification accuracy of the participants on each of the three Neo-Piagetian stages were 85%, 71% and 78%. Participants also rated their agreement with the expert classifications, and indicated high agreement (91%, 83% and 91% across the three Neo-Piagetian stages). Self-rated confidence in applying Neo-Piagetian theory to classifying programming questions before and after the tutorial were 29% and 75% respectively. Our key contribution is the demonstration of the feasibility of the Neo-Piagetian approach to classifying assessment materials, by demonstrating that it is learnable and can be applied reliably by a group of educators. Our tutorial is freely available as a community resource.
Gluga, R, Kay, J, Lister, RF, Kleitman, S & Lever, T 2012, 'Coming to terms with Bloom: an online tutorial for teachers of programming fundamentals', Fourteenth Australasian Computing Education Conference (ACE2012), Australasian Computing Education Conference, Australian Computer Society Inc, Melbourne, Australia, pp. 147-156.
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Abstract: This paper describes a web-based interactive tutorial that enables computer science tutors and lecturers to practice applying the Bloom Taxonomy in classifying programming exam questions. The structure, design and content of the tutorial are described in detail. The results of an evaluation with ten participants highlight important problem areas in the application of Bloom to programming assessments. The key contributions are the content and design of this tutorial and the insights derived from its evaluation. These are important results in continued work on methods of measuring learning progression in programming fundamentals.
Gluga, R, Kay, J, Lister, RF, Kleitman, S & Lever, T 2012, 'Over-Confidence and confusion in using Bloom for programming fundamentals assessment', Proceedings of the 43rd ACM technical symposium on Computer science education, ACM Technical Symposium on Computer Science Education (SIGCSE), Association of Computing Machinery, Raleigh, North Carolina, USA, pp. 147-152.
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Abstract: This paper describes a web-based interactive tutorial that enables computer science tutors and lecturers to practice applying the Bloom Taxonomy in classifying programming exam questions. The structure, design and content of the tutorial are described in detail. The results of an evaluation with ten participants highlight important problem areas in the application of Bloom to programming assessments. The key contributions are the content and design of this tutorial and the insights derived from its evaluation. These are important results in continued work on methods of measuring learning progression in programming fundamentals.
Golsteijn, C, van den Hoven, E, Frohlich, D & Sellen, A 2012, 'Towards a More Cherishable Digital Object', Proceedings of the Designing Interactive Systems Conference, ACM Conference on Designing Interactive Systems, ACM, Newcastle upon Tyne, UK, pp. 655-664.
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As we go about our everyday routines we encounter and interact with numerous physical (e.g. furniture or clothes) and digital objects (e.g. photos or e-mails). Some of these objects may be particular cherished, for example because of memories attached to them. As several studies into cherished objects have shown, we have more difficulties identifying cherished digital objects than physical ones. However, cherishing a small collection of digital objects can be beneficial; e.g. it can encourage active selection of digital objects to keep and discard. This paper presents a study that aimed to increase understanding of cherished physical and digital objects, and beyond that, of how we perceive physical and digital objects, and their advantages and disadvantages. We identified design opportunities for novel products and systems that support the creation of more cherishable digital objects by extrapolating the advantages of the physical to the digital, exploiting the reasons for cherishing digital objects, and aiming for meaningful integrations of physical and digital.
Haider, S, Abidi, SS & Williams, M 2012, 'On evolving a dynamic bipedal walk using Partial Fourier Series', 2012 IEEE International Conference on Robotics and Biomimetics, ROBIO 2012 - Conference Digest, IEEE International Conference on Robotics and Biomimetics, IEEE, Guangzhou, China, pp. 8-13.
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The paper presents a Partial Fourier Series (PFS) based bipedal gait in sagittal and transverse planes. The parameters of the Fourier series are optimized through Evolutionary Algorithms (EA). In addition to evolving the two walks (forward and turn) separately, the paper demonstrates how the combination of the two enables a dynamic and adjustable walk. The stability of the walk is ensured through an effective use of the built-in gyroscope sensor. The evolved walk has been tested on the simulated version of the humanoid Nao robot and is being used within the RoboCup Soccer 3D Simulation competition
Hasan, M, Xu, M, He, S & Chen, L 2012, 'Shot Classification Using Domain Specific Features for Movie Management', Lecture Notes in Computer Science, International Conference on DASFAA, Springer, Busan, South Korea, pp. 314-318.
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Among many video types, movie content indexing and retrieval is a significantly challenging task because of the wide variety of shooting techniques and the broad range of genres. A movie consists of a series of video shots. Managing a movie at shot level provides a feasible way for movie understanding and summarization. Consequently, an effective shot classification is greatly desired for advanced movie management. In this demo, we explore novel domain specific features for effective shot classification. Experimental results show that the proposed method classifies movie shots from wide range of movie genres with improved accuracy compared to existing work
Hu, L, Cao, J, Xu, G & Gu, Z 2012, 'Latent Informative Links Detection', Advances in Knowledge-Based and Intelligent Information and Engineering Systems, 16th International Conference on Knowledge-Based and Intelligent Information & Engineering Systems, IOS Press, San Sebastian, Spain, pp. 1233-1242.
Hua, J, Huang, M, Huang, W, Wang, J & Nguyen, Q 2012, 'Force-directed Graph Visualization with Pre-positioning - Improving Convergence Time and Quality of Layout', 2012 16th IEEE International Conference on Information Visualisation (IV), International Conference on Information Visualisation, IEEE Press, Montpellier, France, pp. 124-129.
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Modern visual analytics tools provide mechanism for users to gain unknown knowledge through effective visual interactions for user to quickly understand the progress of algorithms and adjust the input parameters on intermediate visualizations that towards the production of most satisfied outcome. This requires the quick production of a sequence of graph visualizations. However, the traditional force-directed graph drawing algorithms are very slow to reach an equilibrium configuration of forces. They usually spend tens of seconds producing the layout of a graph converge. Thus, they do not satisfy the requirement of rapid drawing of graphs. This paper proposes a fast convergence method for drawing force-directed graphs. We essentially pre-calculate the geometrical position of all vertices before applying a force-directed layout algorithm to reach the energy minimization of the graph layout. The experimental results have shown that this approach could not only reduce the convergence time but also the number of edge crossings that approves the quality of layout significantly
Huang, K-C, Jung, T-P, Chuang, C-H, Ko, L-W & Lin, C-T 2012, 'Preventing lapse in performance using a drowsiness monitoring and management system.', 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, International Conference of the IEEE Engineering in Medicine and Biology Society, IEEE, San Diego, CA, USA, pp. 3336-3339.
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Research on public security, especially the safe manipulation and control of vehicles, has gained increasing attention in recent years. This study proposes a closed-loop drowsiness monitoring and management system that can estimate subjects' driving performance. The system observes electroencephalographic (EEG) dynamics and behavioral changes, delivers arousing feedback to individuals experiencing momentary cognitive lapses, and assesses the efficacy of the feedback. Results of this study showed that the arousing feedback immediately improved subject performance, which was accompanied by concurrent theta- and alpha-power suppression in the bilateral occipital areas. This study further demonstrated the feasibility of accurately assessing the efficacy of arousing feedback presented to drowsy participants by monitoring the changes in their EEG power spectra.
Huang, M 2012, 'Unlocking the Complexity of Genomic Data of RMS Patients Through Visual Analytics', Proceedings of 2012 International Conference on Computerized Healthcare, ICCH'12, IEEE CS Press, Hong Kong, China.
Huang, M, Huang, T & Lin, C 2012, 'Evaluating force-directed algorithms with a new framework', Proceedings of the ACM Symposium on Applied Computing, SAC 2012, ACM Symposium on Applied Computing, ACM Press, Riva, Italy, pp. 1030-1032.
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Force-directed algorithms are widely used in practice for graph drawing. How to evaluate this type of algorithms has been a challenging issue since their performance largely depends on input parameters and thus is not consistent. In this paper, we first review previous approaches used for evaluation of force-directed algorithms. We then present a case study that compares two force-directed algorithms following a newly proposed evaluation framework. This study evaluates the performance of these algorithms in terms of six commonly applied aesthetic criteria and demonstrates how the framework is used. Advantages of this evaluation framework are discussed.
Huang, T, Huang, M & Zhang, K 2012, 'An Interactive Scatter Plot Metrics Visualization for Decision Trend Analysis', Proceedings of 11th International Conference on Machine Learning and Applications (volumn 2), ICMLA 2012, International Conference on Machine Learning and Applications, IEEE CS Press, Boca Raton, FL, USA, pp. 258-264.
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This paper presents a new interactive scatter plot visualization for multi-dimensional data analysis. We apply RST to reduce the visual complexity through dimensionality reduction. We use an innovative point-to-region mouse click concept to enable direct interactions with scatter points that are theoretically impossible. To show the decision trend we use a virtual Z dimension to display a set of linear flows showing approximation of the decision trend. We have conducted a case study to demonstrate the effectiveness and usefulness of our new technique for identifying the impact sources of wine quality through the visual analytics of a wine dataset consisting of 12 attributes with 4898 samples
Huang, T, Lin, C & Huang, M 2012, 'An aggregation-based approach to quality evaluation of graph drawings', Proceedings of International Symposium on Visual Information Communication and Interaction, VINCI '12, International Symposium on Visual Information Communication and Interaction, ACM Press, Hangzhou, China, pp. 110-113.
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Aesthetics are often used to judge how good a graph drawing is in terms of specific drawing rules. A direct measurement of overall quality is missing. In this paper, we propose to evaluate quality based on aggregation of individual aesthetics. This measure can be used by visualization designers to quickly compare the quality of drawings at hand at the design stage and make decisions accordingly. We present a user study that validates this measure. The implications of the proposed measure for future research are discussed.
Iversen, OS & Leong, T 2012, 'Values-led Participatory Design: Mediating the Emergence of Values', The 7th Nordic conference on Human-Computer Interaction: Making Sense Through Design, Nordic Conference on Human-Computer Interaction, ACM Press, Copenhagen, pp. 468-477.
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Iversen, OS, Leong, TW, Wright, P, Gregory, J & Bowker, G 2012, 'Working with human values in design', ACM International Conference Proceeding Series, pp. 143-144.
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A survey of the literature confirms that engaging with human values when designing technology is an important undertaking. However, despite these efforts, there is still considerable divergence and a lack of agreement in how we conceptualize and approach values during technology design. This workshop seeks to bring expertise from different perspectives on design to explore theoretical, methodological, and relational issues when working with values in design. The aim is to better conceptualize, understand and establish ways we can work more systematically and productively with human values in future designs. © 2012 ACM.
Johnston, AJ 2012, 'Conversational Interaction in Interactive Dance Works', Live Interfaces: Performance, Art, Music, Live Interfaces, Interdisciplinary Centre for Scientific Research in Music, Leeds, UK, pp. 1-4.
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This paper describes an ongoing project to develop an interactive dance/physical theatre work entitled Encoded. The focus is on the use of motion capture and real-time fluid simulation to create systems that we hope performers and audiences find stimulating and engaging. Preliminary findings from a qualitative study of performers experiences with the system raise a number of issues, including the challenges of creating theatrical meaning with interactive systems, using Contact Improvisation as a metaphor for engaging creative systems, and the impact that largescale projections can have on performers engagement
Juszczyszyn, K, Gonczarek, A, Tomczak, JM, Musial, K & Budka, M 2012, 'A Probabilistic Approach to Structural Change Prediction in Evolving Social Networks', 2012 IEEE/ACM INTERNATIONAL CONFERENCE ON ADVANCES IN SOCIAL NETWORKS ANALYSIS AND MINING (ASONAM), IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, IEEE, Kadir Has Univ, Istanbul, TURKEY, pp. 996-1001.
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Kamaleswaran, R & McGregor, C 2012, 'CBPSP: Complex business processes for stream processing', 2012 25th IEEE Canadian Conference on Electrical and Computer Engineering: Vision for a Greener Future, CCECE 2012.
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This paper presents an extension called the Complex Business Processes for Stream Processing (CBPsp) to the Solution Manager Service (SMS) framework to support the definition and enactment of complex business processes for event stream processing. The critical care of an infant involves multiple caregivers performing complex activities, thus a system that is capable of presenting complex business processes to produce context sensitive real-time support is required. The proposed system CBPsp, supports the integration of heterogeneous sequential business processes and distinct data types to produce meaningful business objective driven outputs in real-time. Two research contributions are delivered. The first contribution is the real-time integration of synchronous and asynchronous streams in a loosely coupled model based on Service-Oriented Architecture principles. The second contribution is the definition and enactment of complex business processes along with their meaningful business objectives at the point of analysis within data stream management systems. © 2012 IEEE.
Kamaleswaran, R & McGregor, C 2012, 'Integrating complex business processes for knowledge-driven clinical decision support systems', Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS, pp. 1306-1309.
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This paper presents in detail the component of the Complex Business Process for Stream Processing framework that is responsible for integrating complex business processes to enable knowledge-driven Clinical Decision Support System (CDSS) recommendations. CDSSs aid the clinician in supporting the care of patients by providing accurate data analysis and evidence-based recommendations. However, the incorporation of a dynamic knowledge-management system that supports the definition and enactment of complex business processes and real-time data streams has not been researched. In this paper we discuss the process web service as an innovative method of providing contextual information to a real-time data stream processing CDSS. © 2012 IEEE.
Kamaleswaran, R, McGregor, C & James, A 2012, 'A novel framework for event stream processing of clinical practice guidelines', Proceedings - IEEE-EMBS International Conference on Biomedical and Health Informatics: Global Grand Challenge of Health Informatics, BHI 2012, pp. 933-936.
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Clinical Decision Support Systems (CDSSs) play important roles aiding in patient care; they provide accurate data analysis and timely evidence-informed recommendations. Although the availability of biomedical data continues to flourish, there have been limited translations of this type of data to information in real-time at the bedside. Existing systems have either focused on providing process-oriented or knowledge-modeled frameworks, often relying on retrospective data analysis. We have developed a framework capable of providing clinicians the ability to represent existing knowledge and processes in realtime. This framework presents a real-time environment for modeling clinical workflow processes abstracted from clinical guidelines, while applying existing knowledge to produce intelligent evidence-informed recommendations. In this paper we provide a framework to support the detection of neonatal hypoglycaemia using a design supporting the automated realtime, evidence-informed enactment of complex businessprocesses existing in clinical practice guidelines. © 2012 IEEE.
Kannabiran, G, Light, A & Leong, T 2012, 'Identity, performativity, and HCI', Conference on Human Factors in Computing Systems - Proceedings, pp. 2763-2766.
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Identity is a theme spanning multiple discourses, such as feminist HCI, ICT4D and data control, becoming notable as a culturally understood phenomenon within third-wave HCI. This workshop extends current thinking about identity toward performative aspects: how self and identity is constituted, how this relates to digital technology, and what this means for design and use of such technology. As technology's growth in domestic, social and intimate contexts suggests a new consideration of how identity is invoked, we propose to examine philosophical commitments, methodological implications, and pragmatic aspects of putting performativity to work, identifying blind spots and obstacles that hamper research and practice in this area. And we use hands-on critique, panel discussion and brief presentations, to explore how HCI can respond to the challenge of who we are and what we might become in our pursuit of digitally mediated futures. © 2012 Authors.
Kaur, P, Goyal, ML & Lu, J 2012, 'Price Forecasting Using Dynamic Assessment of Market Conditions and Agent's Bidding Behavior', Lecture Notes in Computer Science, International Conference on Neural Information Processing, Springer-Verlag, Doha, Qatar, pp. 100-108.
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Multiple online auctions need complex bidding decisions for selecting which auction to participate in, whether to place single or multiple bids, do early or late bidding and how much to bid. This paper designs a novel fuzzy dynamic bidding agent (FDBA) which uses a comprehensive method for initial price estimation and price forecasting. First, FDBA selects an auction to participate in and calculates its initial price based on clustering and bid selection approach. Then the price of the auction is forecasted based on the estimated initial price, attitude of the bidders to win the auction and the competition assessment for the late bidders using fuzzy reasoning technique. The experiments demonstrated improved price forecasting outcomes using the proposed approach.
Kennard, R & Leaney, J 2012, 'An Introduction to Software Mining', NEW TRENDS IN SOFTWARE METHODOLOGIES, TOOLS AND TECHNIQUES, 11th International Conference on Intelligent Software Methodologies, Tools, and Techniques (SoMeT), IOS PRESS, Genoa, ITALY, pp. 312-323.
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Khoo, IH, Reddy, HC, Van, LD & Lin, CT 2012, 'Delta operator based 2-D VLSI filter structures without global broadcast and incorporation of the quadrantal symmetry', ISCAS 2012 - 2012 IEEE International Symposium on Circuits and Systems, IEEE International Symposium on Circuits and Systems, IEEE, Institute of Electrical and Electronics Engineers, Seoul, South Korea, pp. 3190-3193.
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Having local data communication (without global broadcast of signals) among the elements is important in VLSI designs. Recently, 2-D systolic digital filter architectures were presented which eliminated the global broadcast of the input and output signals. The delta discrete-time operator based 1-D and 2-D digital filters (in γ-domain) were shown to offer better numerical accuracy and lower coefficient sensitivity in narrowband filter designs when compared to the traditional shiftoperator formulation. Further, the complexity in the design and implementation of 2-D filters can be reduced considerably if the symmetries that might be present in the frequency responses of these filters are utilized. With this motivation we present new 2-D VLSI filter structures, without global broadcast, using delta discrete-time operator for the first time. We also present frame works in γ-domain that realizes 2-D filters possessing quadrantal symmetry in its magnitude response. The separable denominator and quadrantal symmetry structures have the advantage of reduced number of multipliers while ensuring the 2-D filter stability. © 2012 IEEE.
Leijdekkers, P & Gay, VC 2012, 'User Adoption of Mobile Apps for Chronic Disease Management: A Case Study based on myFitness Companion', Lecture Notes in Computer Science, International Conference on Smart Homes and Health Telematics (ICOST), Springer, Artimino, Italy, pp. 42-49.
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Health and fitness apps for smart phones and tablets are changing the way we look after your health. This paper analyses the usage of such an app called myFitnessCompanion for chronic disease management. The analysis is based on data collected from 5000* users over a period of 7 months. Highlights of the study show that blood glucose, weight and blood pressure are teh main physsiological data being monitored. Americans and Germans are the front-runners in adopting mobile health apps and are willing to pay for it. Most users choose to enter data manually instead of using automated wireless Bluetooth sensors. Users prefer to store the collected data on the phone rather than exporting it to Personal Health Record Systems
Li, J & Tao, D 2012, 'Sampling Normal Distribution Restricted on Multiple Regions', International Conference on Neural Information Processing, International Conference on Neural Information Processing, Springer-Verlag, Doha, Qatar, pp. 492-500.
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We develop an accept-reject sampler for probability densities that have the similar form of a normal density function, but supported on restricted regions. Compared to existing techniques, the proposed method deals with multiple disjoint regions, truncated on one or both sides. For the original problem of sampling from one region, the efficiency is enhanced as well. We verify the desirable attributes of the proposed algorithm by both theoretical analysis and simulation studies.
Li, J & Tao, D 2011, 'Wisdom of Crowds: Single Image Super-resolution from the Web', Workshop on Large Scale Visual Analytics with the IEEE International Conference on Data Mining, IEEE International Conference on Data Mining, IEEE- Computer Society, Vancouver, Canada, pp. 812-816.
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This paper addresses the problem of learning based single image super-resolution. Previous research on this problem employs human user to provide a set of images that are similar to the target image as a reference. Then the superresolution algorithm can learn from the provided reference images to predict the high resolution details for the target image. We propose a fully automatic scheme, which leverages the knowledge of the entire visual world and to query relevant references from the Internet. The proposed scheme is free of human supervision, and the performance compromise is small. We conduct experiments to show the effectiveness of the method.
Li, L, Xiao, H & Xu, G 2012, 'Finding Related Micro-blogs Based on WordNet', Database Systems for Advanced Applications - 17th International Conference, DASFAA 2012, International Workshops: FlashDB, ITEMS, SNSM, SIM3, DQDI, Busan, South Korea, April 15-19, 2012. Proceedings, pp. 115-122.
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Li, Q, Liu, S & Pan, Y 2012, 'A cooperative construction approach for SaaS applications', Proceedings of the 2012 IEEE 16th International Conference on Computer Supported Cooperative Work in Design (CSCWD), 2012 IEEE 16th International Conference on Computer Supported Cooperative Work in Design (CSCWD), IEEE.
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Li, Q, Schaffer, P, Pang, J & Mauw, S 2012, 'Comparative Analysis of Clustering Protocols with Probabilistic Model Checking', 2012 Sixth International Symposium on Theoretical Aspects of Software Engineering, 2012 Sixth International Symposium on Theoretical Aspects of Software Engineering (TASE), IEEE.
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Li, Y, Liu, B, Rong, B, Wu, Y, Gagnon, G, Gui, L & Zhang, W 2012, 'On the Performance of LDPC-RS Product Codes for Mobile DTV', 2012 IEEE INTERNATIONAL SYMPOSIUM ON BROADBAND MULTIMEDIA SYSTEMS AND BROADCASTING (BMSB), IEEE International Symposium on Broadband Multimedia Systems and Broadcasting (BMSB), IEEE, Yonsei Univ, Seoul, SOUTH KOREA.
Liang, J, Huang, M & Nguyen, Q 2012, 'Perceptual User Study for Combined Treemap', Proceedings of 11th International Conference on Machine Learning and Applications (volumn 1), ICMLA 2012, International Conference on Machine Learning and Applications, IEEE, Boca Raton, FL, USA, pp. 300-305.
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Space-filling visualization techniques have proved their capability in visualizing large hierarchical structured data. However, most existing techniques restrict their partitioning process in vertical and horizontal direction only, which cause problem with identifying hierarchical structures. According to Gestalt research, limiting tree map visualisation to rectangles blocks the utilisation of human capability on object recognition, due to the same fixed size (90 degrees) of all the angles of the shapes in the tree visualisation. However, this assertion was only supported by theory and not rooted in empirical perception data. We conducted a series of controlled experiments to investigate the effect of shape variation of data elements and container in visual data analysis process. We first studied how shape variation affects users perception in the visual data analysis process. We compared combined treemap with traditional rectangular treemaps, slice & dice treemaps and squarifed treemaps. Finally, we demonstrated the effect of the new approach which combines rectangular and nonrectangular treemaps and validate the method based on the empirical results.
Liang, J, Nguyen, Q, Simoff, SJ & Huang, M 2012, 'Angular Treemaps - A new Technique for Visualizing and Emphasizing Hierarchical Structured Data', 2012 16th International Conference on Information Visualisation (IV), International Conference on Information Visualisation, IEEE, Montpellier, France, pp. 74-80.
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Space-filling visualization techniques have proved their capability in visualizing large hierarchical structured data. However, most existing techniques restrict their partitioning process in vertical and horizontal direction only, which cause problem with identifying hierarchical structures. This paper presents a new spacefilling method named Angular Treemaps that relax the constraint of the rectangular subdivision. The approach of Angular Treemaps utilizes divide and conquer paradigm to visualize and emphasize large hierarchical structures within a compact and limited display area with better interpretability. Angular Treemaps generate various layouts to highlight hierarchical sub-structure based on userâs preferences or system recommendations. It offers flexibility to be adopted into a wider range of applications, regarding different enclosing shapes. Preliminary usability results suggest userâs performance by using this technique is improved in locating and identifying categorized analysis tasks.
Liao, L-D, Chen, Y-Y, Lin, C-T, Chang, J-Y & Li, M-L 2012, 'Functional photoacoustic micro-imaging of rat cerebral hemodynamic response function in single vessels during forepaw electrical stimulation', PHOTONS PLUS ULTRASOUND: IMAGING AND SENSING 2012, Conference on Photons Plus Ultrasound - Imaging and Sensing/Photonics West BiOS Symposium, SPIE-INT SOC OPTICAL ENGINEERING, San Francisco, CA.
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Lin, C-L, Jung, M, Wu, YC, Lin, C-T & She, H-C 2012, 'Brain dynamics of mathematical problem solving.', 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, International Conference of the IEEE Engineering in Medicine and Biology Society, IEEE, San Diego, CA, USA, pp. 4768-4771.
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The purpose of this study is to examine brain activities of participants solving mental math problems. The research investigated how problem difficulty affected the subjects' responses and electroencephalogram (EEG) in different brain regions. In general, it was found that solution latencies (SL) to the math problems increased with difficulty. The EEG results showed that across subjects, the right-central beta, left-parietal theta, left-occipital theta and alpha, right-parietal alpha and beta, medial-frontal beta and medial central theta power decreased as task difficulty increased. This study further explored the effects of problem-solving performance on the EEG. Slow solvers exhibited greater frontal theta activities in the right hemisphere, whereas an inverse pattern of hemispheric asymmetry was found in fast solvers. Furthermore, analyses of spatio-temporal brain dynamics during problem solving show progressively stronger alpha- and beta-power suppression and theta-power augmentation as subjects were reaching a solution. These findings provide a better understanding of cortical activities mediating math-based problem solving and knowledge acquisition that can ultimately benefit math learning and education.
Lin, CT, Tsai, SF, Lee, HC, Huang, HL, Ho, SY & Ko, LW 2012, 'Motion sickness estimation system', Proceedings of the International Joint Conference on Neural Networks.
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Motion sickness occurs when the brain receives conflicting sensory information from body, inner ear and eyes [1]. In some cases, a decreased ability to actively control the body's postural motion also causes motion sickness [2][3]. Many previous studies have indicated that motion sickness had negative effect on driving performance, and sometimes lead to serious traffic accidents due to self-control ability decline. Therefore motion sickness becomes a very important issue in our daily life especially considering driving safety. There are many attempts made by researchers to realize motion sickness, and detect motion sickness in the early stage. Although many motion-sickness-related biomarkers have been identified, estimating human motion sickness level (MSL) remains a challenge in operational environment. In our past studies, we found that features in the occipital area were highly correlated with the driver's driving performance. In this study, we designed a virtual-reality (VR) based driving environment with instinct-MSL-reporting mechanism. When a subject performed a driving task, his/her brain EEG was recorded simultaneously. From those EEG data, features associated with left motor brain area, parietal brain area and occipital midline brain area which predicted MSL were extracted by an optimal classifier implemented by an inheritable bi-objective combinatorial genetic algorithm (IBCGA) with support vector machine. Unlike traditional correlation-based method, IBCGA aims to select a small set of EEG features and maximize the prediction accuracy simultaneously in BCI applications. Once the optimal feature set predicting MSL is successfully found, a driver's cognitive state can be monitored. © 2012 IEEE.
Lin, CT, Wang, YK & Chen, SA 2012, 'A hierarchal classifier for identifying independent components', Proceedings of the International Joint Conference on Neural Networks.
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Brain-computer interface (BCI) has shown explosive growth for multiple applications in the recently years. Removing artifacts and selecting useful brain sources are essential in BCI research. Independent Component Analysis (ICA) has been proven as an effective technique to remove artifacts and many brain related researches are based on ICA. However, the useful independent components with brain sources are usually selected manually according to the scalp-plots. This is great inconvenience and a barrier for real-time BCI applications of EEG. In this investigation, a two-layer automatic identification model is proposed to select useful brain sources. It is based on neural network including support vector machine with radial basis function (SVMRBF) and self-organizing map (SOM). In the first layer, SVM discriminates useful independent components from the artifact effectively. In the second layer, these selected useful components are automatically classified to different spatial brain sources according to SOM. This study suggests this model to one general application for EEG study. It can reduce the effect of subjective judgment and improve the performance of EEG analysis. © 2012 IEEE.
Lin, H & Zhang, G 2012, 'Risk prediction framework and model for bank external fund attrition', 14th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems (IPMU), International Conference on Information Processing and Management of Uncertainty, Springer Berlin Heidelberg, Catania, Italy, pp. 170-180.
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Customer Attrition is a function of customer transaction and service related characteristics and also a combination of cancellation and switching to a competitor. This paper first presents a risk prediction framework for bank customer attrition. A risk prediction approach and a combined sporadic risk prediction model are then proposed to support decision making of financial managers. Real world experiments validate the proposed framework, approach and model and show the positive results for bank customer attrition prediction and marketing decision making.
Lin, Q, Zhang, Y, Zhang, W & Li, A 2012, 'General Spatial Skyline Operator', LNCS - Database Systems for Advanced Applications - Proceedings of the 17th Conference on Database Systems for Advanced Applications, Database Systems for Advanced Applications, Springer, Busan, South Korea, pp. 494-508.
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With the emergence of location-aware mobile device technologies, communication technologies and GPS systems, various location-aware queries have attracted great attentions in the database literature. In many user recommendation systems, the spatial preference query is used to suggest the objects based on their spatial proximity to the facilities. In this paper, we study the problem of general spatial skyline which can provide a minimal set of candidates that contain optimal solutions for any monotonic distance based spatial preference query. An efficient algorithm is proposed to significantly reduce the number of non-promising objects in the computation. The paper also covers a comprehensive performance study of the proposed techniques based on both real and synthetic dat
Lister, RF, Corney, M, Curran, J, D'Souza, D, Fidge, CF, Gluga, R, Hamilton, M, Harland, J, Hogan, J, Kay, J, Murphy, T, Roggenkamp, M, Sheard, J, Simon, S & Teague, D 2012, 'Toward a Shared Understanding of Competency in Programming: An Invitation to the BABELnot Project', Fourteenth Australasian Computing Education Conference (ACE2012), Australasian Computing Education Conference, Australian Computer Society Inc, Melbourne, Australia, pp. 53-60.
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Abstract: The ICT degrees in most Australian universities have a sequence of up to three programming subjects, or units. BABELnot is an ALTC-funded project that will document the academic standards associated with those three subjects in the six participating universities and, if possible, at other universities. This will necessitate the development of a rich framework for describing the learning goals associated with programming. It will also be necessary to benchmark exam questions that are mapped onto this framework. As part of the project, workshops are planned for ACE 2012, ICER 2012 and ACE 2013, to elicit feedback from the broader Australasian computing education community, and to disseminate the projectâs findings. The purpose of this paper is to introduce the project to that broader Australasian computing education community and to invite their active participation.
Liu, L, Fan, D, Liu, M, Xu, G, Chen, S, Zhou, Y, Wang, Q, Wei, Y & Chen, X 2012, 'A MapReduce-Based Parallel Clustering Algorithm for Large Protein-Protein Interaction Networks', Lecture Notes in Computer Science, International Conference on Advanced Data Mining and Applications, Springer, Nanjing, China, pp. 138-148.
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Clustering proteins or identifying functionally related proteins in Protein-Protein Interaction (PPI) networks is one of the most computation-intensive problems in the proteomic community. Most researches focused on improving the accuracy of the clustering algorithms. However, the high computation cost of these clustering algorithms, such as Girvan and Newmans clustering algorithm, has been an obstacle to their use on large-scale PPI networks. In this paper, we propose an algorithm, called Clustering-MR, to address the problem. Our solution can effectively parallelize the Girvan and Newmans clustering algorithms based on edge-betweeness using Map Reduce. We evaluated the performance of our Clustering-MR algorithm in a cloud environment with different sizes of testing datasets and different numbers of worker nodes. The experimental results show that our Clustering-MR algorithm can achieve high performance for large-scale PPI networks with more than 1000 proteins or 5000 interactions
Liu, L, Zhou, Y, Liu, M, Xu, G, Chen, X, Fan, D & Wang, Q 2012, 'Preemptive Hadoop Jobs Scheduling under a Deadline', Proceedings of Eighth International Conference on Semantics, Knowledge and Grids, International Conference on Semantics Knowledge and Grid, IEEE Computer Society, Beijing, China, pp. 72-79.
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Liu, S, Liu, B, Ma, X, Rong, B & Gui, L 2012, 'Low-Complexity PAPR Reduction Algorithm in OFDM Systems by Designing Data Subcarriers', 2012 IEEE GLOBAL COMMUNICATIONS CONFERENCE (GLOBECOM), IEEE Global Communications Conference (GLOBECOM), IEEE, Anaheim, CA, pp. 4747-4751.
Liu, W, Chawla, S, Bailey, J, Leckie, C & Ramamohanarao, K 2012, 'An efficient adversarial learning strategy for constructing robust classification boundaries', Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pp. 649-660.
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Traditional classification methods assume that the training and the test data arise from the same underlying distribution. However in some adversarial settings, the test set can be deliberately constructed in order to increase the error rates of a classifier. A prominent example is email spam where words are transformed to avoid word-based features embedded in a spam filter. Recent research has modeled interactions between a data miner and an adversary as a sequential Stackelberg game, and solved its Nash equilibrium to build classifiers that are more robust to subsequent manipulations on training data sets. However in this paper we argue that the iterative algorithm used in the Stackelberg game, which solves an optimization problem at each step of play, is sufficient but not necessary for achieving Nash equilibria in classification problems. Instead, we propose a method that transforms singular vectors of a training data matrix to simulate manipulations by an adversary, and from that perspective a Nash equilibrium can be obtained by solving a novel optimization problem only once. We show that compared with the iterative algorithm used in recent literature, our one-step game significantly reduces computing time while still being able to produce good Nash equilibria results. © 2012 Springer-Verlag.
Liu, W, Kan, A, Chan, J, Bailey, J, Leckie, C, Pei, J & Kotagiri, R 2012, 'On compressing weighted time-evolving graphs', ACM International Conference Proceeding Series, pp. 2319-2322.
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Existing graph compression techniquesmostly focus on static graphs. However for many practical graphs such as social networks the edge weights frequently change over time. This phenomenon raises the question of how to compress dynamic graphs while maintaining most of their intrinsic structural patterns at each time snapshot. In this paper we show that the encoding cost of a dynamic graph is proportional to the heterogeneity of a three dimensional tensor that represents the dynamic graph. We propose an effective algorithm that compresses a dynamic graph by reducing the heterogeneity of its tensor representation, and at the same time also maintains a maximum lossy compression error at any time stamp of the dynamic graph. The bounded compression error benefits compressed graphs in that they retain good approximations of the original edge weights, and hence properties of the original graph (such as shortest paths) are well preserved. To the best of our knowledge, this is the first work that compresses weighted dynamic graphs with bounded lossy compression error at any time snapshot of the graph. © 2012 ACM.
Loke, L, Khut, PG & Kocaballi, AB 2012, 'Bodily experience and imagination: Designing ritual interactions for participatory live-art contexts', ACM Conference on Designing Interactive Systems, ACM Conference on Designing Interactive Systems, ACM, Newcastle, UK, pp. 779-788.
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We are exploring new possibilities for bodily-focused aesthetic experiences within participatory live-art contexts. As artist-researchers, we are interested in how we can understand and shape bodily experience and imagination as primary components of an interactive aesthetic experience, sonically mediated by digital biofeedback technologies. Through the making of a participatory live-art installation, we illustrate how we used the Bodyweather performance methodology to inform the design of ritual interactions intended to reframe the audience experience of self, body and the world through imaginative processes of scaling and metaphor. We report on the insights into the varieties of audience experience gathered from audience testing of the prototype artwork, with a particular focus on the relationship between the embodied imagination and felt sensation; the influence of objects and costume; and the sonically mediated experience of physiological processes of breathing and heartbeat. We offer some reflections on the use of ritual and scripted interactions as a strategy for facilitating coherent forms of bodily experience.
Long, G, Chen, L, Zhu, X & Zhang, C 2012, 'TCSST: transfer classification of short & sparse text using external data', Proc. Of The 21st ACM Conference on Information and Knowledge Management (CIKM-12), ACM International Conference on Information and Knowledge Management, ACM, Maui, Hawaii, USA, pp. 764-772.
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Short & sparse text is becoming more prevalent on the web, such as search snippets, micro-blogs and product reviews. Accurately classifying short & sparse text has emerged as an important while challenging task. Existing work has considered utilizing external data (e.g. Wikipedia) to alleviate data sparseness, by appending topics detected from external data as new features. However, training a classifier on features concatenated from different spaces is not easy considering the features have different physical meanings and different significance to the classification task. Moreover, it exacerbates the "curse of dimensionality" problem. In this study, we propose a transfer classification method, TCSST, to exploit the external data to tackle the data sparsity issue. The transfer classifier will be learned in the original feature space. Considering that the labels of the external data may not be readily available or sufficiently enough, TCSST further exploits the unlabeled external data to aid the transfer classification. We develop novel strategies to allow TCSST to iteratively select high quality unlabeled external data to help with the classification. We evaluate the performance of TCSST on both benchmark as well as real-world data sets. Our experimental results demonstrate that the proposed method is effective in classifying very short & sparse text, consistently outperforming existing and baseline methods
Lu, L, Huang, M & Huang, T 2012, 'A New Axes Re-ordering Method in Parallel Coordinates Visualization', Proceedings of 11th International Conference on Machine Learning and Applications (volumn 2), ICMLA, International Conference on Machine Learning and Applications, IEEE CS Press, Boca Raton, FL, USA, pp. 252-257.
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Visualization and interaction of multidimensional data always requires optimized solutions to integrate the display, exploration and analytical reasoning of data into one visual pipeline for human-centered data analysis and interpretation. Parallel coordinate, as one of the popular multidimensional data visualization techniques, is suffered from the visual clutter problem. Though changing the ordering of axis is a straightforward way to address it, optimizing the order of axis is a NP-complete problem. In this paper, we propose a new axes re-ordering method in parallel coordinates visualization: a similarity-based method, which is based on the combination of Nonlinear Correlation Coefficient (NCC) and Singular Value Decomposition (SVD) algorithms. By using this approach, the first remarkable axe can be selected based on mathematics theory and all axis are re-ordered in line with the degree of similarities among them. Meanwhile, we would also propose a measurement of contribution rate of each dimension to reveal the property hidden in the dataset. At last, case studies demonstrate the rationale and effectiveness of our approaches: NCC reordering method can enlarge the mean crossing angles and reduce the amount of polylines between the neighboring axes. It can reduce the computational complexity greatly in comparison with other re-ordering methods
Lu, L, Huang, M, Chen, Y, Liang, J & Nguyen, Q 2012, 'Clutter Reduction in Multi-dimensional Visualization of Incomplete Data Using Sugiyama Algorithm', 2012 16th International Conference on Information Visualisation (IV), International Conference on Information Visualisation, IEEE, Montpellier, France, pp. 93-99.
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Visualization of uncertainty in datasets is a new field of research, which aims to represent incomplete data for analysis in real scenarios. In many cases, datasets, especially multi-dimensional datasets, often contain either errors or uncertain values. To address this challenge, we may treat these uncertainties as scalar values like probability. For visual representation in parallel coordinates, we draw a small "circle" to temporarily define a dummy vertex for an uncertain value of a data item, at the crossing point between polylines and the axis of certain dimension. Furthermore, these temporary positions of uncertainty could be permuted to achieve visual effectiveness. This feature provides a great opportunity by optimizing the order of uncertain values to tackle another important challenge in information visualization: clutter reduction. Visual clutter always obscures the visualizing structure even in small datasets. In this paper, we apply Sugiyama's layered directed graph drawing algorithm into parallel coordinates visualization to minimize the number of edge crossing among polylines, which has significantly improved the readability of visual structure. Experiments in case studies have shown the effectiveness of our new methods for clutter reduction in parallel coordinates visualization. These experiments also imply that besides visual clutter, the number of uncertain values and the type of multi-dimensional data are important attributes that affect visualization performance in this field.
Lu, P, Lu, J & Zhang, G 2012, 'Case-Base Maintenance for Concept Drift', WASET Issue 72: Proceedings of the International Conference on Information Systems, International Conference on Information Systems, WASET, Penang, Malaysia, pp. 333-340.
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As the evolving nature of a real data stream, so called concept drift, and its accumulating volume, any deployed Case-Based Reasoning (CBR) system will nead to have procedures for Case-Base Maintenance (CBM). Traditional CBM methods for handling concept drift cannot well distinguish between noise and true concept drift, some of them may even run under the risk of losing case-base competence. Motivated by these two problems, wc present a twostage CBM approach. We propose a Noise-Enhanced Fast Context Switch (NEFCS) algorithm, which targets to remove noise under dynamic environment as Stage 1. We also propose a Recursive Conservative Redundancy Removal (RCRR) algorithm, which removes redundant cases in a recursively unifonn way while keeping the case·base coveragc as Stage 2. Experimental evaluations on realworld datasels show that our approach significant improves the perfonnance compared with other CBM approaches.
Luo, Z, Hu, Z, Song, Y, Xu, Z, Liu, H, Jia, L & Lu, H 2012, 'Economic analyses of plug-in electric vehicle battery providing ancillary services', 2012 IEEE International Electric Vehicle Conference, IEVC 2012, Electric Vehicle Conference (IEVC), IEEE, Institute of Electrical and Electronics Engineers, Greenville, SC, USA.
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This paper explores the potential financial return for using plug-in electric vehicles (PEVs) as a grid resource. There are two methods for PEVs to provide ancillary services call interruptible load and vehicle to grid The contract market is introduced first, then the method to calculate the cost benefit of plug-in electric vehicles (PEVs) to provide ancillary services are proposed. Additionally, the expected profits and profits of providing the ancillary services when considering the uncertainties of driving behaviors are both calculated and compared. The calculation results indicate that profits of participating in frequency regulation are higher than that of reserve services. When penalty is neglected or the penalty coefficient is low, the revenue of regulation down services is relatively high. However, with the increasing of penalty factor, the profits decrease dramatically. When the penalty coefficient is sufficiently high, participating in regulation up services in V2G mode is most profitable. © 2012 IEEE.
McGregor, C, Catley, C & James, A 2012, 'Variability analysis with analytics applied to physiological data streams from the neonatal intensive care unit', Proceedings - IEEE Symposium on Computer-Based Medical Systems.
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Late onset neonatal sepsis (LONS) is one clinical condition that shows promise for earlier onset detection through the analysis of physiological signals. However, current work on Heart Rate Variability (HRV) analysis does not discuss the impact of narcotics and other drugs on early identification of sepsis. We present results of a pilot retrospective data mining study of neonatal intensive care unit patients using a dataset of 30 second spot readings. We derive analytics by creating temporal abstractions of hourly summaries for HRV and respiratory rate variability (RRV). Using representative patient examples, we illustrate an analytics user interface design that shows 1) the potential in using our HRV analytics for early identification of LONS with 30 second spot readings; and 2) that based on initial pilot results, reporting analytics for HRV and RRV concurrently adds value to HRV analysis by distinguishing between patients with low HRV due to imminent sepsis and those patients with low HRV due to the presence of confounding factors such as surgery and narcotics. © 2012 IEEE.
McGregor, C, Steadman, A, Percival, J & James, A 2012, 'A method for modeling health informatics capacity in patient journeys supported by interprofessional teams', Proceedings of the Annual Hawaii International Conference on System Sciences, pp. 2790-2799.
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Neonatal intensive care is one of the most complex areas of healthcare; as a result, information flow within this unit must be as efficient as possible. This paper presents initial research findings based on the use of the patient journey modeling technique known as PaJMa to audit the current state of health informatics within NICUs in Canada and internationally. In this paper, a case study from an Ontario NICU is utilized and their "Investigations" process is modeled using PaJMa. © 2012 IEEE.
Mearns, HK, Leaney, JR, Parakhine, A, Debenham, JK & Verchere, DG 2011, 'An Autonomic Open Marketplace for Inter-Cloud Service Management', 2011 Fourth IEEE International Conference on Utility and Cloud Computing, IEEE/ACM International Conference on Utility and Cloud Computing, IEEE Computer Society, Melbourne, Australia, pp. 186-193.
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The rise of utility in cloud computing and telecommunications has introduced greater complexity in the provisioning and performance management of remote services. We propose extended management strategies for this complexity. Our overall aim is for the management to accept responsibility for the complex service in an open marketplace. Responsibility is, firstly, defined by aiming to cover the totality of modern complex services, managing both the connectivity and virtual infrastructure. Secondly, responsibility is further defined as managing risk and resilience in the provisioning and operation of the complex service. With these aims, we are working towards a bundled service provider agent architecture, which can negotiate on the open service market. This approach aims to also optimise the utilisation of the providers infrastructure while reducing the risk of failure to users through total service management. We present the specification, design and simulation of the bundled service agents in a marketplace environment.
Mearns, HK, Leaney, JR, Parakhine, A, Debenham, JK & Verchere, DG 2012, 'CARMA: Complete autonomous responsible management agents for telecommunications and inter-cloud services', 2012 IEEE Network Operations and Management Symposium (NOMS), IEEE Network Operations and Management Symposium, IEEE, Maui, USA, pp. 1089-1095.
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The continuing rise in telecommunication and cloud services usage is matched by an increased complexity in maintaining adequate performance management. To combat this complexity, researchers and telecommunication companies are exploring a variety of management strategies to leverage their individual infrastructures to provide better performance and increased utilisation. We extend these strategies by addressing the complexities that arise through the interaction of multiple telecommunication and cloud providers when providing a modern complex service. Our overall aim is for the management to accept responsibility for the complex service in an open marketplace. Responsibility is, firstly, defined by aiming to cover the totality of modern complex services, managing both the connectivity and virtual infrastructure. Secondly, responsibility is defined as managing risk and resilience in the provisioning and operation of the complex service. With these aims, we are working towards a bundled service provider agent architecture, which can negotiate on the open service market. This approach aims to also optimise the utilisation of the providers infrastructure while reducing the risk of failure to users through total service management. We present the specification, design and simulation of the Complete Autonomous Responsible Management Agents (CARMA) in a marketplace environment.
Memon, T, Lu, J & Hussain, FK 2012, 'Semantic De-biased Associations (SDA) Model to Improve Ill-Structured Decision Support', Proceedings of the 19th International Conference on Neural Information Processing, International Conference on Neural Information Processing, Springer Verlag, Doha, Qatar, pp. 483-490.
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Meng, Q & Kennedy, PJ 2012, 'Determining the number of clusters in co-authorship networks using social network theory', The 2nd International Conference on Social Computing and Its Applications, International Conference on Social Computing and Its Applications, IEEE, Xiangtan, Hunan, China, pp. 337-343.
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Spectral clustering is a modern data clustering methodology with many notable advantages. However, this method has a weakness in that it requires researchers to specify a priori the number of clusters. In most cases, it is a challenge to know the number of clusters accurately. Here, we propose a novel way to solve this problem by involving the concept of group leaders and members from social network theory. From the perspective of social networks, groups are organized by leaders and this can provide a hint to finding the number of clusters in social networks by identifying group leaders. However, due to the fact that a group can have more than one leader, we also propose an algorithm to combine leaders from the same group. The number of leaders after the combination is expected to be the number of clusters in a network. We validate this proposed approach by using spectral clustering to cluster data comprising the co-authorship network from the University of Technology, Sydney (UTS). The experimental results show that our proposed method is effective in determining the number of cluster and can facilitate spectral clustering to achieve better clusters compared with other methods of calculating the number of clusters
Meng, Q & Kennedy, PJ 2012, 'Using field of research codes to discover research groups from co-authorship networks', IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, IEEE, Istanbul, Turkey, pp. 289-293.
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Nowadays, academic collaboration has become more prevalent and crucial than ever before and many studies of academic collaboration analysis are implemented based on coauthor ship networks. This paper aims to build a novel coauthor ship network by importing field of research codes based on Newman's model, and then analyze and extract research groups via spectral clustering. In order to explain the effectiveness of this revised network, we take the academic collaboration at the University of Technology, Sydney (UTS) as an example. The result of this study advances methods for selecting the most prolific research groups and individuals in research institutions, and provides scientific evidence for policymakers to manage laboratories and research groups more efficiently in the future.
Meng, Q & Kennedy, PJ 2012, 'Using network evolution theory and singular value decomposition method to improve accuracy of link prediction in social networks', Proceedings of the Tenth Australasian Data Mining Conference (AusDM-12),, Australian Data Mining Conference, Australian Computer Society, Sydney, pp. 175-181.
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Link prediction in large networks, especially social networks, has received significant recent attention. Although there are many papers contributing methods for link prediction, the accuracy of most predictors is generally low as they treat all nodes equally. We propose an effective approach to identifying the level of activities of nodes in networks by observing their behaviour during network evolution. It is clear that nodes that have been active previously contribute more to the changes in a network than stable nodes, which have low activity. We apply truncated singular value decomposition (SVD) to exclude the interference of stable nodes by treating them as noise in our dataset. Finally, in order to test the effectiveness of our proposed method, we use co-authorship networks from an Australian university from between 2006 and 2011 as an experimental dataset. The results show that our proposed method achieves higher accuracy in link prediction than previous methods, especially in predicting new links.
Mueller, F, Walmink, W, Toprak, C, Bongers, B, Graether, E & van, DHE 2012, 'Hanging off a Bar', Proceedings of the SIGCHI Conference on Human Factors in Computing Systems 2012 Extended Abstracts (CHI EA 2012), CHI 2012, ACM, Austin, TX, USA, pp. 1055-1058.
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Exertion Games involve physical effort and as a result can facilitate physical health benefits. We present Hanging off a Bar, an action hero-inspired Exertion Game in which players hang off an exercise bar over a virtual river for as long as possible. Initial observations from three events with audiences ranging from the general public to expert game designers suggest that Hanging off a Bar can be engaging for players and facilitate intense exertion within seconds. Furthermore, we collected suggestions for what game elements players believe could entice them to increase their physical effort investment. These suggestions, combined with Hanging off a Bar as research vehicle due to the easy measurement of exertion through hanging time, enable future explorations into the relationship between digital game elements and physical exertion, guiding designers on how to support exertion in digital games.
Murphy, L, Fitzgerald, S, Lister, RF & McCauley, R 2012, 'Ability to 'explain in plain english' linked to proficiency in computer-based programming.', International conference on computing education research, International Computing Education Research Conference, Association of Computing Machinery (ACM), Auckland, New Zealand, pp. 111-118.
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Abstract: This study investigates the relationship between novice programmers' ability to explain code segments and their ability to write code. Results show a strong correlation between ability to correctly answer 'explain in plain English' (EiPE) questions and ability to write code indicating that there are aspects of reasoning about code that are common to both writing code and explaining code. Student explanations were categorized using the Structure of the Observed Learning Outcome (SOLO) taxonomy. The better programmers were more likely to articulate relational aspects of the algorithms. While earlier work also found such a link, the code writing in those earlier studies was done on paper. This is the first such result where the writing component was done with 'hands on' a computer. Our results add further evidence for the existence of an aspect of reasoning about code that is common to both explaining code and writing code, which in turn suggests that a judicious mix of teaching both code skills and code explaining skills may lead to a more effective process by which novices learn to reason about code.
Musial, K & Sastry, N 2012, 'Social media - Are they underpinned by social or interest-based interactions?', ACM International Conference Proceeding Series, pp. 1-6.
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On many social media and user-generated content sites, users can not only upload content but also create links with other users to follow their activities. It is interesting to ask whether the resulting user-user Followers' Network is based more on social ties, or shared interests in similar content. This paper reports our preliminary progress in answering this question using around five years of data from social video-sharing site vimeo. Many links in the Followers' Network are between users who do not have any videos in common, which would imply the network is not interest-based, but rather has a social character. However, the Followers' Network also exhibits properties unlike other social networks, for instance, clustering co-efficient is low, links are frequently not reciprocated, and users form links across vast geographical distances. In addition, analysis of the relationship strength, calculated as the number of commonly liked videos, people who follow each other and share some "likes" have more video likes in common than the general population. We conclude by speculating on the reasons for these differences and proposals for further work. © 2012 ACM.
Nguyen, Q, Qian, Y, Huang, M & Zhang, J 2012, 'TabuVis: a light weight visual analytics system for multidimensional data', Proceedings of International Symposium on Visual Information Communication and Interaction, VINCI '12, International Symposium on Visual Information Communication and Interaction, ACM Press, Hangzhou, China, pp. 61-64.
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This paper describes TabuVis, a light weight visual analytics system that provides a flexible, customizable and effective visualization for multidimensional data. A key aspect of visual analytics of data with multiple attributes is the quality and appropriateness of the analytical platforms whose presentation can be adjusted via domain experts. A commercial-free and comprehensive prototype was developed that used scatter-plot approach to support the visual analytics process. Our system consists of multiple components enabling the complete analysis process, including data processing, automatic marks, interactive visualization and control. We demonstrate the effectiveness of TabuVis with two case studies using medical and Oscars data sets.
Nitsuwa, S, Valuvanathorn, S & Huang, M 2012, 'Multi-feature face recognition based on PSO-SVM', 2012 10th International Conference on ICT and Knowledge Engineering (ICT & Knowledge Engineering), International Conference on ICT and Knowledge Engineering (ICT & Knowledge Engineering), IEEE, Bangkok, Thailand, pp. 140-145.
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Face recognition is a kind of identification and authentication, which mainly use the global-face feature. Nevertheless, the recognition accuracy rate is still not high enough. This research aims to develop a method to increase the efficiency of recognition using global-face feature and local-face feature with 4 parts: the left-eye, right-eye, nose and mouth. We used 115 face images from BioID face dataset for learning and testing. Each-individual person's images are divided into 3 different images for training and 2 different images for testing. The processed histogram based (PHB), principal component analysis (PCA) and two-dimension principal component analysis (2D-PCA) techniques are used for feature extraction. In the recognition process, we used the support vector machine (SVM) for classification combined with particle swarm optimization (PSO) to select the parameters G and C automatically (PSO-SVM). The results show that the proposed method could increase the recognition accuracy rate.
Oberst, S & Lai, JCS 2012, 'Analysis of disc brake squeal: Progress and challenges', 19th International Congress on Sound and Vibration 2012, ICSV 2012, pp. 2874-2881.
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Brake squeal noise has been the subject of intense research efforts owing to concerns of car manufacturers caused by complaints lodged and warranty claim related costs arising from dissatisfied customers. Brake squeal is known to be fugitive, and often not repeatable, even under apparently similar operating conditions. The production of brake squeal is dependent on a large number of interacting parameters, such as the mechanical properties of the brake lining materials, contact conditions, wear, operating pressure and temperature which contribute to its often observed nonrepeatability. In this paper, an overview of the state-of-the-art understanding of brake squeal mechanisms and numerical analysis methods (primarily based on finite element analysis) for the prediction of brake squeal propensity is presented. The question of nonlinearity of brake squeal is raised in terms of analysing the mechanisms and how present solution methods reflect this degree of nonlinearity. This is complemented by a description of current industrial practice in the treatment of brake squeal which is, generally, managed on a case-by-case, trial-and-error basis using expensive equipment and time-consuming noise dynamometer and/or on-vehicle tests. The gaps between theory and industrial practice and, hence, challenges for brake squeal research are identified. Recommendations for bridging these gaps and improving the usefulness of current numerical methods for practical industrial use are proposed.
Oberst, S & Lai, JCS 2012, 'The role of nonlinearity in disc brake squeal', Proceedings - European Conference on Noise Control, pp. 1334-1339.
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The prediction of disc brake squeal propensity remains difficult despite significant progress made in the last two decades towards understanding its nature. Most of the numerical analysis of brake squeal is based on linear methods that have found some success in guiding the development of brakes in industry. One popular approach is the complex eigenvalue analysis using finite element models to predict unstable vibration modes. However, the complex eigenvalue analysis may over-predict or under-predict the number of unstable vibration modes and not all predicted unstable vibration modes will result in squeal. Therefore, extensive brake testing in noise dynamometers is required in order to ensure that the noise performance of brakes is acceptable. Although the analysis of brake squeal propensity is primarily based on linear approaches, it has been recognised that the operation of a brake contains a number of nonlinearities such as the excitation through the friction contact between the disc and pad, material properties, and operating conditions. The purpose of this paper is to provide an overview on nonlinearity as one mechanism of the cause of brake squeal and to discuss how such knowledge could be used to develop alternative strategies in numerical prediction of brake squeal propensity. © European Acoustics Association.
O'Reilly, RD, Morrison, JP & McGregor, C 2012, 'A system for the transmission, processing and visualisation of EEG to support Irish Neonatal Intensive Care Units', 2012 25th IEEE Canadian Conference on Electrical and Computer Engineering: Vision for a Greener Future, CCECE 2012.
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A system, constructed as a "proof of concept", for providing an Irish tele-neurophysiology service is presented. It is based on a distributed architecture and capable of handling synchronous data streams from multiple Irish Neonatal Intensive Care Units. It provides Ireland with an infrastructure for overcoming factors affecting the diagnosis of neurological disorders in neonates. The system supports collaborative efforts by neurophysiologists, removes geographical constraints on expert knowledge and allows for the creation of national data stores while simultaneously supporting the trans-Atlantic processing of EEG. Technical obstacles affecting its successful implementation are outlined and solutions proposed. The implementation of such a system could significantly improve the quality of care provided to neonates. © 2012 IEEE.
Ou, CZ, Lin, BS, Chang, CJ & Lin, CT 2012, 'Brain computer interface-based smart environmental control system', Proceedings of the 2012 8th International Conference on Intelligent Information Hiding and Multimedia Signal Processing, IIH-MSP 2012, International Conference on Intelligent Information Hiding and Multimedia Signal Processing (IIHMSP), IEEE, Institute of Electrical and Electronics Engineers, Piraeus, Greece, pp. 281-284.
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A Brain computer interface-based Smart Environmental Control System (BSECS) was proposed in this study. Many environmental control systems have been proposed to improve human life quality recently. However, few researches focused on environment control by using human's physiological state directly. Based on the advantage of our technique on Brain Computer Interface (BCI), we combined BCI technique with Universal Plug and Play (UPnP) home networking for smart house applications. Our BSECS mainly consists of a wireless physiological signal acquisition module, an embedded signal processing module, a Simple Control Protocol (SCP)/ Power Line Communication (PLC) environment controller, and a host system. Here, the physiological signal acquisition module and embedded signal processing module were designed for long-term electroencephalogram (EEG) monitoring and real-time cognitive state detection respectively. The advantages of low-power consumption and small volume of the above modules are suitable for smart house applications in daily life. The proposed BSECS has been verified in a practical demo room, and can be simply extended and integrated with the UPnP home networking for other applications. © 2012 IEEE.
Pan, R, Dolog, P & Xu, G 2012, 'KNN-Based Clustering for Improving Social Recommender Systems', 8th International Workshop 2012, International Workshop on Agents and Data Mining Interaction, Springer, Valencia, Spain, pp. 115-125.
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Part of the Lecture Notes in Computer Science book series (LNCS, volume 7607)
Pan, R, Xu, G & Dolog, P 2011, 'Improving recommendations in tag-based systems with spectral clustering of tag neighbors', Lecture Notes in Electrical Engineering, International Symposium on Computer Science and Its Applications (CSA), Springer, Jeju Island, Korea, pp. 355-364.
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Tag as a useful metadata reflects the collaborative and conceptual features of documents in social collaborative annotation systems. In this paper, we propose a collaborative approach for expanding tag neighbors and investigate the spectral clustering algorithm to filter out noisy tag neighbors in order to get appropriate recommendation for users. The preliminary experiments have been conducted on MovieLens dataset to compare our proposed approach with the traditional collaborative filtering recommendation approach and naive tag neighbors expansion approach in terms of precision, and the result demonstrates that our approach could considerably improve the performance of recommendations. © 2012 Springer Science+Business Media B.V.
Pan, R, Xu, G, Dolog, P & Zong, Y 2012, 'Group Division for Recommendation in Tag-based Systems', 2012 Second International Conference on Cloud and Green Computing, International Conference on Cloud and Green Computing, IEEE, Xiangtan, China, pp. 399-404.
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Parvin, S & Hussain, FK 2012, 'Trust-based Security for Community-based Cognitive Radio Networks', Proceedings of the 2012 26th IEEE International Conference on Advanced Information Networking and Applications, International Conference on Advanced Information Networking and Applications (was ICOIN), IEEE, Fukuoka, Japan, pp. 518-525.
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Cognitive Radio (CR) is considered to be a necessary mechanism to detect whether a particular segment of the radio spectrum is currently in use, and to rapidly occupy the temporarily unused spectrum without interfering with the transmissions of other users. As Cognitive Radio has dynamic properties, so a member of Cognitive Radio Networks may join or leave the network at any time. These properties mean that the issue of secure communication in CRNs becomes more critical than for other conventional wireless networks. This work thus proposes a trust-based security system for community-based CRNs. A CR node's trust value is analyzed according to its previous behavior in the network and, depending on this trust value, it is decided whether this member node can take part in the communication of CRNs. For security purposes, we have designed our model to ensure that the proposed approach is secure in different contexts.
Parvin, S, Han, S, Rehman, Z, Faruque, MA & Hussain, FK 2012, 'A New Identity-Based Group Signature Scheme Based on Knapsack ECC', 2012 Sixth International Conference on Innovative Mobile and Internet Services in Ubiquitous Computing (IMIS), Ubiquitous Computing, IEEE, Palermo, Italy, pp. 73-80.
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Elliptic curve cryptography (ECC) is a way to provide security for exchanging keys among communicating parties using the Diffie Hellman key exchange algorithm. This paper presents the ECC implementation for identity-based signature authentication and then applies the knapsack algorithm on ECC for signing a message. The group signature is the concatenation of the identity-based signature with the user's public key. In this paper, we attempt to provide a secure ID-based group signature scheme by using knapsack based ECC.
Parvin, S, Hussain, FK & Hussain, O 2012, 'Digital signature-based authentication framework in cognitive radio networks', Proceedings of the 10th International Conference on Advances in Mobile Computing & Multimedia, International Conference on Advances in Mobile Computing and Multimedia, ACM, Bali, Indonesia, pp. 136-142.
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Due to the rapid growth of wireless applications, Cognitive Radio (CR) has been considered as a technology to solve spectrum source deficiency by improving effective utilization of limited radio spectrum resources for future wireless communications and mobile computing. However, the unique characteristics of CRNs make security a greater challenge. Moreover, due to the dynamic characteristics of CRNs, a member of CRNs, may join or leave the network at any time. The issue of supporting secure communication in CRNs therefore becomes more serious than for conventional wireless networks. Public key encryption and signature techniques have been adopted here to ensure the security of message transmission in CRNs. This work proposes a digital signature-based trust-oriented scheme to ensure communication by identifying efficient trustworthy users in CRNs. The security analysis is analyzed to guarantee that the proposed approach achieves security proof.
Ploderer, B, Leong, T, Ashkanasy, S & Howard, S 2012, 'A Process of Engagement: Engaging with the Process', Designing Interactive Systems, Designing Interactive Systems, ACM Press, Newcastle upon Tyne, pp. 224-233.
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Purba, J, Lu, J & Zhang, G 2012, 'An Area Defuzzification Technique and Essential Fuzzy Rules for Defuzzifying Nuclear Event Failure Possibilities into Reliability Data', Uncertainty Modeling in Knowledge Engineering and Decision Making, The 10th International FLINS Conference, World Scientific Publishing Co. Pte. Lt., Istanbul, Turkey, pp. 1208-1213.
Purba, J, Lu, J, Zhang, G & Ruan, D 2012, 'A Failure Possibility-Based Reliability Algorithm for Nuclear Safety Assessment by Fault Tree Analysis', The 1st International Workshop on Safety & Security Risk Assessment and Organisational Cultures (SSRAOC2012), The Belgian Nuclear Research Centre SCKâ¿¢CEN, Antwerp - Belgium, pp. 1-8.
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Reliability data are essential for nuclear power plant probabilistic safety assessment by fault tree analysis. The limitation of conventional reliability data comes from the insufficient reliable historical data for probabilistic calculation. This paper proposes an algorithm to calculate nuclear event reliability data using possibility approach as an alternative to probabilistic approach. Nuclear events are evaluated by a group of experts based on their working experience and expertise, which are expressed in qualitative natural languages and mathematically represented by membership functions of fuzzy numbers. Every expert is given a justification weight to represent his/her knowledge level of the safety system under investigation. A case study on emergency core cooling system of a typical nuclear power plant is given to mathematically verify the proposed algorithm. The results show that this proposed algorithm is a very good alternative to assess nuclear event data when historical data for probabilistic calculation is not available.
Raffe, WL, Zambetta, F & Li, X 2012, 'A Survey of Procedural Terrain Generation Techniques using Evolutionary Algorithms', 2012 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION (CEC), IEEE Congress on Evolutionary Computation (CEC), IEEE, Brisbane, AUSTRALIA.
Ramezani, F & Lu, J 2012, 'A COGNITIVE GROUP DECISION SUPPORT SYSTEM FOR PROJECTS EVALUATION', Uncertainty Modeling in Knowledge Engineering and Decision Making, International Fuzzy Logic and Intelligent technologies in Nuclear Science Conference, World Scientific, Istanbul-Turkey, pp. 231-236.
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In any organization there are some main goals and lots of projects for achieving these goals. For any organization, it is important to determine how much these projects affect on achieving the main goals. This paper proposes a new fuzzy multiple attribute-based decision support system (DSS) for evaluating projects in promoting the goals as such a selection may involve both quantitative and qualitative assessment attributes. In addition the proposed DSS has ability to choose the most appropriate fuzzy ranking method for solving given MADM problem. Also it contains sensitivity analysis system which provides opportunity for analyzing the impacts of attributesâ weights and project sâ performance on achieving organizationsâ goals, and assess the reliability of the decision making process. The proposed DSS can be applied for solving every FMADM problem which needs to rank some alternatives according to some attributes.
Ramezani, F & Lu, J 2012, 'A Fuzzy Group Decision Support System for Projects Evaluation', 14th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, IPMU 2012, International Conference on Information Processing and Management of Uncertainty, Springer, CATANIA, ITALY, pp. 160-169.
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In any organization there are some main goals and lots of projects for achieving these goals. For any organization, it is important to determine how much these projects affect on achieving the main goals. This paper proposes a new fuzzy multiple attribute-based decision support system (DSS) for evaluating projects in promoting the goals as such a selection may involve both quantitative and qualitative assessment attributes. There are many fuzzy ranking methods available to solve multi-attribute decision making (MADM) problems. Some are more suitable than other for particular decision problems. The proposed DSS has ability to choose the most appropriate fuzzy ranking method for solving given MADM problem. In addition it contains sensitivity analysis system which provides opportunity for analyzing the impacts of attributes weights and projects performance on achieving organizations goals. A DSS software prototype has been developed on the basis of the proposed DSS which can be applied for solving every FMADM problem which needs to rank some alternatives according to some attributes.
Raza, S, Haider, S & Williams, M 2012, 'Teaching coordinated strategies to soccer robots via imitation', 2012 IEEE International Conference on Robotics and Biomimetics, ROBIO 2012 - Conference Digest, IEEE International Conference on Robotics and Biomimetics, IEEE, Guangzhou, China, pp. 1434-1439.
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Developing coordination among multiple agents and enabling them to exhibit teamwork is a challenging yet exciting task that can benefit many of the complex real-life problems. This research uses imitation to learn collaborative strategies for a team of agents. Imitation based learning involves learning from an expert by observing him/her demonstrating a task and then replicating it. The key idea is to involve multiple human experts during demonstration to teach autonomous agents how to work in coordination. The effectiveness of the proposed methodology has been assessed in a goal defending scenario of the RoboCup Soccer Simulation 3D league. The process involves multiple human demonstrators controlling soccer agents via game controllers and demonstrating them how to play soccer in coordination. The data gathered during this phase is used as training data to learn a classification model which is later used by the soccer agents to make autonomous decisions during actual matches. Different performance evaluation metrics are derived to compare the performance of imitating agent with that of the human-driven agent and hand-coded (if-then-else rules) agent.
Rehman, Z, Hussain, O & Hussain, FK 2012, 'Iaas Cloud Selection using MCDM Methods', 2012 IEEE Ninth International Conference on e-Business Engineering (ICEBE), IEEE International Conference on e-Business Engineering, IEEE, Hangzhou, China, pp. 246-251.
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The popularity of cloud computing and IaaS has spawned numerous cloud service providers which offer various cloud services, including IaaS, to cloud users. These services vary considerably in terms of their performance and cost and the selection of a suitable cloud service becomes a complex decision making issue for a cloud service user. Furthermore, the cloud services have several attributes all of which are the criteria that have to be taken into account when making a service selection decision. In the presence of these multiple criteria, a compromise has to be made because in most real-world situations, no single service exceeds all other services in all criteria but one service may be better in terms of some of the criteria while other services may outperform it if judged on the basis of the remaining criteria. Multi-criteria decision-making is a sub-field in operations research that deals with the techniques to solve such multi-criteria problems. There are several methods of multicriteria decision-making. In this paper, we use key multi-criteria decision-making methods for IaaS cloud service selection in a case study which contains five basic performance measurements of thirteen cloud services by a third party monitoring service. We demonstrate the use of these multi-criteria methods for cloud service selection and compare the results obtained by using each method to find out how the choice of a particular MCDM method affects the outcome of the decision-making process for IaaS cloud service selection.
Rehman, Z, Hussain, OK, Parvin, S & Hussain, FK 2012, 'A Framework for User Feedback Based Cloud Service Monitoring', Proceedings of the 2012 Sixth International Conference on Complex, Intelligent and Software Intensive Systems (CISIS), International Conference on Complex, Intelligent and Software Intensive Systems, IEEE, Palermo, Italy, pp. 257-262.
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The increasing popularity of the cloud computing paradigm and the emerging concept of federated cloud computing have motivated research efforts towards intelligent cloud service selection aimed at developing techniques for enabling the cloud users to gain maximum benefit from cloud computing by selecting services which provide optimal performance at lowest possible cost. Given the intricate and heterogeneous nature of current clouds, the cloud service selection process is, in effect, a multi criteria optimization or decision-making problem. The possible criteria for this process are related to both functional and nonfunctional attributes of cloud services. In this context, the two major issues are: (1) choice of a criteria-set and (2) mechanisms for the assessment of cloud services against each criterion for thorough continuous cloud service monitoring. In this paper, we focus on the issue of cloud service monitoring wherein the existing monitoring and assessment mechanisms are entirely dependent on various benchmark tests which, however, are unable to accurately determine or reliably predict the performance of actual cloud applications under a real workload. We discuss the recent research aimed at achieving this objective and propose a novel user-feedback-based approach which can monitor cloud performance more reliably and accurately as compared with the existing mechanisms.
Ren, Y, Li, G & Zhou, W 2012, 'Improving Top-N recommendations with user consuming profiles', Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pp. 887-890.
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In this work, we observe that user consuming styles tend to change regularly following some profiles. Therefore, we propose a consuming profile model to capture the user consuming styles, then apply it to improve the Top-N recommendation. The basic idea is to model user consuming styles by constructing a representative subspace. Then, a set of candidate items can be estimated by measuring its reconstruction error from its projection on the representative subspace. The experiment results show that the proposed model can improve the accuracy of Top-N recommendations much better than the state-of-the-art algorithms. © 2012 Springer-Verlag.
Ren, Y, Li, G & Zhou, W 2012, 'Learning rating patterns for top-n recommendations', Proceedings of the 2012 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2012, pp. 472-479.
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Two rating patterns exist in the user×item rating matrix and influence each other: the personal rating patterns are hidden in each user's entire rating history, while the global rating patterns are hidden in the entire user×item rating matrix. In this paper, a Rating Pattern Subspace is proposed to model both of the rating patterns simultaneously by iteratively refining each other with an EM-like algorithm. Firstly, a low-rank subspace is built up to model the global rating patterns from the whole user×item rating matrix; then, the projection for each user on the subspace is refined individually based on his/her own entire rating history. After that, the refined user projections on the subspace are used to improve the modelling of the global rating patterns. Iteratively, we can obtain a well-trained low-rank Rating Pattern Subspace, which is capable of modelling both the personal and the global rating patterns. Based on this subspace, we propose a RapSVD algorithm to generate Top recommendations, and the experiment results show that the proposed method can significantly outperform the other state-of-the-art Top-N recommendation methods in terms of accuracy, especially on long tail item recommendations. © 2012 IEEE.
Ren, Y, Li, G & Zhou, W 2012, 'Learning user preference patterns for Top-N recommendations', Proceedings - 2012 IEEE/WIC/ACM International Conference on Web Intelligence, WI 2012, pp. 137-144.
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In this paper, we observe that the user preference styles tend to change regularly following certain patterns. Therefore, we propose a Preference Pattern model to capture the user preference styles and their temporal dynamics, and apply this model to improve the accuracy of the Top-N recommendation. Precisely, a preference pattern is defined as a set of user preference styles sorted in a time order. The basic idea is to model user preference styles and their temporal dynamics by constructing a representative subspace with an Expectation- Maximization (EM)-like algorithm, which works in an iterative fashion by refining the global and the personal preference styles simultaneously. Then, the degree which the recommendations match the active user's preference styles, can be estimated by measuring its reconstruction error from its projection on the representative subspace. The experiment results indicate that the proposed model is robust to the data sparsity problem, and can significantly outperform the state-of-the-art algorithms on the Top-N recommendation in terms of accuracy. © 2012 IEEE.
Ren, Y, Li, G, Zhang, J & Zhou, W 2012, 'The efficient imputation method for neighborhood-based collaborative filtering', ACM International Conference Proceeding Series, pp. 684-693.
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As each user tends to rate a small proportion of available items, the resulted Data Sparsity issue brings significant challenges to the research of recommender systems. This issue becomes even more severe for neighborhood-based collaborative filtering methods, as there are even lower numbers of ratings available in the neighborhood of the query item. In this paper, we aim to address the Data Sparsity issue in the context of the neighborhood-based collaborative filtering. Given the (user, item) query, a set of key ratings are identified, and an auto-adaptive imputation method is proposed to fill the missing values in the set of key ratings. The proposed method can be used with any similarity metrics, such as the Pearson Correlation Coefficient and Cosine-based similarity, and it is theoretically guaranteed to outperform the neighborhood-based collaborative filtering approaches. Results from experiments prove that the proposed method could significantly improve the accuracy of recommendations for neighborhood-based Collaborative Filtering algorithms. © 2012 ACM.
Robertson, TJ, Durick, JI, Brereton, M, Howard, S, Vetere, F & Nansen, B 2012, 'Knowing Our Users: Scoping Interviews in Design Research with Ageing Participants', Proceedings of the 24th Australian Computer-Human Interaction Conference, Australian Computer Human Interaction Conference, ACM Press, Swinburne University of Technology, Melbourne, Australia, pp. 517-520.
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This paper reports the findings from a series of scoping interviews designed to evaluate, ground and refine the initial understandings, assumptions and concepts of a research team in a larger project about the role of social and tangible technologies in maintaining good habits into old age. Participants understandings of some basic terms used in the research are presented along with a discussion of their current use of new and established information and communications technologies and the existing barriers to ongoing uptake of emerging technologies. The findings suggest that we question common assumptions about both ageing and technology usage by ageing people, demonstrating the contribution such early scoping interviews can make within design research projects.
Rong, B, Xu, Y, Wu, Y, Gagnon, G, Liu, B, Gui, L & Zhang, W 2012, 'Exploring Controllable Deterministic Bits for LDPC Iterative Decoding in WiMAX Networks', 2012 IEEE GLOBAL COMMUNICATIONS CONFERENCE (GLOBECOM), IEEE Global Communications Conference (GLOBECOM), IEEE, Anaheim, CA, pp. 4018-4023.
Schubert, E, Ferguson, S, Farrar, N, Taylor, D & McPherson, GE 2012, 'Continuous Response to Music using Discrete Emotion Faces', Proceedings of the 9th International Symposium on Computer Music Modelling and Retrieval, International Symposium on Computer Music Modeling and Retrieval (CMMR), Queen Mary University of London, London, UK, pp. 3-19.
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An interface based on expressions in simple graphics of faces were aligned in a clock-like distribution with the aim of allowing participants to quickly and easily rate emotions in music continuously. We developed the interface and tested it using six extracts of music, one targeting each of the six faces: `Excited (at 1 oclock), `Happy (3), `Calm (5), `Sad (7), `Scared (9) and `Angry (11). 30 participants rated the emotion expressed by these excerpts on our `emotion-face-clock. By demonstrating how continuous category selections (votes) changed over time, we were able to show that (1) more than one emotion-face could be expressed by music at the same time and (2) the emotion face that best portrayed the emotion the music conveyed could change over time, and that the change could be attributed to changes in musical structure.
Shangguan, Q, Hu, L, Cao, J & Xu, G 2012, 'Book Recommendation Based On Joint Multi-Relational Model', Second International Conference on Social Computing and Its Applications, International Conference on Social Computing and Its Applications, IEEE, Xiangtan, China, pp. 523-530.
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Sharma, N, Pal, U & Blumenstein, M 2012, 'Recent advances in video based document processing: A review', Proceedings - 10th IAPR International Workshop on Document Analysis Systems, DAS 2012, International Workshop on Document Analysis Systems, IEEE, Institute of Electrical and Electronics Engineers, Gold Coast, Australia, pp. 63-68.
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Extraction and recognition of text present in video has become a very popular research area in the last decade. Generally, text present in video frames is of different size, orientation, style, etc. with complex backgrounds, noise, low resolution and contrast. These factors make the automatic text extraction and recognition in video frames a challenging task. A large number of techniques have been proposed by various researchers in the recent past to address the problem. This paper presents a review of various state-of-the-art techniques proposed towards different stages (e.g. detection, localization, extraction, etc.) of text information processing in video frames. Looking at the growing popularity and the recent developments in the processing of text in video frames, this review imparts details of current trends and potential directions for further research activities to assist researchers. © 2012 IEEE.
Sharma, N, Shivakumara, P, Pal, U, Blumenstein, M & Tan, CL 2012, 'A new method for arbitrarily-oriented text detection in video', Proceedings - 10th IAPR International Workshop on Document Analysis Systems, DAS 2012, International Workshop on Document Analysis Systems, IEEE, Institute of Electrical and Electronics Engineers, Gold Coast, Australia, pp. 74-78.
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Text detection in video frames plays a vital role in enhancing the performance of information extraction systems because the text in video frames helps in indexing and retrieving video efficiently and accurately. This paper presents a new method for arbitrarily-oriented text detection in video, based on dominant text pixel selection, text representatives and region growing. The method uses gradient pixel direction and magnitude corresponding to Sobel edge pixels of the input frame to obtain dominant text pixels. Edge components in the Sobel edge map corresponding to dominant text pixels are then extracted and we call them text representatives. We eliminate broken segments of each text representatives to get candidate text representatives. Then the perimeter of candidate text representatives grows along the text direction in the Sobel edge map to group the neighboring text components which we call word patches. The word patches are used for finding the direction of text lines and then the word patches are expanded in the same direction in the Sobel edge map to group the neighboring word patches and to restore missing text information. This results in extraction of arbitrarily-oriented text from the video frame. To evaluate the method, we considered arbitrarily-oriented data, non-horizontal data, horizontal data, Hua's data and ICDAR-2003 competition data (Camera images). The experimental results show that the proposed method outperforms the existing method in terms of recall and f-measure. © 2012 IEEE.
Simon, S, Sheard, J, Carbone, A, Chinn, D, Laakso, M, Clear, T, de Raadt, M, D'Souza, D, Lister, RF, Philpott, A, Skene, J & Warburton, G 2012, 'Introductory programming: examining the exams', Fourteenth Australasian Computing Education Conference (ACE2012), Australasian Computing Education Conference, Australian Computer Society Inc, Melbourne, Australia, pp. 61-70.
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Abstract: This paper describes a classification scheme that can be used to investigate the characteristics of introductory programming examinations. The scheme itself is described and its categories explained. We describe in detail the process of determining the level of agreement among classifiers, that is, the inter-rater reliability of the scheme, and we report the results of applying the classification scheme to 20 introductory programming examinations. We find that introductory programming examinations vary greatly in the coverage of topics, question styles, skill required to answer questions and the level of difficulty of questions. This study is part of a project that aims to investigate the nature and composition of formal examination instruments used in the summative assessment of introductory programming students, and the pedagogical intentions of the educators who construct these instruments.
Stanton, CJ, Ratanasena, E, Haider, S & Williams, M 2012, 'Perceiving forces, bumps, and touches from proprioceptive expectations', Lecture Notes in Computer Science, Robot Soccer World Cup, Springer, Istanbul, Turkey, pp. 377-388.
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We present a method for enabling an Aldebaran Nao humanoid robot to perceive bumps and touches caused by physical contact forces. Dedicated touch, tactile or force sensors are not used. Instead, our approach involves the robot learning from experience to generate a proprioceptive motor sensory expectation from recent motor position commands. Training involves collecting data from the robot characterised by the absence of the impacts we wish to detect, to establish an expectation of normal motor sensory experience. After learning, the perception of any unexpected force is achieved by the comparison of predicted motor sensor values with sensed motor values for each DOF on the robot. We demonstrate our approach allows the robot to reliably detect small (and also large) impacts upon the robot (at each individual joint servo motor) with high, but also varying, degrees of sensitivity for different parts of the body. We discuss current and possible applications for robots that can develop and exploit proprioceptive expectations during physical interaction with the world
Sui, Y, Ye, D & Xue, J 2012, 'Static memory leak detection using full-sparse value-flow analysis', 2012 International Symposium on Software Testing and Analysis, ISSTA 2012 - Proceedings, pp. 254-264.
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We introduce a static detector, Saber, for detecting memory leaks in C programs. Leveraging recent advances on sparse pointer analysis, Saber is the first to use a full-sparse value-flow analysis for leak detection. Saber tracks the flow of values from allocation to free sites using a sparse value-flow graph (SVFG) that captures def-use chains and value flows via assignments for all memory locations represented by both top-level and address-taken pointers. By exploiting field-, flow- and context-sensitivity during different phases of the analysis, Saber detects leaks in a program by solving a graph reachability problem on its SVFG. Saber, which is fully implemented in Open64, is effective at detecting 211 leaks in the 15 SPEC2000 C programs and five applications, while keeping the false positive rate at 18.5%. We have also compared Saber with Fastcheck (which analyzes allocated objects flowing only into top-level pointers) and Sparrow (which handles all allocated objects using abstract interpretation) using the 15 SPEC2000 C programs. Saber is as accurate as Sparrow but is 14.2X faster and reports 40.7% more bugs than Fastcheck at a slightly higher false positive rate but is only 3.7X slower. © 2012 ACM.
Sui, Y, Ye, D & Xue, J 2012, 'Static memory leak detection using full-sparse value-flow analysis', Proceedings of the 2012 International Symposium on Software Testing and Analysis - ISSTA 2012, the 2012 International Symposium, ACM Press.
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Sundaresan, S, Doss, R & Zhou, W 2012, 'A secure search protocol based on Quadratic Residues for EPC Class-1 Gen-2 UHF RFID tags', IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC, pp. 30-35.
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Radio Frequency Identification (RFID) is a technological revolution that is expected to soon replace barcode systems. One of the important features of an RFID system is its ability to search for a particular tag among a group of tags. This task is quite common where RFID systems play a vital role. To our knowledge not much work has been done in this secure search area of RFID. Also, most of the existing work do not comply with the C1G2 standards. Our work aims to fill that gap by proposing a protocol based on Quadratic Residues property that does not use the expensive hash functions or any complex encryption schemes but achieves total compliance with industry standards while meeting the security requirements. © 2012 IEEE.
Sundaresan, S, Doss, R & Zhou, W 2012, 'A serverless ultra-lightweight secure search protocol for EPC Class-1 Gen-2 UHF RFID tags', 2012 International Conference on Computer and Information Science, ICCIS 2012 - A Conference of World Engineering, Science and Technology Congress, ESTCON 2012 - Conference Proceedings, pp. 580-585.
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Radio Frequency Identification (RFID) is a technology that enables the non-contact, automatic and unique identification of objects using radio waves. Its use for commercial applications has recently become attractive with RFID technology seen as the replacement for the optical barcode system that is currently in widespread use. RFID has many advantages over the traditional barcode and these advantages have the potential to significantly increase the efficiency of decentralised business environments such as logistics and supply chain management. One of the important features of an RFID system is its ability to search for a particular tag among a group of tags. In order to ensure the privacy and security of the tags, the search has to be conducted in a secure fashion. To our knowledge not much work has been done in this secure search area of RFID. The limited work that has been done does not comply with the EPC Class-1 Gen-2 standards since most of them use expensive hash operations or sophisticated encryption schemes that cannot be implemented on low-cost passive tags that are highly resource constrained. Our work aims to fill this gap by proposing a serverless ultra-lightweight secure search protocol that does not use the expensive hash functions or any complex encryption schemes but achieves compliance with EPC Class-1 Gen-2 standards while meeting the required security requirements. Our protocol is based on XOR encryption and random numbers - operations that are easily implemented on low-cost RFID tags. Our protocol also provides additional protection using a blind-factor to prevent tracking attacks. Since our protocol is EPC Class-1 Gen-2 compliant it makes it possible to implement it on low-cost passive RFID tags. © 2012 IEEE.
Tafavogh, S, Kennedy, PJ & Catchpoole, DR 2012, 'Determining Cellularity Status of Tumors based on Histopathology using Hybrid Image Segmentation', International Joint Conference on Neural Networks, IEEE International Joint Conference on Neural Networks, IEEE, Brisbane, Australia, pp. 1-8.
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A Computer Aided Diagnosis (CAD) system is developed to determine cellularity status of a tumor. The system helps pathologists to distinguish a tumor with cell proliferation from normal tumors. The developed CAD system implements a hybrid segmentation method to identify and extract the morphological features that are used by pathologists for determining cellularity status of tumor. Adaptive Mean Shift (AMS) clustering as a non-parametric technique is integrated with Color Template Matching (CTM) to construct segmentation approach. We used Expectation Maximization (EM) clustering as a parametric technique for the sake of comparison with our proposed approach. The output of our proposed system and EM are validated by two pathologists as ground truth. The result of our developed system is quite close to the decision of pathologists, and it significantly outperforms EM in terms of accuracy
Taylor, D, Schubert, E, Ferguson, S & McPherson, GE 2012, 'The Role of Musical Features in the Perception of Initial Emotion', Proceedings of the 9th International Symposium on Computer Music Modelling and Retrieval, International Symposium on Computer Music Modeling and Retrieval (CMMR), Queen Mary University of London, London, pp. 136-143.
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170 participants were played short excerpts of orchestral music and instructed to move a mouse cursor as quickly as possible to one of six faces that best corresponded to the emotion they thought the music expressed. Excerpts were analysed and the musical cues coded. Relationships between the number of cues and participantsâ response times were investigated and reported. No relationship between the number of cues available to the listener and the speed of response was found. Findings suggest that the initial response to ecologically plausible musical excerpts is quite complex, and requires further investigation to provide emotion-retrieval models of music with psychologically driven data
Teague, D, Corney, M, Ahadi, A & Lister, RF 2012, 'Swapping as the Hello World of Relational Reasoning: Replications, Reflections and Extensions', Fourteenth Australasian Computing Education Conference (ACE2012), Australasian Computing Education Conference, Australian Computer Society Inc, Melbourne, Australia, pp. 87-94.
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Abstract: At the previous conference in this series, Corney, Lister and Teague presented research results showing relationships between code writing, code tracing and code explaining, from as early as week 3 of semester. We concluded that the problems some students face in learning to program start very early in the semester. In this paper we report on our replication of that experiment, at two institutions, where one is the same as the original institution. In some cases, we did not find the same relationship between explaining code and writing code, but we believe this was because our teachers discussed the code in lectures between the two tests. Apart from that exception, our replication results at both institutions are consistent with our original study.
Teague, D, Corney, M, Fidge, CF, Roggenkamp, M, Ahadi, A & Lister, RF 2012, 'Using Neo-Piagetian Theory, Formative In-Class Tests and Think Alouds to Better Understand Student Thinking: A Preliminary Report on Computer Programming', Proceedings of the 23rd Annual Conference for the Australasian Association for Engineering Education - The Profession of Engineering Education: Advancing Teaching, Research and Careers, AAEE - Annual Conference of Australasian Association for Engineering Education, Swinburne University of Technology, Melbourne, Australia, pp. 1-9.
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BACKGROUND Around the world, and for many years, students have struggled to learn to program computers. The reasons for this are poorly understood by their lecturers. PURPOSE When the intuitions of many skilled lecturers have failed to solve a pedagogical problem, then a systematic research programme is needed. We have implemented a research programme based on three elements: (1) a theory that provides an organising conceptual framework, (2) representative data on how the class performs on formative assessment tasks, and (3) microgenetic data from one-on-one think aloud sessions, to establish why students struggle with some of the formative tasks. DESIGN / METHOD We have adopted neo-Piagetian theory as our organising framework. We collect data by two methods. The first method is a series of small tests that we have students complete during lectures, at roughly two week intervals. These tests did not count toward the studentsâ final grade, which affords us the opportunity to ask unusual questions that probe at the boundaries of student understanding. Think aloud sessions are the second data collection method, in which a small number of selected, volunteer students attempt problems similar to the problems in the in-class tests. RESULTS The results in this paper serve to illustrate our research programme rather than answer a single, tight research question. These illustrative results focus upon one very simple type of programming question that was put to students, very early in their first programming subject. That simple question required students to write code to swap the values in two variables (e.g., temp = a; a = b; b = temp). The common intuition among programming lecturers is that students should be able to easily solve such a problem by, say, week 4 of semester. On the contrary, we found that 40% of students in a class at one of the participating institutions answered this question incorrectly in week 4 of semester. CONCLUSIONS What is emerging from this res...
Thapngam, T, Yu, S & Zhou, W 2012, 'DDoS discrimination by Linear Discriminant Analysis (LDA)', 2012 International Conference on Computing, Networking and Communications, ICNC'12, pp. 532-536.
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In this paper, we propose an effective approach with a supervised learning system based on Linear Discriminant Analysis (LDA) to discriminate legitimate traffic from DDoS attack traffic. Currently there is a wide outbreak of DDoS attacks that remain risky for the entire Internet. Different attack methods and strategies are trying to challenge defence systems. Among the behaviours of attack sources, repeatable and predictable features differ from source of legitimate traffic. In addition, the DDoS defence systems lack the learning ability to fine-tune their accuracy. This paper analyses real trace traffic from publicly available datasets. Pearson's correlation coefficient and Shannon's entropy are deployed for extracting dependency and predictability of traffic data respectively. Then, LDA is used to train and classify legitimate and attack traffic flows. From the results of our experiment, we can confirm that the proposed discrimination system can differentiate DDoS attacks from legitimate traffic with a high rate of accuracy. © 2012 IEEE.
Tu, TY, Chao, PCP & Lin, CT 2011, 'A new liquid crystal lens with axis-tunability via three sector electrodes', Microsystem Technologies, Information Storage and Processing Systems (ISPS), Springer, Santa Clara, CA, USA, pp. 1297-1307.
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A novel liquid crystal (LC) lens with an on-line tunability on focus length and optical axis is proposed in this study. The designed lens has a LC layer sandwiched by two ITO glasses, one of which is patterned with three sector electrodes. With varied sets of pre-designed voltages applied to these three electrodes, the LC lens can not only render focusing effects but also tunability on the optical axis of the lens to an arbitrary axis. A vector-form equation is developed to predict the direction of axis tuning. Simulations are next conducted to predict dynamics of the LCs in the lens and also the focusing and axis-tuning properties of the lens. Important sizes and materials and fabrication process of the lens are determined and optimized based on simulation results. The designed LC lens is fabricated, and then experiments are conducted to demonstrate the performance of the designed LC lens on axis tuning. It shows that the focusing axis of the LC lens can be effectively changed by pre-calculated combinations of three voltages. It is also shown that the average movement of the focal point per applied voltage reaches 4.778 lm/V. © Springer-Verlag 2012.
Uehara, M, Hussain, F & Durresi, A 2012, 'Welcome message from workshops co-chairs of NBiS 2012', Proceedings of the 2012 15th International Conference on Network-Based Information Systems, NBIS 2012.
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Vines, J, Clarke, R, Leong, T, McCarthy, J, Iversen, OS, Wright, P & Olivier, P 2012, 'Invited SIG - Participation and HCI: Why involve people in design?', Conference on Human Factors in Computing Systems - Proceedings, pp. 1217-1220.
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Participation is of high relevance to the CHI Design community. Participatory work has been performed with very different intentions: to democratize the design process; to better inform the design of new systems; to engage the public in the construction of their own futures; or simply to appease funding commitments. Whilst this increased attention has lead to a large amount of methodological innovation, very little effort has been spent reflecting on why various participatory approaches should, or should not be, used and how we can assess their impacts on the design process and products. This invited SIG will bring together invited experts who have explored participation to different degrees within their past work to provoke group and plenary audience discussion. The aim of this SIG is to provide an opportunity for discussion and reflection on how and why participative methods are used in HCI research and practice. © 2012 Authors.
Vines, J, Clarke, R, Leong, TW, Wright, P, Light, A & Iversen, OS 2012, 'Perspectives on participation: Evaluating cross-disciplinary tools, methods and practices', Proceedings of the Designing Interactive Systems Conference, DIS '12, pp. 799-800.
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This workshop brings together a cross-disciplinary community of researchers and practitioners interested in participative practice and interactive systems design. The workshop addresses growing fascination with participation across interaction design, community informatics, the arts, science and social science, and asks workshop participants to reflect on the ethics and efficacy of the tools and methods used in these diverse practices. The aim of the workshop will be to map out a critical framework exploring the qualities of participation from multiple disciplines. The workshop outcomes will outline how cross-disciplinary perspectives on participation can contribute to participatory and user-centred interaction design. © 2012 Authors.
Wang, W, Johnston, BG & Williams, M 2012, 'Social networking for robots to share knowledge, skills and know-how', International Conference on Social Robotics, International Conference on Social Robotics (ICSR), Springer, Chengdu, China, pp. 418-427.
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A major bottleneck in robotics research and development is the difficulty and time required to develop and implement new skills for robots to realize task-independence. In spite of work done in terms of task model transfer among robots, so far little work has been done on how to make robots task-independent. In this paper, we describe our work-in-progress towards the development of a robot social network called Numbots that draws on the principle of sharing information in human social networking. We demonstrate how Numbots has the potential to assist knowledge sharing, know-how and skill transfer among robots to realize task-independence.
Wang, X, Wang, Z & Xu, X 2012, 'Analytic profit optimization of service-based systems', Proceedings - 2012 IEEE 19th International Conference on Web Services, ICWS 2012, pp. 359-367.
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Service computing has become a dominant paradigm enabling the building of complex service-oriented systems, with the aim of business added-value. Because these systems are inevitably based on uncontrollable services on the unpredictable Internet, it is important to find effective ways of maximizing the profit of service-oriented systems in such unreliable environment. In this paper, we propose an analytic approach that employs a build-time analysis of the runtime dynamics of service execution to maximize the net profit from delivering composite services under full probability of uncertainty. We also present methods for improving the optimization efficiency, including reusing intermediate computation results and adopting specialized profit optimization algorithms. The superiority of the proposed approach is both theoretically proved and empirically demonstrated through experiments. © 2012 IEEE.
Wang, Y-T, Cheng, C-K, Huang, K-C, Lin, C-T, Wang, Y & Jung, T-P 2012, 'Cell-phone Based Drowsiness Monitoring and Management System', 2012 IEEE BIOMEDICAL CIRCUITS AND SYSTEMS CONFERENCE (BIOCAS): INTELLIGENT BIOMEDICAL ELECTRONICS AND SYSTEM FOR BETTER LIFE AND BETTER ENVIRONMENT, IEEE Biomedical Circuits and Systems Conference (BioCAS), IEEE, Hsinchu, TAIWAN, pp. 200-203.
Williams, M 2012, 'Robot social intelligence', Lecture Notes in Computer Science, International Conference on Social Robotics (ICSR), Springer, Chengdu, China, pp. 45-55.
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Robots are pervading human society today at an ever-accelerating rate, but in order to actualize their profound potential impact, robots will need cognitive capabilities that support the necessary social intelligence required to fluently engage with people and other robots. People are social agents and robots must develop sufficient social intelligence to engage with them effectively. Despite their enormous potential, robots will not be accepted in society unless they exhibit social intelligence skills. They cannot work with people effectively if they ignore the limitations, needs, expectations and vulnerability of people working in and around their workspaces. People are limited social agents, i.e. they do not have unlimited cognitive, computational and physical capabilities. People have limited ability in perceiving, paying attention, reacting to stimuli, anticipating, and problem-solving. In addition, people are constrained by their morphology; it limits their physical strength for example. People cannot be expected to and will not compensate for social deficiencies of robots, hence widespread acceptance and integration of robots into society will only be achieved if robots possess the sufficient social intelligence to communicate, interact and collaborate with people. In this paper we identify the key cognitive capabilities robots will require to achieve appropriate levels of social intelligence for safe and effective engagement with people. This work serves as a proto-blueprint that can inform the emerging roadmap and research agenda for the new exciting and challenging field of social robotics.
Wu, D, Zhang, G, Lu, J & Halang, WA 2012, 'A Similarity Measure on Tree Structured Business Data', ACIS 2012 : Location, location, location : Proceedings of the 23rd Australasian Conference on Information Systems 2012, Australasian Conference on Information Systems, ACIS, Geelong, Vic., pp. 1-10.
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In many business situations, products or user profile data are so complex that they need to be described by use of tree structures. Evaluating the similarity between tree-structured data is essential in many applications, such as recommender systems. To evaluate the similarity between two trees, concept corresponding nodes should be identified by constructing an edit distance mapping between them. Sometimes, the intension of one concept includes the intensions of several other concepts. In that situation, a one-to-many mapping should be constructed from the point of view of structures. This paper proposes a tree similarity measure model that can construct this kind of mapping. The similarity measure model takes into account all the information on nodes concepts, weights, and values. The conceptual similarity and the value similarity between two trees are evaluated based on the constructed mapping, and the final similarity measure is assessed as a weighted sum of their conceptual and value similarities. The effectiveness of the proposed similarity measure model is shown by an illustrative example and is also demonstrated by applying it into a recommender system
Wu, L, Pan, Y, Liu, S & Li, Q 2012, 'Construct SaaS Applications from Multi-abstract-level: Method and System', 2012 Seventh ChinaGrid Annual Conference, 2012 Seventh ChinaGrid Annual Conference (ChinaGrid), IEEE.
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Wu, S-L, Liao, L-D, Liou, C-H, Chen, S-A, Ko, L-W, Chen, B-W, Wang, P-S, Chen, S-F & Lin, C-T 2012, 'Design of the multi-channel electroencephalography-based brain-computer interface with novel dry sensors.', Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference, International Conference of the IEEE Engineering in Medicine and Biology Society, IEEE, San Diego, CA, USA, pp. 1793-1797.
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The traditional brain-computer interface (BCI) system measures the electroencephalography (EEG) signals by the wet sensors with the conductive gel and skin preparation processes. To overcome the limitations of traditional BCI system with conventional wet sensors, a wireless and wearable multi-channel EEG-based BCI system is proposed in this study, including the wireless EEG data acquisition device, dry spring-loaded sensors, a size-adjustable soft cap. The dry spring-loaded sensors are made of metal conductors, which can measure the EEG signals without skin preparation and conductive gel. In addition, the proposed system provides a size-adjustable soft cap that can be used to fit user's head properly. Indeed, the results are shown that the proposed system can properly and effectively measure the EEG signals with the developed cap and sensors, even under movement. In words, the developed wireless and wearable BCI system is able to be used in cognitive neuroscience applications.
Xiang, Y, Natgunanathan, I, Peng, D, Zhou, W & Yu, S 2012, 'A dual-channel time-spread echo method for audio watermarking', IEEE Transactions on Information Forensics and Security, pp. 383-392.
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This work proposes a novel dual-channel time-spread echo method for audio watermarking, aiming to improve robustness and perceptual quality. At the embedding stage, the host audio signal is divided into two subsignals, which are considered to be signals obtained from two virtual audio channels. The watermarks are implanted into the two subsignals simultaneously. Then the subsignals embedded with watermarks are combined to form the watermarked signal. At the decoding stage, the watermarked signal is split up into two watermarked subsignals. The similarity of the cepstra corresponding to the watermarked subsignals is exploited to extract the embedded watermarks. Moreover, if a properly designed colored pseudonoise sequence is used, the large peaks of its auto-correlation function can be utilized to further enhance the performance of watermark extraction. Compared with the existing time-spread echo-based schemes, the proposed method is more robust to attacks and has higher imperceptibility. The effectiveness of our method is demonstrated by simulation results. © 2006 IEEE.
Xiong, P & Zhu, T 2012, 'An anonymization method based on tradeoff between utility and privacy for data publishing', Proceedings - 2012 International Conference on Management of e-Commerce and e-Government, ICMeCG 2012, pp. 72-78.
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Privacy preserving is an important issue in data publishing. Many anonymization algorithms are available in meeting the privacy requirements of the privacy models such as k-anonymity, l-diversity and t-closeness. In this paper, we discuss the requirements that anonymized data should meet and propose a new data anonymization approach based on tradeoff between utility and privacy to resist probabilistic inference attacks. To evaluate the quality of anonymized results, a method of measuring the utility loss and privacy gain of anonymized data is brought out which can be used to find the optimal anonymization solution. The result of the experiments validates the availability of the approach. © 2012 IEEE.
Xu, G & Wu, Z 2012, 'On Smart and Accurate Contextual Advertising', Lecture Notes in Computer Science, Database Systems for Advanced Applications, Springer Berlin / Heidelberg, Busan, South Korea, pp. 104-104.
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Wide Web to attract customers, has become one of the most important marketing channels. As one prevalent type ofWeb advertising, contextual advertising refers to the placement of the most relevant commercial ads into the content of a Web page, so as to increase the number of adclicks. However, some problems such as homonymy and polysemy, low intersection of keywords, and context mismatch, can lead to the selection of irrelevant ads for a generic page, making that the traditional keyword matching techniques generally present a poor accuracy. Furthermore, existing contextual advertising techniques only take into consideration how to select as relevant ads for a generic page as possible, without considering the positional effect of the ad placement in the page. In this paper, we propose a new contextual advertising framework to tackle problems, which (1) usesWikipedia concept and category information to enrich the semantic representation of a page (or a textual ad) and (2) takes the placement position of embedded advertise into account. To accomplish these steps, we first map each page (or ad) into three feature vectors: a keyword vector, a concept vector and a category vector. Second, we determine the relevant ads for a given page based on a similarity measure which combines the above three feature vectors. In dealing with position-wise contextual advertising, the relevant ads are selected based on not only global context relevance but also local context relevance, so that the embedded ads yield contextual relevance to both the whole targeted page and the insertion positions where the ads are placed. We experimentally validate our approach by using a real ads set, a real pages set , and a set of more than 260,000 concepts and 12,000 categories from Wikipedia. The experimental results show that our approach performs better than the simple keyword matching and can improve the precision of ads-selection effectively.
Xu, Y, Luo, T, Xu, G & Pan, R 2012, 'A topic-oriented syntactic component extraction model for social media', Lecture Notes in Electrical Engineering, Human Centric Technology and Service in Smart Space, Springer, Gwangju, Korea, pp. 221-229.
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Topic-oriented understanding is to extract information from various language instances, which reflects the characteristics or trends of semantic information related to the topic via statistical analysis. The syntax analysis and modeling is the basis of such work. Traditional syntactic formalization approaches widely used in natural language understanding could not be simply applied to the text modeling in the context of topic-oriented understanding. In this paper, we review the information extraction mode, and summarize its inherent relationship with the "Subject- Predicate" syntactic structure in Aryan language. And we propose a syntactic element extraction model based on the "topic-description" structure, which contains six kinds of core elements, satisfying the desired requirement for topic-oriented understanding. This paper also describes the model composition, the theoretical framework of understanding process, the extraction method of syntactic components, and the prototype system of generating syntax diagrams. The proposed model is evaluated on the Reuters 21578 and SocialCom2009 data sets, and the results show that the recall and precision of syntactic component extraction are up to 93.9% and 88%, respectively, which further justifies the feasibility of generating syntactic component through the word dependencies. © 2012 Springer Science+Business Media.
Yaish, HM, Goyal, ML & Feuerlicht, G 2012, 'A Novel Multi-Tenant Architecture Design For Software As A Service Applications', 2nd International Conference on Cloud Computing and Services Science, International Conference on Cloud Computing and Services Science, Springer-Verlag, Porto, Portugal, pp. 82-88.
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Software as a Service (SaaS) is a web based delivery model which permits a third party provider offering software services to unlimited number of tenants based on multi-tenant architecture design. Multi tenancy is the primary characteristic of SaaS, it allows SaaS vendors to run a single instance application which supports multiple tenants on the same hardware and software infrastructure. This application should be highly configurable to meet tenantsâ expectations and business requirements. Nevertheless, configuring multi-tenant application is hard and complex task to accomplish. This paper is generally focusing on SaaS multi-tenancy in the context of providing a configurable architecture design to support multi-tenant applications in designing and developing a configurable multi-tenant database schema, User Interface, and access control. This novel configurable multi-tenant architecture design provides critical and fundamental solution to the development of multi tenant SaaS applications, once it is achieved it will be a vital contribution to SaaS industry.
Yang, SR, Hsu, SC, Lu, SW, Ko, LW & Lin, CT 2012, 'Development of adaptive QRS detection rules based on center differentiation method for clinical application', ISCAS 2012 - 2012 IEEE International Symposium on Circuits and Systems, IEEE International Symposium on Circuits and Systems, IEEE, Seoul, South Korea, pp. 2071-2074.
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Interpretation of cardiac rhythms is highly dependent on accurate detection of atrial activity. The robustness is an important requirement for clinical usage. This study presents an adaptive QRS detection method for real-time clinical ECG signals. In this method, center differentiation is applied as a whitening filer, and a composite function enhances the high frequency QRS energy. To robustly detect clinical data, a novel threshold selection method based on statistics is proposed. Moreover, this study provides a benchmarking clinical dataset acquired from cardiac patients. Our extensive experimental results using the MIT-BIH arrhythmia database show that our technique can detect beats with 99.67% accuracy, and the sensitivity is 99.83%. With the exceptional QRS detection result, further testing of the proposed method with clinical data shows the accuracy for atrial and ventricular arrhythmias is 82.9% and 90.2%, respectively. © 2012 IEEE.
Yang, SR, Shi-An, C, Shu-Fang, T & Lin, CT 2012, 'Transcutaneous electrical nerve stimulation system for improvement of flight orientation in a VR-based motion environment', ISCAS 2012 - 2012 IEEE International Symposium on Circuits and Systems, IEEE International Symposium on Circuits and Systems, IEEE, Seoul, South Korea, pp. 2055-2058.
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It is very important to reduce the possibility of spatial disorientation because spatial disorientation is a major cause of aircraft crashes. In this research, we assess the effect of transcutaneous electrical nerve stimulation (TENS) on spatial cognitive function by measuring physiological signals, including brain waves measured by electroencephalography (EEG). Through physiological signals such as brain waves, we can objectively understand a subject's cognitive state. Moreover, we use virtual reality technology to build 3D scenery that provides navigation clues in an environment with no visual reference frame. Using the virtual environment, we confirm that TENS lessens spatial disorientation. Across subjects and sessions, the parietal component of brain activity exhibited baseline elevation predominantly in the theta (4-7 Hz) and alpha (8-12 Hz) band as the subjects navigated. This study also found that subjects performed better after TENS in terms of behavioral and EEG data. The results facilitate understanding of the cognitive function of maintaining spatial orientation and development of a device for assisting pilots and reducing the occurrence of spatial disorientation. © 2012 IEEE.
Yu, S, Zhou, W, Dou, W & Makki, SK 2012, 'Why it is hard to fight against cyber criminals?', Proceedings - 32nd IEEE International Conference on Distributed Computing Systems Workshops, ICDCSW 2012, pp. 537-541.
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We are witnessing numerous cyber attacks every day, however, we do not see many cyber criminals are brought to justice. One reason is that it is technically hard to identify and trace cyber criminals. One reason for this passive situation is our limited or even inappropriate understanding of the cyber space. In this paper, we survey the challenges and opportunities in this research field for interested readers. We also list promising tools and directions based on our understanding. © 2012 IEEE.
Yu, W, Lin, X, Zhang, W, Zhang, Y & Le, J 2012, 'SimFusion+: extending simfusion towards efficient estimation on large and dynamic networks', Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieva, International ACM SIGIR conference on Research and development in information retrieva, ACM, Portland, USA, pp. 365-374.
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SimFusion has become a captivating measure of similarity between objects in a web graph. It is iteratively distilled from the notion that "the similarity between two objects is reinforced by the similarity of their related objects". The existing SimFusion model usually exploits the Unified Relationship Matrix (URM) to represent latent relationships among heterogeneous data, and adopts an iterative paradigm for SimFusion computation. However, due to the row normalization of URM, the traditional SimFusion model may produce the trivial solution; worse still, the iterative computation of SimFusion may not ensure the global convergence of the solution. This paper studies the revision of this model, providing a full treatment from complexity to algorithms. (1) We propose SimFusion+ based on a notion of the Unified Adjacency Matrix (UAM), a modification of the URM, to prevent the trivial solution and the divergence issue of SimFusion. (2) We show that for any vertex-pair, SimFusion+ can be performed in O(1) time and O(n) space with an O(km)-time precomputation done only once, as opposed to the O(kn3) time and O(n2) space of its traditional counterpart, where n, m, and k denote the number of vertices, edges, and iterations respectively. (3) We also devise an incremental algorithm for further improving the computation of SimFusion+ when networks are dynamically updated, with performance guarantees for similarity estimation. We experimentally verify that these algorithms scale well, and the revised notion of SimFusion is able to converge to a non-trivial solution, and allows us to identify more sensible structure information in large real-world networks.
Zhan, L, Zhang, Y, Zhang, W & Lin, X 2012, 'Finding Top k Most Influential Spatial Facilities Over Uncertain Objects', Proceedings of the 21st ACM international conference on Information and knowledge management, ACM International Conference on Information and Knowledge Management, ACM, Maui, Hawaii, USA, pp. 922-931.
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Uncertainty is inherent in many important applications, such as location-based services (LBS), sensor monitoring and radio-frequency identification (RFID). Recently, considerable research efforts have been put into the field of uncertainty-aware spatial query processing. In this paper, we study the problem of finding top k most influential facilities over a set of uncertain objects, which is an important spatial query in the above applications. Based on the maximal utility principle, we propose a new ranking model to identify the top k most influential facilities, which carefully captures influence of facilities on the uncertain objects. By utilizing two uncertain object indexing techniques, R-tree and U-Quadtree, effective and efficient algorithms are proposed following the filtering and verification paradigm, which significantly improves the performance of the algorithms in terms of CPU and I/O costs. Comprehensive experiments on real datasets demonstrate the effectiveness and efficiency of our techniques.
Zhang, J, Chen, C, Xiang, Y & Zhou, W 2012, 'Classification of correlated internet traffic flows', Proc. of the 11th IEEE Int. Conference on Trust, Security and Privacy in Computing and Communications, TrustCom-2012 - 11th IEEE Int. Conference on Ubiquitous Computing and Communications, IUCC-2012, pp. 490-496.
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A critical problem for Internet traffic classification is how to obtain a high-performance statistical feature based classifier using a small set of training data. The solutions to this problem are essential to deal with the encrypted applications and the new emerging applications. In this paper, we propose a new Naive Bayes (NB) based classification scheme to tackle this problem, which utilizes two recent research findings, feature discretization and flow correlation. A new bag-of-flow (BoF) model is firstly introduced to describe the correlated flows and it leads to a new BoF-based traffic classification problem. We cast the BoF-based traffic classification as a specific classifier combination problem and theoretically analyze the classification benefit from flow aggregation. A number of combination methods are also formulated and used to aggregate the NB predictions of the correlated flows. Finally, we carry out a number of experiments on a large scale real-world network dataset. The experimental results show that the proposed scheme can achieve significantly higher classification accuracy and much faster classification speed with comparison to the state-of-the-art traffic classification methods. © 2012 IEEE.
Zhang, J, Chen, C, Xiang, Y & Zhou, W 2012, 'Semi-supervised and compound classification of network traffic', Proceedings - 32nd IEEE International Conference on Distributed Computing Systems Workshops, ICDCSW 2012, pp. 617-621.
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This paper presents a new semi-supervised method to effectively improve traffic classification performance when few supervised training data are available. Existing semi supervised methods label a large proportion of testing flows as unknown flows due to limited supervised information, which severely affects the classification performance. To address this problem, we propose to incorporate flow correlation into both training and testing stages. At the training stage, we make use of flow correlation to extend the supervised data set by automatically labeling unlabeled flows according to their correlation to the pre-labeled flows. Consequently, the traffic classifier has better performance due to the extended size and quality of the supervised data sets. At the testing stage, the correlated flows are identified and classified jointly by combining their individual predictions, so as to further boost the classification accuracy. The empirical study on the real-world network traffic shows that the proposed method outperforms the state-of-the-art flow statistical feature based classification methods. © 2012 IEEE.
Zhang, W, Xu, J, Liang, X, Zhang, Y & Lin, X 2012, 'Top-k Similarity Join over Multi-valued Objects', LNCS - Database Systems for Advanced Applications - Proceedings of the 17th International Conference on Database Systems for Advanced Applications, Database Systems for Advanced Applications, Springer, Busan, Korea, pp. 509-525.
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The top-k similarity joins have been extensively studied and used in a wide spectrum of applications such as information retrieval, decision making, spatial data analysis and data mining. Given two sets of objects U and V, a top-k similarity join returns k pairs of most similar objects from U×V. In the conventional model of top-k similarity join processing, an object is usually regarded as a point in a multi-dimensional space and the similarity between two objects is usually measured by distance metrics such as Euclidean distance. However, in many applications an object may be described by multiple values (instances) and the conventional model is not applicable since it does not address the distributions of object instances. In this paper, we study top-k similarity join queries over multi-valued objects. We apply quantile based distance to explore the relative instance distribution among the multiple instances of objects. Efficient and effective techniques to process top-k similarity joins over multi-valued objects are developed following a filtering-refinement framework. Novel distance, statistic and weight based pruning techniques are proposed. Comprehensive experiments on both real and synthetic datasets demonstrate the efficiency and effectiveness of our techniques.
Zhang, Y, Zhang, W, Lin, Q & Lin, X 2012, 'Effectively Indexing the Multi-Dimensional Uncertain Objects for Range Searching', Proceedings of the 15th International Conference on Extending Database Technology, Extending Database Technology, ACM, Berlin, Germany, pp. 504-515.
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The range searching problem is fundamental in a wide spectrum of applications such as radio frequency identification (RFID) networks, location based services (LBS), and global position system (GPS). As the uncertainty is inherent in those applications, it is highly demanded to address the uncertainty in the range search since the traditional techniques cannot be applied due to the inherence difference between the uncertain data and traditional data. In the paper, we propose a novel indexing structure, named U-Quadtree, to organize the uncertain objects in a multi-dimensional space such that the range searching can be answered efficiently by applying filtering techniques. Particularly, based on some insights of the range search on uncertain data, we propose a cost model which carefully considers various factors that may impact the performance of the range searching. Then an effective and efficient index construction algorithm is proposed to build the optimal U-Quadtree regarding the cost model. Comprehensive experiments demonstrate that our technique outperforms the existing works for range searching on multi-dimensional uncertain objects.
Zhao, Y, Li, J, Christen, P & Kennedy, PJ 2012, 'Preface', Conferences in Research and Practice in Information Technology Series, p. vii.
Zhou, A, Xu, G, Agarwal, N, King, I, Nejdl, W & Wang, F 2012, 'Message from the SCA2012 chairs', Proceedings - 2nd International Conference on Cloud and Green Computing and 2nd International Conference on Social Computing and Its Applications, CGC/SCA 2012.
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The 2nd International Conference on Social Computing and Its Applications (SCA2012) was held in Xiangtan, China, November 1-3, 2012. SCA (Social Computing and its Applications) is created to provide a prime international forum for researchers, industry practitioners and environment experts to exchange the latest fundamental advances in the state of the art and practice of social computing and broadly related areas. SCA2012 consists of the main conference and three workshops: the 2012 International Workshop on Social Network Analysis and Information Diffusion Modelling (SNAIDM2012), the 2012 International Workshop on Web Wisdom (WW2012), and the 2012 International Workshop on Social Network Service on Databases (SNSDB2012). We greatly thank the Workshop Chairs for their valuable time and effort in organizing the workshops. SCA2012 is held jointly with the 2nd International Conference on Cloud and Green Computing (CGC2012). SCA2012 received 98 submissions from Germany, Canada, Japan, Australia, Sweden, South Korea, Portugal, Denmark, Poland and Mainland China. Each paper was peer reviewed by at least three program committee members. The final decision has been taken after a high quality review process. There are 45 paper accepted and the regular paper acceptance rate is about 32%. © 2012 IEEE.
Zhou, J, Luo, T & Xu, G 2012, 'Academic Recommendation on Graph with Dynamic Transfer Chain', Proceedings for the 2012 Second International Conference on Cloud and Green Computing, International Conference on Cloud and Green Computing, IEEE, Xiangtan, China, pp. 331-336.
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Zhou, W, Wen, S, Wang, Y, Xiang, Y & Zhou, W 2012, 'An analytical model on the propagation of modern email worms', Proc. of the 11th IEEE Int. Conference on Trust, Security and Privacy in Computing and Communications, TrustCom-2012 - 11th IEEE Int. Conference on Ubiquitous Computing and Communications, IUCC-2012, pp. 533-540.
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Email worms propagate across networks by taking advantage of email relationships. Modeling the propagation of email worms can help predict their potential damages and develop countermeasures. We propose a novel analytical model on the propagation process of modern reinfection email worms. It relies on probabilistic analysis, and thus can provide a steady and reliable assessment on the propagation dynamics. Additionally, by introducing virtual users to represent the repetitious spreading process, the proposed model overcomes the computational challenge caused by reinfection processes. To demonstrate the benefits of our model, we conduct a series of experimental evaluation. The results show that our novel approach achieves a greater accuracy and is more suitable for modeling modern email worms than previous models. © 2012 IEEE.
Zong, Y, Xu, G, Jin, P, Yi, X, Chen, E & Wu, Z 2012, 'A projective clustering algorithm based on significant local dense areas', Proceedings of The 2012 International Joint Conference on Neural Networks (IJCNN), IEEE International Joint Conference on Neural Networks, IEEE, Brisbane, Australia, pp. 1-8.
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