Publications

Xu, G, Zhang, Y & Li, L 2011, Web Mining and Social Networking - Techniques and Applications, 1, Springer, Germany.
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This book examines the techniques and applications involved in the Web Mining, Web Personalization and Recommendation and Web Community Analysis domains, including a detailed presentation of the principles, developed algorithms, and systems of the research in these areas. The applications of web mining, and the issue of how to incorporate web mining into web personalization and recommendation systems are also reviewed. Additionally, the volume explores web community mining and analysis to find the structural, organizational and temporal developments of web communities and reveal the societal sense of individuals or communities. The volume will benefit both academic and industry communities interested in the techniques and applications of web search, web data management, web mining and web knowledge discovery, as well as web community and social network analysis.

Zhou, W, Cuzzocrea, A & Hobbs, M 2011, Message from the ADCN 2011 chairs.
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Bian, W & Tao, D 2011, 'Face Subspace Learning' in Li, SZ & Jain, AK (eds), Handbook of Face Recognition, Springer-Verlag London Ltd., London UK, pp. 51-77.
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Ferguson, S, Martens, W & Cabrera, D 2011, 'Statistical Sonification for Exploratory Data Analysis' in Hermann, T, Hunt, A & Neuhoff, JG (eds), The Sonification Handbook, Logos Verlag Berlin GmBH, Berlin, Germany, pp. 175-196.
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At the time of writing, it is clear that more data is available than can be practically digested in a straightforward manner without some form of processing for the human observer. This problem is not a new one, but has been the subject of a great deal of practical investigation in many fields of inquiry. Where there is ready access to existing data, there have been a great many contributions from data analysts who have refined methods that span a wide range of applications, including the analysis of physical, biomedical, social, and economic data. A central concern has been the discovery of more or less hidden information in available data, and so statistical methods of data mining for `the gold in there have been a particular focus in these developments. A collection of tools that have been amassed in response to the need for such methods form a set that has been termed Exploratory Data Analysis [48], or EDA, which has become widely recognized as constituting a useful approach. The statistical methods employed in EDA are typically associated with graphical displays that seek to `tease out a structure in a dataset, and promote the understanding or falsification of hypothesized relationships between parameters in a dataset.

Johnston, AJ 2011, 'Almost Tangible Musical Interfaces' in Candy, L & Edmonds, E (eds), Interacting Art, Research and the Creative Practitioner, Libri Publishing, Faringdon, Oxfordshire, U.K, pp. 211-224.
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Primarily I see myself as a musician. Certainly Im a researcher too, but my research is with and for musicians and is inextricably bound up in the practice of performing. Research questions arise through the execution of, reflection upon and examination of performance. This is because Id like the findings of my research, and the performance works which are at the core of the work, to be interesting and relevant to other musicians and composers. As someone who put a lot of work into trying to be a good musician for quite some time, this feels like a natural way to operate. I understand how musicians think, I speak the language and I respect their skill and dedication. I dont for a moment propose that the practicebased research approach I will describe in this chapter is the one and only way to conduct research in this area. It is, however, an approach that has worked for me. It has enabled me to continue to work creatively, while also engaging in research grounded in an epistemology of practice.

Ma, J, Zhang, G & Lu, J 2011, 'A Fuzzy Hierarchical Multiple Criteria Group Decision Support System - Decider - And Its Applications' in Kacprzyk, PJ (ed), Studies In Fuzziness And Soft Computing, Springer, Berlin, Germany, pp. 383-403.
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Decider is a Fuzzy Hierarchical Multiple Criteria Group Decision Support System (FHMC-GDSS) designed for dealing with subjective, in particular linguistic, information and objective information simultaneously to support group decision making particularly on evaluation. In this chapter, the fuzzy aggregation decision model, functions and structure of Decider are introduced. The ideas to resolve decision and evaluation problems we have faced in the development and application of Decider are presented. Two real applications of the Decider system are briefly illustrated. Finally, we discuss our further research in this area.

Smith, ST, Talaei-Khoei, A, Ray, M & Ray, PK 2011, 'Agent-Based Monitoring of Functional Rehabilitation Using Video Games' in Advanced Computational Intelligence Paradigms in Healthcare 5, Springer, Germany, pp. 113-141.
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In recent years, there has been an increasing trend towards using video games for health applications. In particular interactive video games, where an individual interacts with the game by moving their limbs or whole body, have started to find application in the field of rehabilitation medicine. The often dull and repetitive nature of rehabilitation exercise can be transformed into an activity to which patients happily adhere via the use of engaging video games that are enjoyable to play. One additional potential benefit of video game use in rehabilitation is that patients can continue to interact with the video game system in their own home following discharge from hospital. As such, video games may offer a means for rehabilitation specialists to remotely assess compliance of patients with their rehabilitation therapy and monitor changes in function over time. Although the use of technology for monitoring health at home is now widespread, an as yet unexplored challenge lies in integrating information technologies with rehabilitation games. This keeps the health professional informed about compliance and progress of the video game exercise, while the patient performs her/his prescribed rehabilitation routine at home. Therefore, there is a strong need for a computational framework to support the medical professional and patient by using an agent-based architecture. Agents are pieces of software that act on behalf of human roles, involved in rehabilitation process. The objective of this chapter is to thus address major issues in designing an agent-based mobile monitoring system for rehabilitation treatments. The chapter also suggests how to remotely measure the patients progress in rehabilitation treatments while the patient plays video games at home.

Adeel, MS & Saqib, MA 2011, 'An adaptive scheme for power-related measurements and power-factor correction', Australian Journal of Electrical and Electronics Engineering, vol. 8, no. 3, pp. 211-218.
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This paper presents a fast, low cost and accurate instrumentation scheme for powerrelated measurements and power-factor correction. These measurements include the root-meansquare values of current and voltage, the active and reactive powers, the total harmonic distortion and the true power factor. It is a microcontroller-based digital sampling system which runs a fast algorithm for displacement power factor measurement. The controlling system monitors and senses any variations in power factor, and accordingly switches the appropriate capacitor combination across the load. The scheme presents an economical and efficient solution to the power distribution companies for its customers. © Institution of Engineers Australia, 2011.

Anaissi, A, Kennedy, PJ & Goyal, ML 2011, 'Dimension Reduction of Microarray Data Based on Local Principal Component', World Academy of Science, Engineering and Technology, vol. 77, pp. 68-73.
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Analysis and visualization of microarraydata is veryassistantfor biologists and clinicians in the field of diagnosis and treatment of patients. It allows Clinicians to better understand the structure of microarray and facilitates understanding gene expression in cells. However, microarray dataset is a complex data set and has thousands of features and a very small number of observations. This very high dimensional data set often contains some noise, non-useful information and a small number of relevant features for disease or genotype. This paper proposes a non-linear dimensionality reduction algorithm Local Principal Component (LPC) which aims to maps high dimensional data to a lower dimensional space. The reduced data represents the most important variables underlying the original data. Experimental results and comparisons are presented to show the quality of the proposed algorithm. Moreover, experiments also show how this algorithm reduces high dimensional data whilst preserving the neighbourhoods of the points in the low dimensional space as in the high dimensional space.

Barolli, L, Takizawa, M & Hussain, FK 2011, 'Special issue on emerging trends in cyber-physical systems', Journal of Ambient Intelligence and Humanized Computing, vol. 2, no. 4, pp. 249-250.
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Bian, W & Tao, D 2011, 'Max-Min Distance Analysis By Using Sequential SDP Relaxation For Dimension Reduction', IEEE Transactions On Pattern Analysis And Machine Intelligence, vol. 33, no. 5, pp. 1037-1050.
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Abstract - We propose a new criterion for discriminative dimension reduction, max-min distance analysis (MMDA). Given a data set with C classes, represented by homoscedastic Gaussians, MMDA maximizes the minimum pairwise distance of these C classes in the selected low-dimensional subspace. Thus, unlike Fishers linear discriminant analysis (FLDA) and other popular discriminative dimension reduction criteria, MMDA duly considers the separation of all class pairs. To deal with general case of data distribution, we also extend MMDA to kernel MMDA (KMMDA). Dimension reduction via MMDA/KMMDA leads to a nonsmooth max-min optimization problem with orthonormal constraints. We develop a sequential convex relaxation algorithm to solve it approximately. To evaluate the effectiveness of the proposed criterion and the corresponding algorithm, we conduct classification and data visualization experiments on both synthetic data and real data sets. Experimental results demonstrate the effectiveness of MMDA/KMMDA associated with the proposed optimization algorithm.

Bremner, MJ, Jozsa, R & Shepherd, D 2011, 'Classical simulation of commuting quantum computations implies collapse of the polynomial hierarchy', Proceedings Of The Royal Society A-Mathematical Physical And Engineering Sciences, vol. 467, no. 2126, pp. 459-472.
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We consider quantum computations comprising only commuting gates, known as IQP computations, and provide compelling evidence that the task of sampling their output probability distributions is unlikely to be achievable by any efficient classical means. More specifically, we introduce the class post-IQP of languages decided with bounded error by uniform families of IQP circuits with post-selection, and prove first that post-IQP equals the classical class PP. Using this result we show that if the output distributions of uniform IQP circuit families could be classically efficiently sampled, either exactly in total variation distance or even approximately up to 41 per cent multiplicative error in the probabilities, then the infinite tower of classical complexity classes known as the polynomial hierarchy would collapse to its third level. We mention some further results on the classical simulation properties of IQP circuit families, in particular showing that if the output distribution results from measurements on only O(log n) lines then it may, in fact, be classically efficiently sampled.

Budka, M, Gabrys, B & Musial, K 2011, 'On Accuracy of PDF Divergence Estimators and Their Applicability to Representative Data Sampling', ENTROPY, vol. 13, no. 7, pp. 1229-1266.
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Chao, PC-P, Liao, P-Y, Tsai, M-Y & Lin, C-T 2011, 'Robust control design for precision positioning of a generic piezoelectric system with consideration of microscopic hysteresis effects', MICROSYSTEM TECHNOLOGIES-MICRO-AND NANOSYSTEMS-INFORMATION STORAGE AND PROCESSING SYSTEMS, vol. 17, no. 5-7, pp. 1009-1023.
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Chen, H-T, Wei, L-Y & Chang, C-F 2011, 'Nonlinear Revision Control for Images', ACM TRANSACTIONS ON GRAPHICS, vol. 30, no. 4.
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Chen, P-Y, Van, L-D, Khoo, I-H, Reddy, HC & Lin, C-T 2011, 'Power-Efficient and Cost-Effective 2-D Symmetry Filter Architectures', IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-REGULAR PAPERS, vol. 58, no. 1, pp. 112-125.
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Chen, S-W, Lin, S-H, Liao, L-D, Lai, H-Y, Pei, Y-C, Kuo, T-S, Lin, C-T, Chang, J-Y, Chen, Y-Y, Lo, Y-C, Chen, S-Y, Wu, R & Tsang, S 2011, 'Quantification and recognition of parkinsonian gait from monocular video imaging using kernel-based principal component analysis', BIOMEDICAL ENGINEERING ONLINE, vol. 10.
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Cheng, JL, Qiao, M, Bian, W & Tao, D 2011, '3D Human Posture Segmentation By Spectral Clustering With Surface Normal Constraint', Signal Processing, vol. 91, no. 9, pp. 2204-2212.
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In this paper, we propose a new algorithm for partitioning human posture represented by 3D point clouds sampled from the surface of human body. The algorithm is formed as a constrained extension of the recently developed segmentation method, spectral clu

Chiu, T-T, Lin, C-L, Young, K-Y, Lin, C-T, Hsu, S-H, Yang, B-S & Huang, Z-R 2011, 'A STUDY OF FITTS' LAW ON GOAL-DIRECTED AIMING TASK WITH MOVING TARGETS', PERCEPTUAL AND MOTOR SKILLS, vol. 113, no. 1, pp. 339-352.
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Chonka, A, Xiang, Y, Zhou, W & Bonti, A 2011, 'Cloud security defence to protect cloud computing against HTTP-DoS and XML-DoS attacks', Journal of Network and Computer Applications, vol. 34, no. 4, pp. 1097-1107.
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Cloud computing is still in its infancy in regards to its software as services (SAS), web services, utility computing and platform as services (PAS). All of these have remained individualized systems that you still need to plug into, even though these systems are heading towards full integration. One of the most serious threats to cloud computing itself comes from HTTP Denial of Service or XML-Based Denial of Service attacks. These types of attacks are simple and easy to implement by the attacker, but to security experts they are twice as difficult to stop. In this paper, we recreate some of the current attacks that attackers may initiate as HTTP and XML. We also offer a solution to traceback through our Cloud TraceBack (CTB) to find the source of these attacks, and introduce the use of a back propagation neutral network, called Cloud Protector, which was trained to detect and filter such attack traffic. Our results show that we were able to detect and filter most of the attack messages and were able to identify the source of the attack within a short period of time. © 2010 Elsevier Ltd. All rights reserved.

Chu, DH, Wang, XZ, Wang, ZJ & Xu, XF 2011, 'Personalized requirement oriented virtual service resource aggregation method', Jisuanji Xuebao/Chinese Journal of Computers, vol. 34, no. 12, pp. 2370-2380.
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Personalization and composition are two important features of modern service eco-systems nowadays. A personalized requirements oriented virtual resource aggregation method is proposed in this paper. Service resources are formally described based on multi-dimensioned classification. Personalized requirements from applications are classified, reduced and finally expressed in formal and reusable manners. On this basis, a dynamic pruning based resource aggregation method is presented. The method pays attention to the features of both customer requirements and the organization of service resources. Multiple resources can be dynamically aggregated into coarse-grained virtual resources thus satisfy the requirements rapidly. Experiments show fairly good effectiveness and efficiency of the proposed method.

Clear, T, Whalley, J, Robbins, P, Philpott, A, Eckerdal, A, Laakso, M & Lister, RF 2011, 'Report on the final BRACElet workshop: Auckland University of Technology, September 2010', Journal of Applied Computing and Information Technology, vol. 15, no. 1.
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Abstract This paper reports on the thirteenth and final BRACElet workshop. In this paper we provide a brief retrospective review of the workshops and the findings that have resulted from this multi-institutional multinational investigation into the teaching and learning of novice programmers. Subsequently we report on the work undertaken during the final workshop and then discuss future avenues for research that have evolved as a result of the BRACElet project.

Dengler, KA, Scarfe, G, Redshaw, S & Wilson, V 2011, 'The heart beads program', Journal for Specialists in Pediatric Nursing, vol. 16, pp. 80-84.
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From July 2008 through June 2009, 760 infants and children with cardiac conditions were admitted to a pediatric hospital in Australia with approximately 360 cardiac surgical procedures performed. This was the first experience in hospital for many of these children, with diagnoses signaling the beginning of a long and arduous journey. These children undergo multiple treatments and procedures, as well as multiple admissions for further surgeries. Procedures in any regard can cause stress and anxiety, especially in children who often have limited understanding and so little control over what happens to them (Lau, 2002).

Dong, H & Hussain, FK 2011, 'Focused Crawling for Automatic Service Discovery, Annotation, and Classification in Industrial Digital Ecosystems', IEEE Transactions On Industrial Electronics, vol. 58, no. 6, pp. 2106-2116.
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Digital Ecosystems make use of Service Factories for service entities' publishing, classification, and management. However, before the emergence of Digital Ecosystems, there existed ubiquitous and heterogeneous service information in the Business Ecosyst

Dong, H & Hussain, FK 2011, 'Semantic service matchmaking for digital health ecosystems', Knowledge-based Systems, vol. 24, no. 6, pp. 761-774.
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The vision of Digital Ecosystems was initiated by the European Commission, with the purpose of constructing an information and communication technology environment to facilitate the sustainable development of small and medium enterprises. As a key sub-domain of Digital Ecosystems, Digital Health Ecosystems provide crucial services to maintain the health of the main participants of Digital Ecosystems. We are concerned with the large-scale, ambiguous, heterogeneous, and untrustworthy nature of health service information in Digital Health Ecosystems. An intensive survey found that current research cannot support accurate and trustworthy matchmaking between health service requests and health service advertisements in Digital Health Ecosystems. Therefore, in this paper, we propose a framework for a semantic service matchmaker that takes into account the ambiguous, heterogeneous nature of service information in Digital Health Ecosystems. This framework is designed to make four major contributions, which are health service domain knowledge modeling, online health service information disambiguation, health service query disambiguation and health service quality evaluation and ranking. In order to thoroughly evaluate this framework, we implement a prototype - a Semantic Health Service Search Engine, and conduct a series of experiments on the prototype using a functional testing and simulation approach

Dong, H, Hussain, FK & Chang, E 2011, 'A context-aware semantic similarity model for ontology environments', Concurrency and Computation, vol. 23, no. 5, pp. 505-524.
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While many researchers have contributed to the field of semantic similarity models so far, we find that most of the models are designed for the semantic network environment. When applying the semantic similarity model within the semantic-rich ontology en

Dong, H, Hussain, FK & Chang, E 2011, 'A framework for discovering and classifying ubiquitous services in digital health ecosystems', Journal of Computer and System Sciences, vol. 77, no. 4, pp. 687-704.
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A digital ecosystem is a widespread type of ubiquitous computing environment comprised of ubiquitous, geographically dispersed, and heterogeneous species, technologies and services. As a subdomain of the digital ecosystems, digital health ecosystems are crucial for the stability and sustainable development of the digital ecosystems. However, since the service information in the digital health ecosystems exhibits the same features as those in the digital ecosystems, it is difficult for a service consumer to precisely and quickly retrieve a service provider for a given health service request. Consequently, it is a matter of urgency that a technology is developed to discover and classify the health service information obtained from the digital health ecosystems. A survey of state-of-the-art semantic service discovery technologies reveals that no significant research effort has been made in this area. Hence, in this paper, we present a framework for discovering and classifying the vast amount of service information present in the digital health ecosystems. The framework incorporates the technology of semantic focused crawler and social classification. A series of experiments are conducted in order to respectively evaluate the framework and the employed mathematical model.

Dong, H, Hussain, FK & Chang, E 2011, 'A service concept recommendation system for enhancing the dependability of semantic service matchmakers in the service ecosystem environment', Journal Of Network And Computer Applications, vol. 34, no. 2, pp. 619-631.
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A Service Ecosystem is a biological view of the business and software environment, which is comprised of a Service Use Ecosystem and a Service Supply Ecosystem. Service matchmakers play an important role in ensuring the connectivity between the two ecosystems. Current matchmakers attempt to employ ontologies to disambiguate service consumers' service queries by semantically classifying service entities and providing a series of human computer interactions to service consumers. However, the lack of relevant service domain knowledge and the wrong service queries could prevent the semantic service matchmakers from seeking the service concepts that can be used to correctly represent service requests. To resolve this issue, in this paper, we propose the framework of a service concept recommendation system, which is built upon a semantic similarity model. This system can be employed to seek the concepts used to correctly represent service consumers' requests, when a semantic service matchmaker finds that the service concepts that are eventually retrieved cannot match the service requests. Whilst many similar semantic similarity models have been developed to date, most of them focus on distance-based measures for the semantic network environment and ignore content-based measures for the ontology environment. For the ontology environment in which concepts are defined with sufficient datatype properties, object properties, and restrictions etc., the content of concepts should be regarded as an important factor in concept similarity measures. Hence, we present a novel semantic similarity model for the service ontology environment. The technical details and evaluation details of the framework are discussed in this paper

Dong, H, Hussain, FK & Chang, E 2011, 'A Service Search Engine for the Industrial Digital Ecosystems', IEEE Transactions On Industrial Electronics, vol. 58, no. 6, pp. 2183-2196.
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Digital ecosystem (DE) is comprised of heterogeneous and distributed species which can play the dual role of service provider and service requester. Nowadays, DE lacks semantic search support, which means it cannot provide a reliable and trustworthy link

Dong, H, Hussain, FK & Chang, E 2011, 'ORPMS: An Ontology-based Real-time Project Monitoring System in the Cloud', Journal of Universal Computer Science, vol. 17, no. 8, pp. 1161-1182.
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Ferguson, S, Schubert, E & Dean, R 2011, 'Continuous subjective loudness responses to reversals and inversions of a sound recording of an orchestral excerpt', Musicae Scientiae, vol. 15, no. 3, pp. 387-401.
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Twenty-four respondents continuously rated the loudness of the first 65 seconds of a Dvorak Slavonic Dance, which was known to vary considerably in loudness. They also rated the same excerpt when the sound file was digitally treated so that (1) the sound pressure level (SPL) was inverted or (2) it was temporally reversed or (3) both 1 and 2. Specifically we wanted to see if acoustic intensity was processed into the percept of loudness primarily using a bottom-up (indifferent to timbral environment and thematic cues) or top-down style (where musical context, such as instrument identity and musical expectation affects the loudness rating). Comparing the different versions (conditions) allowed us to ascertain which style they were likely to be using. A single, six-second region was located as being differentiated across two conditions, where loudness seemed to be increased due to expectation of the instrument and orchestral texture, despite the lower SPL. We named this effect an auditory loudness stroop. A second region was differentiated between the two conditions, but its explanation appears to involve two factors, auditory looming perception and the reversal of stimulus note ramps. The overall conclusion was that the predominant processing style for loudness rating was bottom-up. Implications for further research and application to models of loudness are discussed.

Gao, Y, Zhang, G, Lu, J & Wee, H 2011, 'Particle swarm optimization for bi-level pricing problems in supply chains', Journal Of Global Optimization, vol. 51, no. 2, pp. 245-254.
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With rapid technological innovation and strong competition in hi-tech industries such as computer and communication organizations, the upstream component price and the downstream product cost usually decline significantly with time. As a result, an effective pricing supply chain model is very important. This paper first establishes two bi-level pricing models for pricing problems with the buyer and the vendor in a supply chain designated as the leader and the follower, respectively. A particle swarm optimization (PSO) based algorithm is developed to solve problems defined by these bi-level pricing models. Experiments illustrate that this PSO based algorithm can achieve a profit increase for buyers or vendors if they are treated as the leaders under some situations, compared with the existing methods.

Goebel, R & Williams, M 2011, 'Editorial : The Expansion Continues: Stitching together the Breadth of Disciplines Impinging on Artificial Intelligence', Artificial Intelligence Journal, vol. 175, no. 5-6, pp. 929-929.

Golsteijn, C & van den Hoven, E 2011, 'Facilitating Communication About Books Through An Online Community', Personal and Ubiquitous Computing, vol. 15, no. 2, pp. 197-217.
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Reading books can serve as a means of gathering information, relaxing and escaping daily stress. Although reading is often primarily an individual activity, many readers also enjoy sharing reading experiences with friends, relatives, colleagues and, through the internet, even with strangers. Apart from valuing these individual and collective book activities, books as physical artifacts are also valued, for example because of the memories associated with them. This paper investigates how books can be enhanced with a new product, system or service. In a qualitative interview study, the main reasons for valuing books were found to be related to the self (individual activities and feelings), experiences (e.g., enjoyment or release) and personal values (e.g., embodiment of ideals or personification). As a result, it was decided for the remainder of this study to focus on communication about books, because in addition to individual book-related activities and feelings, users indicated to communicate about books a lot. A book community Web site, called Shelf, was developed to investigate whether book communication could be increased by facilitating an online community and whether users would appreciate the Website functionality. Shelf was used in a 14-day user evaluation, and it was concluded that the Web site increased the extent to which readers communicated about books. We expect that such an online book community would be a valuable enhancement of current book customs, in particular in combination with the current e-book trend, for various types of readers who would like to share their experiences.

Gramann, K, Gwin, JT, Ferris, DP, Oie, K, Jung, T-P, Lin, C-T, Liao, L-D & Makeig, S 2011, 'Cognition in action: imaging brain/body dynamics in mobile humans', REVIEWS IN THE NEUROSCIENCES, vol. 22, no. 6, pp. 593-608.
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Guo, Z, Wu, J, Lu, H & Wang, J 2011, 'A Case Study On A Hybrid Wind Speed Forecasting Method Using BP Neural Network', Knowledge-Based Systems, vol. 24, no. 7, pp. 1048-1056.
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Wind energy, which is intermittent by nature, can have a significant impact on power grid security, power system operation, and market economics, especially in areas with a high level of wind power penetration. Wind speed forecasting has been a vital part of wind farm planning and the operational planning of power grids with the aim of reducing greenhouse gas emissions. Improving the accuracy of wind speed forecasting algorithms has significant technological and economic impacts on these activities, and significant research efforts have addressed this aim recently. However, there is no single best forecasting algorithm that can be applied to any wind farm due to the fact that wind speed patterns can be very different between wind farms and are usually influenced by many factors that are location-specific and difficult to control. In this paper, we propose a new hybrid wind speed forecasting method based on a back-propagation (BP) neural network and the idea of eliminating seasonal effects from actual wind speed datasets using seasonal exponential adjustment. This method can forecast the daily average wind speed one year ahead with lower mean absolute errors compared to figures obtained without adjustment, as demonstrated by a case study conducted using a wind speed dataset collected from the Minqin area in China from 2001 to 2006.

Gwin, JT, Gramann, K, Makeig, S & Ferris, DP 2011, 'Electrocortical activity is coupled to gait cycle phase during treadmill walking', NEUROIMAGE, vol. 54, no. 2, pp. 1289-1296.
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Hardy, CA & Williams, SP 2011, 'Assembling E-Government Research Designs: A Transdisciplinary View and Interactive Approach', PUBLIC ADMINISTRATION REVIEW, vol. 71, no. 3, pp. 405-413.
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Huang, T & Huang, M 2011, 'Exploring the Relative Importance of Number of Edge Crossings and Size of Crossing Angle: A Quantitative Perspective', International Journal of Advanced Intelligence (IJAI), vol. 3, no. 1, pp. 25-42.
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Recent research has indicated that human graph reading performance can be affected by the size of crossing angles. The aesthetic of crossing angles is closely related to another aesthetic factor: edge crossings. Although the number of edge crossings has been previously identi?ed as the most important aesthetic, its relative impact on human graph reading, compared to the size of crossing angles, has not been investigated. In this paper, we present an exploratory user study investigating the relative importance between crossing number and crossing angle. This study also aims to further examine the effects of crossing number and crossing angle not only on task performance measured as response time and accuracy, but also on cognitive load and visualization ef?ciency. The experimental results reinforce the previous ?ndings that the two aesthetics each signi?cantly affect performance of human graph reading. Further, in terms of the relative importance, the study demonstrates that given the current setting of the user study, the number of edge crossings is relatively more important than the size of crossing angles. To be more speci?c, crossing number and crossing angle together explain about 40% of the variance in response time, mental effort and visualization ef?ciency, with about 83% of the explained variance being attributed to crossing number. In regard to response accuracy, crossing number and crossing angle together explain about 14% of the variance, with a slightly larger portion of the explained variance being attributed to crossing number

Hussain, O, Dillon, TS, Hussain, FK & Chang, E 2011, 'Probabilistic assessment of financial risk in e-business associations', Simulation Modelling Practice and Theory, vol. 19, no. 2, pp. 704-717.
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Business activities are a result of carefully formed associations between different users in order to achieve certain pre-decided outcomes. Decision-making in such associations is an important step and transactional risk analysis is one of the integral processes that facilitates this step. This paper presents an approach that determines the negative consequences (termed as financial risk) of forming e-business associations. Unlike other approaches, our model captures the different types of events and their uncertainties to determine the financial risk by using the convolution operator and expressing it as a probabilistic measure rather than as a crisp financial value. Such representation makes sense as the financial risk may be determined at a point of time in future where nothing is certain. Depending upon the complexity of the problem, we explain the different ways of using the convolution operator to determine the financial risk. The simulation result shows a better representation and understanding of the financial risk that will provide important inputs to the transactional risk analysis and the decision-making process.

Jay, B & Given-Wilson, T 2011, 'A Combinatory Account of Internal Structure', Journal of Symbolic Logic, vol. 76, pp. 807-826.
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Kazienko, P, Musial, K & Kajdanowicz, T 2011, 'Multidimensional Social Network in the Social Recommender System', IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART A-SYSTEMS AND HUMANS, vol. 41, no. 4, pp. 746-759.
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Kennard, R & Leaney, JR 2011, 'Is There Convergence in the Field of UI Generation?', Journal of Systems and Software, vol. 84, no. 12, pp. 2079-2087.
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For many software projects, the construction of the User Interface (UI) consumes a significant proportion of their development time. Any degree of automation in this area therefore has clear benefits. But it is difficult to achieve such automation in a way that will be widely adopted by industry because of the diversity of UIs, software architectures, platforms and development environments. In a previous article, the authors identified five key characteristics any UI generator would need in order to address this diversity. We asserted that, without these characteristics, a UI generator should not expect wide industry adoption or standardisation. We supported this assertion with evidence from industry adoption studies. A further source of validation would be to see if other research teams, who were also conducting industry field trials, were independently converging on this same set of characteristics. Conversely, it would be instructive if they were found to be converging on a different set of characteristics. In this article, the authors look for such evidence of convergence by interviewing the team behind one of the research community's most significant UI generators: Naked Objects. We observe strong signs of convergence, which we believe signal the beginning of a general purpose architecture for UI generation, one that both industry and the research community could standardise upon.

Lai, W, Huang, X & Huang, M 2011, 'SWING: A System for Visualizing Web Graphs', Advances in Information Sciences and Service Sciences (AISS), vol. 3, no. 2, pp. 94-101.
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A Web graph refers to the graph that is used to represent relationships between Web pages in cyberspace, where a node represents a URL and an edge indicates a link between two URLs. A Web graph is a very huge graph as growing with cyberspace. This paper presents a pipeline for extracting web information from cyberspace to a web graph and layout techniques for making the web graph more readable. As the size of computer screen is limited, only a small part of the Web graph can be displayed. Several layout techniques should be adapted and combined effectively for web graph visualization. The visualization process incorporates graph drawing algorithms, layout adjustment methods, as well as filtering and clustering methods in order to decide which part of the Web graph should be displayed and how to display it based on the users focus in navigation.

Li, C-H, Kuo, B-C & Lin, C-T 2011, 'LDA-Based Clustering Algorithm and Its Application to an Unsupervised Feature Extraction', IEEE TRANSACTIONS ON FUZZY SYSTEMS, vol. 19, no. 1, pp. 152-163.
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Li, L, Xu, G, Zhang, Y & Kitsuregawa, M 2011, 'Random walk based rank aggregation to improving web search', Knowledge-based Systems, vol. 24, no. 7, pp. 943-951.
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In Web search, with the aid of related query recommendation, Web users can revise their initial queries in several serial rounds in pursuit of finding needed Web pages. In this paper, we address the Web search problem on aggregating search results of related queries to improve the retrieval quality. Given an initial query and the suggested related queries, our search system concurrently processes their search result lists from an existing search engine and then forms a single list aggregated by all the retrieved lists. We specifically propose a generic rank aggregation framework which consists of three steps. First we build a so-called Win/Loss graph of Web pages according to a competition rule, and then apply the random walk mechanism on the Win/Loss graph. Last we sort these Web pages by their ranks using a PageRank-like rank mechanism. The proposed framework considers not only the number of wins that an item won in competitions, but also the quality of its competitor items in calculating the ranking of Web page items. Experimental results show that our search system can clearly improve the retrieval quality in a parallel manner over the traditional search strategy that serially returns result lists. Moreover, we also provide empirical evidences as to demonstrate how different rank aggregation methods affect the retrieval quality.

Liao, L-D, Wang, I-J, Chen, S-F, Chang, J-Y & Lin, C-T 2011, 'Design, Fabrication and Experimental Validation of a Novel Dry-Contact Sensor for Measuring Electroencephalography Signals without Skin Preparation', SENSORS, vol. 11, no. 6, pp. 5819-5834.
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Liao, Y, Gramann, K, Feng, W, Deak, GO & Li, H 2011, 'This ought to be good: Brain activity accompanying positive and negative expectations and outcomes', PSYCHOPHYSIOLOGY, vol. 48, no. 10, pp. 1412-1419.
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Lin, C, L. W., K, H. Y., T & T. P., J 2011, 'A Mobile Eeg Device For On-line Assessment Of Sleep Quality', Sleep and Biological Rhythms, vol. 9, no. 4, pp. 222-223.
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Lin, CJ, Chen, CH & Lin, CT 2011, 'An efficient evolutionary algorithm for fuzzy inference systems', Evolving Systems, vol. 2, no. 2, pp. 83-99.
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In this paper, a novel self-constructing evolutionary algorithm (SCEA) for designing a TSK-type fuzzy model (TFM) is proposed. The proposed SCEA method is different from normal genetic algorithms (GAs). A chromosome of a population in traditional GAs represents a full solution and only one population presents all solutions in each generation. Our proposed method uses a population to evaluate a partial solution locally and applies several populations to construct a full solution. Thus, a chromosome represents only a partial solution. The proposed SCEA method uses the self-constructing learning algorithm to construct the TFM automatically that is based on the input training data to decide on the input partition. Fuzzy rules are created and begin to grow as the first training pattern arrives. Thus, the user need not give any a priori knowledge or even any initial information on the SCEA. We also adopted the sequence search-based dynamic evolution (SSDE) method to carry out parameter learning of the TFM. Simulation results have shown that the proposed SCEA method performs better than some existing methods. © 2010 Springer-Verlag.

Lin, CT & Lee, CS 2011, 'FUZZ-IEEE 2011', IEEE Computational Intelligence Magazine, vol. 6, no. 4, pp. 22-23.
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The FUZZ-IEEE is one of the premier international conferences in the field of fuzzy sets and systems. The 2011 IEEE International Conference on Fuzzy Systems (FUZZIEEE 2011) was held at the Grand Hyatt Taipei, Taiwan, from June 27 to 30, 2011. Paper submissions were reviewed by at least three reviewers, with no specific treatment given to papers submitted for special sessions. The IEEE CIS travel grants program provided travel grants to assist 10 IEEE CIS student members to attend the conference to present their papers. FUZZ-IEEE 2011 consisted of 5 workshops, 18 regular sessions, 43 special sessions, and 4 poster sessions, covering both traditional and emerging topics on the whole range of research and applications in fuzzy systems and soft computing. In additional to the excellent technical program, a series of social events were held to allow participants to better appreciate the sights and sounds of Taiwan.

Lin, C-T, Chen, S-A, Chiu, T-T, Lin, H-Z & Ko, L-W 2011, 'Spatial and temporal EEG dynamics of dual-task driving performance.', Journal of NeuroEngineering and Rehabilitation, vol. 8, pp. 11-11.
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BACKGROUND: Driver distraction is a significant cause of traffic accidents. The aim of this study is to investigate Electroencephalography (EEG) dynamics in relation to distraction during driving. To study human cognition under a specific driving task, simulated real driving using virtual reality (VR)-based simulation and designed dual-task events are built, which include unexpected car deviations and mathematics questions. METHODS: We designed five cases with different stimulus onset asynchrony (SOA) to investigate the distraction effects between the deviations and equations. The EEG channel signals are first converted into separated brain sources by independent component analysis (ICA). Then, event-related spectral perturbation (ERSP) changes of the EEG power spectrum are used to evaluate brain dynamics in time-frequency domains. RESULTS: Power increases in the theta and beta bands are observed in relation with distraction effects in the frontal cortex. In the motor area, alpha and beta power suppressions are also observed. All of the above results are consistently observed across 15 subjects. Additionally, further analysis demonstrates that response time and multiple cortical EEG power both changed significantly with different SOA. CONCLUSIONS: This study suggests that theta power increases in the frontal area is related to driver distraction and represents the strength of distraction in real-life situations.

Lin, C-T, Liao, L-D, Liu, Y-H, Wang, I-J, Lin, B-S & Chang, J-Y 2011, 'Novel Dry Polymer Foam Electrodes for Long-Term EEG Measurement', IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, vol. 58, no. 5, pp. 1200-1207.
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Lister, R 2011, 'Computing education research - Programming, syntax and cognitive load (Part 2)', ACM Inroads, vol. 2, no. 3, pp. 16-17.
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Lister, RF 2011, 'COMPUTING EDUCATION RESEARCH: What If We Approached Teaching Like Software Engineering?', ACM Inroads, vol. 2, no. 1, pp. 17-18.
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This is a regular invited column I write for this journal.

Lister, RF 2011, 'Programming, syntax and cognitive load', ACM Inroads, vol. 2, no. 2, pp. 21-22.
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This is a regular invited column I write for this journal.

Lister, RF 2011, 'Programming, Syntax and Cognitive Load (Part 2)', ACM Inroads, vol. 2, no. 3, pp. 16-17.
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This is a regular invited column I write for this journal.

Lister, RF 2011, 'Ten years after the McCracken Working Group', ACM Inroads, vol. 2, no. 4, pp. 18-19.
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This is a regular invited column I write for this journal.

Lu, J & Zhang, G 2011, 'Guest editorial: Optimization Techniques for Business Intelligence', Journal Of Global Optimization, vol. 51, no. 2, pp. 185-187.
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Lu, J, Ma, J, Zhang, G, Zhu, Y, Zeng, X & koehl, L 2011, 'Theme-Based Comprehensive Evaluation In New Product Development Using Fuzzy Hierarchical Criteria Group Decision-Making Method', Ieee Transactions On Industrial Electronics, vol. 58, no. 6, pp. 2236-2246.
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AbstractOne of the features of the digital ecosystem is the integration of human cognition and socio-economic themes into the process of new product development (NPD). In a socio-economic theme-based NPD, ranking a set of product prototypes that have been designed always requires the participation of multiple evaluators and consideration of multiple evaluation criteria. Using the well-being theme-based garment NPD as a background, this paper first presents a fuzzy hierarchical criteria group decision-making (FHCGDM) method which can effectively calculate final ranking results through fusing all assessment data from human beings and machines. It then presents a garment NPD comprehensive evaluation model with hierarchical criteria under the well-being theme through identifying a set of marketing tactics from a consumer acceptance survey. It further provides an establishment process for an NPD evaluation model under the digital ecosystem framework. Finally, a garment NPD case study further demonstrates the proposed well-being NPD comprehensive evaluation model and the FHCGDM method. The advantages of the proposed evaluation method include successfully handling criteria in a hierarchical structure, automatically processing both objective measurements from machines and subjective assessments from human evaluators, and using the most suitable type of fuzzy numbers to describe linguistic terms.

Macinnis-Ng, CM, Zeppel, MJ, Williams, M & Eamus, D 2011, 'Applying a SPA model to examine the impact of climate change on GPP of open woodlands and the potential for woody thickening', Ecohydrology, vol. 4, no. 3, pp. 379-393.
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Woody thickening is a global phenomenon that influences landscape C density, regional ecohydrology and biogeochemical cycling. The aim of the work described here is to test the hypothesis that increased atmospheric CO2 concentration, with or without photosynthetic acclimation, can increase gross primary production (GPP) and that this can explain woody thickening. We examine mechanisms underlying the response of GPP and highlight the importance of changes in soil water content by applying a detailed soil-plant-atmosphere model. Through this model, we show that CO2 enrichment with decreased or increased D and photosynthetic acclimation results in decreased canopy water use because of reduced gs. The decline in water use coupled with increased photosynthesis resulted in increased GPP, water-use efficiency and soil moisture content. This study shows that this is a valid mechanism for GPP increase because of CO2 enrichment coupled with either a decrease or an increase in D, in water-limited environments. We also show that a large increase in leaf area index could be sustained in the future as a result of the increased soil moisture content arising from CO2 enrichment and this increase was larger if D decreases rather than increases in the future. Large-scale predictions arising from this simple conceptual model are discussed and found to be supported in the literature. We conclude that woody thickening in Australia and probably globally can be explained by the changes in landscape GPP and soil moisture balance arising principally from the increased atmospheric CO2 concentration.

Macnamara, J & Kenning, G 2011, 'E-electioneering 2010: Trends in social media use in Australian political communication', Media International Australia, vol. 139, no. May, pp. 7-22.
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In the wake of the ‘turning point’ 2004 US presidential election, the Obama campaign of 2008, the 2010 UK election and e-democracy movements globally, Australians went to the polls in 2010 in a media-hyped flurry of tweeting, YouTube videos, Facebook befriending and ‘liking’, blogging and other social media activities. Following a study showing that the 2007 Australian election was not a ‘YouTube election’, as claimed by many media and commentators, and that social media use in the campaign was mostly non-interactive promotional messaging, a study was undertaken during the 2010 federal election campaign to gain comparative data and updated insights. This article reports quantitative and qualitative content analysis of social media use by 206 federal political candidates and the two major political parties during the 2010 Australian election to identify trends in the volume of e-electioneering content and activity, as well as the main ways in which social media are being used in political communication.

Nizami, S, Green, JR & McGregor, C 2011, 'Service Oriented Architecture to Support Real-Time Implementation of Artifact Detection in Critical Care Monitoring', 2011 ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC), pp. 4925-4928.

Oberst, S & Lai, JCS 2011, 'Chaos in brake squeal noise', JOURNAL OF SOUND AND VIBRATION, vol. 330, no. 5, pp. 955-975.
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Oberst, S & Lai, JCS 2011, 'Statistical analysis of brake squeal noise', JOURNAL OF SOUND AND VIBRATION, vol. 330, no. 12, pp. 2978-2994.
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O'Hara, ML, Sample, S & Williams, MA 2011, 'Heart failure: From the icu to step‐down—and home', Nursing Management, vol. 37, no. 8, pp. 36-39.
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A detailed transition plan can help prepare eligible patientsfor discharge. © 2011 Lippincott Williams & Wilkins, Inc.

Panozzo, D, Puppo, E, Tarini, M, Pietroni, N & Cignoni, P 2011, 'Automatic construction of quad-based subdivision surfaces using fitmaps', IEEE transactions on visualization and computer graphics, vol. 17, pp. 1510-1520.

Parvin, S, Hussain, FK, Han, S & Hussain, O 2011, 'Trust-based spectrum sharing for cognitive radio networks', Journal of Interconnection Networks, vol. 12, no. 3, pp. 155-171.
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Cognitive Radio Networks (CRNs) is a promising technology which deals with shared spectrum access and usage in order to improve the utilization of limited radio spectrum resources for future wireless communications and mobile computing. Security becomes a very challenging issue in CRNs as different types of attacks are very common to cognitive radio technology compared to general wireless networks. The proper working of cognitive radio and the functionality of CRNs relies on the compliant behaviour of the secondary user. In order to address this issue, we propose two approaches in this paper. Firstly, we propose a trust aware model to authenticate the secondary users of CRNs which offers a reliable technique to provide a security-conscious decision by using trust evaluation for CRNs. Secondly, we propose an analytical model for analyzing the availability of spectrum in CRNs using a stochastic approach. We have modeled and analyzed the availability of free spectrum for the usage of secondary users by adopting different activities in a spectrum management scheme to improve the spectrum availability in CRNs

Pietroni, N, Massimiliano, C, Cignoni, P & Scopigno, R 2011, 'An interactive local flattening operator to support digital investigations on artwork surfaces', IEEE transactions on visualization and computer graphics, vol. 17, pp. 1989-1996.

Pietroni, N, Tarini, M, Sorkine, O & Zorin, D 2011, 'Global Parametrization of Range Image Sets', ACM Transactions on Graphics, vol. 30, no. 6, pp. 1-10.
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We present a method to globally parameterize a surface represented by height maps over a set of planes (range images). In contrast to other parametrization techniques, we do not start with a manifold mesh. The parametrization we compute defines a manifold structure, it is seamless and globally smooth, can be aligned to geometric features and shows good quality in terms of angle and area preservation, comparable to current parametrization techniques for meshes. Computing such global seamless parametrization makes it possible to perform quad remeshing, texture mapping and texture synthesis and many other types of geometry processing operations. Our approach is based on a formulation of the Poisson equation on a manifold structure defined for the surface by the range images. Construction of such global parametrization requires only a way to project surface data onto a set of planes, and can be applied directly to implicit surfaces, nonmanifold surfaces, very large meshes, and collections of range scans. We demonstrate application of our technique to all these geometry types. © 2011, ACM. All rights reserved.

Pietroni, N, Tarini, M, Sorkine, O & Zorin, D 2011, 'Global Parametrization of Range Image Sets', ACM TRANSACTIONS ON GRAPHICS, vol. 30, no. 6.
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Pollatos, O & Gramann, K 2011, 'Electrophysiological evidence of early processing deficits in alexithymia', BIOLOGICAL PSYCHOLOGY, vol. 87, no. 1, pp. 113-121.
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Purba, J, Lu, J, Ruan, D & Zhang, G 2011, 'Failure possibilities for nuclear safety assessment by fault tree analysis', International Journal of Nuclear Knowledge Management, vol. 5, no. 2, pp. 162-177.
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Fault tree analysis (FTA) is a deductive tool to assess the safety of nuclear power plants. This analysis can only be implemented if all basic events in the tree have their corresponding failure rates. Therefore, safety analysts have to provide those failure rates well in advance. However, it is often difficult to obtain those failure rates due to insufficient data, changing environment or new components. This paper proposes a failure possibility based FTA approach to overcome the limitation of the conventional FTA for nuclear safety assessment. It utilises the concept of failure possibilities to evaluate basic event failure without historical data, fuzzy numbers to map component failure possibilities into mathematical form and defuzzification algorithms to convert fuzzy numbers into component failure rates. A case study on evaluating a typical high pressure core spray system of a boiling water reactor illustrates the applicability of the proposed approach.

Raza, M, Hussain, O, Hussain, FK & Chang, E 2011, 'Maturity, distance and density (MD(2)) metrics for optimizing trust prediction for business intelligence', Journal Of Global Optimization, vol. 51, no. 2, pp. 285-300.
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The modelling and management of trust between interacting parties are crucial parts of the overall business intelligence strategy for any organization. Predicting trust values is a key element of modelling and managing trust. It is of critical importance when the interaction is to be conducted at a future point in time. In the existing body of work, there are a few approaches for predicting trust. However, none of these approaches proposes a framework or methodology by which the predicted trust value can be considered in light of its accuracy or confidence level. This is a key element in order to ensure optimized trust prediction. In this paper, we propose a methodology to address this critical issue. The methodology comprises a suite of metricsmaturity, distance and density (MD2) which are capable of capturing various aspects of the confidence level in the predicted trust value. The proposed methodology is exemplified with the help of case studies.

Redshaw, S, Wilson, V, Scarfe, G & Dengler, KA 2011, 'Narratives of the heart: telling the story of children with a cardiac condition through a bead program', Journal Of Clinical Nursing, vol. 20, no. 19-20, pp. 2802-2811.
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Aims. To present and discuss the significance of a bead program in assisting families to put together the story of a childâs journey through cardiac intervention. The main focus of the article is the importance to families of developing a narrative in making sense of the experience of discovering their child has a cardiac condition and how this is enhanced by the bead program. Background. The Heart Beads Program involved giving families beads related to procedures and processes the children undergo while they are in hospital. Research on narratives related to illness suggests that forming a narrative that incorporates the health condition facilitates the ability to talk about these experiences and helps to make sense of and deal with the stressors related to such traumatic life events. Design. A qualitative methodology was used to evaluate the program employing semi-structured interviews and content analysis following a grounded theory approach. Methods. Interviews were undertaken with 11 families to highlight their experiences of being involved in the Heart Beads Program. Themes were identified from the interviews and critical discussion was used to structure and connect the themes. Results. The major theme that emerged from the analysis of the interviews was the importance of the beads in enabling the telling of the childâs story. Five subthemes were identified in this theme: symbolism, encouraging/uplifting, acknowledgement, connection with others and imagining the future. The themes are outlined and expressed through specific comments from interviews. Conclusions. The Heart Beads are seen as presenting a significant way for children and families to comprehend their time in hospital as part of the childâs life story. Relevance to clinical practice. The program can offer the opportunity for health care professionals to relate to the child and familyâs story and to engage with that story in a person centred way.

Saqib, MA, Stokes, AD, James, BW & Falconer, IS 2011, 'Electron temperature and arc diameter in a sand-filled HBC fuse', IEEE Transactions on Plasma Science, vol. 39, no. 7, pp. 1619-1630.
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The electron temperature as a function of time in a model high-breaking-capacity fuse has been determined from measurement of the relative intensity of the Si II spectral lines at 505, 597, and 636 nm. The fuses used in this paper consisted of a 0.55-mm-diameter Ag wire fusible element surrounded by silica (SiO2) sand. The spectra were resolved with a grating spectrometer and recorded by a gated image intensifier coupled to a linear photodiode array for prospective currents of 1.25-and 4.5-kA amplitudes and for arc lengths of 112 and 240 mm. The electron temperatures varied during the life of the arc from no significant change (for 1.25-kA peak prospective current through the long fuse) to ∼50% decrease (for 4.5-kA peak prospective current through the short fuse). Average temperatures, excluding data points at the early and late times during the arc discharge when the most extreme temperatures were measured, were as follows: 1.8 ×104 K and 1.1 ×104 K at 1.25-and 4.5-kA peak prospective currents, respectively, for the 112-mm fuse and 1.4 ×104 K and 1.5 ×104 K at 1.25-and 4.5-kA peak prospective currents, respectively, for the 240-mm fuse. The individual data points, however, exhibited a wide scatter about the line of best fit. Detailed analysis of the data indicates that it is essential to include the intensity of all of the doublets previously listed when measuring the plasma electron temperature and that self-absorption at 636 nm is, at least for the present experiment, not a source of error. The measured electron temperatures were used to calculate the Spitzer conductivity of the plasma which, together with the measured electrical characteristics of the arc, enabled the variation of the diameter of the arc over time to be estimated. © 2011 IEEE.

Schubert, P & Williams, SP 2011, 'A framework for identifying and understanding enterprise systems benefits', Business Process Management Journal, vol. 17, no. 5, pp. 808-828.
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Purpose: Identifying the benefits arising from implementations of enterprise systems and realizing business value remains a significant challenge for both research and industry. This paper aims to consolidate previous work. It presents a framework for investigating enterprise systems benefits and business change, which addresses the identified limitations of previous research and provides a more detailed analysis of benefits and their contextual variation. Design/methodology/approach: Drawing on data gathered from 31 real-world organizations (case studies) of differing size, maturity, and industry sector, the study adopts an iterative content analysis to empirically derive a comprehensive benefits framework. Findings: The content analysis provides a detailed classification of expectations and benefits, which is described in a four-level framework. The four levels (areas) are further subdivided into aspects and criteria plus an attributed appraisal value. The resulting scheme for the "three-level benefit codes" provides a greater level of detail about the nature of expected and realized benefits. Practical implications: The high level of detail and the code scheme comprising 60 different codes and the method for deriving the codes allows companies to identify and define benefits as well as to assess the outcome of enterprise systems implementation projects. Originality/value: The paper empirically develops an applicable benefits framework, which addresses the lack of detail of previous frameworks. © Emerald Group Publishing Limited.

Schubert, P, Williams, SP & Woelfe, R 2011, 'Sustainable competitive advantage in e-commerce and the role of the enterprise system', International Journal of Enterprise Information Systems, vol. 7, no. 2, pp. 1-17.
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Developing and sustaining a competitive advantage from the use of information technology is a topic of concern for information systems research. Mata et al. (1995) present a model that is founded on the resource-based view of the firm. The model is used to discuss factors that lead to competitive advantage in e-commerce companies. This paper explores factors that enable sustainable competitive advantages in B2C retailing. The analysis is based on a single in-depth case study of an Internet pioneer company (Le Shop), which was observed by the authors since its inception more than 10 years ago. The research data stems from a series of interviews with managers at Le Shop as well as two case studies about the company from two different points in time (2000 and 2009). Le Shop is an online pioneer, which began selling groceries on the Internet in Switzerland in April 1998. After a turbulent few years, Le Shop is now one of the few successful e-commerce suppliers in the supermarket segment worldwide. The discussion includes an analysis of further critical resources of the company from a resource-based view. Copyright © 2011, IGI Global.

Seely, AJE, Kauffman, SA, Bates, JHT, Macklem, PT, Suki, B, Marshall, JC, Batchinsky, AI, Perez-Velazquez, JL, Seiver, A, McGregor, C, Maksym, G, Eng, MVKP, Similowski, T, Buchman, TG, Letellier, C, Filoche, M, Frasch, MG, Straus, C, Glass, L, Godin, PJ, Morris, JA, Sow, D, Nenadovic, V, Arnold, RC, Norris, P & Moorman, JR 2011, 'Proceedings from the Montebello Round Table Discussion. Second annual conference on Complexity and Variability discusses research that brings innovation to the bedside', JOURNAL OF CRITICAL CARE, vol. 26, no. 3, pp. 325-327.
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Su, M-T, Chen, C-H, Lin, C-J & Lin, C-T 2011, 'A Rule-Based Symbiotic MOdified Differential Evolution for Self-Organizing Neuro-Fuzzy Systems', APPLIED SOFT COMPUTING, vol. 11, no. 8, pp. 4847-4858.
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Talaei-Khoei, A, Solvoll, T, Ray, P & Parameshwaran, N 2011, 'Policy-based Awareness Management (PAM): Case study of a wireless communication system at a hospital', Journal of Systems and Software, vol. 84, no. 10, pp. 1791-1805.
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The present paper evaluates the use of software agents to identify relevance of information, called awareness. This evaluation is based on existing policies and scenarios in the context of wireless communication of a hospital in Norway. The study is to address the lack of literature for experimental studies on a method to employ software agents for awareness identification. Research in computer supported cooperative work indicates the significant contributions of software agents to assist individuals. There are bodies of work that show awareness provides the means for software agents in which effective cooperation can take place. In addition, the role of the methods to identify awareness is emphasized in the literature of both computer supported cooperative work and software agents. This paper explains a step-wise process, called Policy-based Awareness Management, which allows agents to use policies as a source to identify awareness and thus change their behaviors accordingly. The contribution of this method is based on the concepts proposed by the logic of general awareness. The present study applies Directory Enabled Networks-next generation as the policy structure for the method. The paper evaluates the process via its application to identify the relevance of information in wireless communication scenarios in a hospital. The present study conducts observations, interviews and discussions on the wireless communication system of the hospital to identify the different scenarios happening in the system. The paper presents a set of simulations on these scenarios and concludes that the method is effective and cost-efficient.

Tarini, M, Puppo, E, Panozzo, D, Pietroni, N & Cignoni, P 2011, 'Simple quad domains for field aligned mesh parametrization', ACM Transactions on Graphics, vol. 30, no. 6, pp. 1-1.
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Toellner, T, Zehetleitner, M, Gramann, K & Mueller, HJ 2011, 'Stimulus Saliency Modulates Pre-Attentive Processing Speed in Human Visual Cortex', PLOS ONE, vol. 6, no. 1.
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Tomamichel, M & Renner, R 2011, 'Uncertainty Relation for Smooth Entropies', PHYSICAL REVIEW LETTERS, vol. 106, no. 11.
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Tomamichel, M, Schaffner, C, Smith, A & Renner, R 2011, 'Leftover Hashing Against Quantum Side Information', IEEE TRANSACTIONS ON INFORMATION THEORY, vol. 57, no. 8, pp. 5524-5535.
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Turini, G, Pietroni, N, Megali, G, Ganovelli, F, Pietrabissa, A & Mosca, F 2011, 'New techniques for computer-based simulation in surgical training', International Journal of Biomedical Engineering and Technology, vol. 5, pp. 303-316.

van den Hoven, E & Mazalek, A 2011, 'Grasping gestures: Gesturing with physical artefacts', Artificial Intelligence For Engineering Design, Analysis And Manufacturing, vol. 25, no. 3, pp. 255-271.
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Gestures play an important role in communication. They support the listener, who is trying to understand the speaker. However, they also support the speaker by facilitating the conceptualization and verbalization of messages and reducing cognitive load. Gestures thus play an important role in collaboration and also in problem-solving tasks. In human-computer interaction, gestures are also used to facilitate communication with digital applications, because their expressive nature can enable less constraining and more intuitive digital interactions than conventional user interfaces. Although gesture research in the social sciences typically considers empty-handed gestures, digital gesture interactions often make use of handheld objects or touch surfaces to capture gestures that would be difficult to track in free space. In most cases, the physical objects used to make these gestures serve primarily as a means of sensing or input. In contrast, tangible interaction makes use of physical objects as embodiments of digital information. The physical objects in a tangible interface thus serve as representations as well as controls for the digital information they are associated with. Building on this concept, gesture interaction has the potential to make use of the physical properties of hand-held objects to enhance or change the functionality of the gestures made. In this paper, we look at the design opportunities that arise at the intersection of gesture and tangible interaction. We believe that gesturing while holding physical artifacts opens up a new interaction design space for collaborative digital applications that is largely unexplored. We provide a survey of gesture interaction work as it relates to tangible and touch interaction. Based on this survey, we define the design space of tangible gesture interaction as the use of physical devices for facilitating, supporting, enhancing, or tracking gestures people make for digital interaction purposes, and outline the ...

Wang, J, Chi, D, Wu, J & Lu, H 2011, 'Chaotic Time Series Method Combined With Particle Swarm Optimization And Trend Adjustment For Electricity Demand Forecasting', Expert Systems With Applications, vol. 38, no. 7, pp. 8419-8429.
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Electricity demand forecasting plays an important role in electric power systems planning. In this paper, nonlinear time series modeling technique is applied to analyze electricity demand. Firstly, the phase space, which describes the evolution of the be

Wang, X, Wang, Z, Xu, X & Liu, Y 2011, 'A service composition method for tradeoff between satisfactions of multiple requirements', Jisuanji Yanjiu yu Fazhan/Computer Research and Development, vol. 48, no. 4, pp. 627-637.
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Service composition is effective in constructing value-added service rapidly for service-oriented applications. Existing selection models for composite services rely severely on assumptions that customers' each requirement is raised alone, while in reality, service requirements can be numerous in practical applications. And when a small time slide is focused on, multiple requirements can be seen as concurrent and service sets involved by sub-solutions corresponding to each individual requirement have intersections, resulting in competitions or sharing of certain services between requirements. Therefore, current single requirement-oriented methods can not deal with the situation that multiple service requirements arrive concurrently competing for services. This paper presents a multiple service requirements-oriented service composition model and algorithm. In the light that service can either be exclusive or sharable and decisive priority relations exist between all assessment factors, an assessment method based on confliction-avoidance scheduling and graded weighting priorities is put forward. On that basis, tradeoff strategies are proposed for genetic algorithm and a service composition method is put forward for tradeoff between satisfactions of multiple service requirements. Experiment results show that this method ensures proportionality of all sub-solutions and sub-optimal solutions can be gained efficiently by improving its coding manner. Compared with other possible strategies, it has proved superior applicability to different circumstances of quantity and quality of available services.

Wang, Y, Wen, S, Cesare, S, Zhou, W & Xiang, Y 2011, 'Eliminating errors in worm propagation models', IEEE Communications Letters, vol. 15, no. 9, pp. 1022-1024.
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Research on worm propagation has been conducted for over a decade. However, traditional models overestimate the scale of the infected network that leads to propagation errors because of limited and inaccurate analysis of the propagation procedure between each pair of nodes in the network. This paper studies the propagation mechanism of the two main classes of worms: scanning worms (Code Red II) and nonreinfection email worms. We aim at eliminating overestimation in worm propagation modeling caused by errors. Through the analysis of the propagation procedure, we observe that the error is mainly caused by propagation cycles in the propagation path, which are usually ignored by traditional models. Our simulations and analysis show the fact that the existence of errors has non-negligible effect on worm propagation modeling. We quantify the error and propose a method to eliminate it. © 2011 IEEE.

Wang, Y, Wen, S, Cesare, S, Zhou, W & Xiang, Y 2011, 'The microcosmic model of worm propagation', Computer Journal, vol. 54, no. 10, pp. 1700-1720.
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Each year, large amounts of money and labor are spent on patching the vulnerabilities in operating systems and various popular software to prevent exploitation by worms. Modeling the propagation process can help us to devise effective strategies against those worms' spreading. This paper presents a microcosmic analysis of worm propagation procedures. Our proposed model is different from traditional methods and examines deep inside the propagation procedure among nodes in the network by concentrating on the propagation probability and time delay described by a complex matrix. Moreover, since the analysis gives a microcosmic insight into a worm's propagation, the proposed model can avoid errors that are usually concealed in the traditional macroscopic analytical models. The objectives of this paper are to address three practical aspects of preventing worm propagation: (i) where do we patch? (ii) how many nodes do we need to patch? (iii) when do we patch? We implement a series of experiments to evaluate the effects of each major component in our microcosmic model. Based on the results drawn from the experiments, for high-risk vulnerabilities, it is critical that networks reduce the number of vulnerable nodes to below 80%. We believe our microcosmic model can benefit the security industry by allowing them to save significant money in the deployment of their security patching schemes.

Winkler, S, Tomamichel, M, Hengl, S & Renner, R 2011, 'Impossibility of Growing Quantum Bit Commitments', PHYSICAL REVIEW LETTERS, vol. 107, no. 9.
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Wu, D, Lu, J & Zhang, G 2011, 'Similarity measure models and algorithms for hierarchical cases', Expert Systems with Applications, vol. 38, no. 12, pp. 15049-15056.
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Many business situations such as events, products and services, are often described in a hierarchical structure. When we use case-based reasoning (CBR) techniques to support business decision-making, we require a hierarchical-CBR technique which can effectively compare and measure similarity between two hierarchical cases. This study first defines hierarchical case trees (HC-trees) and discusses related features. It then develops a similarity evaluation model which takes into account all the information on nodes structures, concepts, weights, and values in order to comprehensively compare two hierarchical case trees. A similarity measure algorithm is proposed which includes a node concept correspondence degree computation algorithm and a maximum correspondence tree mapping construction algorithm, for HC-trees. We provide two illustrative examples to demonstrate the effectiveness of the proposed hierarchical case similarity evaluation model and algorithms, and possible applications in CBR systems

Xiang, Y & Zhou, W 2011, 'Special issue: Building secure parallel and distributed networks and systems', Computer Communications, vol. 34, no. 4, p. 525.
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Xiang, Y & Zhou, W 2011, 'Special Section: Trusted computing', Future Generation Computer Systems, vol. 27, no. 5, pp. 527-528.
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Xiang, Y, Hu, J & Zhou, W 2011, 'Editorial: Advances in network and system security', Computers and Security, vol. 30, no. 5, pp. 295-296.
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Xiang, Y, Li, K & Zhou, W 2011, 'Low-rate DDoS attacks detection and traceback by using new information metrics', IEEE Transactions on Information Forensics and Security, vol. 6, no. 2, pp. 426-437.
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A low-rate distributed denial of service (DDoS) attack has significant ability of concealing its traffic because it is very much like normal traffic. It has the capacity to elude the current anomaly-based detection schemes. An information metric can quantify the differences of network traffic with various probability distributions. In this paper, we innovatively propose using two new information metrics such as the generalized entropy metric and the information distance metric to detect low-rate DDoS attacks by measuring the difference between legitimate traffic and attack traffic. The proposed generalized entropy metric can detect attacks several hops earlier (three hops earlier while the order α = 10) than the traditional Shannon metric. The proposed information distance metric outperforms (six hops earlier while the order α = 10) the popular KullbackLeibler divergence approach as it can clearly enlarge the adjudication distance and then obtain the optimal detection sensitivity. The experimental results show that the proposed information metrics can effectively detect low-rate DDoS attacks and clearly reduce the false positive rate. Furthermore, the proposed IP traceback algorithm can find all attacks as well as attackers from their own local area networks (LANs) and discard attack traffic. © 2011 IEEE.

Xiang, Y, Lopez, J, Wang, H & Zhou, W 2011, 'Special issue: Securing distributed networks and systems', Concurrency Computation Practice and Experience, vol. 23, no. 12, pp. 1311-1312.
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Xiang, Y, Peng, D, Natgunanathan, I & Zhou, W 2011, 'Effective pseudonoise sequence and decoding function for imperceptibility and robustness enhancement in time-spread echo-based audio watermarking', IEEE Transactions on Multimedia, vol. 13, no. 1, pp. 2-13.
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This paper proposes an effective pseudonoise (PN) sequence and the corresponding decoding function for time-spread echo-based audio watermarking. Different from the traditional PN sequence used in time-spread echo hiding, the proposed PN sequence has two features. Firstly, the echo kernel resulting from the new PN sequence has frequency characteristics with smaller magnitudes in perceptually significant region. This leads to higher perceptual quality. Secondly, the correlation function of the new PN sequence has three times more large peaks than that of the existing PN sequence. Based on this feature, we propose a new decoding function to improve the robustness of time-spread echo-based audio watermarking. The effectiveness of the proposed PN sequence and decoding function is illustrated by theoretical analysis, simulation examples, and listening test. © 2010 IEEE.

Xu, G, Li, L, Zhang, Y, Yi, X & Kitsuregawa, M 2011, 'Modeling user hidden navigational behavior for Web recommendation', Web Intelligence and Agent Systems-An international journal, vol. 9, no. 3, pp. 239-255.
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Web users exhibit a variety of navigational interests through clicking a sequence of Web pages. Analyses of Web usage data will lead to discovering Web user access patterns, and in turn, facilitating users to locate more preferable Web contents via collaborative recommendation techniques. In the context of Web usage mining, Latent Semantic Analysis (LSA) based on probability inference provides a promising approach to capture not only user hidden navigational patterns, but also the associations between users, pages and hidden navigational patterns. The discovered user access patterns could be used as a usage reference base for identifying the new users access preferences and making usage-based collaborative Web recommendations. In this paper, we propose a novel usage-based Web recommendation framework, in which Latent Dirichlet Allocation (LDA) is employed to learn the underlying task space from the training Web log data and infer the task distribution for a target user via task inference. The main advantages of the adapted LDA model are its capabilities of efficiently learning the semantic usage information from the Web log data and effectively inferring the access preference of the target user even with a few Web clicks that might be unseen in the training data. In this paper, we also investigate the determination of an optimizing task number, which is another important problem commonly encountered in latent semantic analysis. Experiments conducted on a real Web log dataset show that this approach can achieve better recommendation performance in comparison to other existing techniques. And the discovered task-simplex expression can also provide a better interpretation for Web designers or users to better understand the user navigational preference.

Yang, X, Zhang, G, Lu, J & Ma, J 2011, 'A kernel fuzzy c-means clustering based fuzzy support vector machine algorithm for classification problems with outliers or noises', IEEE Transactions on Fuzzy Systems, vol. 19, no. 1, pp. 105-115.
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The support vector machine (SVM) has provided higher performance than traditional learning machines and has been widely applied in real-world classification problems and nonlinear function estimation problems. Unfortunately, the training process of the SVM is sensitive to the outliers or noises in the training set. In this paper, a common misunderstanding of Gaussianfunction- based kernel fuzzy clustering is corrected, and a kernel fuzzy c-means clustering-based fuzzy SVM algorithm (KFCMFSVM) is developed to deal with the classification problems with outliers or noises. In the KFCM-FSVM algorithm, we first use the FCM clustering to cluster each of two classes from the training set in the high-dimensional feature space. The farthest pair of clusters, where one cluster comes from the positive class and the other from the negative class, is then searched and forms one new training set with membership degrees. Finally, we adopt FSVM to induce the final classification results on this new training set. The computational complexity of the KFCM-FSVM algorithm is analyzed. A set of experiments is conducted on six benchmarking datasets and four artificial datasets for testing the generalization performance of the KFCM-FSVM algorithm. The results indicate that the KFCM-FSVM algorithm is robust for classification problems with outliers or noises.

Zhang, G, Zhang, G, Gao, Y & Lu, J 2011, 'Competitive Strategic Bidding Optimization In Electricity Markets Using Bilevel Programming And Swarm Technique', Ieee Transactions On Industrial Electronics, vol. 58, no. 6, pp. 2138-2146.
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AbstractCompetitive strategic bidding optimization is now a key issue in electricity generator markets. Digital ecosystems provide a powerful technological foundation and support for the implementation of the optimization. This paper presents a new strategic bidding optimization technique which applies bilevel programming and swarm intelligence. In this paper, we first propose a general multileader-one-follower nonlinear bilevel (MLNB) optimization concept and related definitions based on the generalized Nash equilibrium. By analyzing the strategic bidding behavior of generating companies, we create a specific MLNB decision model for day-ahead electricity markets.

Zhang, G, Zheng, Z, Lu, J & He, Q 2011, 'An Algorithm For Solving Rule Sets-Based Bilevel Decision Problems', Computational Intelligence, vol. 27, no. 2, pp. 235-259.
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Bilevel decision addresses the problem in which two levels of decision makers each tries to optimize their individual objectives under certain constraints, and to act and react in an uncooperative and sequential manner. Given the difficulty of formulatin

Zhang, J, Lu, J & Zhang, G 2011, 'A Hybrid Knowledge-Based Risk Prediction Method Using Fuzzy Logic And Cbr For Avian Influenza Early Warning', Journal of Multiple-Valued Logic and Soft Computing, vol. 17, no. 4 Special Issue, pp. 363-386.
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The threat of highly pathogenic avian influenza persists, with the size of the epidemic growing worldwide. Various methods have been applied to measure and predict the threat. This paper outlines our research which develops a knowledge-based method that makes full use of previous knowledge to perform a comprehensive forecast of the risk of avian influenza and generate reliable warning signals for a specific region at a specific time. The method contains a risk estimation model and a knowledge-based prediction method using fuzzy logic and case-based reasoning (CBR) to generate timely early warnings to support decision makers to identify underlying vulnerabilities and implement relevant strategies. An example is presented that illustrates the capabilities and procedures of the proposed method in avian influenza early warning systems.

Zhang, J, Lu, J & Zhang, G 2011, 'A Seasonal Auto-regressive Model Based Support Vector Regression Prediction Method For H5n1 Avian Influenza Animal Events', International Journal of Computational Intelligence and Applications, vol. 10, no. 2, pp. 199-230.
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The time series prediction of avian influenza epidemics is a complex issue, because avian influenza has latent seasonality which is difficult to identify. Although researchers have applied a neural network (NN) model and the Box-Jenkins model for the seasonal epidemic series research area, the results are limited. In this study, we develop a new prediction seasonal auto-regressive-based support vector regression (SAR-SVR) model which combines the seasonal auto-regressive (SAR) model with a support vector regression (SVR) model to address this prediction problem to overcome existing limitations. Fast Fourier transformation is also merged into this method to identify the latent seasonality inside the time series. The experiments demonstrate that the developed SARSVR method out-performs SVR, Box-Jenkins models and two layer feed forward NN model-both in accuracy and stability in the avian influenza epidemic disease time series prediction.

Zhang, J, Lu, J & Zhang, G 2011, 'Joint Sub-classifiers One Class Classification Model For Avian Influenza Outbreak Detection', International Journal of Computational Intelligence and Applications, vol. 10, no. 4, pp. 425-443.
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H5N1 avian influenza outbreak detection is a significant issue for early warning of epidemics. This paper proposes domain knowledge-based joint one class classification model for avian influenza outbreak. Instead of focusing on manipulations of the one class classification model, we delve into the one class avian influenza dataset, divide it into subclasses by domain knowledge, train the sub-class classifiers and unify the result of each classifier. The proposed joint method solves the one class classification and features selection problems together. The experiment results demonstrate that the proposed joint model definitely outperforms the normal one class classification model on the animal avian influenza dataset.

Zhang, J, Xiang, Y, Zhou, W, Ye, L & Mu, Y 2011, 'Secure image retrieval based on visual content and watermarking protocol', Computer Journal, vol. 54, no. 10, pp. 1661-1674.
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As an interesting application on cloud computing, content-based image retrieval (CBIR) has attracted a lot of attention, but the focus of previous research work was mainly on improving the retrieval performance rather than addressing security issues such as copyrights and user privacy. With an increase of security attacks in the computer networks, these security issues become critical for CBIR systems. In this paper, we propose a novel two-party watermarking protocol that can resolve the issues regarding user rights and privacy. Unlike the previously published protocols, our protocol does not require the existence of a trusted party. It exhibits three useful features: security against partial watermark removal, security in watermark verification and non-repudiation. In addition, we report an empirical research of CBIR with the security mechanism. The experimental results show that the proposed protocol is practicable and the retrieval performance will not be affected by watermarking query images.

Zhang, R, Lu, J & Zhang, G 2011, 'A knowledge-based multi-role decision support system for ore blending cost optimization of blast furnaces', European Journal Of Operational Research, vol. 215, no. 1, pp. 194-203.
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Literature illustrates the difficulties in obtaining the lowest-cost optimal solution to an ore blending problem for blast furnaces by using the traditional trial-and-error method in iron and steel enterprises. To solve this problem, we developed a cost optimization model which we have implemented in a multi-role-based decision support system (DSS). On the basis of analyzing the business flow and working process of ore blending, we propose an architecture of DSS which is built based on multi-roles. This DSS construction pre-processes the data for materials and elements, builds a general database, abstracts the related optimal operations research models and introduces the reasoning mechanism of an expert system. A non-linear model of ore blending for blast furnaces and its solutions are provided. A database, a model base and a knowledge base are integrated into the expert system-based multi-role DSS to meet the different demands of data, information and decision-making knowledge for the various roles of users. A comparison of the results for the DSS and the trial-and-error method is provided. The system has produced excellent economic benefits since it was implemented at the Xiangtan Iron & Steel Group Co. Ltd., China.

Zhang, R, Lu, J & Zhang, G 2011, 'An information presentation method based on tree-like super entity component', Journal of Systems and Software, vol. 84, no. 8, pp. 1306-1318.
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Information systems are increasingly oriented in the direction of large-scale integration due to the explosion of multi-source information. It is therefore important to discuss how to reasonably organize and present information from multiple structures and sources on the same information system platform. In this study, we propose a 3C (Components, Connections, Container) component model by combining white-box and black-box methods, design a tree-like super entity based on the model, present its construction and related algorithm, and take a tree-like super entity as the information organization method for multi-level entities. In order to represent structural, semi-structural and non-structural data on the same information system platform, an information presentation method based on an editable e-book component has been developed by combining the tree-like super entity component, QQ-style menu and 1/K switch connection component, which has been successfully applied in the Flood Protection Project Information System of the Yangtze River in China.

Zhang, Y, Zhang, W, Lin, X, Jiang, B & Pei, J 2011, 'Ranking uncertain sky: The probabilistic top-k skyline operator', Information Systems, vol. 36, no. 5, pp. 898-915.
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Many recent applications involve processing and analyzing uncertain data. In this paper, we combine the feature of top-k objects with that of skyline to model the problem of top-k skyline objects against uncertain data. The problem of efficiently computing top-k skyline objects on large uncertain datasets is challenging in both discrete and continuous cases. In this paper, firstly an efficient exact algorithm for computing the top-k skyline objects is developed for discrete cases. To address applications where each object may have a massive set of instances or a continuous probability density function, we also develop an efficient randomized algorithm with an @e@?approximation guarantee. Moreover, our algorithms can be immediately extended to efficiently compute p-skyline; that is, retrieving the uncertain objects with skyline probabilities above a given threshold. Our extensive experiments on synthetic and real data demonstrate the efficiency of both algorithms and the randomized algorithm is highly accurate. They also show that our techniques significantly outperform the existing techniques for computing p-skyline.

Zheng, L, Jin, J, Guo, Y, Xu, W, Lu, H & Zhu, J 2011, 'Characteristics and Optimization of a PMLSM for HTS Magnetic Suspension Propulsion System', Journal of Applied Superconductivity and Electromagnetics, vol. 1, no. 1, pp. 66-74.
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¾Permanent magnet (PM) linear synchronous motors (PMLSMs) can be integrated with a high temperature superconducting (HTS) magnetic suspension system to be used in such as electromagnetic aircraft launcher and maglev transportation which have a levitated object moving on a long linear track. This paper presents the design and electromagnetic characteristic analysis of a long-primary single-sided PMLSM for a HTS bulk-PM guideway repulsion magnetic suspension propulsion system. Based on the characteristics and performance analysis of the PMLSM, a new type of HTS suspension propulsion system driven by a double-sided PMLSM with an optimal PM structure is then proposed. The running characteristics of the linear propulsion systems are studied through finite element analysis (FEA) with comprehensive performance results obtained for practical development.

Zong, Y, Xu, G, Jin, P, Zhang, Y & Chen, E 2011, 'HC_AB: A new heuristic clustering algorithm based on Approximate Backbone', Information Processing Letters, vol. 111, no. 17, pp. 857-863.
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Clustering is an important research area with numerous applications in pattern recognition, machine learning, and data mining. Since the clustering problem on numeric data sets can be formulated as a typical combinatorial optimization problem, many researches have addressed the design of heuristic algorithms for finding sub-optimal solutions in a reasonable period of time. However, most of the heuristic clustering algorithms suffer from the problem of being sensitive to the initialization and do not guarantee the high quality results. Recently, Approximate Backbone (AB), i.e., the commonly shared intersection of several sub-optimal solutions, has been proposed to address the sensitivity problem of initialization. In this paper, we aim to introduce the AB into heuristic clustering to overcome the initialization sensitivity of conventional heuristic clustering algorithms. The main advantage of the proposed method is the capability of restricting the initial search space around the optimal result by defining the AB, and in turn, reducing the impact of initialization on clustering, eventually improving the performance of heuristic clustering. Experiments on synthetic and real world data sets are performed to validate the effectiveness of the proposed approach in comparison to three conventional heuristic clustering algorithms and three other algorithms with improvement on initialization

Zong, Y, Xu, GD, Zhang, YC & Li, MC 2011, 'Node priority guided clustering algorithm', Kongzhi yu Juece/Control and Decision, vol. 26, no. 6.
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Density-based clustering algorithms have the advantages of clustering with arbitrary shapes and handling noise data, but cannot deal with unsymmetrical density distribution and high dimensionality dataset. Therefore, a node priority guided clustering algorithm(NPGC) is proposed. A direct K neighbor graph of dataset is set up based on KNN neighbor method. Then the local information of each node in graph is captured by using KNN kernel density estimate method, and the node priority is calculated by passing the local information through graph. Finally, a depth-first search on graph is applied to find out the clustering results based on the local kernel degree. Experiment results show that NPGC has the ability to deal with unsymmetrical density distribution and high dimensionality dataset.

Al-hassan, MW, Lu, H & Lu, J 2010, 'Personalized e-Government Services: Tourism Recommender System Framework', Web Information Systems and Technologies - Lecture Notes in Computer Science Vol 75 Part III, International Conference on Web Information Systems and Technologies, Springer, Valencia, Spain, pp. 173-178.
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Most governments around the globe use the internet and information technologies to deliver information and services for citizens and businesses. One of the main directions in the current e-government (e-Gov) development strategy is to provide better online services to citizens such that the required information can be located by citizens with less time and effort. Tourism is one of the main focused areas of e-Gov development strategy because it is one of the major profitable industries. Significant efforts have been devoted by governments to improve tourism services. However, the current e-Gov tourism services are limited to simple online presentation; intelligent e-Gov tourism services are highly desirable. Personalization techniques, particularly recommendation systems, are the most promising techniques to deliver personalized e-Gov (Pe-Gov) tourism services. This study proposes ontology-based personalized e-Gov tourism recommender system framework, which would enable tourism information seekers to locate the most interesting destinations and find the most preferable attractions and activities with less time and effort. The main components of the proposed framework and some outstanding features are presented along with a detailed description of a scenario.

Al-Sharawneh, JA, Williams, M, Wang, X & Goldbaum, D 2011, 'Mitigating Risk in Web-Based Social Network Service Selection: Follow the Leader', The Sixth International Conference on Internet and Web Applications and Services (ICIW 2011), International Conference on Internet and Web Applications and Services, The International Academy, Research and Industry Association (IARIA), St. Maarten, The Netherlands Antilles, pp. 156-164.
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In the Service Web, a huge number of Web services compete to offer similar functionalities from distributed locations. Since no Web service is risk free, this paper aims to mitigate the risk in service selection using 'Follow the Leader' principle as a new approach for risk-reducing strategy. First, we define the user credibility model based on the 'Follow the Leader' principle in web-based social networks. Next we show how to evaluate the Web service credibility based on its trustworthiness and expertise. Finally, we present a dynamic selection model to select the best service with the perceived performance risk and customer risk-attitude considerations. To demonstrate the feasibility and effectiveness of the new 'Follow the Leader' driven approach to alleviate the risk in service selection, we used a Social Network Analysis Studio (SNAS) to verify the validity of the proposed model. The empirical results incorporated in this paper, demonstrate that our approach is a significantly innovative approach as riskreducing strategy in service selection.

Anaissi, A, Kennedy, PJ & Goyal, M 2011, 'Dimension reduction of microarray data based on local principal component', World Academy of Science, Engineering and Technology, pp. 1176-1181.
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Analysis and visualization of microarraydata is veryassistantfor biologists and clinicians in the field of diagnosis and treatment of patients. It allows Clinicians to better understand the structure of microarray and facilitates understanding gene expression in cells. However, microarray dataset is a complex data set and has thousands of features and a very small number of observations. This very high dimensional data set often contains some noise, non-useful information and a small number of relevant features for disease or genotype. This paper proposes a non-linear dimensionality reduction algorithm Local Principal Component (LPC) which aims to maps high dimensional data to a lower dimensional space. The reduced data represents the most important variables underlying the original data. Experimental results and comparisons are presented to show the quality of the proposed algorithm. Moreover, experiments also show how this algorithm reduces high dimensional data whilst preserving the neighbourhoods of the points in the low dimensional space as in the high dimensional space.

Anaissi, A, Kennedy, PJ & Goyal, ML 2011, 'Feature Selection of Imbalanced Gene Expression Microarray Data', Proceedings 12th ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, IEEE Computer Society, Sydney, pp. 73-78.
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Gene expression data is a very complex data set characterised by abundant numbers of features but with a low number of observations. However, only a small number of these features are relevant to an outcome of interest. With this kind of data set, feature selection becomes a real prerequisite. This paper proposes a methodology for feature selection for an imbalanced leukaemia gene expression data based on random forest algorithm. It presents the importance of feature selection in terms of reducing the number of features, enhancing the quality of machine learning and providing better understanding for biologists in diagnosis and prediction. Algorithms are presented to show the methodology and strategy for feature selection taking care to avoid overfitting. Moreover, experiments are done using imbalanced Leukaemia gene expression data and special measurement is used to evaluate the quality of feature selection and performance of classification.

Antle, AN, Marshall, P & van den Hoven, E 2011, 'Workshop on Embodied Interaction: Theory and Practice in HCI', Proceedings of CHI Extended Abstracts 2011, ACM, Vancouver, Canada, pp. 5-8.
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For over ten years researchers in human-computer interaction (HCI) have explored an embodied perspective that seeks to describe and explain the fundamental role played by the physical body in how we experience, interact with and understand computation in the world we live in. Recently, such a perspective has been used to discuss human actions and interactions with a range of computational applications including tangibles, mobiles, wearables, tabletops and interactive environments. This workshop aims to enable participants to critically explore the different approaches to incorporating an embodied perspective in HCI research, and to develop a shared set of understandings and identification of differences, similarities and synergies between our research approaches.

Arefin, AS, Inostroza-Ponta, M, Mathieson, L, Berretta, R & Moscato, P 2011, 'Clustering nodes in large-scale biological networks using external memory algorithms', Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), International Conference on Algorithms and Architectures for Parallel Processing, Springer, Melbourne, Australia, pp. 375-386.
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Novel analytical techniques have dramatically enhanced our understanding of many application domains including biological networks inferred from gene expression studies. However, there are clear computational challenges associated to the large datasets generated from these studies. The algorithmic solution of some NP-hard combinatorial optimization problems that naturally arise on the analysis of large networks is difficult without specialized computer facilities (i.e. supercomputers). In this work, we address the data clustering problem of large-scale biological networks with a polynomial-time algorithm that uses reasonable computing resources and is limited by the available memory. We have adapted and improved the MSTkNN graph partitioning algorithm and redesigned it to take advantage of external memory (EM) algorithms. We evaluate the scalability and performance of our proposed algorithm on a well-known breast cancer microarray study and its associated dataset. © 2011 Springer-Verlag.

Babai, L, Codenotti, P, Grochow, JA & Qiao, Y 2011, 'Code equivalence and group isomorphism', Proceedings of the twenty-second annual ACM-SIAM symposium on Discrete Algorithm, ACM/SIAM Symposium on Discrete Algorithms, ACM, San Francisco, USA, pp. 1395-1408.
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The isomorphism problem for groups given by their multiplication tables has long been known to be solvable in time nlog n+O(1). The decades-old quest for a polynomial-time algorithm has focused on the very difficult case of class-2 nilpotent groups (groups whose quotient by their center is abelian), with little success. In this paper we consider the opposite end of the spectrum and initiate a more hopeful program to find a polynomial-time algorithm for semisimple groups, defined as groups without abelian normal subgroups. First we prove that the isomorphism problem for this class can be solved in time nO(log log n). We then identify certain bottlenecks to polynomial-time solvability and give a polynomial-time solution to a rich subclass, namely the semisimple groups where each minimal normal subgroup has a bounded number of simple factors. We relate the results to the filtration of groups introduced by Babai and Beals (1999). One of our tools is an algorithm for equivalence of (not necessarily linear) codes in simply-exponential time in the length of the code, obtained by modifying Luks's algorithm for hypergraph isomorphism in simply-exponential time in the number of vertices (FOCS 1999). We comment on the complexity of the closely related problem of permutational isomorphism of permutation groups.

Babar, A, Wong, B & Gill, AQ 2011, 'An evaluation of the goal-oriented approaches for modelling strategic alignment concept', Proceedings of the Fifth International Conference on Research Challenges in Information Science (RCIS), International Conference on Research Challenges in Information Science, IEEE, Gosier, pp. 1-8.
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Bakker, S, van den Hoven, E & Antle, A 2011, 'MoSo Tangibles: Evaluating Embodied Learning', Proceedings of the Fifth International Conference on Tangible, Embedded and Embodied Interaction, Tangible, Embedded, and Embodied Interaction, ACM, Madeira, Portugal, pp. 85-92.
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Using tangible interaction in interactive educational systems can benefit learning. This can be supported by relying on experientially originating schemata in the interaction design of learning systems. This paper presents the design and evaluation of MoSo Tangibles, a set of interactive, physical artifacts with which children manipulate the pitch, volume and tempo of ongoing tones, in order to structure their understanding of these abstract sound concepts in terms of multiple different concrete body-based concepts. The results indicate that MoSo provided children with a physical handle to reason about the targeted abstract concepts.

Barkowsky, T, Bertel, S, Broz, F, Chaudhri, VK, Eagle, N, Genesereth, M, Halpin, H, Hamner, E, Hoffmann, G, Hölscher, C, Horvitz, E, Lauwers, T, McGuinness, DL, Michalowski, M, Mower, E, Shipley, TF, Stubbs, K, Vogl, R & Williams, MA 2011, 'Reports of the AAAI 2010 spring symposia', AI Magazine, pp. 115-122.
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The Association for the Advancement of Artificial Intelligence, in cooperation with Stanford University's Department of Computer Science, presented the 2010 Spring Symposium Series Monday through Wednesday, March 22-24, 2010, at Stanford University. The titles of the seven symposia were Artificial Intelligence for Development; Cognitive Shape Processing; Educational Robotics and Beyond: Design and Evaluation; Embedded Reasoning: Intelligence in Embedded Systems; Intelligent Information Privacy Management; It's All in the Timing: Representing and Reasoning about Time in Interactive Behavior; and Linked Data Meets Artificial Intelligence. Copyright © 2010.

Behbood, V & Lu, J 2011, 'Efficiency Prediction in Decision Making Units Merger using Data Envelopment Analysis and Neural Network', 19th Triennial Conference of the International Federation of Operational Research Societies, IFORS, Australia.

Behbood, V & Lu, J 2011, 'Financial Early Warning System: Adaptive Inference-based Fuzzy Neural Network', 19th Triennial Conference of the International Federation of Operational Research Societies, IFORS, Australia.

Behbood, V & Lu, J 2011, 'Fuzzy Refinement-based Transductive Transfer Learning for Bank Failure Prediction', World Conference on Soft Computing, IEEE, USA.

Behbood, V & Lu, J 2011, 'Intelligent Financial Warning Model Using Fuzzy Neural Network and Case-Based Reasoning', Proceedings for the IEEE Symposium on Computational Intelligence for Financial Engineering & Economics, IEEE Symposium on Computational Intelligence for Financial Engineering, IEEE, Paris, France, pp. 9-15.
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Creating an applicable and precise financial early warning model is highly desirable for decision makers and regulators in the financial industry. Although Business Failure Prediction (BFP) especially banks has been extensively a researched area since late 1960s, the next critical step which is the decision making support scheme has been ignored. This paper presents a novel model for financial warning which combines a fuzzy inference system with the learning ability of neural network as a Fuzzy Neural Network (FNN) to predict organizational financial status and also applies reasoning capability of Fuzzy Case-Based Reasoning (FCBR) to support decision makers measuring appropriate solutions. The proposed financial warning model generates an adaptive fuzzy rule base to predict financial status of target case and then if it is predicted to fail, the FCBR is used to find similar survived cases. Finally according similar cases and a fuzzy rule base, the model provides financial decisions to change particular features as company goals in upcoming year to avoid future financial distress.

Behbood, V, Lu, J & Zhang, G 2011, 'Long Term Bank Failure Prediction using Fuzzy Refinement-based Transductive Transfer Learning', 2011 IEEE International Conference on Fuzzy Systems (FUZZ), IEEE International Conference on Fuzzy Systems, IEEE, Taipei, Taiwan, pp. 2676-2683.
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Machine learning algorithms, which have been considered as robust methods in different computational fields, assume that the training and test data are drawn from the same distribution. This assumption may be violated in many real world applications like bank failure prediction because training and test data may come from different time periods or domains. An efficient novel algorithm known as Fuzzy Refinement (FR) is proposed in this paper to solve this problem and improve the performance. The algorithm utilizes the fuzzy system and similarity concept to modify the instances' labels in target domain which was initially predicted by shift-unaware Fuzzy Neural Network (FNN) proposed by [1]. The experiments are performed using bank failure financial data of United States to evaluate the algorithm performance. The results address a significant improvement in the predictive accuracy of FNN due to applying the proposed algorithm.

Bian, W & Tao, D 2011, 'Learning a Distance Metric by Empirical Loss Minimization', Proceedings of the Twenty-Second International Joint Conference on Artificial Intelligence, International Joint Conference on Artificial Intelligence, AAAI Press/International Joint Conferences on Artificial Intelligence, Barcelona, Catalonia, Spain, pp. 1186-1191.
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In this paper, we study the problem of learning a metric and propose a loss function based metric learning framework, in which the metric is estimated by minimizing an empirical risk over a training set. With mild conditions on the instance distribution and the used loss function, we prove that the empirical risk converges to its expected counterpart at rate of root-n. In addition, with the assumption that the best metric that minimizes the expected risk is bounded, we prove that the learned metric is consistent. Two example algorithms are presented by using the proposed loss function based metric learning framework, each of which uses a log loss function and a smoothed hinge loss function, respectively. Experimental results suggest the effectiveness of the proposed algorithms.

Bremner, MJ 2011, 'Classical simulation of commuting quantum computations implies collapse of the polynomial hierarchy', 14th Workshop on Quantum Information Processing, Singapore.
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Quantum Information Processing (QIP) is a rapidly developing field of research spanning both physics and computer science. As the name implies, the field extends information processing (including computing and cryptography) to physical regimes where quantum effects become significant. QIP 2011 was the fourteenth workshop on theoretical aspects of quantum computing, quantum cryptography, and quantum information in a series that started in Aarhus in 1998 and was held 2010 at ETH Zurich, Switzerland. QIP 2011 featured a tutorial programme, invited talks, contributed talks, and a poster session. In addition, there was a rump session with short informal talks.

Bródka, P, Skibicki, K, Kazienko, P & Musiał, K 2011, 'A degree centrality in multi-layered social network', Proceedings of the 2011 International Conference on Computational Aspects of Social Networks, CASoN'11, pp. 237-242.
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Multi-layered social networks reflect complex relationships existing in modern interconnected IT systems. In such a network each pair of nodes may be linked by many edges that correspond to different communication or collaboration user activities. Multi-layered degree centrality for multi-layered social networks is presented in the paper. Experimental studies were carried out on data collected from the real Web 2.0 site. The multi-layered social network extracted from this data consists of ten distinct layers and the network analysis was performed for different degree centralities measures. © 2011 IEEE.

Brynskov, M, Leong, T & Fritch, J 2011, 'Bridging the Affective Gap to Make News Felt: Civic Engagement in the Climate Debate', 5th International Conference on Communities and Technologies, International Conference on Communities and Technologies, ACM Press, Brisbane, QLD, pp. 50-59.
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Brynskov, M, Leong, TW & Fritsch, J 2011, 'Bridging the affective gap to make news felt: Spaces of aestheticized public voice', 5th International Conference on Communities and Technologies, Conference Proceedings, International Conference on Communities & Technologies, ACM, Brisbane, Australia, pp. 50-59.
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We report our experiences of how public voice, news reporting, and sensor information can be blended and mediated digitally in ways different from the traditional formats of civic debate. We use Klimatrends (Climate Trends), an iPhone app and related infrastructure, as a probe to understand how citizens, journalists, and other stakeholders can engage in conversations and reflections on an important topic or event understood as a space for aestheticized public voice. By attempting to make news "felt" through bridging an "affective gap" between readers/consumers and news/information providers we offer a tentative design strategy for public engagement with civic debate. © 2011 ACM.

Chang, JY, Lin, YY, Han, MF & Lin, CT 2011, 'A functional-link based interval type-2 compensatory fuzzy neural network for nonlinear system modeling', 2011 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2011), IEEE International Conference on Fuzzy Systems, IEEE, Taipei, Taiwan, pp. 939-943.
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In this paper, the Functional-Link based Interval Type-2 Compensatory Fuzzy Neural Network (FLIT2CFNN) is a six-layer structure, which combines compensatory fuzzy reasoning method, and the consequent part is combined the proposed functional-link neural network with interval weights. The compensatory fuzzy reasoning method uses adaptive fuzzy operations of neuro-fuzzy systems that can make the fuzzy logic system more adaptive and effective. Initially, there is no rule in the FLIT2CFNN. A FLIT2CFNN is constructed using concurrent structure and parameter learning. The advantages of this learning algorithm are that it converges quickly and the obtained fuzzy rules are more precise. All of the antecedent part parameters and compensatory degree values are learned by gradient descent algorithm. Several simulation results show that the FLIT2CFNN achieves better performance than other feedforword type-1 and type-2 FNNs. © 2011 IEEE.

Cheema, MA, Lin, X, Zhang, W & Zhang, Y 2011, 'Influence zone: Efficiently processing reverse k nearest neighbors queries', 2011 IEEE 27th International Conference on Data Engineering, IEEE International Conference on Data Engineering, IEEE, Hannover, Germany, pp. 577-588.
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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 which 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 analyse the area of the influence zone and IO costs of our RkNN processing algorithms. Our experiments demonstrate the accuracy of our theoretical analysis.

Chen, CH, Lin, CJ & Lin, CT 2011, 'An immune symbiotic evolution learning for compensatory neural fuzzy networks and its applications', 2011 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2011), IEEE International Conference on Fuzzy Systems, Institute of Electrical and Electronics Engineers Inc., Taipei, Taiwan, pp. 2819-2826.
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This study presents an efficient immune symbiotic evolution learning algorithm for the compensatory neural fuzzy network (CNFN). The proposed immune symbiotic evolution learning method (ISEL) includes three major components initial population, subgroup symbiotic evolution and immune system algorithm. The advantage of the proposed ISEL method are that the subgroup symbiotic evolution method uses the subgroup-based population to evaluate the fuzzy rules locally and the adopted immune system algorithm can accelerate the search and increase global search capacity. Finally, the simulation results have shown that the proposed CNFN-ISEL can outperform other methods. © 2011 IEEE.

Chen, L & Zhang, C 2011, 'Semi-supervised Variable Weighting for Clustering', Proceedings of the Eleventh SIAM International Conference on Data Mining, SIAM International Conference on Data Mining, SIAM / Omnipress, Mesa, Arizona, USA, pp. 863-871.
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Semi-supervised learning, which uses a small amount of labeled data in conjunction with a large amount of unlabeled data for training, has recently attracted huge research attention due to the considerable improvement in learning accuracy. In this work, we focus on semi- supervised variable weighting for clustering, which is a critical step in clustering as it is known that interesting clustering structure usually occurs in a subspace defined by a subset of variables. Besides exploiting both labeled and unlabeled data to effectively identify the real importance of variables, our method embeds variable weighting in the process of semi-supervised clustering, rather than calculating variable weights separately, to ensure the computation efficiency. Our experiments carried out on both synthetic and real data demonstrate that semi-supervised variable weighting signicantly improves the clustering accuracy of existing semi-supervised k-means without variable weighting, or with unsupervised variable weighting.

Chen, S & Williams, M 2011, 'Grounding Data Purpose And Data Usage For Better Privacy Requirements Development: An Information System Perspective', The Pacific Asia Conference on Information Systems, Pacific Asia Conference on Information Systems, PACIS, Brisbane, Australia, pp. 1-13.
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Data purpose is a central concept to modeling privacy requirements for information systems. Existing purpose-centric 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. Given the lack of practical purpose-centric solutions, we argue that a grounded understanding of the underlying concepts of data purpose and usage is fundamental to modeling privacy requirements. In recognition of an existing "privacy rights" framework, this paper develops an ontological grounding of data purpose and usage that can be used to understand their implications on fundamental privacy rights for modeling privacy requirements for information systems.

Chou, YH, Chuang, CC, Zao, JK, Ko, LW & Lin, CT 2011, 'An fMRI study of abrupt-awake episodes during behavioral microsleeps', Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS, International Conference of the IEEE Engineering in Medicine and Biology Society, IEEE, Boston, MA, USA, pp. 5060-5063.
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This paper reports the brain activation patterns of five subjects who were abruptly awakened from microsleeps in a simulated automotive driving experiment. By comparing the BOLD signals between behavioral microsleep (BM), abrupt awakening (AA) and post-abrupt awakening (post-AA) stages, we observed that visual area, frontal cortex, limbic lobe manifested more intense activation during the AA stage while frontal cortex, temporal cortex, primary motor area and insula were more activated during the post-AA stage. These results suggested that the subjects were likely in mental states differ from those associated with decision making processes as they went through and emerged from the abrupt awakening episodes. © 2011 IEEE.

Chu, HS, Kuo, BC, Li, CH & Lin, CT 2011, 'A semisupervised feature extraction method based on fuzzy-type linear discriminant analysis', IEEE International Conference on Fuzzy Systems, IEEE International Conference on Fuzzy Systems, IEEE, Taipei, Taiwan, pp. 1927-1932.
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Linear discriminant analysis (LDA) is a commonly used feature extraction (FE) method to resolve the Hughes phenomenon for classification. The Hughes phenomenon (also called the curse of dimensionality) is often encountered in classification when the dimensionality of the space grows and the size of the training set is fixed, especially in the small sampling size problem. Recent studies show that the spatial information can greatly improve the classification performance. Hence, for hyperspectral image classification, it is not only necessary to use the available spectral information but also to exploit the spatial information. In this paper, a semisupervised feature extraction method which is based on the scatter matrices of the fuzzy-type LDA and uses the semi-information is proposed. The experimental results on two hyperspectral images, the Washington DC Mall and the Indian Pine Site, show that the proposed method can yield a better classification performance than LDA in the small sampling size problem. © 2011 IEEE.

Corney, M, Lister, RF & Teague, D 2011, 'Early Relational Reasoning and the Novice Programmer: Swapping as the Hello World of Relational Reasoning', Thirteenth Australasian Computing Education Conference, Australasian Computing Education Conference, Australian Computer Society, Perth, Australia, pp. 95-104.
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Abstract We report on a longitudinal research study of the development of novice programmers in their first semester of programming. In the third week, almost half of our sample of students could not answer an explain-in-plain-English question, for code consisting of just three assignment statements, which swapped the values in two variables. We regard code that swaps the values of two variables as the simplest case of where a programming student can manifest a SOLO relational response. Our results demonstrate that the problems many students face with understanding code can begin very early, on relatively trivial code. However, using traditional programming exercises, these problems often go undetected until late in the semester. New approaches are required to detect and fix these problems earlier.

Delgrande, JP & Peppas, P 2011, 'Revising horn theories', IJCAI International Joint Conference on Artificial Intelligence, International Joint Conference on Artificial Intelligence, AAAI Press, Barcelona, Spain, pp. 839-844.
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This paper investigates belief revision where the underlying logic is that governing Horn clauses. It proves to be the case that classical (AGM) belief revision doesn't immediately generalise to the Horn case. In particular, a standard construction based on a total preorder over possible worlds may violate the accepted (AGM) postulates. Conversely, Horn revision functions in the obvious extension to the AGM approach are not captured by total preorders over possible worlds. We address these difficulties by first restricting the semantic construction to "well behaved" orderings; and second, by augmenting the revision postulates by an additional postulate. This additional postulate is redundant in the AGM approach but not in the Horn case. In a representation result we show that these two approaches coincide. Arguably this work is interesting for several reasons. It extends AGM revision to inferentially-weaker Horn theories; hence it sheds light on the theoretical underpinnings of belief change, as well as generalising the AGM paradigm. Thus, this work is relevant to revision in areas that employ Horn clauses, such as deductive databases and logic programming, as well as areas in which inference is weaker than classical logic, such as in description logic.

Doss, R, Zhou, W, Yu, S & Gao, L 2011, 'A novel mutual authentication scheme with minimum disclosure for RFID systems', Proceedings of the 2011 7th International Conference on Intelligent Sensors, Sensor Networks and Information Processing, ISSNIP 2011, pp. 544-549.
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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 take into account the computational constraints of EPC Class-1 Gen-2 passive RFID tags and only the cyclic redundancy check (CRC) and pseudo random number generator (PRNG) functions that passive RFID tags are capable of are employed. Detailed security analysis of our scheme shows that it can offer robust security properties in terms of tag anonymity and tag untraceability 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 proposed scheme and its impact on authentication delay. © 2011 IEEE.

Durao, F, Bayyapu, K, Xu, G, Dolog, P & Lage, R 2011, 'Using tag-neighbors for query expansion in medical information retrieval', 2011 International Conference on Information Science and Applications, ICISA 2011, International Conference on Information Science and Applications, IEEE, Jeju Island, South Korea.
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In the context of medical document retrieval, users often under-specified queries lead to undesired search results that suffer from not containing the information they seek, inadequate domain knowledge matches and unreliable sources. To overcome the limitations of under-specified queries, we utilize tags to enhance information retrieval capabilities by expanding users' original queries with context-relevant information. We compute a set of significant tag neighbor candidates based on the neighbor frequency and weight, and utilize the most frequent and weighted neighbors to expand an entry query that has terms matching tags. The proposed approach is evaluated using MedWorm medical article collection and standard evaluation methods from the text retrieval conference (TREC). We compared the baseline of 0.353 for Mean Average Precision (MAP), reaching a MAP 0.491 (+39%) with the query expansion. In-depth analysis shows how this strategy is beneficial when compared with different ranks of the retrieval results. © 2011 IEEE.

Eklund, JM, Catley, C, McGregor, C & James, A 2011, 'Detection of apnoea in newborn infants using impedance respiratory wave data', Proceedings of the IASTED International Symposia on Imaging and Signal Processing in Healthcare and Technology, ISPHT 2011, pp. 90-94.
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Apnoea is a serious condition that occurs frequently in prematurely born infants as well as other patients requiring critical care. At least while in the intensive care environment, these patients are provided with constant care assisted by modern medical monitoring systems. The systems record continuous data from each patient, however most of these data are not used except when a care provider observes the device directly, or when an alert - that is used to draw the attention of those same providers - is generated. This paper explores how these continuous data streams can be used in real-time to provide better alert mechanisms and diagnostics, with particular focus on the impedance respiratory waveform, a high rate physiological stream that measures the expansion and contraction of the patient's chest and is traditionally used to determine the respiratory rate. The direct use of this data stream is compared to the derived respiratory rate as a means to estimate the onset of a suspected case of apnoea.

Felix Navarro, KM, Lawrence, EM, Garcia Marin, JA & Sax, C 2011, 'A Dynamic and Customisable Layered Serious Game Design Framework for Improving the Physical and Mental Health of the Aged and the Infirm', The Third International Conference on eHealth, Telemedicine, and Social Medicine (eTELEMED 2011), International Conference on eHealth, Telemedicine and Social Medicine, IARIA Conference, Gosier, Guadeloupe, France, pp. 140-145.
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This paper proposes a dynamic and customizable layered serious game design framework for improving the physical and mental health of the aged after presenting the results obtained from a study with mainstream and alternative/complimentary health professionals concerning the usage of interactive games as a tool to improve both physical and mental well-being of the elderly. This study reports on the commonality of design and health factors regarding the usability of video games for the aged to ensure the elderly benefit from traditional and alternative healthcare professionalsâ perspectives.

Garcia Marin, JA, Felix Navarro, KM & Lawrence, EM 2011, 'Serious Games to Improve the Physical Health of the Elderly: A Categorization Scheme', The Fourth International Conference on Advances in Human-oriented and Personalized Mechanisms, Technologies, and Services (CENTRIC 2011), International Conference on Advances in Human-oriented and Personalized Mechanisms, Technologies, and Services, IARIA, Barcelona, Spain, pp. 64-71.
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this paper aims to provide a snapshot of the current status in the field of serious games for improving the physical health of the elderly. This work covers recent research projects for stroke rehabilitation and for falls prevention where user-center design methodologies were applied in order to satisfy this audience. A classification of the most relevant work in this area is provided along with a brief description of the platform, technology required and user-center design principles applied.

Garcia Marin, JA, Lawrence, EM, Felix Navarro, KM & Sax, C 2011, 'Heuristic Evaluation for Interactive Games within Elderly Users', The Third International Conference on eHealth, Telemedicine, and Social Medicine (eTELEMED 2011), International Conference on eHealth, Telemedicine and Social Medicine, IARIA Conference, Gosier, Guadalupe, France, pp. 130-133.
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This paper presents the results obtained after performing a number of demonstrations followed by a series of interviews concerning the usage of interactive games as a tool to improve both physical and mental well-being of elderly persons. This study points out the importance of a proper design regarding the usability of video games for the aged to ensure the elderly benefit from such games.

Ghous, H, Ho, N, Catchpoole, DR & Kennedy, PJ 2011, 'Comparing functional visualizations of genes', The 5th International Workshop on Data Mining in Functional Genomics and Proteomics: Current Trends and Future Directions, International Workshop on Data Mining in Functional Genomics and Proteomics: Current Trends and Future Directions, European Conference on Machine Learning, Athens, Greece, pp. 12-21.
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Gill, AQ & Bunker, D 2011, 'Connceptualization of a Context Aware Cloud Adaptation (CACA) Framework', 2011 IEEE Ninth International Conference on Dependable, Autonomic and Secure Computing (DASC), International Conference on Dependable, Autonomic and Secure Computing, IEEE CPS, Sydney, pp. 760-767.
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Gill, AQ, Bunker, D & Seltsikas, P 2011, 'An Empirical Analysis of Cloud, Mobile, Social and Green Computing: Financial Services IT Strategy and Enterprise Architecture', 2011 IEEE Ninth International Conference on Dependable, Autonomic and Secure Computing (DASC), International Conference on Dependable, Autonomic and Secure Computing, IEEE CPS, Sydney, pp. 697-704.
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Gluga, R, Kay, J, Lister, RF & Lever, T 2011, 'An architecture for systematic tracking of skills and competence level progression in computer science', Proceedings of the 2nd Annual International Conferences on Computer Science Education: Innovation and Technology (CSEIT 2011) And Software Engineering & Applications (SEA 2011), Annual International Conference on Computer Science Education: Innovation and Technology, Global Science & Technology Forum (GSTF), Singapore, pp. 65-69.
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A typical Computer Science degree is three to five years long, consists of four to six subjects per semester, and two semesters per year. A student enrolled in such a degree is expected to learn both discipline-specific skills and transferable generic skills. These skills are to be taught in a progressive sequence through the duration of the degree. As the student progresses through the subjects and semesters of a degree, his skill portfolio and competence level for each skill is expected to grow. Effectively modeling these curriculum skills, mapping them to assessment tasks across subjects of a degree, and measuring the progression in learner competence level is, largely, still an unsolved problem. Previous work at this scale is limited. This systematic tracking of skills and competence is crucial for effective quality control and optimization of degree structures. Our main contribution is an architecture for a curriculum information management system to facilitate this systematic tracking of skill and competence level progression in a Computer Science context.

Goyal, M 2011, 'Development of agent-based intelligent tutoring system for teaching object-oriented programming concepts', IMSCI 2011 - 5th International Multi-Conference on Society, Cybernetics and Informatics, Proceedings, pp. 17-22.
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Agent-based technology can be used in developing educational tutoring systems. An Intelligent Tutoring System, named as 'ProgTool' has been developed for teaching object-oriented programming concepts. The 'Prog-Tool' has been developed using JADE (Java Agents Development Environment) framework. This system helps the students to learn about Objects, Classes and other programming concepts by taking tutorials from it sitting anywhere and anytime. This paper shows that usage of 'Prog-Tool' helps students with topic sequencing, visual representation, and choice of multiple exercises and tests on each topic makes it a very useful for students.

Goyal, ML 2011, 'Development of Agent-Based Intelligent Tutoring System for Teaching Object-Oriented Programming Concepts', Proceedings of the 9th International Conference on Education and Information Systems, Technologies and Applications, International Conference on Education and Information Systems, Technologies and Applications, International Institute of Informatics and Systemics, Orlando, Florida, USA, pp. 1-6.
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Agent-based technology can be used in developing educational tutoring systems. An Intelligent Tutoring System, named as `ProgTool has been developed for teaching object-oriented programming concepts. The `Prog-Tool has been developed using JADE (Java Agents Development Environment) framework. This system helps the students to learn about Objects, Classes and other programming concepts by taking tutorials from it sitting anywhere and anytime. This paper shows that usage of `Prog-Tool helps students with topic sequencing, visual representation, and choice of multiple exercises and tests on each topic makes it a very useful for students.

Huang, CS, Ko, LW, Lu, SW, Chen, SA & Lin, CT 2011, 'A vectorcardiogram-based classification system for the detection of Myocardial infarction', Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS, International Conference of the IEEE Engineering in Medicine and Biology Society, IEEE, Boston, MA, USA, pp. 973-976.
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Myocardial infarction (MI), generally known as a heart attack, is one of the top leading causes of mortality in the world. In clinical diagnosis, cardiologists generally utilize 12-lead ECG system to classify patients into MI symptoms: 1. ST segment elevation, 2. ST segment depression or T wave inversion. However unstable ischemic syndromes have rapidly changing supply versus demand characteristics that is one of the several limitations of 12-lead ECG system for MI detection. In addition, the ECG sensor placements of 12-lead system is not easily donned and doffed for tele-healthcare monitoring at home. Vectorcardiogram (VCG) system in clinic is another type of diagnosis plot which represents the magnitude and direction of the electrical potential in the form of a vector loop during cardiac electric activity. The VCG system can easily acquire three ECG waves from X, Y, Z directions to composite vector signal in space and the VCG signals can be transferred to 12-lead ECG signal through Dower transformation and vice versa. Hence, this study attempts to develop a VCG-based classification system for the detection of Myocardial infarction. In the experiment results, the proposed system can select the proper ECG features based on cardiologist's knowledge and proposed principal moments of QRS complex. The classification performance of MI detection can be reached to 99.89% of sensitivity, 92.51% of specificity, 95.35% of positive predictive value, and 96.96% overall accuracy with maximum-likelihood classifier (MLC). © 2011 IEEE.

Huang, M, Zhang, J, Nguyen, Q & Wang, J 2011, 'Visual Clustering of Spam Emails for DDoS Analysis', Proc. of 15th IEEE International Conference on Information Visualization (2011), IEEE Information Visualization Conference, IEEE Computer Society, London, United Kingdom, pp. 65-72.
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Networking attacks embedded in spam emails are increasingly becoming numerous and sophisitcated in nature. Hence this has given a growing need for spam e-mail analysis to identify these attacks. The use of these intrusion detection systems has given rise to other two issues 1) the presentation and undersatanding of large ammounts of spam e-mails, 2) the user assisted input and quantified adjustment during the analysis process. In this paper we introduce a new analytical model that uses two coefficient vectors: 'density' and 'weight' for the analysis of spam email viruses and attacks. We then use a visual clustering method to classify and display the spam emails. The visualisation allows users to interactively select and scale down the scope of views for better undersanding of different types of the spam email attacks. The experiment shows that this new model with the clustering visualization can be effecitvely used for network security analysis.

Huang, T, Huang, M & Jin, J 2011, 'Parallel Rough Set: Dimensionality Reduction and Feature Discovery of Multi-Dimensional Data in Visualization', Lecture Notes in Computer Science (LNCS) 7063, International Conference on Neural Information Processing, Springer, Shanghai, China, pp. 99-108.
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Attempt to visualize high dimensional datasets typically encounter over plotting and decline in visual comprehension that makes the knowledge discovery and feature subset analysis difficult. Hence, reshaping the datasets using dimensionality reduction technique is paramount by removing the superfluous attributes to improve visual analytics. In this work, we applied rough set theory as dimensionality reduction and feature selection methods on visualization to facilitate knowledge discovery of multi-dimensional datasets. We provided the case study using real datasets and comparison against other methods to demonstrate the effectiveness of our approach.

Huang, T, Huang, M & Lin, C 2011, 'Aesthetic of Angular Resolution for Node-Link Diagrams: Validation and Algorithm', Proc. of 2011 IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC 2011), IEEE Symposium on Visual Languages and Human-Centric Computing, IEEE Computer Society, Pittsburgh, PA, USA, pp. 213-216.
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When visualizing graphs into node-link diagrams, angular resolution is often used as one of the aesthetic criteria measuring the diagram quality in terms of human comprehension. However, angualr resolution has not been empirically vailidated for its relevance to humans. In addition although many force-directed algorithms have been proposed for automatic graph drawing, performance evaluation of these algorithms has not been conclusive due to the lack of proper methods. To shorten these gaps, this paper 1) validates the aesthetic based on human experimental data and identifies the best of angular resolution measures used in the literature; 2) introduces a force-directed algorithm, forceAR, for improving angular resolution; 3) proposes a new framework for more reliable and thorough evaluation of force-directed algorithms. Finally as a case study, our forceAR algorthim is evaluated using this framework.

Huang, T, Song, X & Huang, M 2011, 'Optimized data acquisition by time series clustering in OPC', Proc. Of 6th IEEE Int'l Conference on Industrial Electronics and Applications (ICIEA 11), IEEE Conference on Industrial Electronics and Applications, IEEE Press, Beijing, China, pp. 2480-2486.
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How to optimized OPE Group Management is the most frequently asked question when integrating ope with a SeADA system. Group management assumes that the ope client has the information to partition ope items into homogeneous ope groups with optimal configuration parameters, such as update rate or dead band. In reality, supervised group management mandates an empirical configuration which often leads to high group polling rate on the server and low item update rate on the client. In this paper we propose an unsupervised ope group management concept and algorithm by modeling the ope items as time series functions in order to quantify the similarities. Partitioning items into the optimal ope groups is achieved using the hierarchical clustering that does not require the number of optimal clusters to be known in advance as oppose to K-mean which often produces suboptimal result and reduce the homogeneity within the group. An evaluation comparison is provided for the unsupervised and supervised method that suggests that our approach produced outstanding performance.

Hussain, FK & Chang, E 2011, '3. Message from the editors', IEEE International Conference on Digital Ecosystems and Technologies, p. 8.
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Janjua, NK & Hussain, FK 2011, 'Defeasible reasoning based argumentative Web-IDSS for Virtual Teams (VTs)', Proceedings - 2011 IEEE/WIC/ACM International Joint Conferences on Web Intelligence and Intelligent Agent Technology - Workshops, WI-IAT 2011, IEEE/WIC/ACM international Conference on Web Intelligence, IEEE, Lyon, France, pp. 330-334.
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TheWeb-based intelligent decision support system (Web-IDSS) is pivotal for a Virtual Team (VT) to successfully execute business-related tasks. The current generation of Web-IDSS built on top of semantic web technologies for VTs lacks the capability to provide decision support when underlying information is incomplete and/or contradictory. In this article, we address this limitation of current Web-IDSS through defeasible logic based argumentation formalism. The proposed Web-IDSS uses a hybrid reasoning approach: forward chaining (data-driven) for the construction of arguments over incomplete information, and backward chaining (goal-driven) for conflict identification and resolution with explanation. The proposed Web-IDSS adheres to web standards and publishes the outcome of argumentative reasoning in Argument Interchange Format (AIF). © 2011 IEEE.

Janjua, NK & Hussain, FK 2011, 'Rule-based business policies specification, reasoning and integration for business process model extraction', Proceedings - 2011 International Conference on Broadband and Wireless Computing, Communication and Applications, BWCCA 2011, International Conference on Broadband and Wireless Computing, Communication and Applications (BWCCA), IEEE, Barcelona, Spain, pp. 51-56.
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Business policies are pervasive in web-based information systems and the introduction of the semantic web has opened new fertile horizons for their representation and automated processing. However, a number of challenges have also emerged. First is the formal representation and handling of contradictory business policies. Second, is the extraction of process models from a given set of business policies. This paper reports on a semantic, rule-based information system for business policies representation, and argumentative reasoning to resolve conflicts and integrate them to produce a business process model for a given task. We demonstrate the working of the proposed system with help of a case study. © 2011 IEEE.

Jansen, M, Qiao, Y & Sarma, MNJ 2010, 'Deterministic Black-Box Identity Testing pi-Ordered Algebraic Branching Programs', IARCS International Conference on Foundations of Software Technology and Theoretical Computer Science, International Conference on Foundations of Software Technology and Theoretical Computer Science, Dagstuhl Publishing, Chennai, India, pp. 296-307.
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In this paper we study algebraic branching programs (ABPs) with restrictions on the order and the number of reads of variables in the program. An ABP is given by a layered directed acyclic graph with source $s$ and sink $t$, whose edges are labeled by variables taken from the set $\{x_1, x_2, \ldots, x_n\}$ or field constants. It computes the sum of weights of all paths from $s$ to $t$, where the weight of a path is defined as the product of edge-labels on the path. Given a permutation $\pi$ of the $n$ variables, for a $\pi$-ordered ABP ($\pi$-OABP), for any directed path $p$ from $s$ to $t$, a variable can appear at most once on $p$, and the order in which variables appear on $p$ must respect $\pi$. One can think of OABPs as being the arithmetic analogue of ordered binary decision diagrams (OBDDs). We say an ABP $A$ is of read $r$, if any variable appears at most $r$ times in $A$. Our main result pertains to the polynomial identity testing problem, i.e. the problem of deciding whether a given $n$-variate polynomial is identical to the zero polynomial or not. We prove that over any field $\F$, and in the black-box model, i.e. given only query access to the polynomial, read $r$ $\pi$-OABP computable polynomials can be tested in $\DTIME[2^{O(r\log r \cdot \log^2 n \log\log n)}]$. In case $\F$ is a finite field, the above time bound holds provided the identity testing algorithm is allowed to make queries to extension fields of $\F$.

Jay, B & Palsberg, J 2011, 'Typed Self-Interpretation by Pattern Matching', Proceedings of the 2011 ACM Sigplan International Conference on Functional Programming, pp. 247-58.
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Jay, B & Palsberg, J 2011, 'Typed self-interpretation by pattern matching', Proceedings of the ACM SIGPLAN International Conference on Functional Programming, ICFP, pp. 247-258.
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Self-interpreters can be roughly divided into two sorts: self-recognisers that recover the input program from a canonical representation, and self-enactors that execute the input program. Major progress for statically-typed languages was achieved in 2009 by Rendel, Ostermann, and Hofer who presented the first typed selfrecogniser that allows representations of different terms to have different types. A key feature of their type system is a type:type rule that renders the kind system of their language inconsistent. In this paper we present the first statically-typed language that not only allows representations of different terms to have different types, and supports a self-recogniser, but also supports a selfenactor. Our language is a factorisation calculus in the style of Jay and Given-Wilson, a combinatory calculus with a factorisation operator that is powerful enough to support the pattern-matching functions necessary for a self-interpreter. This allows us to avoid a type:type rule. Indeed, the types of System F are sufficient. We have implemented our approach and our experiments support the theory. Copyright © 2011 ACM.

Jay, B & Vergara, J 2011, 'Growing a Language in Pattern Calculus'.
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Jiang, J, Lu, J & Zhang, G 2011, 'An innovative self-adaptive configuration optimization system in cloud computing', Dependable, Autonomic and Secure Computing (DASC), 2011 IEEE Ninth International Conference on, IEEE, pp. 621-627.
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Jiang, J, Lu, J, Zhang, G & Long, G 2011, 'Scaling-up item-based collaborative filtering recommendation algorithm based on hadoop', 2011 IEEE World Congress on Services, IEEE, pp. 490-497.
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Johnston, AJ 2011, 'Beyond Evaluation: Linking Practice and Theory in New Musical Interface Design', NIME 2011: Proceedings of the International Conference on New Inferfaces for Musical Expression, New Interfaces for Musical Expression, Department of Musicology, University of Oslo Norwegian Academy of Music, Oslo, Norway, pp. 280-283.
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Johnston, AJ & CLARKSON, D 2011, 'Designing for Conversational Interaction with Interactive Dance Works', Proceedings of the Workshop: The Body In Design, The Australasian Computer Human Interaction Conference (OzCHI), Australian Computer Human Interaction Conference, Interaction Design and Work Practice Laboratory (IDWoP), Canberra, pp. 13-16.
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In this paper we describe ongoing work, which explores the physicality of human-computer interaction in dance works. The use of physical simulations in the interface to connect with the performers and audiences lived experience of the physical world is discussed. Drawing on past work with musicians, we argue that this approach is effective in encouraging creative, `conversational interactions in live performance.

Johnston, B 2011, 'An interface for crowd-sourcing spatial models of commonsense', AAAI Spring Symposium - Technical Report, pp. 139-142.
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Commonsense is a challenge not only for representation and reasoning but also for large scale knowledge engineering required to capture the breadth of our 'everyday' world. One approach to knowledge engineering is to 'outsource' the effort to the public through games that generate structured commonsense knowledge from user play. To date, such games have focused on symbolic and textual knowledge. However, an effective commonsense reasoning system will require spatial and physical reasoning capabilities. In this paper, I propose a tool for gathering commonsense information from ordinary people. It is a user-friendly 3D sculpting tool for modeling and annotating models of physical objects and spaces. Copyright © 2011, Association for the Advancement of Artificial Intelligence. All rights reserved.

Johnston, BG 2011, 'An Interface for Crowd-sourcing Spatial Models of Commonsense', Commonsense 2011, Symposium on Logical Formalizations of Commonsense Reasoning, AAAI Press, Stanford University, pp. 1-4.
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Commonsense is a challenge not only for representation and reasoning but also for large scale knowledge engineering required to capture the breadth of our `everyday world. One approach to knowledge engineering is to `outsource the effort to the public through games that generate structured commonsense knowledge from user play. To date, such games have focused on symbolic and textual knowledge. However, an effective commonsense reasoning system will require spatial and physical reasoning capabilities. In this paper, I propose a tool for gathering commonsense information from ordinary people. It is a user-friendly 3D sculpting tool for modeling and annotating models of physical objects and spaces.

Johnston, BG 2011, 'The Collection of Physical Knowledge and Its Application in Intelligent Systems', Proceedings of the 4th International Conference, AGI 2011: Artificial General Intelligence - Lecture Notes in Compter Science, Conference on Artificial General Intelligence (AGI), Springer, Mountain View, USA, pp. 163-173.
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Intelligence is a multidimensional problem of which physical reasoning and physical knowledge are important dimensions. However, there are few resources of physical knowledge that can be used in data-driven approaches to Artificial Intelligence. Comirit Objects is a project intended to encourage the general public to contribute to research in Artificial Intelligence by building simple 3D models of everyday objects via an interactive web-site. This paper describes the simplified representation and web-interface used by Comirit Objects and a preliminary investigation into the potential applications of the collected models

Juszczyszyn, K, Budka, M & Musial, K 2011, 'The Dynamic Structural Patterns of Social Networks Based on Triad Transitions', 2011 INTERNATIONAL CONFERENCE ON ADVANCES IN SOCIAL NETWORKS ANALYSIS AND MINING (ASONAM 2011), International Conference on Advances in Social Networks Analysis and Mining (ASONAM), IEEE COMPUTER SOC, Kaohsiung, TAIWAN, pp. 581-586.
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Juszczyszyn, K, Musiał, K & Budka, M 2011, 'Link prediction based on Subgraph evolution in dynamic social networks', Proceedings - 2011 IEEE International Conference on Privacy, Security, Risk and Trust and IEEE International Conference on Social Computing, PASSAT/SocialCom 2011, pp. 27-34.
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We propose a new method for characterizing the dynamics of complex networks with its application to the link prediction problem. Our approach is based on the discovery of network subgraphs (in this study: triads of nodes) and measuring their transitions during network evolution. We define the Triad Transition Matrix (TTM) containing the probabilities of transitions between triads found in the network, then we show how it can help to discover and quantify the dynamic patterns of network evolution. We also propose the application of TTM to link prediction with an algorithm (called TTM-predictor) which shows good performance, especially for sparse networks analyzed in short time scales. The future applications and research directions of our approach are also proposed and discussed. © 2011 IEEE.

Kassenaar, P, Bredies, K & van den Hoven, E 2011, 'Designing for utilization: Putting design principles into practice', Proceedings of the Nordes '11: The 4th Nordic Design Research Conference MAKING DESIGN MATTER!, Nordic Design Research Conference, School of Art and Design, Aalto University, Helsinki, Finland, pp. 324-329.
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Designers do not only create usable products for a predefined purpose, but also to explore new materials and technologies. In doing so, they should not restrict themselves to existing conventions, but develop new ones out of the medium at hand. These new interface forms should encourage users to appropriate an object for their own purposes - i.e. utilize it. In this paper, we will describe the development of a fabric interface prototype that should exploit the material and encourage utilization of the interface. We discuss how our theoretical perspective was translated into a concrete design, and how appropriate we judge it for utilization. We conclude that design without final goal is surprisingly hard to do, but can show the value of the medium used.

Kaur, P, Goyal, ML & Lu, J 2011, 'Data Mining Driven agents for Predicting Online Auction's End Price', 2011 IEEE Symposium Series on Computational Intelligence Proceedings, IEEE Symposium on Computational Intelligence and Data Mining, IEEE Computational Intelligence Society, Paris, France, pp. 141-147.
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Abstract Auctions can be characterized by distinct nature of their feature space. This feature space may include opening price, closing price, average bid rate, bid history, seller and buyer reputation, number of bids and many more. In this paper, a clustering based method is used to forecast the end-price of an online auction for autonomous agent based system. In the proposed model, the input auction space is partitioned into groups of similar auctions by kmeans clustering algorithm. The recurrent problem of finding the value of k in k-means algorithm is solved by employing elbow method using one way analysis of variance (ANOVA). Then k numbers of regression models are employed to estimate the forecasted price of an online auction. Based on the transformed data after clustering and the characteristics of the current auction, bid selector nominates the regression model for the current auction whose price is to be forecasted. Our results show the improvements in the end price prediction for each cluster which support in favor of the proposed clustering based model for the bid prediction in the online auction environment.

Kaur, P, Goyal, ML & Lu, J 2011, 'Pricing Analysis in Online Auctions Using Clustering and Regression Tree Approach', Lecture Notes in Artificial Intelligence 5980 - Agents and Data Mining Interaction, International Workshop on Agents and Data Mining Interaction, Springer-Verlag Berlin / Heidelberg, Taipei, Taiwan, pp. 248-257.
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Auctions can be characterized by distinct nature of their feature space. This feature space may include opening price, closing price, average bid rate, bid history, seller and buyer reputation, number of bids and many more. In this paper, a price forecasting agent (PFA) is proposed using data mining techniques to forecast the end-price of an online auction for autonomous agent based system. In the proposed model, the input auction space is partitioned into groups of similar auctions by kmeans clustering algorithm. The recurrent problem of finding the value of k in k-means algorithm is solved by employing elbow method using one way analysis of variance (ANOVA). Based on the transformed data after clustering, bid selector nominates the cluster for the current auction whose price is to be forecasted. Regression trees are employed to predict the end-price and designing the optimal bidding strategies for the current auction. Our results show the improvements in the end price prediction using clustering and regression tree approach.

Kazienko, P, Kukla, E, Musial, K, Kajdanowicz, T, Brodka, P & Gaworecki, J 2011, 'A Generic Model for a Multidimensional Temporal Social Network', E-TECHNOLOGIES AND NETWORKS FOR DEVELOPMENT, 1st International Conference on e-Technologies and Networks for Development (ICeND 2011), SPRINGER-VERLAG BERLIN, Inst Finance Management, Dar es Salaam, TANZANIA, pp. 1-14.

Kazienko, P, Musial, K, Kukla, E, Kajdanowicz, T & Brodka, P 2011, 'Multidimensional Social Network: Model and Analysis', COMPUTATIONAL COLLECTIVE INTELLIGENCE: TECHNOLOGIES AND APPLICATIONS, PT I, 3rd International Conference on Computational Collective Intelligence (ICCCI 2011), SPRINGER-VERLAG BERLIN, Gdynia Maritime Univ, Gdynia, POLAND, pp. 378-387.

Kimman, F, Weda, H, van den Hoven, E, de Zeeuw, T & Luitjens, S 2011, 'Spinning in Control: Design Exploration of a Cross-Device Remote', Proceedings of Fifth International Conference on Tangible, Embedded and Embodied Interaction, Tangible, Embedded, and Embodied Interaction, ACM, Funchal, Portugal, pp. 189-192.
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You buy a new TV and get a new remote, you buy a DVD player and you get another remote, you buy a sound system and guess what? Almost every digital media product comes with its own designated remote control (RC). What would happen if one remote adapts to the owner's activities and is able to have cross-device control? In this paper we describe a design exploration conducted to create new ways to interact with digital media products. The main ingredients are: fit for a social setting, portable, and including physical interaction. The result is an exploration of a button less single-hand remote control concept.

Ko, LW, Wei, CS, Chen, SA & Lin, CT 2011, 'EEG-based motion sickness estimation using principal component regression', Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), International Conference on Neural Information Processing, Springer, Shanghai, China, pp. 717-724.
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Driver's cognitive state monitoring system has been implicated as a causal factor for the safety driving issue, especially when the driver fell asleep or distracted in driving. However, the limitation in developing this system is lack of a major indicator which can be applied to a realistic application. In our past studies, we investigated the physiological changes in the transition of driver's cognitive state by using EEG power spectrum analysis and found that the features in the occipital area were highly correlated with the driver's driving performance. In this study, we construct an EEG-based self-constructed neural fuzzy system to estimate the driver's cognitive state by using the EEG features from the occipital area. Experimental results show that the proposed system had the better performance than other neural networks. Moreover, the proposed system can not only be limited to apply to individual subjects but also sufficiently works in between subjects. © 2011 Springer-Verlag.

Ko, LW, Wei, CS, Jung, TP & Lin, CT 2011, 'Estimating the level of motion sickness based on EEG spectra', Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), International Conference on Foundations of Augmented Cognition, Springer, Orlando, Florida, USA, pp. 169-176.
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Motion sickness (MS) is a normal response to real, perceived, or even anticipated movement. People tend to get motion sickness on a moving boat, train, airplane, car, or amusement park rides. Although many motion sickness-related biomarkers have been identified, but how to estimate human's motion sickness level (MSL) is a big challenge in the operational environment. Traditionally, questionnaire and physical check are the common ways to passively evaluate subject's sickness level. Our past studies had investigated the EEG activities correlated with motion sickness in a virtual-reality based driving simulator. The driving simulator comprised an actual automobile mounted on a Stewart motion platform with six degrees of freedom, providing both visual and vestibular stimulations to induce motion-sickness in a manner that is close to that in daily life. EEG data were acquired at a sampling rate of 500 Hz using a 32-channel EEG system. The acquired EEG signals were analyzed using independent component analysis (ICA) and time-frequency analysis to assess EEG correlates of motion sickness. Subject's degree of motion-sickness was simultaneously and continuously reported using an onsite joystick, providing non-stop psychophysical references to the recorded EEG changes. We found that the parietal, motor, occipital brain regions exhibited significant EEG power changes in response to vestibular and visual stimuli. Based on these findings and experimental results, this study aims to develop an EEG-based system to estimate subject's motion sickness level upon the EEG power spectra from motion-sickness related brain areas. The MS evaluation system can be applied to early detection of the subject's motion sickness and prevent its uncomfortable syndromes in our daily life. Furthermore, the experiment results could also lead to a practical human-machine interface for noninvasive monitoring of motion sickness of drivers or passengers in real-world environments. © 2011 Springer-Verla...

Lawrence, EM, Felix Navarro, KM, Sax, C & Garcia Marin, J 2011, 'Towards Building Health Systems', The Sixth International Conference on Systems, International Conference on Systems, IARIA Conference, St. Maarten, The Netherlands Antilles, pp. 109-114.
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This paper reports on a series of interviews with three mainstream and three alternative/complimentary health professionals about the use of interactive technologies as a tool to improve the physical and mental well-being of the elderly. The questions are based around an Analytic Framework for investigating Interactive Technologies and the elderly. Four balance games using the Wii were demonstrated to the interviewees and their opinion of the suitability or otherwise of these games are discussed. The chosen games did not meet with universal approval but did provide us with useful insights on how to ensure the development of appropriate games for the elderly.

Leong, T, Harper, R & Regan, T 2011, 'Nudging towards Serendipity: A Case with Personal Digital Photos', BCS Conference on Human-Computer Interaction, British Computer Society Conference on Human-Computer Interaction, British Computer Society, Newcastle upon Tyne, pp. 385-394.
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Leong, TW, Taylor, R, Gaye, L, Wright, P & Tanaka, A 2011, 'The user in flux: Bringing HCI and digital arts together to interrogate shifting roles in interactive media', Conference on Human Factors in Computing Systems - Proceedings, CHI '11 Extended Abstracts on Human Factors in Computing Systems, ACM DL, Vancouver, BC, Canada, pp. 45-48.
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With the advent of interactive digital media, people are no longer simply 'users'. They actively shift between various roles: author, collaborator, and even performer. We coin the term "user in flux" to problematize static definitions of "the user" and highlight how people's roles and practices switch and evolve when engaged in such interactions. Drawing from participatory practices and seeking inspiration from interactive artists, this workshop explores the "user in flux" with an aim to establish directions and approaches that can revitalize the HCI community's understanding of the user and inform the design of technologies used for interacting with digital media, and promote a new research agenda.

Li, CH, Chu, HS, Kuo, BC & Lin, CT 2011, 'Hyperspectral image classification using spectral and spatial information based linear discriminant analysis', International Geoscience and Remote Sensing Symposium (IGARSS), IEEE International Geoscience and Remote Sensing Symposium, IEEE, Vancouver, BC, Canada, pp. 1716-1719.
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Feature extraction plays an essential role in Hyperspectral image classification. Linear discriminant analysis (LDA) is a commonly used feature extraction (FE) method to resolve the Hughes phenomenon for classification. The Hughes phenomenon (also called the curse of dimensionality) is often encountered in classification when the dimensionality of the space grows and the size of the training set is fixed, especially in the small sampling size problem. Recent studies show that the spatial information can greatly improve the classification performance. Hence, for hyperspectral image classification, it is not only necessary to use the available spectral information but also to exploit the spatial information. In this paper, spatial information is acquired by the concept of the Markov random field (MRF), and this spatial information is used to form the membership values of every pixel in the hyperspectral image. The experimental results on two hyperspectral images, the Washington DC Mall and the Indian Pine Site, show that the proposed method can yield a better classification performance than LDA in the small sampling size problem. © 2011 IEEE.

Li, J & Tao, D 2011, 'A Probabilistic Model for Discovering High Level Brain Activities from fMRI', Lecture Notes in Computer Science, International Conference on Neural Information Processing, Springer-Verlag, Shanghai, China, pp. 329-336.
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Functional magnetic resonance imaging (fMRI) has provided an invaluable method of investing real time neuron activities. Statistical tools have been developed to recognise the mental state from a batch of fMRI observations over a period. However, an interesting question is whether it is possible to estimate the real time mental states at each moment during the fMRI observation. In this paper, we address this problem by building a probabilistic model of the brain activity. We model the tempo-spatial relations among the hidden high-level mental states and observable low-level neuron activities. We verify our model by experiments on practical fMRI data. The model also implies interesting clues on the task-responsible regions in the brain.

Li, J, Bian, W, Tao, D & Zhang, C 2011, 'Learning Colours from Textures by Sparse Manifold Embedding', Lecture Notes in Artificial Intelligence.AI 2011: Advances in Artificial Intelligence.24th Australasian Joint Conference, Australasian Joint Conference on Artificial Intelligence, Springer-Verlag Berlin / Heidelberg, Perth, Australia, pp. 600-608.
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The capability of inferring colours from the texture (grayscale contents) of an image is useful in many application areas, when the imaging device/environment is limited. Traditional colour assignment involves intensive human effort. Automatic methods have been proposed to establish relations between image textures and the corresponding colours. Existing research mainly focuses on linear relations. In this paper, we employ sparse constraints in the model of texture-colour relationship. The technique is developed on a locally linear model, which assumes manifold assumption of the distribution of the image data. Given the texture of an image patch, learning the model transfers colours to the texture patch by combining known colours of similar texture patches. The sparse constraint checks the contributing factors in the model and helps improve the stability of the colour transfer. Experiments show that our method gives superior results to those of the previous work.

Li, J, Wang, J & Huang, M 2011, 'Twig Pattern Matching: A Revisit', Lecture Notes in Computer Science, LNCS 6861, International Conference on Database and Expert Systems Applications, Springer, Toulouse, France, pp. 43-50.
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Twig pattern matching plays a cruical role in CML query processing. In order to reduce the processing time, some exisiting holistice one-phase twig pattern matching algorithms (e.g., HolisticTwigStack [3], TwigFast [5], etc) use the core function getNext of TwigStack [2] to efectively and efficiently filter out the useless elements. However, using getNext as a filter may incur other redundant computation. We propose two apporaches, namely re-test checking and forward-to-end, which can avoid the redundant computation and can be easily applied to both holistic one-phase and two phase algorithms. The experiments show that our apporach can significantly improve the efficiency by avoiding the redundant computation.

Li, L, Xu, G, Yang, Z, Zhang, Y & Kitsuregawa, M 2011, 'A Feature-Free Flexible Approach to Topical Classification of Web Queries', Proceedings of Seventh International Conference on Semantics Knowledge and Grid, International Conference on Semantics Knowledge and Grid, IEEE, Beijing, China, pp. 59-66.
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Li, M, Gao, L & Zhou, W 2011, 'MAR: Message-aware routing for opportunistic wireless ad hoc networks', Australasian Telecommunication Networks and Applications Conference, ATNAC 2011.
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In this paper we study the problem of routing in opportunistic wireless network, and propose a novel routing mechanism, message-aware routing (MAR). Using MAR, the messages can be prioritized at mobile nodes and the resources will be allocated accordingly. The MAR uses the message-aware socializing model to classify mobile nodes into different social groups. In MAR, nodes only maintain up-to-date routing information for the nodes in the same social group and the messages for the nodes in the same social group will have higher priority to be delivered. The MAR improves the routing efficiency in terms of reduced traffic and a higher delivery success rate. Further, MAR is constructed in decentralized way and does not require any centralized infrastructure. Experiments using NS2 simulator show that the MAR achieves higher delivery rate than the Epidemic and Prophet routing. © 2011 IEEE.

Liao, LD, Chen, YY, Lin, CT, Chang, JY & Li, ML 2011, 'Functional transcranial photoacoustic micro-imaging of mouse cerebrovascular cross-section and hemoglobin oxygenation changes during forepaw electrical stimulation', Progress in Biomedical Optics and Imaging - Proceedings of SPIE, Conference on Photons Plus Ultrasound - Imaging and Sensing/Photonics West BiOS Symposium, SPIE, USA.
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In this study, we report on using a 50-MHz functional photoacoustic microscopy (PAM) to transcranially image the cross-section and hemoglobin oxygenation (SO 2 ) changes of single mouse cortical vessels in response to left forepaw electrical stimulation. Three difference levels of the cortical vessels (i.e., with different-sized diameters of 350, 100 and 55 μm) on activated regions were marked to measure their functional cross-section and SO 2 changes as a function of time. Electrical stimulation of the mouse left forelimb was applied to evoke functional changes in vascular dynamics of the mouse somatosensory cortex. The applied current pulses were with a pulse frequency of 3 Hz, pulse duration of 0.2 ms, and pulse amplitude of 2 mA. The cerebrovascular cross-section changes, which indicate changes in cerebral blood volume (CBV), were probed by images acquired at 570 nm, a hemoglobin isosbestic point, while SO 2 changes were monitored by the derivatives of 560-nm images normalized to 570-nm ones. The results show that vessel diameter and SO 2 were significantly dilated and increased when compared with those of the controlled ones. In summary, the PAM shows its promise as a new imaging modality for transcranially functional quantification of single vessel diameter (i.e., CBV) and SO 2 changes without any contrast agents applied during stimulation. © 2011 SPIE.

Lin, CT, Chen, SA, Ko, LW & Wang, YK 2011, 'EEG-based brain dynamics of driving distraction', Proceedings of the International Joint Conference on Neural Networks, The 2011 International Joint Conference on Neural Networks, IEEE, San Jose, CA, USA, pp. 1497-1500.
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Distraction during driving has been recognized as a significant cause of traffic accidents. The aim of this study is to investigate Electroencephalography (EEG) -based brain dynamics in response to driving distraction. To study human cognition under specific driving tasks in a simulated driving experiment, this study utilized two simulated events including unexpected car deviations and mathematics questions. The raw data were first separated into independent brain sources by Independent Component Analysis. Then, the EEG power spectra were used to evaluate the time-frequency brain dynamics. Results showed that increases of theta band and beta band power were observed in the frontal cortex. Further analysis demonstrated that reaction time and multiple cortical EEG power had high correlation. Thus, this study suggested that the features extracted by EEG signal processing, which were the theta power increases in frontal area, could be used as the distracted indexes for early detection of driver inattention in real driving. © 2011 IEEE.

Lin, CT, Chiou, JC & Song, KT 2011, 'Welcome message from conference chairs', ASCC 2011 - 8th Asian Control Conference - Final Program and Proceedings, p. 4.

Lin, CT, Han, MF, Lin, YY, Liao, SH & Chang, JY 2011, 'Neuro-fuzzy system design using differential evolution with local information', 2011 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2011), IEEE International Conference on Fuzzy Systems, IEEE, Taipei, Taiwan, pp. 1003-1006.
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This paper proposes a differential evolution with local information for TSK-type neuro-fuzzy system optimization. The differential evolution with local information consider neighborhood between each individual to keep the diversity of population. An adaptive parameter tuning based on 1/5th rule is used to trade off between local search and global search. For structure learning algorithm, the on-line clustering algorithm is used for rule generation. The structure learning algorithm generates a new rule which compares the firing strength. Initially, there is no rule in neuro-fuzzy system model. The rules are automatically generated by fuzzy measure. For parameter learning, the parameters are optimized by differential evolution algorithm. Finally, the proposed neuro-fuzzy system with novel differential evolution model is applied in chaotic sequence prediction problem. Results of this paper demonstrate the effectiveness of the proposed model. © 2011 IEEE.

Lin, CT, Kuo, YH, Lee, CS, Ishibuchi, H & Wang, WJ 2011, 'A message from the conference organizers: 2011 IEEE international conference on fuzzy systems', IEEE International Conference on Fuzzy Systems, p. 4.
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Lin, CT, Li, DL & Chang, JY 2011, 'Self-adjusting feature maps network', Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), International Conference on Neural Information Processing, Springer Link, Shanghai, China, pp. 356-364.
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In this paper, we propose a novel artificial neural network, called self-adjusting feature map (SAM), and its unsupervised learning algorithm with self-adjusting mechanism. After the training of SAM network, we will obtain a map composed of a set of representative connected neurons. The trained network structure of representative connected neurons not only displays the spatial relation of the input data distribution but also quantizes the data well. SAM can automatically isolate a set of connected neurons, in which the number of the set may indicate the number of clusters to be used. The idea of self-adjusting mechanism is based on combining of mathematical statistics and neurological advance and retreat of waste. For each representative neuron, there are three periods, growth, adaptation and decline, in its training process. The network of representative neurons will first create the necessary neurons according to the local density of the input data in the growth period. Then it will adjust neighborhood neuron pair's connected/disconnected topology constantly according to the statistics of input feature data in the adaptation period. Lastly the unnecessary neurons of the network will be merged or deleted in the decline period. In this study, we exploit SAM to handle some peculiar cases that cannot be well dealt with by classical unsupervised learning networks such as self-organizing feature map (SOM) network. Furthermore, we also take several real world cases to exhibit the remarkable characteristics of SAM. © 2011 Springer-Verlag.

Lin, C-T, Lin, C-L, Chiu, T-W, Duann, J-R & Jung, T-P 2011, 'Effect of respiratory modulation on relationship between heart rate variability and motion sickness.', 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, International Conference of the IEEE Engineering in Medicine and Biology Society, IEEE, Boston, MA, USA, pp. 1921-1924.
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This study investigates the interplay among heart rate variability (HRV), respiration, and the severity of motion sickness (MS) in a realistic passive driving task. Although HRV is a commonly used metrically in physiological research or even believed to be a direct measure of sympathovagal activities, the results of MS-effected HRV remain mixed across studies. The goal of this study is to find the source of these contradicting results of HRV associated with MS. Experimental results of this study showed that the group trend of the low-frequency (LF) component and the LF/HF ratio increased and high-frequency (HF) component decreased significantly as self-reported MS level increased (p<0.001), consistent with a perception-driven autonomic response of the cardiovascular system. However, in one of the subjects, the relationship was reversed when individuals intentionally adjust themselves (deep breathing) to relieve the discomfort of MS during the experiments. It appears that the correlations between HRV and MS level were higher when individuals made fewer adjustments (the number of deep breathing) during the passive driving experiments.

Lin, CT, Wang, WR, Wang, IJ, Liao, LD, Chen, SF, Tseng, K & Ko, LW 2011, 'A new design of the multi-channels mobile and wireless EEG system', Communications in Computer and Information Science, International Conference on Human-Computer Interaction, Springer, Orlando, Florida, USA, pp. 293-298.
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Most researchers acquired EEG by using standard measurement system like NeuroScan system, which includes AgCl electrode cap, SynAmps Amplifier and Scan software to provide good reliability for the acquisition of EEG data. However, it is still not convenient for Brain Computer Interface (BCI) application in daily life because of needing conduction gels to contact skins and being wired, expensive and heavy. Moreover, the conduction gel will trend to be drying, so it does not suitable for long-term monitoring. In this study, we developed a mobile and wireless EEG system. The system consists of frond-end 16-channel dry electrode cap, a miniature low-power wireless portable circuitry, and a back-end program receiving events and digital EEG data simultaneously. We demonstrate the recorded EEG data have high correlations between from our system and from NeuroScan system. © 2011 Springer-Verlag.

Lin, C-T, Wang, Y-K & Chen, S-A 2011, 'An EEG-Based Brain-Computer Interface for Dual Task Driving Detection', NEURAL INFORMATION PROCESSING, PT I, 18th International Conference on Neural Information Processing (ICONIP), SPRINGER-VERLAG BERLIN, Shanghai, PEOPLES R CHINA, pp. 701-+.

Lin, X, Zhang, Y, Zhang, W & Cheema, MA 2011, 'Stochastic Skyline Operator', 2011 IEEE 27th International Conference on Data Engineering, IEEE International Conference on Data Engineering, IEEE, Hannover, Germany, pp. 721-732.
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In many applications involving the multiple criteria optimal decision making, users may often want to make a personal trade-off among all optimal solutions. As a key feature, the skyline in a multi-dimensional 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 mater how their preferences vary. Driven by many 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 paper we propose a novel skyline operator, namely stochastic skyline. In the light of the expected utility principle, stochastic skyline guarantees to provide the minimum set of candidates for the optimal solutions over all possible monotonic multiplicative utility functions. In contrast to the conventional skyline or the probabilistic skyline computation, we show that the problem of stochastic skyline is NP-complete with respect to the dimensionality.

Lin, Y-P, Chen, J-H, Duann, J-R, Lin, C-T & Jung, T-P 2011, 'Generalizations of the subject-independent feature set for music-induced emotion recognition.', 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, Boston, Massachusetts, USA, pp. 6092-6095.
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Electroencephalogram (EEG)-based emotion recognition has been an intensely growing field. Yet, how to achieve acceptable accuracy on a practical system with as fewer electrodes as possible is less concerned. This study evaluates a set of subject-independent features, based on differential power asymmetry of symmetric electrode pairs [1], with emphasis on its applicability to subject variability in music-induced emotion classification problem. Results of this study have evidently validated the feasibility of using subject-independent EEG features to classify four emotional states with acceptable accuracy in second-scale temporal resolution. These features could be generalized across subjects to detect emotion induced by music excerpts not limited to the music database that was used to derive the emotion-specific features.

Lister, RF 2011, 'Concrete and Other Neo-Piagetian Forms of Reasoning in the Novice Programmer', Thirteenth Australasian Computing Education Conference, Australasian Computing Education Conference, Australian Computer Society, Perth, Australia, pp. 9-18.
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Abstract This paper brings together a number of empirical research results on novice programmers, using a neo-Piagetian theoretical framework. While there already exists literature connecting programming with classical Piagetian theory, in this paper we apply neo-Piagetian theory. Using that neo-Piagetian perspective, we offer an explanation as to why attempts to predict ability for programming via classical Piagetian tests have yielded mixed results. We offer a neo-Piagetian explanation of some of the previously puzzling observations about novice programmers, such as why many of them make little use of diagrams, and why they often manifest a non-systematic approach to writing programs. We also develop the relatively unexplored relationship between concrete operational reasoning and programming, by exploring concepts such as conservation and reversibility.

McGregor, C 2011, 'A cloud computing framework for real-time rural and remote service of critical care', Proceedings - IEEE Symposium on Computer-Based Medical Systems.
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Critical care patients in rural, remote and some urban healthcare facilities do not have the same level of access to intensivist specialist support as patients in higher care level urban critical care units (CCUs). New clinical research is also demonstrating that computationally intensive analysis of physiological data streams in near real-time has the potential to detect the onset of certain conditions earlier. The provision of clinical decision support tools, in a cost effective way to all CCUs has the potential to reduce mortality and morbidity rates, reduce critical care patient transportation between CCUs and in so doing reduce healthcare costs. This research presents Artemis Cloud, a cloud computing based Software-asa-Service and Data-as-a-Service approach for the provision of remote real-time patient monitoring and support for clinical research. This research is demonstrated using a neonatal intensive care unit case study supporting clinical research for earlier onset detection of late onset neonatal sepsis. © 2011 IEEE.

McGregor, C, Catley, C & James, A 2011, 'A process mining driven framework for clinical guideline improvement in critical care', CEUR Workshop Proceedings.
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This paper presents a framework for process mining in critical care. The framework uses the CRISP-DM model, extended to incorporate temporal and multidimensional aspects (CRISP-TDM n ), combined with the Patient Journey Modeling Architecture (PaJMa), to provide a structured approach to knowledge discovery of new condition onset pathophysiologies in physiological data streams. The approach is based on temporal abstraction and mining of physiological data streams to develop process flow mappings that can be used to update patient journeys; instantiated in critical care within clinical practice guidelines. We demonstrate the framework within the neonatal intensive care setting, where we are performing clinical research in relation to pathophysiology within physiological streams of patients diagnosed with late onset neonatal sepsis. We present an instantiation of the framework for late onset neonatal sepsis, using CRISP-TDM n for the process mining model and PaJMa for the knowledge representation.

Mcgregor, C, Catley, C, James, A & Padbury, J 2011, 'Next Generation Neonatal Health Informatics with Artemis', USER CENTRED NETWORKED HEALTH CARE, 23 rd Conference of the European Federation of Medical Informatics (MIE), IOS PRESS, Forum Databehandling Helsesektoren, Oslo, NORWAY, pp. 115-119.
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Mearns, HK, Leaney, JR, Parakhine, A, Debenham, JK & Verchere, DG 2011, 'An autonomic open marketplace for service management and resilience', Proceedings for the Conference on Network & service Management (CNSM 2011), International Conference on Network and Service Management, IEEE, Paris, France, pp. 1-5.
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Expansion in telecommunications services, such as triple play and unified communications, introduces complexity that adversely affects service and network provisioning, especially in terms of provisioning times and the risk of delivery (failure) of new services. We envision a marketplace in which all manner of complex services will be provisioned, and their performance managed, especially against poor performance. The first phase of our work is a focus on the architecture, negotiation and management, which will lead to effective specification of network management requirements. We are working towards a bundled service agent architecture, which can negotiate on an open single service market, and which will eventually help to optimise the utilisation of the providers networks while reducing the risk of failure to users. Our work to date has been on the specification, behaviour, service definition and simulation of service agents for bundled service delivery.

Nguyen, Q, Gleeson, A, Ho, N, Huang, M, Simoff, SJ & Catchpoole, DR 2011, 'Visual Analytics of Clinical and Genetic Datasets of Acute Lymphoblastic Leukaemia', Lecture Notes in Computer Science (LNCS) 7062, International Conference on Neural Information Processing, Springer, Shanghai, China, pp. 113-120.
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This paper presents a novel visual analytics method that incorporates knowledge from the analysis domain so that it can extract knowledge from complex genetic and clinical data and then visualizing them in a meaningful and interpretable way. The domain experts that are both contributors to formulating the requirements for the design of the system and the actual user of the system include microbiologists, biostatisticians, clinicians and computational biologists. A comprehensive prototype has been developed to support the visual analytics process. The system consists of multiple components enabling the complete analysis process, including data mining, interactive visualization, analytical views, gene comparison. A visual highlighting method is also implemented to support the decision making process. The paper demonstrates its effectiveness on a case study of childhood cancer patients.

Nizami, S, Green, JR & McGregor, C 2011, 'Service oriented architecture to support real-time implementation of artifact detection in critical care monitoring.', Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference, pp. 4925-4928.
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The quality of automated real-time critical care monitoring is impacted by the degree of signal artifact present in clinical data. This is further complicated when different clinical rules applied for disease detection require source data at different frequencies and different signal quality. This paper proposes a novel multidimensional framework based on service oriented architecture to support real-time implementation of clinical artifact detection in critical care settings. The framework is instantiated through a Neonatal Intensive Care case study which assesses signal quality of physiological data streams prior to detection of late-onset neonatal sepsis. In this case study requirements and provisions of artifact and clinical event detection are determined for real-time clinical implementation, which forms the second important contribution of this paper.

Novianto, R & Williams, M 2011, 'Innate and Learned Emotion Network', Proceedings of the Second Annual Meeting of the BICA Society - Biologically Inspired Cognitive Architectures 2011 - Frontiers in Artificial Intelligence and Applications vol 233, Biologically Inspired Cognitive Architectures, IOS Press, Arlington, USA, pp. 263-268.
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Autonomous agents sometimes can only rely on the subjective information in terms of emotions to make decision due to the inavailability of the non-subjective knowledge. However, current emotion models lack of integrating innate emotion and learned emotion and tend to focus on a specific aspect. This paper describes the underlying new computational emotion model in ASMO which integrates both innate and learned emotions as well as reasoning based on probabilistic causal network. ASMO's emotion model is compared with other models and related works and shows its practical capabilities to utilize subjective knowledge in decision making.

Oberst, S & Lai, JCS 2011, 'Nonlinear friction coupling in disc brake squeal', 18th International Congress on Sound and Vibration 2011, ICSV 2011, International Congress on Sound and Vibration, International Institute of Acoustics & Vibration, Rio de Janeiro, Brazil, pp. 1748-1755.
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Friction-induced noise, such as disc brake squeal as a research area of practical importance to the automotive industry, has been investigated for many years. In recent years research focus was on dynamic instabilities such as mode coupling as the most prominent squeal mechanism, rather than on physical or geometric instabilities as trigger mechanisms. However, many trigger mechanisms such as contact and friction nonlinearity are still poorly understood. In brake squeal analysis, pad-dynamics is poorly understood and in-plane radial and out-of-plane pad vibrations are often neglected as most research has been directed towards understanding the dynamics of the rotor as the main structure radiating sound. However, recent research has shown that transient radial in-plane vibrations of the pad might be a novel squeal mechanism. In this study, the transient nature of these radial in-plane vibrations and their influence on the overall vibration and dynamic behaviour is investigated. For this purpose a sinusoidally driven in-plane sliding of a friction-coupled 2-dof oscillator (in the form of a slider over a moving belt) is formulated based on the most stable configuration of a 1-dof dry friction oscillator with continuous/ locking contact using a friction law with constant/static-kinetic/velocitydependent friction coefficient. It is found that due to nonlinear friction-coupling, steady-state in-plane radial vibrations induce a broadband spectrum in the overall dynamics of the friction oscillator with slightly fractal POINCARE section for a small belt's angle. The results indicate the importance of in-plane pad-vibrations as a possible trigger squeal mechanism. Copyright © (2011) by the International Institute of Acoustics & Vibration.

Palantei, E, Andani, A, Baharuddin, M, Nauman, NK, Syarif, S, Anshar, M, Mokobombang, NNA, Suyuti, A, Muslimin, Z, Zainuddin, Z, Indrabayu, A, Mayasari, F, Salam, AEU, Kanata, S, Hasanuddin, ZB, Emakarim, LR, Zain, N & Mariani, D 2011, 'Internal Antennas for Digital TV Receiver', 2011 IEEE INTERNATIONAL SYMPOSIUM ON ANTENNAS AND PROPAGATION (APSURSI), IEEE International Symposium on Antennas and Propagation (APSURSI)/USNC/URSI National Radio Science Meeting, IEEE, Spokane, WA, pp. 817-820.

Pang, LX, Chawla, S, Liu, W & Zheng, Y 2011, 'On mining anomalous patterns in road traffic streams', Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pp. 237-251.
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Large number of taxicabs in major metropolitan cities are now equipped with a GPS device. Since taxis are on the road nearly twenty four hours a day (with drivers changing shifts), they can now act as reliable sensors to monitor the behavior of traffic. In this paper we use GPS data from taxis to monitor the emergence of unexpected behavior in the Beijing metropolitan area. We adapt likelihood ratio tests (LRT) which have previously been mostly used in epidemiological studies to describe traffic patterns. To the best of our knowledge the use of LRT in traffic domain is not only novel but results in very accurate and rapid detection of anomalous behavior. © 2011 Springer-Verlag.

Papapetrou, O & Chen, L 2011, 'XStreamCluster: an Efficient Algorithm for Streaming XML Data Clustering', Lecture Notes in Computer Science: Database Systems for Advanced Applications 16th International Conference, DASFAA 2011, Database Systems for Advanced Applications, Springer, Hongkong, China, pp. 496-510.
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XML clustering finds many applications, ranging from storage to query processing. However, existing clustering algorithms focus on static XML collections, whereas modern information systems frequently deal with streaming XML data that needs to be processed online. Streaming XML clustering is a challenging task because of the high computational and space efficiency requirements implicated for online approaches. In this paper we propose XStreamCluster, which addresses the two challenges using a two-layered optimization. The bottom layer employs Bloom filters to encode the XML documents, providing a space-efficient solution to memory usage. The top layer is based on Locality Sensitive Hashing and contributes to the computational efficiency. The theoretical analysis shows that the approximate solution of XStreamCluster generates similarly good clusters as the exact solution, with high probability. The experimental results demonstrate that XStreamCluster improves both memory efficiency and computational time by at least an order of magnitude without affecting clustering quality, compared to its variants and a baseline approach.

Parvin, S & Hussain, FK 2011, 'Digital signature-based secure communication in cognitive radio networks', Proceedings - 2011 International Conference on Broadband and Wireless Computing, Communication and Applications, BWCCA 2011, International Conference on Broadband and Wireless Computing, Communication and Applications (BWCCA), IEEE, Barcelona, Spain, pp. 230-235.
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Due to the rapid growth of wireless applications, Cognitive Radio (CR) has been considered as a demanding concept for improving the utilization of limited radio spectrum resources for future wireless communications and mobile computing. The unique characteristics of Cognitive Radio Networks (CRNs) make security more challenging. Since a member of Cognitive Radio Networks may join or leave the network at any time, the issue of supporting secure communication in CRNs becomes more critical than for other conventional wireless networks. This work thus proposes digital signature-based secure communication for identifying efficient primary users in CRNs. The security analysis is analyzed to guarantee that the proposed approach achieves security proof. © 2011 IEEE.

Parvin, S, Han, S, Hussain, F & Tian, B 2011, 'A combinational approach for trust establishment in cognitive radio networks', Proceedings of the International Conference on Complex, Intelligent and Software Intensive Systems, CISIS 2011, Computational Intelligence in Security for Information Systems, IEEE, Seoul, South Korea, pp. 227-232.
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Cognitive Radio is considered as a promising and demanding technology to examine whether a particular radio spectrum band is currently in use or not and to switch into the temporarily unoccupied spectrum band in order to improve the usage of the radio electromagnetic spectrum without creating interference to the transmissions of other users. Because of the dynamic properties of CRNs, the issue of supporting secure communication in CRNs becomes more critical than that of other conventional wireless networks. In this paper, we propose a combination of certificate-based trust with a behavior-based trust which will benefit both by representing the trust as certificates in the the predeployment trust relation and by providing a continuous behaviour-based evalution of trust. © 2011 IEEE.

Pietroni, N, Tarini, M, Sorkine, O & Zorin, D 2011, 'Global parametrization of range image sets', ACM Transactions on Graphics (TOG), ACM, pp. 149-149.

Qiao, Y, Sarma, JMN & Tang, B 2011, 'On Isomorphism Testing of Groups with Normal Hall Subgroups', 28TH INTERNATIONAL SYMPOSIUM ON THEORETICAL ASPECTS OF COMPUTER SCIENCE (STACS 2011), 28th International Symposium on Theoretical Aspects of Computer Science (SATCS), SCHLOSS DAGSTUHL, LEIBNIZ CENTER INFORMATICS, Dortmund, GERMANY, pp. 567-578.
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Raffe, WL, Zambetta, F & Li, X 2011, 'Evolving patch-based terrains for use in video games', GECCO '11 Proceedings of the 13th annual conference on Genetic and evolutionary computation, The Genetic and Evolutionary Computation Conference, ACM, Dublin, Ireland, pp. 363-370.
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Procedurally generating content for video games is gaining interest as an approach to mitigate rising development costs and meet users' expectations for a broader range of experiences. This paper explores the use of evolutionary algorithms to aid in the content generation process, especially the creation of three-dimensional terrain. We outline a prototype for the generation of in-game terrain by compiling smaller height-map patches that have been extracted from sample maps. Evolutionary algorithms are applied to this generation process by using crossover and mutation to evolve the layout of the patches. This paper demonstrates the benefits of an interactive two-level parent selection mechanism as well as how to seamlessly stitch patches of terrain together. This unique patch-based terrain model enhances control over the evolution process, allowing for terrain to be refined more intuitively to meet the user's expectations. Copyright 2011 ACM.

Ramezani, F & Lu, J 2011, 'A new approach for choosing the most appropriate fuzzy ranking algorithm for solving MADM problems', Autonomous Systems: Developments and Trends, Workshop Autonomous Systems, Springer-Verlag Berlin / Heidelberg, Mallorca, Spain, pp. 13-24.
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There are many fuzzy ranking algorithms available to solve multi-attribute decision making (MADM) problems. Some are more suitable than others for particular decision problems. This paper proposes a new method for choosing the most appropriate fuzzy ranking algorithm for solving MADM problems based on the type and number of attributes and the number of alternatives, considering the least time consumption and the least computation for ranking alternatives. In addition, we develop a software to simulate three main fuzzy ranking algorithms: SAW, Negi, and Chen and Hwang (Chen and Hwang 1992). This software can be used in any MADM decision support system.

Ramezani, F, Memariani, A & Lu, J 2011, 'A Dynamic Fuzzy Multi-Criteria Group Decision Support System for Manager Selection', Practical Applications of Intelligent Systems, International Conference on Intelligent Systems and Knowledge Engineering, Springer-Verlag Berlin / Heidelberg, Shanghai, China, pp. 265-274.
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In any organization, because of the importance of management responsibility and its effect on efficiency improvement, the selection of the appropriate person as a manager is one of the important decision making subjects. This paper proposes a new fuzzy multiple attribute-based decision support system (DSS) for choosing suitable managers 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, based on the type of attributes and the size of the problem, considering the least computation and time consumption for ranking alternatives. 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.

Rehman, ZU, Hussain, FK & Hussain, OK 2011, 'Towards multi-criteria cloud service selection', Proceedings - 2011 5th International Conference on Innovative Mobile and Internet Services in Ubiquitous Computing, IMIS 2011, International Conference on Innovative Mobile and Internet Services in Ubiquitous Computing, IEEE, Seoul, South Korea, pp. 44-48.
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Cloud computing despite being in an early stage of adoption is becoming a popular choice for businesses to replace in-house IT infrastructure due to its technological advantages such as elastic computing and cost benefits resulting from pay-as-you-go pricing and economy of scale. These factors have led to a rapid increase in both the number of cloud vendors and services on offer. Given that cloud services could be characterized using multiple criteria (cost, pricing policy, performance etc.) it is important to have a methodology for selecting cloud services based on multiple criteria. Additionally, the end user requirements might map to different criteria of the cloud services. This diversity in services and the number of available options have complicated the process of service and vendor selection for prospective cloud users and there is a need for a comprehensive methodology for cloud service selection. The existing research literature in cloud service selection is mostly concerned with comparison between similar services based on cost or performance benchmarks. In this paper we discuss and formalize the issue of cloud service selection in general and propose a multi-criteria cloud service selection methodology. © 2011 IEEE.

Rudduck, SG, Williams, M & Stoianoff, NP 2011, 'Visualizing the Shape of Quality: An application in the context of Intellectual Property', SHAPES 1.0 The Shape Of Things 2011, Proceedings of the First Interdisciplinary Workshop on SHAPES, Interdisciplinary Workshop on SHAPES, CUER Wokshop Proceeedings, Karlsruhe, Germany, pp. 1-10.
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The aim of this work is to explore how the concept of shape can be applied in the context of Intellectual Property Law (IPL). Despite the global nature of IPL, the system is plagued with considerable uncertainty, especially in the specific instrument of patents. We believe the shape concept can find a balance between the inventive ideas, patent claims and objects in the world. The outcomes of this can then be measured as a time-dependent expectancy that an invention will conform to legal rules when under examination by officials. Specifically, we establish an empirical-based benchmark which can be utilized to test whether shape (via visual figures) is useful in reducing the uncertainty (measured via number of examination actions) which an applicant might face in patenting technological ideas.

Santosa, H, Milton, J & Kennedy, PJ 2011, 'HMXT-GP: an information-theoretic approach to genetic programming that maintains diversity', SAC 2011: Proceedings of the 26th Annual ACM Symposium on Applied Computing 2011, ACM Symposium on Applied Computing, Association for Computing Machinery, Taichung, Taiwan, pp. 1070-1075.
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This paper applies a recent informationtheoretic approach to controlling Genetic Algorithms (GAs) called HMXT to treebased Genetic Programming (GP). HMXT, in a GA domain, requires the setting of selection thresholds in a population and the application of high levels of crossover to thoroughly mix alleles. Applying these in a treebased GP setting is not trivial. We present results comparing HMXT GP to Kozastyle GP for varying amounts of crossover and over three different optimisation (minimisation) problems. Results show that average fitness is better with HMXTGP because it maintains more diversity in populations, but that the minimum fitness found was better with Koza. HMXT allows straightforward tuning of population diversity and selection pressure by altering the position of the selection thresholds.

Scifleet, P & Williams, SP 2011, 'Constructing digital documents: Emerging themes in documentary practice', Proceedings of the Annual Hawaii International Conference on System Sciences.
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The encoding of digital documents using markup languages provides organisations with a means of improving digital information management by making digital content more accessible, more comprehensible and more shareable than has previously been possible. Whilst these benefits of document encoding are widely acknowledged, very little is known about the management of document encoding projects or the information design practice that is taking place. Using practice theory as a theoretical framework, we investigate markup language usage with the aim of understanding the ways that practitioners are engaging in this documentary practice. In this paper we identify the key themes coming forward from a study of markup language use and discuss the implications for framing and understanding digital document design. © 2011 Crown Copyright.

Scifleet, P & Williams, SP 2011, 'Understanding Documentary Practice: Lessons Learnt from the Text Encoding Initiative', RESEARCH AND ADVANCED TECHNOLOGY FOR DIGITAL LIBRARIES, TPDL 2011, 15th International Conference on Theory and Practice of Digital Libraries (TPDL 2011), SPRINGER-VERLAG BERLIN, Berlin, GERMANY, pp. 272-+.

Sheard, J, Simon, S, Carbone, A, Chinn, D, Laakso, M, Clear, T, de Raadt, M, Dâ¿¿Souza, D, Harland, J, Lister, RF, Philpott, A & Warburton, G 2011, 'Exploring programming assessment instruments: a classification scheme for examination questions', Proceedings of the ACM SIGCSE 2011 International Computing Education Research Workshop, INTERNATIONAL COMPUTING EDUCATION RESEARCH WORKSHOP, Association of Computing Machinery, Providence, Rhode Island, USA, pp. 33-38.
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This paper describes the development of a classification scheme that can be used to investigate the characteristics of introductory programming examinations. We describe the process of developing the scheme, explain its categories, and present a taste of the results of a pilot analysis of a set of CS1 exam papers. 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.

Smith, A, Reitsma, L, van den Hoven, E, Kotze, P & Coetzee, L 2011, 'Towards Preserving Indigenous Oral Stories Using Tangible Objects', Proceedings of Culture and Computing 2011, IEEE International Conference on Culture and Computing, IEEE Computer Society, Kyoto, Japan, pp. 86-91.
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Handcrafted beadwork produced by the BaNtwane people of South Africa is loaded with meaning. Communicating indigenous oral stories is important for passing on culture-specific traditions and community memory, such as the meaning of the handcrafted beadwork. Oral stories are told within the physical confines of the community. The community we focus on in this paper suffers from younger generations moving away physically, start preferring the English language over their mother tongue and digital over oral communication, and therefore this co-located storytelling process is interrupted. As part of the StoryBeads project we have created an interactive system that incorporates a combination of physical objects and modern technology for recording and replaying oral stories that can help preserve the meaning of the handcrafted beadwork of the BaNtwane people.

Speelpenning, T, Antle, A, Doering, T & van den Hoven, E 2011, 'Exploring How Tangible Tools Enable Collaboration in a Multi-Touch Tabletop Game', Proceedings of the 13th IFIP TC 13 international conference on Human-computer interaction, IFIP TC13 Conference on Human-Computer Interaction, Springer, Lisbon, Portugal, pp. 605-621.
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Digital tabletop surfaces afford multiple user interaction and collaboration. Hybrid tabletops that include both tangible and multi-touch elements are increasingly being deployed in public settings (e.g. Microsoft Surface, reacTable). Designers need to understand how the different characteristics of tangible and multi-touch interface elements affect collaborative activity on tabletops. In this paper, we report on a mixed methods exploratory study of a collaborative tabletop game about sustainable development. We explore the effects of tangible and multi-touch tools on collaborative activity. Forty-five participants, in trios, played the game using both versions of the tools. Our analysis includes quantitative performance measures, qualitative themes and behavioral measures. Findings suggest that both tangible and multi-touch tools enabled effective tool use and that collaborative activity was more influenced by group dynamics than tool modality. However, we observed that the physicality of the tangible tools facilitated individual ownership and announcement of tool use, which in turn supported group and tool awareness.

Sui, Y, Ye, S, Xue, J & Yew, PC 2011, 'SPAS: Scalable path-sensitive pointer analysis on full-sparse SSA', Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pp. 155-171.
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We present a new SPAS (Scalable PAth-Sensitive) framework for resolving points-to sets in C programs that exploits recent advances in pointer analysis. SPAS enables intraprocedural path-sensitivity to be obtained in flow-sensitive and context-sensitive (FSCS) techniques scalably, by using BDDs to manipulate program paths and by performing pointer analysis level-by-level on a full-sparse SSA representation similarly as the state-of-the-art LevPA (the FSCS version of SPAS). Compared with LevPA using all 27 C benchmarks in SPEC CPU2000 and CPU2006, SPAS incurs 18.42% increase in analysis time and 10.97% increase in memory usage on average, while guaranteeing that all points-to sets are obtained with non-decreasing precision. © 2011 Springer-Verlag.

Talaei-Khoei, A, Ray, P, Parameswaran, N & Beydoun, G 2011, 'Modeling awareness of agents using policies', Proceedings of the 6th International Conference on Software and Data Technologies, International Conference on Software and Data Technologies, SciTePress, Seville, Spain, pp. 353-358.
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In addition to cooperation, research in disaster management exposes the need for policy awareness to recognize relevant information in enhancing cooperation. Intelligent software agents have previously been employed for problem solving in disaster situations but without incorporating how the agents can create or model awareness. This paper presents an awareness based modelling method, called MAAP, to maintain awareness of software agents of a given set of policies. The paper presents preliminary results indicating that the use of policies as a source of awareness, as facilitated by MAAP, is a potentially effective method to enhance cooperation.

Talaei-Khoei, A, Ray, PK & Parameshwaran, N 2011, 'Policy-Based Awareness: Implications in Rehabilitation Video Games', 2011 44th Hawaii International Conference on System Sciences, Hawaii International Conference on System Sciences, IEEE, Kauai, USA, pp. 1-10.
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Interactive video games are being used increasingly to transform the dull and repetitive nature of rehabilitation exercises into an enjoyable play by moving limbs or whole body. One major benefit of using video games in rehabilitation is the possibility of home-based treatments. Video games open up new options for occupation therapists to remotely supervise the compliance of patients with their rehabilitation therapy while monitoring changes in patients' functions over a period. For this to happen efficiently, in this paper we propose that some routine activities of occupational therapists be partially incorporated into software agents. These agents should recognize the relevance of patient's problems to their exercise tasks based on their awareness about patients' conditions. We present a 3-step process, called Required Awareness of Agents based on Policies (RAAP), to create awareness about policies in agents where policies are obtained from the domain of rehabilitation treatment, and demonstrate that the actions of such agents are always policy compliant.

Tan, C & Johnston, AJ 2011, 'Towards a Non-Disruptive, Practical and Objective Automated Playtesting Process', Proceedings of The Artificial Intelligence and Interactive Digital Entertainment Conference - Workshops at the Seventh Artificial Intelligence and Interactive Digital Entertainment Conference, Artificial Intelligence in the Game Design Process, AAAI Press, Stanford, USA, pp. 25-28.
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Playtesting is the primary process that allows a game designer to access game quality. Current playtesting methods are often intrusive to play, involves much manual labor, and might not even portray the player's true feedback. This paper aims to alleviate these shortcomings by presenting the position that state of the art artificial intelligence techniques can construct automated playtesting systems that supplement or even substitute this process to a certain extent. Several potential research directions are proposed in this theme. A work-inprogress report is also included to demonstrate the conceptual feasibility of the potentials of this research area.

Tao, D, Li, Z, Li, J, Katsaggelos, A, Bian, W, Chen, Y, Fan, J, Hu, Y, Izquierdo, E, Ji, S, Jiang, X, Kwok, J, Li, Q, Liu, J, Loog, M, Lu, H, Lu, YL, Maybank, SJ, Pau, D, Ro, YM, Shan, C, Shao, L, Smeraldi, F, Song, Y, Wang, F, Xu, Y, Yang, L, Ye, J, Yu, J, Zhang, D, Zhang, J, Zhao, X, Huang, K, Ying, Y & Zhou, C 2011, 'Preface', Proceedings - IEEE International Conference on Data Mining, ICDM.
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Tarini, M, Puppo, E, Panozzo, D, Pietroni, N & Cignoni, P 2011, 'Simple quad domains for field aligned mesh parametrization', ACM Transactions on Graphics (TOG), ACM, pp. 142-142.

Thapngam, T, Yu, S, Zhou, W & Beliakov, G 2011, 'Discriminating DDoS attack traffic from flash crowd through packet arrival patterns', 2011 IEEE Conference on Computer Communications Workshops, INFOCOM WKSHPS 2011, pp. 952-957.
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Current DDoS attacks are carried out by attack tools, worms and botnets using different packet-transmission strategies and various forms of attack packets to beat defense systems. These problems lead to defense systems requiring various detection methods in order to identify attacks. Moreover, DDoS attacks can mix their traffics during flash crowds. By doing this, the complex defense system cannot detect the attack traffic in time. In this paper, we propose a behavior based detection that can discriminate DDoS attack traffic from traffic generated by real users. By using Pearson's correlation coefficient, our comparable detection methods can extract the repeatable features of the packet arrivals. The extensive simulations were tested for the accuracy of detection. We then performed experiments with several datasets and our results affirm that the proposed method can differentiate traffic of an attack source from legitimate traffic with a quick response. We also discuss approaches to improve our proposed methods at the conclusion of this paper. © 2011 IEEE.

Tseng, HC, Shyu, JJ, Chang, JY & Lin, CT 2011, 'Exploiting automatic image segmentation to human detection and depth estimation', IEEE SSCI 2011 - Symposium Series on Computational Intelligence - CIMSIVP 2011: 2011 IEEE Symposium on Computational Intelligence for Multimedia, Signal and Vision Processing, IEEE Symposium on Computational intelligence for Multimedia Signal and Vision Processing, IEEE, Paris, France, pp. 19-25.
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In this paper, we combine image segmentation techniques and face detection methods to extract the human from scenes. Firstly, skin regions are detected and an ellipse fitting method is employed to detect the face region and consequently locate the human position. Then we propose an improved automatic seeded region growing algorithm to segment the image. The initial seeds are generated automatically, and the remaining pixels are classified to the nearest region. After the region growing procedure, two neighboring regions with high similarity are merged. The human body is determined by confining semantic human body region in segmented regions, and those belonging to the human face and human body are merged afterward. Lastly, we will detect the human vertical y-coordinate values in the image, and the depths can then be estimated according to the depth look-up tables of the camera. © 2011 IEEE.

Vamplew, P, Stranieri, A, Ong, K, Christen, P & Kennedy, PJ 2011, 'Data Mining and Analytics 2011 (AusDM'11)', Proceedings of the Ninth Australasian Data Mining Conference (AusDM'11), Ninth Australasian Data Mining Conference, Australian Computer Society, Ballarat, Australia, pp. i-229.
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We are delighted to welcome you to the Ninth Australasian Data Mining Conference (AusDM'11) being held this year in Ballarat, Victoria. AusDM started in 2002 and is now the annual flagship meeting for data mining and analytics professionals in Australia. Both scholars and practitioners present the state-of-the-art in the field. Endorsed by the peak professional body, the Institute of Analytics Professionals of Australia, AusDM has developed a unique profile in nurturing this joint community. The conference series has grown in size each year from early events held in Canberra (2002, 2003), Cairns (2004), Sydney (2005, 2006), the Gold Coast (2007), Glenelg (2008) and Melbourne (2009).

van Erve, D, Vos, G, van den Hoven, E & Frohlich, D 2011, 'Cueing the Past: Designing Embodied Interaction for Everyday Remembering', Proceedings of the Second International Conference on Creativity and Innovation in Design, Desire Conference: Creativity and Innovation in Design, ACM, Eindhoven, The Netherlands, pp. 335-345.
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Embodied interaction describes how meaning in interaction is created through engagement. With this approach as a source of inspiration for three exploratory design cases this paper explores the possibilities of embodied interaction in storing, retrieving and enriching everyday memories. Following the principles of designing for embodiment, all three design cases aim at cueing memories through visual modalities like photo and video. We discuss these case studies in light of the embodied interaction and memory theory. Our findings indicate that everyday remembering may be a suitable application area for combining it with embodied interaction, because of its abstract and personal nature.

Van, A, Gay, VC, Kennedy, PJ, Barin, E & Leijdekkers, P 2011, 'Understanding risk factors in cardiac rehabilitation patients with random forests and decision trees', Proceedings of the Ninth Australasian Data Mining Conference (AusDM'11), Australian Data Mining Conference, Australian Computer Society, Ballarat, Australia, pp. 11-22.
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Vu, H, Liu, S, Li, Z & Li, G 2011, 'Microphone Identification using One Class-Classification Approach', The 2nd Workshop on Applications and Techniques in Information Security, International Conference on Applications and Techniques in Information Security (ATIS), Melbourne, Australia, pp. 30-37.
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Rapid growth of technical developments has created huge challenges for microphone forensics -a sub-category of audio forensic science, because of the avail-ability 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 inves-tigation 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. Research 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.

Wang, X & Williams, MA 2011, 'Risk, uncertainty and possible worlds', Proceedings - 2011 IEEE International Conference on Privacy, Security, Risk and Trust and IEEE International Conference on Social Computing, PASSAT/SocialCom 2011, ASE/IEEE International Conference on Social Computing (SocialCom), IEEE, Boston, MA, USA, pp. 1278-1283.
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Risk is an important and ubiquitous concept that plays a crucial role in decision makings across domains. Risk is also a vague notion that carries different meaning under different domain context and perspectives. This paper aims to provide a formal generalised definition of risk based on the possible world paradigm and expected utility theory and the meanings of risk from both qualitative and quantitative level. This definition of risk is developed from the perspective an intelligent agent or information system. It provides a solid theoretical foundation upon which we can construct an intelligent generalised risk modelling and management framework using techniques from Artificial Intelligence research. This framework can be implemented as an integral part of an information system for better decision support and management of businesses. © 2011 IEEE.

Wang, X, Wang, Z & Xu, X 2011, 'Price heuristics for highly efficient profit optimization of service composition', Proceedings - 2011 IEEE International Conference on Services Computing, SCC 2011, pp. 378-385.
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Service composition follows a three-party paradigm, i.e., a broker mediates between service providers and service consumers to properly select and compose a set of distributed services together so that requirements raised by consumers are satisfied by the composite service on demand. As the de facto provider of composite services, the broker charges the consumers; on the other hand, it awards cost to the providers whose services are involved in the composite services. Besides traditional quality-oriented optimization from the consumers' point of view, the profit that a broker could earn from the composition is another objective to be optimized. But just as the quality optimization, service selection for profit optimization suffers from dramatic efficiency decline along with the growth in the number of candidate services. On the premise that the expected quality are guaranteed, this paper presents a "divide and select" approach for high-efficiency profit optimization, with price as heuristics. This approach can be applied to both static and dynamic pricing scenarios of service composition. Experiments demonstrate the feasibility. © 2011 IEEE.

Wang, X, Wang, Z & Xu, X 2011, 'Semi-empirical service composition: A clustering based approach', Proceedings - 2011 IEEE 9th International Conference on Web Services, ICWS 2011, pp. 219-226.
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Service composition has the capability of constructing coarse-grained solutions by dynamically aggregating a set of services to satisfy complex requirements, but it suffers from dramatic decrease on the efficiency of determining the best composition solution when large scale candidate services are available. Most current approaches look for the optimal composition solution by real-time computation, and the composition efficiency greatly depends on the adopted algorithms. To eliminate such deficiency, this paper proposes a semi-empirical composition approach which incorporates two stages, i.e., periodical clustering and real-time composition. The former partitions the candidate services and historical requirements into clusters based on similarity measurement, and then the probabilistic correspondences between service clusters and requirement clusters are identified by statistical analysis. The latter deals with a new requirement by firstly finding its most similar requirement cluster and the corresponding service clusters by leveraging Bayesian inference, then a set of concrete services are optimally selected from such reduced solution space and constitute the final composition solution. Instead of relying on solely historical data exploration or on pure real-time computation, our approach distinguishes from traditional methods by combining the two perspectives together. Experiments demonstrate the advantages of this approach. © 2011 IEEE.

Wang, Y, Wen, S, Zhou, W, Zhou, W & Xiang, Y 2011, 'The probability model of peer-to-peer botnet propagation', Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pp. 470-480.
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Active Peer-to-Peer worms are great threat to the network security since they can propagate in automated ways and flood the Internet within a very short duration. Modeling a propagation process can help us to devise effective strategies against a worm's spread. This paper presents a study on modeling a worm's propagation probability in a P2P overlay network and proposes an optimized patch strategy for defenders. Firstly, we present a probability matrix model to construct the propagation of P2P worms. Our model involves three indispensible aspects for propagation: infected state, vulnerability distribution and patch strategy. Based on a fully connected graph, our comprehensive model is highly suited for real world cases like Code Red II. Finally, by inspecting the propagation procedure, we propose four basic tactics for defense of P2P botnets. The rationale is exposed by our simulated experiments and the results show these tactics are of effective and have considerable worth in being applied in real-world networks © 2011 Springer-Verlag.

Wei, CS, Chuang, SW, Wang, WR, Ko, LW, Jung, TP & Lin, CT 2011, 'Implementation of a motion sickness evaluation system based on EEG spectrum analysis', Proceedings - IEEE International Symposium on Circuits and Systems 2011, International Symposium on Circuits and Systems Nano-Bio Circuit Fabrics and Systems (ISCAS), Institute of Electrical and Electronics Engineers, Rio de Janeiro, Brazil, pp. 1081-1084.
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Motion sickness is a normal response to real, perceived, or even anticipated movement. People tend to get motion sickness on a moving boat, train, airplane, car, or amusement park rides. Motion sickness occurs when the body, the inner ear, and the eyes send conflicting signals to the brain. Sensory conflict theory that came about in the 1970's has become the most widely accepted theorem of motion-sickness among scientists [1]. The theory proposed that the conflict between the incoming sensory inputs could induce motion-sickness. However, some new research studies have appeared to tackle the issue of the vestibular function in central nervous system (CNS). In the previous human subject studies, researchers attempt to confirm the brain areas involved in the conflict in multi-modal sensory systems by means of clinical or anatomical methods. Our past studies had investigated the EEG activities correlated with motion sickness in a virtual-reality based driving simulator. We found that the parietal, motor, occipital brain regions exhibited significant EEG power changes in response to vestibular and visual stimuli. Based on these experimental results, we attempt to implement an EEG-based evaluation system to estimate subject's motion sickness level upon the major EEG power spectra from these motion sickness related brain area in this study. The evaluation system can be applied to early detect the subject's motion sickness level and prevent the uncomfortable syndromes occurred in advance in our daily life. © 2011 IEEE.

Wei, CS, Ko, LW, Chuang, SW, Jung, TP & Lin, CT 2011, 'EEG-based evaluation system for motion sickness estimation', 2011 5th International IEEE/EMBS Conference on Neural Engineering, NER 2011, International IEEE Engineering-in-Medicine-and-Biology-Society (EMBS) Conference on Neural Engineering (NER), IEEE, Cancun, Mexico, pp. 100-103.
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Motion sickness is a common symptom which occurs when the brain receives conflicting sensory information. Although many motion sickness-related biomarkers have been identified, estimating humans' motion sickness level (MSL) remains a challenge in operational environments. Traditionally, questionnaire and physical check are the common ways to passively evaluate subject's sickness level. This study proposes a physiology-based estimation system that can automatically assess subject's motion-sickness level in operational environments. Our previous study showed that increases in self-reported MSL in a Virtual-reality based driving experiment on a motion platform were accompanied by elevated alpha (8-12Hz) power most prominently in the occipital midline electroencephalogram (EEG). This study explores the feasibility of an automatic MSL estimation based on spontaneous EEG spectrum. To this end, this study employed three different estimators: 1) Linear regression (LR), 2) Radial basis function neural network (RBFNN), and 3) Support vector regression (SVR). The results of this study showed that SVR outperformed LR and RBFNN in estimating MSL from EEG spectrum. The averaged accuracy of MSL estimation by SVR was 86.926.09% across 6 subjects. This demonstration could lead to a practical system for noninvasive monitoring of the motion sickness in real-world environments. © 2011 IEEE.

Wei, CS, Ko, LW, Chuang, SW, Jung, TP & Lin, CT 2011, 'Genetic feature selection in EEG-based motion sickness estimation', Proceedings of the International Joint Conference on Neural Networks, IEEE International Joint Conference on Neural Networks, IEEE, San Jose, CA, USA, pp. 365-369.
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Motion sickness is a common symptom that occurs when the brain receives conflicting information about the sensation of movement. Many motion sickness biomarkers have been identified, and electroencephalogram (EEG)-based motion sickness level estimation was found feasible in our previous study. This study employs genetic feature selection to find a subset of EEG features that can further improve estimation performance over the correlation-based method reported in the previous studies. The features selected by genetic feature selection were very different from those obtained by correlation analysis. Results of this study demonstrate that genetic feature selection is a very effective method to optimize the estimation of motion-sickness level. This demonstration could lead to a practical system for noninvasive monitoring of the motion sickness of individuals in real-world environments. © 2011 IEEE.

Wijnen, J & van den Hoven, E 2011, 'Connected Sketchbook: Linking Digital Files to Physical Pages', Proceedings of the Second International Conference on Creativity and Innovation in Design, Desire Conference: Creativity and Innovation in Design, ACM, Eindhoven, The Netherlands, pp. 43-46.
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A lot of designers carry around sketchbooks, also called design journals, to record everyday inspirations. This paper describes a concept in which digital files are connected to specific pages of such a physical sketchbook. This way initial notes, drawings or other types of recordings can be united with their digital equivalents, related files or end results (like digital drawings and presentations). Our informal user evaluation points out that indicating file types is preferred over indicating number of files, since it helps users to recollect the digital files that are related to the work described on the physical pages.

Williams, SP & Hardy, CA 2011, 'Information Management Issues and Challenges in an Enterprise 2.0 Era: Imperatives for Action', 24TH BLED ECONFERENCE: EFUTURE: CREATING SOLUTIONS FOR THE INDIVIDUAL, ORGANISATIONS AND SOCIETY, 24th Bled Conference - eFuture: Creating Solutions for the Individual, Organisations and Society, UNIV MARIBOR, Bled, SLOVENIA, pp. 56-67.

Williams, SP & Schubert, P 2011, 'An Empirical Study of Enterprise 2.0 in Context', 24TH BLED ECONFERENCE: EFUTURE: CREATING SOLUTIONS FOR THE INDIVIDUAL, ORGANISATIONS AND SOCIETY, 24th Bled Conference - eFuture: Creating Solutions for the Individual, Organisations and Society, UNIV MARIBOR, Bled, SLOVENIA, pp. 42-55.

Wu, D & Zhang, G 2011, 'Fuzzy Similarity Measure Model for Trees with Duplicated Attributes', Nonlinear Mathematics for Uncertainty and Its Applications, International Conference on Nonlinear Mathematics for Uncertainty and Its Applications, Springer-Verlag Berlin Heidelberg, Beijing, China, pp. 333-340.
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In many business situations, complex user profiles are described by tree structures, and evaluating the similarity between these trees is essential in many applications, such as recommender systems. This paper proposes a fuzzy similarity measure model for trees with duplicated attributes. In this model, the conceptual similarity between attributes and the weights of nodes are expressed by linguistic terms. To deal with duplicated attributes in the trees, nodes with the same concept are clustered. The most conceptual corresponding cluster pairs among two trees are identified. Based on the corresponding cluster pairs, the conceptual similarity and the value similarity between two trees are evaluated, and the final similarity measure is assessed as a weighted sum of their conceptual and value similarities.

Wu, Z, Xu, G, Pan, R, Zhang, Y, Hu, Z & Lu, J 2011, 'Leveraging Wikipedia concept and category information to enhance contextual advertising', Proceedings of the 20th ACM Conference on Information and Knowledge Management, ACM International Conference on Information and Knowledge Management, ACM, Glasgow, Scotland, UK, pp. 2105-2108.
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Xie, B, Bian, W, Tao, D & Chordia, P 2011, 'Music tagging with regularized logistic regression', Proceedings of the 12th International Society for Music Information Retrieval Conference, ISMIR 2011, International Society for Music Information Retrieval Conference, University of Miami, Miami, Florida, USA, pp. 711-716.
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In this paper, we present a set of simple and efficient regularized logistic regression algorithms to predict tags of music. We first vector-quantize the delta MFCC features using k-means and construct "bag-of-words" representation for each song. We then learn the parameters of these logistic regression algorithms from the "bag-of- words" vectors and ground truth labels in the training set. At test time, the prediction confidence by the linear classifiers can be used to rank the songs for music annotation and retrieval tasks. Thanks to the convex property of the objective functions, we adopt an efficient and scalable generalized gradient method to learn the parameters, with global optimum guaranteed. And we show that these efficient algorithms achieve stateof- the-art performance in annotation and retrieval tasks evaluated on CAL-500. © 2011 International Society for Music Information Retrieval.

Xu, G, Gu, Y, Dolog, P, Zhang, Y & Kitsuregawa, M 2011, 'SemRec: A Semantic Enhancement Framework for Tag Based Recommendation.', Proceedings of the Twenty-Fifth AAAI Conference on Artificial Intelligence, AAAI Conference on Artificial Intelligence, AAAI Press, San Francisco, California, pp. 1267-1272.
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Xu, G, Gu, Y, Zhang, Y, Yang, Z & Kitsuregawa, M 2011, 'TOAST: A Topic-Oriented Tag-Based Recommender System', Web Information System Engineering WISE 2011 Lecture Notes in Computer Science, International Conference on Web Information Systems Engineering, Springer Berlin / Heidelberg, Sydney, Australia, pp. 158-171.
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Social Annotation Systems have emerged as a popular application with the advance of Web 2.0 technologies. Tags generated by users using arbitrary words to express their own opinions and perceptions on various resources provide a new intermediate dimension between users and resources, which deemed to convey the user preference information. Using clustering for topic extraction and incorporating it with the capture of user preference and resource affiliation is becoming an effective practice in tag-based recommender systems. In this paper, we aim to address these challenges via a topic graph approach. We first propose a Topic Oriented Graph (TOG), which models the user preference and resource affiliation on various topics. Based on the graph, we devise a Topic-Oriented Tag-based Recommendation System (TOAST) by using the preference propagation on the graph. We conduct experiments on two real datasets to demonstrate that our approach outperforms other state-of-the-art algorithms.

Xu, G, Lee, W, Chen, L & Chen, L 2011, 'CSN 2011: Message from the workshop co-chairs', Proceedings - IEEE 9th International Conference on Dependable, Autonomic and Secure Computing, DASC 2011.
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Xu, G, Zong, Y, Pan, R, Dolog, P & Jin, P 2014, 'On Kernel Information Propagation for Tag Clustering in Social Annotation Systems', Knowlege-Based and Intelligent Information and Engineering Systems Lecture Notes in Computer Science, International Conference on Knowledge-Based and Intelligent Information and Engineering Systems, Springer Berlin / Heidelberg, Kaiserslautern, Germany, pp. 505-514.
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In social annotation systems, users label digital resources by using tags which are freely chosen textual descriptors. Tags are used to index, annotate and retrieve resource as an additional metadata of re- source. Poor retrieval performance remains a major challenge of most social annotation systems resulting from the severe problems of ambigu- ity, redundancy and less semantic nature of tags. Clustering method is a useful approach to handle these problems in the social annotation sys- tems. In this paper, we propose a novel clustering algorithm named kernel information propagation for tag clustering. This approach makes use of the kernel density estimation of the KNN neighbor directed graph as a start to reveal the prestige rank of tags in tagging data. The random walk with restart algorithm is then employed to determine the center points of tag clusters. The main strength of the proposed approach is the capability of partitioning tags from the perspective of tag prestige rank rather than the intuitive similarity calculation itself. Experimental studies on three real world datasets demonstrate the effectiveness and superiority of the proposed method.

Yaish, HM, Goyal, ML & Feuerlicht, G 2011, 'An Elastic Multi-tenant Database Schema for Software as a Service', Dependable, Autonomic and Secure Computing, 2011 Ninth IEEE International Conference on, International Conference on Dependable, Autonomic and Secure Computing, Institute of Electrical and Electronics Engineers ( IEEE ), Sydney, Australia, pp. 737-743.
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Software as a Service (SaaS) is an online software delivery model which permits a third party provider offering software services to be used on-demand by tenants over the internet, instead of installing and maintaining them in their premises. Nowadays, more and more companies are offering their web-base business application by adopting this model. 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 customizable to meet tenantsâ expectations and business requirements. In this paper, we propose a novel customizable database design for multi-tenant applications. Our design introduces an Elastic Extension Tables (EET) which consists of Common Tenant Tables (CTT) and Virtual Extension Tables (VET). This design enables tenants to create their own elastic database schema during multi-tenant application run-time execution to satisfy their business needs.

Yu, PS, Fan, W, Nejdl, W, Chen, L, Sun, A, Simovici, D, Baralis, E, Nguifo, EM, Xu, G, Yin, J, Ceci, M, Cortez, P, Christen, P, Berka, P, Alves, R, Xu, S, Elomaa, T, Kosters, W, Graco, W, Wang, W, Balke, WT & Zhao, Y 2011, 'Preface', Proceedings - IEEE International Conference on Data Mining, ICDM.
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Zhang, J, Huang, M & Hoang, DB 2011, 'Detecting DDoS Attack in Spam Emails using Density-Weight Model', Volume II, Proceedings of 2011 IEEE International Conference on Information Theory and Information Security, IEEE International Conference on Information Theory and Information Security, IEEE Press, Hangzhou, China, pp. 344-352.
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DDoS attacks whose are embedded in spam emails are increasingly becoming numerous and sophisticated in nature. Hence this has given a growing need for spam email analysis to identify these attacks. The uses of these intrusion detection systems have given rise to two new challenges, 1) how to incrase the accuracy of detection, 2) how to present large spam email networks for better understanding. In this paper we introduce a new analytical model that uses two coefficient vectors: 'density' and 'weight' to measure the network density and system workload for the analysis of DDoS attack of spam emails. We then use a visual clustering method to classify and display the spam emails for better understanding of the spam email network. The experiment shows that the proposed new model can increase the accuracy of the detection of DDoS attacks.

Zhang, J, Lu, J & Zhang, G 2011, 'Combining one class classification models for avian influenza outbreaks', IEEE SSCI 2011 - Symposium Series on Computational Intelligence - MCDM 2011: 2011 IEEE Symposium on Computational Intelligence in Multicriteria Decision-Making, IEEE Symposium on Computational Intelligence in Multicriteria Decision-Making (MDCM), IEEE, Paris, France, pp. 190-196.
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The prediction of avian influenza outbreak animal cases is a genuine one class classification issue because the real world outliers are impractical to obtain. In this paper, a new combining one class classification method has been presented and illustrated on the avian influenza outbreak dataset. The presented combining methods outperform the previous combining methods both on the original avian influenza outbreak dataset and dimension reduction one. The new one classification combining model can be adapted to the warning surveillance purpose and proved to be practical on the avian influenza outbreak prediction tasks. © 2011 IEEE.

Zhang, J, Zhang, Y, Guo, Q, Fu, L & Huang, M 2011, 'Coaxial Interactive Viewer: A Multi-Dimensional Data Visualization with Spatial Distortional Views', Proc. of the 2011 Visual Information Communication - International Symposium (VINCI'11), Visual Information Communications International, ACM Press, Hong Kong, pp. 1-7.
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We present a navigatable multi-dimensional visualization of data named coaxial interactive visualization which is based on the coaxial axes. In this visualization, the dimensions of data in ndimensional space are mapped to n concentric circular axes drawn in a planar space with polar coordinates. A data item in ndimensional space is represented as a poly-curve with n vertices across all circular axes. Via the spatial distortion in polar system, the view of multi-dimensional data is interactively adjusted to satisfy viewers interest. The viewer, thus, can effectively navigate the underlying visual pattern to reach the great detail for uncovering trends and patterns in the visualization. One novelties of this work is performing focus+context viewing in polar coordinate system.

Zhang, L, Bian, W, Song, M, Tao, D & Liu, X 2011, 'Integrating Local Features into Discriminative Graphlets for Scene Classification', Lecture Notes in Computer Science. Neural Information Processing. 18th International Conference, ICONIP 2011, International Conference on Neural Information Processing, Springer-Verlag Berlin / Heidelberg, Shanghai, China, pp. 657-666.
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Scene classification plays an important role in multimedia information retrieval. Since local features are robust to image transformation, they have been used extensively for scene classification. However, it is difficult to encode the spatial relations of local features in the classification process. To solve this problem, Geometric Local Features Integration(GLFI) is proposed. By segmenting a scene image into a set of regions, a so-called Region Adjacency Graph(RAG) is constructed to model their spatial relations. To measure the similarity of two RAGs, we select a few discriminative templates and then use them to extract the corresponding discriminative graphlets(connected subgraphs of an RAG). These discriminative graphlets are further integrated by a boosting strategy for scene classification. Experiments on five datasets validate the effectiveness of our GLFI.

Zhang, L, Song, M, Bian, W, Tao, D, Liu, X, Bu, J & Chen, C 2011, 'Feature Relationships Hypergraph for Multimodal Recognition', Lecture Notes in Computer Science. Neural Information Processing. 18th International Conference, ICONIP 2011, International Conference on Neural Information Processing, Springer-Verlag Berlin / Heidelberg, Shanghai, China, pp. 589-598.
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Utilizing multimodal features to describe multimedia data is a natural way for accurate pattern recognition. However, how to deal with the complex relationships caused by the tremendous multimodal features and the curse of dimensionality are still two crucial challenges. To solve the two problems, a new multimodal features integration method is proposed. Firstly, a so-called Feature Relationships Hypergraph (FRH) is proposed to model the high-order correlations among the multimodal features. Then, based on FRH, the multimodal features are clustered into a set of low-dimensional partitions. And two types of matrices, the interpartition matrix and intra-partition matrix, are computed to quantify the inter- and intra- partition relationships. Finally, a multi-class boosting strategy is developed to obtain a strong classifier by combining the weak classifiers learned from the intra- partition matrices. The experimental results on different datasets validate the effectiveness of our approach

Zhang, L, Yu, S, Wu, D & Watters, P 2011, 'A survey on latest botnet attack and defense', Proc. 10th IEEE Int. Conf. on Trust, Security and Privacy in Computing and Communications, TrustCom 2011, 8th IEEE Int. Conf. on Embedded Software and Systems, ICESS 2011, 6th Int. Conf. on FCST 2011, pp. 53-60.
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A botnet is a group of compromised computers, which are remotely controlled by hackers to launch various network attacks, such as DDoS attack and information phishing. Botnet has become a popular and productive tool behind many cyber attacks. Recently, the owners of some botnets, such as storm worm, torpig and conflicker, are employing fluxing techniques to evade detection. Therefore, the understanding of their fluxing tricks is critical to the success of defending from botnet attacks. Motivated by this, we survey the latest botnet attacks and defenses in this paper. We begin with introducing the principles of fast fluxing (FF) and domain fluxing (DF), and explain how these techniques were employed by botnet owners to fly under the radar. Furthermore, we investigate the state-of-art research on fluxing detection. We also compare and evaluate those fluxing detection methods by multiple criteria. Finally, we discuss future directions on fighting against botnet based attacks. © 2011 IEEE.

Zhou, W, Chakraborty, S & Atiquzzaman, M 2011, 'EUC 2011: Message from the general chairs', Proceedings - 2011 IFIP 9th International Conference on Embedded and Ubiquitous Computing, EUC 2011.
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Zhu, K, Zhang, W, Zhu, G, Zhang, Y & Lin, X 2011, 'BMC: An Efficient Method to Evaluate Probabilistic Reachability Queries', LNCS - Database Systems for Advanced Applications - Part 1, Proceedings of the 16th International Conference on Database Systems for Advanced Applications, Database Systems for Advanced Applications, Springer, Hong Kong, pp. 434-449.
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Reachability query is a fundamental problem in graph databases. It answers whether or not there exists a path between a source vertex and a destination vertex and is widely used in various applications including road networks, social networks, world wide web and bioinformatics. In some emerging important applications, uncertainties may be inherent in the graphs. For instance, each edge in a graph could be associated with a probability to appear. In this paper, we study the reachability problem over such uncertain graphs in a threshold fashion, namely, to determine if a source vertex could reach a destination vertex with probabilty larger than a user specified probability value t. Finding reachability on uncertain graphs has been proved to be NP-Hard. We first propose novel and effective bounding techniques to obtain the upper bound of reachability probability between the source and destination. If the upper bound fails to prune the query, efficient dynamic Monte Carlo simulation technqiues will be applied to answer the probabilitistic reachability query with an accuracy guarantee. Extensive experiments over real and synthetic datasets are conducted to demonstrate the efficiency and effectiveness of our techniques.

Zong, Y, Xu, G, Jin, P, Dolog, P & Jiang, S 2011, 'A Local Information Passing Clustering Algorithm for Tagging Systems', Database Systems for Adanced Applications, Lecture Notes in Computer Science, Database Systems for Advanced Applications, Springer Berlin / Heidelberg, Hong Kong, China, pp. 333-343.
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Under social tagging systems, a typical Web2.0 application, users label digital data sources by using tags which are freely chosen textual descriptions. Tags are used to index, annotate and retrieve resource as an additional metadata of resource. Poor retrieval performance remains a major problem of most social tagging systems resulting from the severe difficulty of ambiguity, redundancy and less semantic nature of tags. Clustering method is a useful tool to increase the ability of information retrieval in the aforementioned systems. In this paper, we propose a novel clustering algorithm named LIPC (Local Information Passing Clustering algorithm). The main steps of LIPC are: (1) we estimate a KNN neighbor directed graph G of tags and calculate the kernel density of each tag in its neighborhood; (2) we generate local information, local coverage and local kernel of each tag; (3) we pass the local information on G by I and O operators until they are converged and tag priory are generated; (4) we use tag priory to find out the clusters of tags. Experimental results on two real world datasets namely MedWorm and MovieLens demonstrate the efficiency and the superiority of the proposed method.

Zong, Y, Xu, G, Jin, P, Zhang, Y, Chen, E & Pan, R 2011, 'APPECT: An Approximate Backbone-Based Clustering Algorithm for Tags', Advanced Data Mining and Applications, Lecture Notes in Computer Science, International Conference on Advanced Data Mining and Applications, Springer Berlin / Heidelberg, Beijing, China, pp. 175-189.
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In social annotation systems, users label digital resources by using tags which are freely chosen textual descriptions. Tags are used to index, anno- tate and retrieve resource as an additional metadata of resource . Poor retrieval performance remains a major problem of most social tagging systems resulting from the severe difficulty of ambiguity, redundancy and less semantic nature of tags. Clustering method is a useful tool to address the aforementioned difficul- ties. Most of the researches on tag cluste ring are directly using traditional clus- tering algorithms such as K-means or Hierarchical Agglomerative Clustering on tagging data, which possess the inherent drawbacks, such as the sensitivity of initialization. In this paper, we instead make use of the approximate backbone of tag clustering results to find out better tag clusters. In particular, we propose an APProximate backbonE-based Clustering algorithm for Tags (APPECT). The main steps of APPECT are: (1) we execute the K-means algorithm on a tag similarity matrix for M times and collect a set of tag clustering results Z={C 1 ,C 2 ,...,C m } ; (2) we form the approximate backbone of Z by executing a greedy search; (3) we fix the approximate backbone as the initial tag clustering result and then assign the rest tags into the corresponding clusters based on the similarity. Experimental results on three real world datasets namely MedWorm, MovieLens and Dmoz demonstrate the effectiveness and the superiority of the proposed method against the traditional approaches.

Johnston, B, Shuard, C, Parajuli, P & Williams, M 2011, 'UTS Song and Dance', University of Technology Sydney.

Cignoni, P, Ranzuglia, G, Callieri, M, Corsini, M, Ganovelli, F, Pietroni, N & Tarini, M 2011, 'MeshLab'.