Publications

Howlett, RJ, Gabrys, B, Musial-Gabrys, K & Roach, J 2013, Innovation through Knowledge Transfer 2012.
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Huang, ML & Huang, W 2013, Innovative Approaches of Data Visualization and Visual Analytics (Preface), IGI Global.
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Due to rapid advances in hardware and software technologies, network infrastructure and data have become increasingly complex, requiring efforts to more effectively comprehend and analyze network topologies and information systems. Innovative Approaches of Data Visualization and Visual Analytics evaluates the latest trends and developments in force-based data visualization techniques, addressing issues in the design, development, evaluation, and application of algorithms and network topologies. This book will assist professionals and researchers working in the fields of data analysis and information science, as well as students in computer science and computer engineering, in developing increasingly effective methods of knowledge creation, management, and preservation.

Hussain, O, Dillon, TS, Hussain, FK & Chang, E 2013, Risk Assessment and Management in the Networked Economy, 1, Springer, Netherlands.
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This book, authored by some of the leading researchers in the field, includes chapters that shed a new light over the domain. The book builds on the important idea that users confidence in online services will be increasingly based on a VI Foreword sound, shared notion of dynamic transactional risk, rather then on todays heuristics. Such notion, as proposed in this book, captures the fundamental aspects of occasional online transactions, including time-dependence and possible information asymmetries.

Luo, T, Chen, S, Xu, G & Zhou, J 2013, Trust-based Collective View Prediction, 1, Springer, Germany.
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Collective view prediction is to judge the opinions of an active web user based on unknown elements by referring to the collective mind of the whole community. Content-based recommendation and collaborative filtering are two mainstream collective view prediction techniques. They generate predictions by analyzing the text features of the target object or the similarity of users past behaviors. Still, these techniques are vulnerable to the artificially-injected noise data, because they are not able to judge the reliability and credibility of the information sources. Trust-based Collective View Prediction describes new approaches for tackling this problem by utilizing users trust relationships from the perspectives of fundamental theory, trust-based collective view prediction algorithms and real case studies. The book consists of two main parts a theoretical foundation and an algorithmic study. The first part will review several basic concepts and methods related to collective view prediction, such as state-of-the-art recommender systems, sentimental analysis, collective view, trust management, the Relationship of Collective View and Trustworthy, and trust in collective view prediction. In the second part, the authors present their models and algorithms based on a quantitative analysis of more than 300 thousand users data from popular product-reviewing websites. They also introduce two new trust-based prediction algorithms, one collaborative algorithm based on the second-order Markov random walk model, and one Bayesian fitting model for combining multiple predictors.

Xu, G & Li, L 2013, Social media mining and social network analysis: Emerging research, IGI Global, USA.
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Social Media Mining and Social Network Analysis: Emerging Research highlights the advancements made in social network analysis and social web mining and its influence in the fields of computer science, information systems, sociology, organization science discipline and much more. This collection of perspectives on developmental practice is useful for industrial practitioners as well as researchers and scholars. © 2013 by IGI Global. All rights reserved.

Xu, G, Zong, Y & Yang, Z 2013, Applied Data Mining, 1, CRC Press, USA.
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Cao, L, Motoda, H, Srivastava, J, Lim, EP, King, I, Yu, PS, Nejdl, W, Xu, G, Li, G & Zhang, Y 2013, 'Preface' in Behavior and Social Computing, Springer, Germany, pp. v-vi.
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Gill, AQ & Bunker, D 2013, 'SaaS Requirements Engineering for Agile Development' in Wang, X, Ali, N, Ramos, I & Vidgen, R (eds), Agile and Lean Service-Oriented Development: Foundations, Theory, and Practice, IGI Global, USA, pp. 64-93.
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The emergence of Software as a Service (SaaS) has made it possible to develop dynamic and complex business processes as eServices. The development of business processes as eServices (SaaS) can be assisted by the means of adaptive or agile development processes. The development of business processes in terms of SaaS require to perform SaaS requirements engineering (RE), which is an important phase of a software development process for the success of any project. The challenge here is how best to do SaaS RE (e.g. mapping business process to eServices) and select agile development practices for developing business processes in terms of SaaS. In order to address this challenge, an integrated agile RE model for SaaS project development environments is outlined within this chapter. The purpose of the proposed RE model is to aid in iteratively determining SaaS requirements in short iterations as opposed to the only first and onetime upfront phase of a development process. Each identified SaaS requirement or a set of requirements for a given iteration is linked to a single or set of specific agile practices for implementation in short iterations. This model can be used as a guideline by organisations wishing to understand the challenging task of mapping business processes to SaaS and its implementation by using agile software development processes or practices.

Hussain, OK, Dillon, TS, Hussain, FK & Chang, EJ 2013, 'Understanding risk and its importance in business activities', Springer, pp. 1-313.
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Motivation: Nearly all of us have used the word risk in our conversations or have heard it in our daily life experience. To mention a few such situations: (i) you risk losing your driving license if you are caught drink driving; (ii) you risk your enrolment being cancelled if you are caught cheating; (iii) you risk losing your job if you don't improve your performance; (iv) your business is at risk if the current financial and economic situation does not improve; (v) you risk not reaching your job interview in Sydney on time on Monday if you leave from Perth by car on Friday. In all the above mentioned situations, risk is associated with an outcome that highlights losing a certain thing; for example losing a license, losing an enrolment, losing a job, losing a business, not reaching an interview on time. In all these examples, the thing which may be lost is considered an important one, hence the word 'losing' is associated with them. © 2013 Springer-Verlag Berlin Heidelberg.

Li, L, Xiao, H & Xu, G 2013, 'Recommending Related Microblogs' in Xu, G & Li, L (eds), Social Media Mining and Social Network Analysis: Emerging Research, IGI Global, Hershey, USA, pp. 202-210.
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Computing similarity between short microblogs is an important step in microblog recommendation. In this chapter, the authors utilize three kinds of approachestraditional term-based approach, WordNet-based semantic approach, and topic-based approachto compute similarities between micro-blogs and recommend top related ones to users. They conduct experimental study on the effectiveness of the three approaches in terms of precision. The results show that WordNet-based semantic similarity approach has a relatively higher precision than that of the traditional term-based approach, and the topic-based approach works poorest with 548 tweets as the dataset. In addition, the authors calculated the Kendall tau distance between two lists generated by any two approaches from WordNet, term, and topic approaches. Its average of all the 548 pair lists tells us the WordNet-based and term-based approach have generally high agreement in the ranking of related tweets, while the topic-based approach has a relatively high disaccord in the ranking of related tweets with the WordNet-based approach.

Lin, CT 2013, 'ABC intelligence on fuzziness' in On Fuzziness: A Homage to Lotfi A. Zadeh, Elsevier, The Netherlands, pp. 377-381.
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Three research areas, Artificial Intelligence (AI), Brain-like Intelligence (BI) and Computational Intelligence (CI) (denoted as ABC Intelligence), intertwine throughout my career. In my early days, I have shown strong interest in biology, psychology, and later on engineering. When I was an undergraduate student from 1982 to 1986, several hands-on courses on robotics covering automatic control, computer vision, AI, and microprocessor inspired my devotion of machine intelligence. When I arrived in West Lafayette of India for my graduate studies at Purdue University in 1988, I was given the book, Parallel Distributed Processing: Explorations in the Microstructure of Cognition by James L. McClelland, David E. Rumelhart and the PDP Research Group [1]. This book has opened my eyes on the “Connectionism”, representing a set of approaches in the fields of artificial intelligence, cognitive psychology, cognitive science, neuroscience, and philosophy of mind. I have been deeply intrigued by the book due to its cross-disciplinary nature

Raza, SA & Haider, S 2013, 'Designing and optimization of omni-directional kick for bipedal robots', pp. 292-301.

Redshaw, SJ 2013, 'Feminist Preludes to Relational Sociology' in Powell, C & Dépelteau, F (eds), Conceptualizing Relational Sociology Ontological and Theoretical Issues, Palgrave Macmillan, New York, pp. 13-26.
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Feminists have critiqued many of the dichotomies in Western thought such as nature and culture, mind and body, emotion and reason, public and private, and developed critiques of central notions such as individualism and abstract generalization. In this chapter, Nancy Chodorow’s relational individualism, Benhabib’s generalized and concrete other and Gilligan’s “different voice” are discussed, and their relevance to Crossley’s relational sociology is highlighted.

Wang, Z, Xu, X & Wang, X 2013, 'Mass Customization Oriented and Cost-Effective Service Network', SPRINGER-VERLAG BERLIN, pp. 172-185.

Xu, G, Gu, Y & Yi, X 2013, 'On Group Extraction and Fusion for Tag-Based Social Recommendation' in Xu, G & Li, L (eds), Social Media Mining and Social Network Analysis: Emerging Research, IGI Global, Hershey, USA, pp. 211-223.
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With the recent information explosion, social websites have become popular in many Web 2.0 applications where social annotation services allow users to annotate various resources with freely chosen words, i.e., tags, which can facilitate users finding preferred resources. However, obtaining the proper relationship among user, resource, and tag is still a challenge in social annotation-based recommendation researches. In this chapter, the authors aim to utilize the affinity relationship between tags and resources and between tags and users to extract group information. The key idea is to obtain the implicit relationship groups among users, resources, and tags and then fuse them to generate recommendation. The authors experimentally demonstrate that their strategy outperforms the state-of-the-art algorithms that fail to consider the latent relationships among tagging data.

Zong, Y & Xu, G 2013, 'Clustering Algorithms for Tags' in Xu, G & Li, L (eds), Social Media Mining and Social Network Analysis: Emerging Research, IGI Global, Hershey, USA, pp. 39-53.
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With the development and application of social media, more and more user-generated contents are created. Tag data, a kind of typical user generated content, has attracted lots of interests of researchers. In general, tags are the freely chosen textual descriptions by users to label digital data sources in social tagging systems. 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 chapter, the authors (1) review the background of state-of-the-art tagging clustering and the tag data description, (2) present five kinds of tag similarity measurements proposed by researchers, and (3) finally propose a new clustering algorithm for tags based on local information that is derived from Kernel function. This chapter aims to benefit both academic and industry communities who are interested in the techniques and applications of tagging clustering

Anaissi, A, Kennedy, PJ, Goyal, M & Catchpoole, DR 2013, 'A balanced iterative random forest for gene selection from microarray data', BMC Bioinformatics, vol. 14, pp. 1-10.
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Background The wealth of gene expression values being generated by high throughput microarray technologies leads to complex high dimensional datasets. Moreover, many cohorts have the problem of imbalanced classes where the number of patients belonging to each class is not the same. With this kind of dataset, biologists need to identify a small number of informative genes that can be used as biomarkers for a disease. Results This paper introduces a Balanced Iterative Random Forest (BIRF) algorithm to select the most relevant genes for a disease from imbalanced high-throughput gene expression microarray data. Balanced iterative random forest is applied on four cancer microarray datasets: a childhood leukaemia dataset, which represents the main target of this paper, collected from The Children’s Hospital at Westmead, NCI 60, a Colon dataset and a Lung cancer dataset. The results obtained by BIRF are compared to those of Support Vector Machine-Recursive Feature Elimination (SVM-RFE), Multi-class SVM-RFE (MSVM-RFE), Random Forest (RF) and Naive Bayes (NB) classifiers. The results of the BIRF approach outperform these state-of-the-art methods, especially in the case of imbalanced datasets. Experiments on the childhood leukaemia dataset show that a 7% ∼ 12% better accuracy is achieved by BIRF over MSVM-RFE with the ability to predict patients in the minor class. The informative biomarkers selected by the BIRF algorithm were validated by repeating training experiments three times to see whether they are globally informative, or just selected by chance. The results show that 64% of the top genes consistently appear in the three lists, and the top 20 genes remain near the top in the other three lists. Conclusion The designed BIRF algorithm is an appropriate choice to select genes from imbalanced high-throughput gene expression microarray data. BIRF outperforms the state-of-the-art methods, especially the ability to handle the class-imbalanced data. Moreover, the analysis...

Ashraf, J, Hussain, OK & Hussain, FK 2013, 'A Framework for Measuring Ontology Usage on the Web', Computer Journal, vol. 56, no. 9, pp. 1083-1101.
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A decade-long conscious effort by the Semantic Web community has resulted in the formation of a decentralized knowledge platform which enables data interoperability at a syntactic and semantic level. For information interoperability, at a syntactic level, RDF provides the standard format for publishing data and RDFS gives structure to the information. For semantic-level interoperability, ontologies are used which allow information dissemination and assimilation among diverse applications and systems; where information is equally accessible and useful to humans and machines. The success of the linked open data project, recognition of explicit semantics (annotated through web ontologies) by search engines and the realized potential advantages of semantic data for publishers have resulted in tremendous growth in the use of web ontologies on the web. In order to promote the adoption of ontologies (to new users), reusability of adopted ontologies, effective and efficient utilization on ontological knowledge and evolving the ontological model, erudite insight on the usage of ontologies is imperative. While ontology evaluation attempts to evaluate a developed ontology to assess its fitness and quality, it does not provide any insight into how ontologies are being used and what is the state of prevalent knowledge patterns. Realizing the importance of measuring and analysing ontology usage to advance the adoption, reusability and exploitation of ontologies, we present a semantic framework for measuring and analysing ontology usage on the Web on empirical grounding. Our methodological approach is discussed to highlight the detail and role of each step. A framework is presented along with the set of metrics developed to measure ontology usage from different aspects such as ontology richness, usage and incentives to provide a holistic view on the state of ontology usage. The framework is then evaluated using an important use-case scenario to identify the prevalent knowledge ...

Bakshi, A, Talaei-Khoei, A & Ray, P 2013, 'Adaptive policy framework: A systematic review', Journal of Network and Computer Applications, vol. 36, no. 4, pp. 1-11.
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This paper presents a systematic literature review to gain an understanding of adaptive policies. This review looks at papers published between 1970 and 2011 and examines the background and trends in this area. Based on the results, we establish a 4-step framework for managing and handling adaptive policies. We also demonstrate gaps in existing literature, the implications to theory and practice as well as avenues for potential future research.

Behbood, V, Lu, J & Zhang, G 2013, 'Fuzzy bridged refinement domain adaptation: Long-term bank failure prediction', International Journal of Computational Intelligence and Applications, vol. 12, no. 1, pp. 1-17.
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Machine learning methods, such as neural network (NN) and support vector machine, assume that the training data and the test data are drawn from the same distribution. This assumption may not be satisfied in many real world applications, like long-term financial failure prediction, because the training and test data may each come from different time periods or domains. This paper proposes a novel algorithm known as fuzzy bridged refinement-based domain adaptation to solve the problem of long-term prediction. The algorithm utilizes the fuzzy system and similarity concepts to modify the target instances' labels which were initially predicted by a shift-unaware prediction model. The experiments are performed using three shift-unaware prediction models based on nine different settings including two main situations: (1) there is no labeled instance in the target domain; (2) there are a few labeled instances in the target domain. In these experiments bank failure financial data is used to validate the algorithm. The results demonstrate a significant improvement in the predictive accuracy, particularly in the second situation identified above

Bhoemer, M & van, DHE 2013, 'Interaction design for supporting communication between Chinese sojourners', Personal and Ubiquitous Computing, vol. 17, no. 1, pp. 145-157.
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In our global village, distance is not a barrier anymore for traveling. People experience new cultures and face accompanying difficulties in order to live anywhere. Social support can help these sojourners to cope with difficulties, such as culture shock. In this paper, we investigate how computer-mediated communication (CMC) tools can facilitate social support when living physically separated from loved-ones in different cultures. The goal is to understand the design considerations necessary to design new CMC tools. We studied communication practices of Chinese sojourners living in the Netherlands and the use of a technology probe with a novel video communication system. These results led to recommendations which can help designers to design interactive communication tools that facilitate communication across cultures. We conclude the paper with an interactive communication device called Circadian, which was designed based on these recommendations. We experienced the design recommendations to be abstract enough to leave space for creativity while providing a set of clear requirements which we used to base design decisions upon.

Budka, M, Juszczyszyn, K, Musial, K & Musial, A 2013, 'Molecular model of dynamic social network based on e-mail communication', Social Network Analysis and Mining, vol. 3, no. 3, pp. 543-563.
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© 2013, The Author(s). In this work we consider an application of physically inspired sociodynamical model to the modelling of the evolution of email-based social network. Contrary to the standard approach of sociodynamics, which assumes expressing of system dynamics with heuristically defined simple rules, we postulate the inference of these rules from the real data and their application within a dynamic molecular model. We present how to embed the n-dimensional social space in Euclidean one. Then, inspired by the Lennard-Jones potential, we define a data-driven social potential function and apply the resultant force to a real e-mail communication network in a course of a molecular simulation, with network nodes taking on the role of interacting particles. We discuss all steps of the modelling process, from data preparation, through embedding and the molecular simulation itself, to transformation from the embedding space back to a graph structure. The conclusions, drawn from examining the resultant networks in stable, minimum-energy states, emphasize the role of the embedding process projecting the non–metric social graph into the Euclidean space, the significance of the unavoidable loss of information connected with this procedure and the resultant preservation of global rather than local properties of the initial network. We also argue applicability of our method to some classes of problems, while also signalling the areas which require further research in order to expand this applicability domain.

Cesare, S, Xiang, Y & Zhou, W 2013, 'Malwise-an effective and efficient classification system for packed and polymorphic malware', IEEE Transactions on Computers, vol. 62, no. 6, pp. 1193-1206.
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Signature-based malware detection systems have been a much used response to the pervasive problem of malware. Identification of malware variants is essential to a detection system and is made possible by identifying invariant characteristics in related samples. To classify the packed and polymorphic malware, this paper proposes a novel system, named Malwise, for malware classification using a fast application-level emulator to reverse the code packing transformation, and two flowgraph matching algorithms to perform classification. An exact flowgraph matching algorithm is employed that uses string-based signatures, and is able to detect malware with near real-time performance. Additionally, a more effective approximate flowgraph matching algorithm is proposed that uses the decompilation technique of structuring to generate string-based signatures amenable to the string edit distance. We use real and synthetic malware to demonstrate the effectiveness and efficiency of Malwise. Using more than 15,000 real malware, collected from honeypots, the effectiveness is validated by showing that there is an 88 percent probability that new malware is detected as a variant of existing malware. The efficiency is demonstrated from a smaller sample set of malware where 86 percent of the samples can be classified in under 1.3 seconds. © 1968-2012 IEEE.

Cheng, J, Bian, W & Tao, D 2013, 'Locally regularized sliced inverse regression based 3D hand gesture recognition on a dance robot', Information Sciences, vol. 221, pp. 274-283.
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Gesture recognition plays an important role in human machine interactions (HMIs) for multimedia entertainment. In this paper, we present a dimension reduction based approach for dynamic real-time hand gesture recognition. The hand gestures are recorded as acceleration signals by using a handheld with a 3-axis accelerometer sensor installed, and represented by discrete cosine transform (DCT) coefficients. To recognize different hand gestures, we develop a new dimension reduction method, locally regularized sliced inverse regression (LR-SIR), to find an effective low dimensional subspace, in which different hand gestures are well separable, following which recognition can be performed by using simple and efficient classifiers, e.g., nearest mean, k-nearest-neighbor rule and support vector machine. LR-SIR is built upon the well-known sliced inverse regression (SIR), but overcomes its limitation that it ignores the local geometry of the data distribution. Besides, LR-SIR can be effectively and efficiently solved by eigen-decomposition. Finally, we apply the LR-SIR based gesture recognition to control our recently developed dance robot for multimedia entertainment. Thorough empirical studies on `digits-gesture recognition suggest the effectiveness of the new gesture recognition scheme for HMI.

Cirelli, J, McGregor, C, Graydon, B & James, A 2013, 'Analysis of continuous oxygen saturation data for accurate representation of retinal exposure to oxygen in the preterm infant', Studies in Health Technology and Informatics, vol. 183, pp. 126-131.
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Maintaining blood oxygen saturation within the intended target range for preterm infants receiving neonatal intensive care is challenging. Supplemental oxygen is believed to lead to increased risk of retinopathy of prematurity and hence managing the level of oxygen within this population is important within their care. Current quality improvement activities use coarse hourly spot readings to measure supplemental oxygen levels as associated with targeted ranges that vary based on gestational age. In this research we use Artemis, a real-time online healthcare analytics platform to ascertain if the collection of second by second data provides a better representation of retinal exposure to oxygen than an infrequent, intermittent spot reading. We show that Artemis is capable of producing more accurate information from the higher frequency data, as it includes all the episodic events in the activity of the hour, which provides a better understanding of oxygen fluctuation ranges which affect the physiological status of the infant.. © 2013 ITCH 2013 Steering Committee and IOS Press. All rights reserved.

Do, Q & Hussain, FK 2013, 'A hybrid approach for the personalisation of cloud-based e-governance services', International Journal of High Performance Computing and Networking, vol. 7, no. 3, pp. 205-214.
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Cloud computing is a new and promising paradigm for service delivery including computing resources over the internet. Cloud computing standards and architecture play an important role in benefiting governments by reducing operating costs and increasing governance effectiveness. Cloud-based e-governance contributes to managing security, reducing cost based on a pay-as-you-go method, IT labour cost reduction, and increasing scalability. Given the importance of cloud computing in the today's emerging technologies, personalisation in cloud computing is also significant in supporting users to obtain what they need without being required to request it explicitly. This research will focus mainly on a personalisation algorithm to for cloud computing. A case study in which a user can suggest the language they want to use without making an explicit request will be provided to assist further understanding of the new algorithm, which is a combination of the TOPSIS and Pearson correlation coefficient methods.

Dong, H & Hussain, FK 2013, 'SOF: A Semi-supervised Ontology-learning-based Focused Crawler', Concurrency and Computation: Practice and Experience, vol. 25, no. 12, pp. 1755-1770.
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The rapid increase in the volume of data available on the Internet makes it increasingly impractical for a crawler to index the whole Web. Instead, many intelligent crawlers, known as ontology-based semantic focused crawlers, have been designed by making use of Semantic Web technologies for topic-centered Web information crawling. Ontologies, however, have constraints of validity and time, which may influence the performance of the crawlers. Ontology-learning-based focused crawlers are therefore designed to automatically evolve ontologies by integrating ontology learning technologies. Nevertheless, surveys indicate that the existing ontology-learning-based focused crawlers do not have the capability to automatically enrich the content of ontologies, which makes these crawlers unreliable in the open and heterogeneous Web environment. Hence, in this paper, we propose a framework for a novel semi-supervised ontology-learning-based focused (SOF) crawler, the SOF crawler, which embodies a series of schemas for ontology generation and Web information formatting, a semi-supervised ontology learning framework, and a hybrid Web page classification approach aggregated by a group of support vector machine models. A series of tests are implemented to evaluate the technical feasibility of this proposed framework. The conclusion and the future work are summarized in the final section

Dong, H, Hussain, FK & Chang, E 2013, 'Semantic Web Service matchmakers: State of the art and challenges', Concurrency and Computation: Practice and Experience, vol. 25, no. 7, pp. 961-988.
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Web services provide a standard means for the interoperable operations between electronic devices in a network. The mission of Web service discovery is to seek an appropriate Web service for a service requester on the basis of the service descriptions in Web service advertisements and the service requesterâs requirements. Nevertheless, the standard language used for encoding service descriptions does not have the capacity to specify the capabilities of a Web service, leading to the problem of ambiguity in the service discovery process. This brings up the vision of SemanticWeb Services and SemanticWeb Service discovery, which make use of the SemanticWeb technologies to enrich the semantics of service descriptions for service discovery. Semantic Web Service matchmakers are the programs or frameworks designed to implement the task of Semantic Web Service discovery and have drawn a significant amount of attention from both academia and industry from the start of this century. In this paper, we conduct a survey of the contemporary Semantic Web Service matchmakers in order to obtain an overview of the state of the art in this research area. We summarize six technical dimensions from the past literature and analyze the typical Semantic Web Service matchmakers mostly developed during the past 4 or 5 years in terms of the six dimensions. By means of this analysis, we gain an understanding of the current research and summarize a series of potential issues to that would provide the foundation for future research in this area. Copyright © 2012 John Wiley & Sons, Ltd

Doss, R, Sundaresan, S & Zhou, W 2013, 'A practical quadratic residues based scheme for authentication and privacy in mobile RFID systems', Ad Hoc Networks, vol. 11, no. 1, pp. 383-396.
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In this paper we propose a novel approach to authentication and privacy in mobile RFID systems based on quadratic residues and in conformance to EPC Class-1 Gen-2 specifications. Recently, Chen et al. (2008) [10] and Yeh et al. (2011) [11] have both proposed authentication schemes for RFID systems based on quadratic residues. However, these schemes are not suitable for implementation on low-cost passive RFID tags as they require the implementation of hash functions on the tags. Consequently, both of these current methods do not conform to the EPC Class-1 Gen-2 standard for passive RFID tags which from a security perspective requires tags to only implement cyclic redundancy checks (CRC) and pseudo-random number generators (PRNG) leaving about 2.5k-5k gates available for any other security operations. Further, due to secure channel assumptions both schemes are not suited for mobile/wireless reader applications. We present the collaborative authentication scheme suitable for mobile/wireless reader RFID systems where the security of the server-reader channel cannot be guaranteed. Our schemes achieves authentication of the tag, reader and back-end server in the RFID system and protects the privacy of the communication without the need for tags to implement expensive hash functions. Our scheme is the first quadratic residues based scheme to achieve compliance to EPC Class-1 Gen-2 specifications. Through detailed security analysis we show that the collaborative authentication scheme achieves the required security properties of tag anonymity, reader anonymity, reader privacy, tag untraceability and forward secrecy. In addition, it is resistant to replay, impersonation and desynchronisation attacks. We also show through strand space analysis that the proposed approach achieves the required properties of agreement, originality and secrecy between the tag and the server. © 2012 Elsevier B.V. All rights reserved.

Doss, R, Zhou, W & Yu, S 2013, 'Secure RFID tag ownership transfer based on quadratic residues', IEEE Transactions on Information Forensics and Security, vol. 8, no. 2, pp. 390-401.
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In this paper, we propose a novel approach to secure ownership transfer in RFID systems based on the quadratic residue property. We present two secure ownership transfer schemes - the closed loop and open loop schemes. An important property of our schemes is that ownership transfer is guaranteed to be atomic. Further, both our schemes are suited to the computational constraints of EPC Class-1 Gen-2 passive RFID tags as they only use operations that such passive RFID tags are capable of. We provide a detailed security analysis to show that our schemes achieve strong privacy and satisfy the required security properties of tag anonymity, tag location privacy, forward secrecy, and forward untraceability. We also show that the schemes are resistant to replay (both passive and algebraic), desynchronization, and server impersonation attacks. Performance comparisons demonstrate that our schemes are practical and can be implemented on low-cost passive RFID tags. © 2005-2012 IEEE.

Dzeng, R-J, Lin, C-T & Hsiao, F-Y 2013, 'An Integrated Model for Simulating Activities and Optimizing Space Function in Educational Facility', International Journal of Information and Education Technology, vol. 3, no. 6, pp. 582-586.
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Determining the function for each space in a building plays an important role for assessing the service level of an educational facility. The function layout affects how users move between spaces during their participation of activities in the facility. This research describes the integration of an activity-based simulation model and a space-function assignment optimization model with six phases, including data collection, data preparation, data mining, optimization, verification, and refinement. The paper also uses a real case to demonstrate the use of the proposed model, and has shown a 4.96% improvement on the objective value compared to the contracted architect’s original plan.

Esfijani, A, Hussain, FK & Chang, E 2013, 'University social responsibility ontology', Engineering Intelligent Systems, vol. 21, no. 4, pp. 271-281.
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This paper draws on the existing body of knowledge to develop an ontology for university social responsibility (USR). There are numerous terms and definitions for USR in the existing literature. However, there is no consensus among them. In order to address this issue, we used a semi-automated text mining approach for ontology engineering. The developed ontology covered USR and its associated terms by which social responsibilities of a university to its communities have been described in the existing literature. The developed ontology, which is an explicit specification of USR concept, its components and their relationships, can contribute to develop a unified understanding of the concept for measurement purposes

Fazal, A, Hussain, FK & Dillon, TS 2013, 'An Innovative Approach For Automatically Grading Spelling In Essays Using Rubric-based Scoring', Journal of Computer and System Sciences, vol. 79, no. 7, pp. 1040-1056.
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Automated Essay Grading (AEG) is defined as a computer technology that evaluates and scores written prose. A number of AEG systems have been developed since the 1960s and in most of them, an ad-hoc or generalized approach is used to grade spelling even though it is an important element of an essay-scoring rubric. Existing approaches do not therefore give an accurate representation or measure of spelling in essays. According to the rubric-based scoring method used in the National Assessment Program Literacy and Numeracy (NAPLAN) in Australia, spelling is marked in three steps first, by identifying the correct and incorrect words in the essay; second, by categorizing each word based on the difficulty level into one of four classes: Simple, Common, Difficult or Challenging, and counting the number of correct and incorrect words in each category; finally, by using the pre-defined NAPLAN rubric scale to assign the mark. Only a small number of existing AEG systems can be used for rubric-based scoring, and none can be used to grade spelling according to the NAPLAN rubric. In this paper, we address this shortcoming in the existing literature and present an innovative approach to automatically mark spelling using rubric based scoring. We develop two algorithms based on the rules and heuristics of the English language to formulize the rubric for spelling and then implement these algorithms in Java language and perform a series of evaluations of our system using an essay dataset. Our results are very promising, even though it is the first system of this kind.

Ferguson, S, Kenny, DT, Mitchell, HF, Ryan, M & Cabrera, D 2013, 'Change in messa di voce characteristics during 3 years of classical singing training at the tertiary level', Journal of Voice, vol. 27, no. 4, pp. 35-48.
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A 3-year longitudinal study was conducted to investigate changes in vocal quality as a result of singing training at a tertiary level conservatorium in Australia. Singers performed a messa di voce (MDV) at intervals of 6 months over the 3-year period of training. The study investigated the evolving acoustic features of the singers' voices exhibited during the MDV, including sound pressure level (SPL), short-term energy ratio (STER), duration, and vibrato parameters of the fundamental frequency (F0), SPL, and STER. The maximum SPL exhibited a marginal systematic increase over the training period, but the maximum STER did not systematically change. F0 vibrato extent increased significantly, whereas the extent of SPL and STER vibrato did not change significantly.

Frati, F, Gaspers, S, Gudmundsson, J & Mathieson, L 2013, 'Augmenting graphs to minimize the diameter', Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 8283 LNCS, pp. 383-393.
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We study the problem of augmenting a weighted graph by inserting edges of bounded total cost while minimizing the diameter of the augmented graph. Our main result is an FPT 4-approximation algorithm for the problem. © 2013 Springer-Verlag.

Fuestoes, J, Gramann, K, Herbert, BM & Pollatos, O 2013, 'On the embodiment of emotion regulation: interoceptive awareness facilitates reappraisal', SOCIAL COGNITIVE AND AFFECTIVE NEUROSCIENCE, vol. 8, no. 8, pp. 911-917.
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Furqan, F & Hoang, DB 2013, 'Wireless fair intelligent congestion control - A QoS performance evaluation', Journal of Interconnection Networks, vol. 14, no. 3.
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In Broadband Wireless Access (BWA) networks, provisioning of Quality of Service (QoS) is absolutely essential for real time and non real time services. Congestion in these networks can lead to deterioration in QoS experienced by the network users. Congestion avoidance is rarely considered to ensure the QoS of wireless connections. Efforts are mainly aimed at reducing the overload once it has occurred. To avoid congestion at the base station in WiMAX networks, the WiMAX Fair Intelligent Congestion Control (WFICC) was proposed to ensure the traffic is scheduled in such a way that the base station output buffer operates around a target operating point without violating the QoS requirements of connections. The aim of this paper is to investigate WFICC thoroughly and evaluate its performance in terms of throughput, delay and jitter for different Classes of Services (CoSs) under various parameter settings of the algorithm. A detailed and comprehensive simulation study on various settings of parameters is performed in ns-2. The results show that WFICC performs excellently in allocating resources fairly among Class of Services (CoSs) and also preserves their QoS requirements. Furthermore, WFICC is robust and easily adapted to various traffic conditions. © World Scientific Publishing Company.

Gao, L, Li, M, Bonti, A, Zhou, W & Yu, S 2013, 'Multidimensional routing protocol in human-associated delay-tolerant networks', IEEE Transactions on Mobile Computing, vol. 12, no. 11, pp. 2132-2144.
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Human-associated delay-tolerant networks (HDTNs) are new networks where mobile devices are associated with humans and can be viewed from multiple dimensions including geographic and social aspects. The combination of these different dimensions enables us to comprehend delay-tolerant networks and consequently use this multidimensional information to improve overall network efficiency. Alongside the geographic dimension of the network, which is concerned with geographic topology of routing, social dimensions such as social characters can be used to guide the routing message to improve not only the routing efficiency for individual nodes, but also efficiency for the entire network. We propose a multidimensional routing protocol (M-Dimension) for the human-associated delay-tolerant networks which uses local information derived from multiple dimensions to identify a mobile node more accurately. The importance of each dimension has been measured by the weight function and it is used to calculate the best route. The greedy routing strategy is applied to select an intermediary node to forward message. We compare M-Dimension to the existing benchmark routing protocols via MIT reality Data Set and INFOCOM 2006 Data Set, which are real human-associated mobile network trace files. The results of our simulations show that M-Dimension significantly increases the average success ratio with a competitive end-to-end delay when compared with other multicast DTNs routing protocols. © 2002-2012 IEEE.

Gill, AQ & Bunker, D 2013, 'Towards the development of a cloud-based communication technologies assessment tool: An analysis of practitioners' perspectives', VINE: Journal of Information and Knowledge Management Systems, vol. 43, no. 1, pp. 57-77.
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Purpose - In distributed adaptive development environments (DADE), a primary concern is that of human communication and knowledge sharing among developers. Developers' task performance will be enhanced when their task needs are aligned with the communication media or technology capabilities of the development environment. What are actual communication needs of developers; and how do we enable developers to self-assess and select appropriate communication technology for their tasks in the DADE. The purpose of this paper is to investigate and present research based on the developers' needs for communication technologies in the context of DADE. Design/methodology/approach The authors applied an exploratory qualitative research method to investigate, analyze and integrate survey information sourced from 40 developers, to identify their communication technology needs and, based on this information, the authors then set up a practical tool communication technologies assessment tool (CTAT) to assist developers in the self-assessment and selection of appropriate communication technologies for their DADE; and also to share this assessment knowledge with other developers or teams located in various DADEs. Findings The results of this research suggest that an effective CTAT should be an integral part of the DADE; and a DADE should have a single source of information in order to avoid possible communication inconsistencies and ambiguities.

Gluga, R, Kay, J, Lister, RF, simon, S & Kleitman, S 2013, 'Mastering Cognitive Development Theory in Computer Science Education', Computer Science Education, vol. 23, no. 1, pp. 24-57.
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Abstract: To design an effective computer science curriculum, educators require a systematic method of classifying the difficulty level of learning activities and assessment tasks. This is important for curriculum design and implementation and for communication between educators. Different educators must be able to use the method consistently, so that classified activities and assessments are comparable across the subjects of a degree, and, ideally, comparable across institutions. One widespread approach to supporting this is to write learning objects in terms of Blooms Taxonomy. This, or other such classifications, is likely to be more effective if educators can use them consistently, in the way experts would use them. To this end, we present the design and evaluation of our online interactive web-based tutorial system, which can be configured and used to offer training in different classification schemes. We report on results from three evaluations. First, 17 computer science educators complete a tutorial on using Blooms Taxonomy to classify programming examination questions. Second, 20 computer science educators complete a Neo-Piagetian tutorial. Third evaluation was a comparison of inter-rater reliability scores of computer science educators classifying programming questions using Blooms Taxonomy, before and after taking our tutorial. Based on the results from these evaluations, we discuss the effectiveness of our tutorial system design for teaching computer science educators how to systematically and consistently classify programming examination questions. We also discuss the suitability of Blooms Taxonomy and Neo-Piagetian theory for achieving this goal. The Blooms and Neo-Piagetian tutorials are made available as a community resource. The contributions of this paper are the following: the tutorial system for learning classification schemes for the purpose of coding the difficulty of computing learning materials; its evaluation; new insights into the consis...

Goeke, CM, Koenig, P & Gramann, K 2013, 'Different strategies for spatial updating in yaw and pitch path integration', FRONTIERS IN BEHAVIORAL NEUROSCIENCE, vol. 7.
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Golsteijn, C & van den Hoven, E 2013, 'Facilitating parent-teenager communication through interactive photo cubes', Personal and Ubiquitous Computing, vol. 17, no. 2, pp. 273-286.
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Because most teenagers strive for freedom and try to live autonomously, communication with their parents could be improved. It appeared from a literature review and a diary study that parent-teenager communication primarily addresses teenager-oriented everyday activities. However, it also showed teenagers have a substantial interest in getting to know their parents and their parents' past. The study described in this paper seeks to address this opportunity by designing a product for parents and teenagers that facilitates communication about the past of the parents. The resulting design, called Cueb, is a set of interactive digital photo cubes with which parents and teenagers can explore individual and shared experiences and are triggered to exchange stories. An evaluation of a prototype of Cueb with four families showed that the participants felt significantly more triggered and supported to share their experiences and tell stories with Cueb's full functionality (connecting cubes, switching, and locking photographs) than with limited functionality (shaking to display random photographs), similar to more traditional photo media.

Goodswen, SJ, Kennedy, PJ & Ellis, JT 2013, 'A guide to in silico vaccine discovery for eukaryotic pathogens', Briefings in Bioinformatics, vol. 14, no. 6, pp. 753-774.
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In this article, a framework for an in silico pipeline is presented as a guide to high-throughput vaccine candidate discovery for eukaryotic pathogens, such as helminths and protozoa. Eukaryotic pathogens are mostly parasitic and cause some of the most damaging and difficult to treat diseases in humans and livestock. Consequently, these parasitic pathogens have a significant impact on economy and human health. The pipeline is based on the principle of reverse vaccinology and is constructed from freely available bioinformatics programs. There are several successful applications of reverse vaccinology to the discovery of subunit vaccines against prokaryotic pathogens but not yet against eukaryotic pathogens. The overriding aim of the pipeline, which focuses on eukaryotic pathogens, is to generate through computational processes of elimination and evidence gathering a ranked list of proteins based on a scoring system. These proteins are either surface components of the target pathogen or are secreted by the pathogen and are of a type known to be antigenic. No perfect predictive method is yet available; therefore, the highest-scoring proteins from the list require laboratory validation.

Goodswen, SJ, Kennedy, PJ & Ellis, JT 2013, 'A novel strategy for classifying the output from an in silico vaccine discovery pipeline for eukaryotic pathogens using machine learning algorithms', BMC Bioinformatics, vol. 14, no. 1, pp. 315-327.
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An in silico vaccine discovery pipeline for eukaryotic pathogens typically consists of several computational tools to predict protein characteristics. The aim of the in silico approach to discovering subunit vaccines is to use predicted characteristics to identify proteins which are worthy of laboratory investigation. A major challenge is that these predictions are inherent with hidden inaccuracies and contradictions. This study focuses on how to reduce the number of false candidates using machine learning algorithms rather than relying on expensive laboratory validation. Proteins from Toxoplasma gondii, Plasmodium sp., and Caenorhabditis elegans were used as training and test datasets.

Goodswen, SJ, Kennedy, PJ & Ellis, JT 2013, 'A review of the infection, genetics, and evolution of Neospora caninum: from the past to the present', Infection, Genetics and Evolution, vol. 13, no. 1, pp. 133-150.
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This paper is a review of current knowledge on Neospora caninum in the context of other apicomplexan parasites and with an emphasis on: life cycle, disease, epidemiology, immunity, control and treatment, evolution, genomes, and biological databases and web resources. N. caninum is an obligate, intracellular, coccidian, protozoan parasite of the phylum Apicomplexa. Infection can cause the clinical disease neosporosis, which most notably is associated with abortion in cattle. These abortions are a major root cause of economic loss to both the dairy and beef industries worldwide. N. caninum has been detected in every country in which a study has been specifically conducted to detect this parasite in cattle. The major mode of transmission in cattle is transplacental (or vertical) transmission and several elements of the N. caninum life cycle are yet to be studied in detail. The outcome of an infection is inextricably linked to the precise timing of the infection coupled with the status of the immune system of the dam and foetus. There is no community consensus as to whether it is the dams pro-inflammatory cytotoxic response to tachyzoites that kills the foetus or the tachyzoites themselves. From economic analysis the most cost-effective approach to control neosporosis is a vaccine. The perfect vaccine would protect against both infection and the clinical disease, and this implies a vaccine is needed that can induce a non-foetopathic cell mediated immunity response. Researchers are beginning to capitalise on the vast potential of -omics data (e.g. genomes, transcriptomes, and proteomes) to further our understanding of pathogens but especially to identify vaccine and drug targets. The recent publication of a genome for N. caninum offers vast opportunities in these areas.

Gramann, K 2013, 'Embodiment of Spatial Reference Frames and Individual Differences in Reference Frame Proclivity', SPATIAL COGNITION AND COMPUTATION, vol. 13, no. 1, pp. 1-25.
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Gramann, K & Schluepmann, H 2013, 'Film-History at the Kinothek Asta Nielsen', ZEITGESCHICHTE, vol. 40, no. 4, pp. 236-+.

Hammadi, A, Hussain, OK, Dillon, TS & Hussain, FK 2013, 'A Framework for SLA Management in Cloud Computing for informed decision making', Cluster Computing: The Journal of Networks, Software Tools and Applications, vol. 16, no. 4, pp. 961-977.
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In cloud computing, service providers offer cost-effective and on-demand IT services to service users on the basis of Service Level Agreements (SLAs). However the effective management of SLAs in cloud computing is essential for the service users to ensure that they achieve the desired outcomes from the formed service. In this paper, we introduce a SLA management framework that will enable service users to select the best available service provider on the basis of its reputation and then monitor the run time performance of the service provider to determine whether or not it will fulfill its promise defined in the SLA. Such analysis will assist the service user to make an informed decision about the continuation of service with the service provider.

Han, M-F, Liao, S-H, Chang, J-Y & Lin, C-T 2013, 'Dynamic group-based differential evolution using a self-adaptive strategy for global optimization problems', APPLIED INTELLIGENCE, vol. 39, no. 1, pp. 41-56.
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Han, MF, Lin, CT & Chang, JY 2013, 'Efficient differential evolution algorithm-based optimisation of fuzzy prediction model for time series forecasting', International Journal of Intelligent Information and Database Systems, vol. 7, no. 3, pp. 225-241.
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This paper proposes a differential evolution algorithm with efficient mutation strategy (DEEMS) for fuzzy prediction model (FPM) optimisation. The proposed DEEMS uses a modified mutation operation which considers local information nearby each individual to trade-off between the exploration ability and the exploitation ability. In the FPM design, we adopt an entropy measure method to determine the number of rules. Initially, there is no rule in the FPM. Fuzzy rules are automatically generated by entropy measure. Subsequently, the DEEMS algorithm is performed to optimise all the free parameters. During evolution process, the scale factor and crossover rate in the DEEMS algorithm are adjusted by adaptive parameter tuning strategy for each generation. It is thus helpful to enhance the robustness of the DEEMS algorithm. In the simulation, the proposed FPM with DEEMS model (FPM-DEEMS) is applied to two real world problems. Results show that the proposed FPM-DEEMS model obtains better performance than other algorithms. Copyright © 2013 Inderscience Enterprises Ltd.

Han, M-F, Lin, C-T & Chang, J-Y 2013, 'Differential evolution with local information for neuro-fuzzy systems optimisation', KNOWLEDGE-BASED SYSTEMS, vol. 44, pp. 78-89.
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Han, MF, Lin, CT, Chang, JY & Li, DL 2013, 'Group-based differential evolution for numerical optimization problems', International Journal of Innovative Computing, Information and Control, vol. 9, no. 3, pp. 1357-1372.
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This paper proposes a group-based differential evolution (GDE) algorithm for numerical optimization problems. The proposed GDE algorithm provides a new process using two mutation strategies to effectively enhance the search for the globally optimal solution. Initially, all individuals in the population are partitioned into an elite group and an inferior group based on their fitness value. In the elite group, individuals with a better fitness value employ the local mutation operation to search for better solutions near the current best individual. The inferior group, which is composed of individuals with worse fitness values, uses a global mutation operation to search for potential solutions and to increase the diversity of the population. Subsequently, the GDE algorithm employs crossover and selection operations to produce offspring for the next generation. This paper also proposes two parameter-tuning strategies for the robustness of the GDE algorithm in the evolution process. To validate the performance of the GDE algorithm, 13 well-known numerical benchmark functions were tested on low- and high-dimensional problems. The simulation results indicate that our approach is efficient. © 2013 ICIC International.

Horanont, T, Phithakkitnukoon, S, Leong, T, Sekimoto, Y & Shibasaki, R 2013, 'Weather Effects on the Patterns of People's Everyday Activities: A Study Using GPS Traces of Mobile Phone Users', Plos One, vol. 8, no. 12, pp. 1-14.
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This study explores the effects that the weather has on people's everyday activity patterns. Temperature, rainfall, and wind speed were used as weather parameters. People's daily activity patterns were inferred, such as place visited, the time this took

Huang, W, Khoury, R, Dawborn, T, Huang, B, Huang, M & Huang, X 2013, 'Webevis: Analyzing User Web Behavior Through Visual Metaphors', Science China Information Sciences, vol. 56, no. 5, pp. 1-15.
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The rapid growth of Internet usage has dramatically changed the way we interact with the outside world. Many people read news, communicate with friends and purchase goods online. These activities are usually done via web browsing, and web browsers record information about these activities. The recorded data can be used to understand web browsing behavior of users and improve their browsing experience. For example, website usability and the personalization of online services could both benefit from knowledge of user browsing behavior. A number of methods including data mining, text processing and visualization have been used to uncover user browsing patterns. However, these methods are mainly used to analyze and gain insights into collective behavior patterns of either a large amount of separate web users or users within an online community over a prolonged period of time. Very few systems are available for analyzing the detailed behavior of a single user within a relatively short and specific period of time. In an attempt to shorten this gap, we have developed a visual analytic system called WeBeVis. This system offers three different ways of visualizing web browsing data based on our proposed visual metaphors. It also provides a common interface for users to interact with the visualizations. In this paper, we describe this system and present a user study of it. We show that by visualizing the web browsing history of a user, we are able to uncover interesting patterns in the way that individuals use the web.

Hussain, FK & Fachrunnisa, O 2013, 'A Methodology for Maintaining Trust in Industrial Digital Ecosystems', IEEE Transactions On Industrial Electronics, vol. 60, no. 3, pp. 1042-1058.
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Trust is widely considered to be essential for the smooth functioning of digital ecosystems. However, trust by its very nature, and due to the virtual connection between entities, is extremely fragile. Trust has a life cycle which is composed of building, maintaining, and declining. Given the fragility of trust in virtual environments, it is challenging to work out how to maintain the level of trust (specifically positive trust) between two interacting parties. Once positive trust has been established in the trust building phase, a methodological framework is needed to maintain the existing trust level, so that the relationship may be sustained in the future. In this paper, we present a methodology for maintaining trust in industrial digital ecosystems. The methodology proposes the use of a third party agent, an iterative negotiation process, proactive performance monitoring, and intelligence metrics recalibration of the trust level. In a trust-based relationship, trust can be regarded as having been maintained if the final trust is greater than or equal to initial trust. We demonstrate the validity of the methodology by engineering a prototype setup and running simulations under various operational conditions.

Jacobson, A, Panozzo, D, Schüller, C, Diamanti, O, Zhou, Q, Pietroni, N & others 2013, 'libigl: A simple C++ geometry processing library', Google Scholar.

Janjua, NK, Hussain, FK & Hussain, OK 2013, 'Semantic information and knowledge integration through argumentative reasoning to support intelligent decision making', Information Systems Frontiers, vol. 15, no. 2, pp. 167-192.
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The availability of integrated, high quality information is a pre-requisite for a decision support system (DSS) to aid in the decision-making process. The introduction of semantic web ensures the seamless integration of information derived from diverse sources and transforms the DSS to an adoptable and flexible Semantic Web-DSS (Web-DSS). However, due to the monotonic nature of the layered development of semantic web, it lacks the capability to represent, reason and integrate incomplete and conflicting information. This, in turn, renders an enterprise incapable of knowledge integration; that is, integration of information about a subject that could potentially be incomplete, inconsistent and distributed among different Web-DSS within or across enterprises. In this article, we address the issues of incomplete and inconsistent semantic information and knowledge integration by using argumentation and argumentation schemes. We discuss the Argumentation-enabled Information Integration Web-DSS (Web@IDSS) along with its syntax and semantics for semantic information integration, and devise a methodology for sharing the results of Web@IDSS in Argument Interchange Format (AIF) format. We also discuss Argumentation-enabled Knowledge Integration Web-DSS (Web@KIDSS) for semantic knowledge integration. We provide formal syntax and semantics for the Web@KIDSS, propose a conceptual framework, and describe it in detail. We present the algorithms for knowledge integration and the prototype application for validation of results

Kaniewski, J, Tomamichel, M, Haenggi, E & Wehner, S 2013, 'Secure Bit Commitment From Relativistic Constraints', IEEE TRANSACTIONS ON INFORMATION THEORY, vol. 59, no. 7, pp. 4687-4699.
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Kazem, A, Sharifi, E, Hussain, FK, Saberi, M & Hussain, OK 2013, 'Support Vector Regression with chaos-based firefly algorithm for stock market price forecasting', Applied Soft Computing, vol. 13, no. 2, pp. 947-958.
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Due to the inherent non-linearity and non-stationary characteristics of financial stock market price time series, conventional modeling techniques such as the BoxJenkins autoregressive integrated moving average (ARIMA) are not adequate for stock market price forecasting. In this paper, a forecasting model based on chaotic mapping, firefly algorithm, and support vector regression (SVR) is proposed to predict stock market price. The forecasting model has three stages. In the first stage, a delay coordinate embedding method is used to reconstruct unseen phase space dynamics. In the second stage, a chaotic firefly algorithm is employed to optimize SVR hyperparameters. Finally in the third stage, the optimized SVR is used to forecast stock market price. The significance of the proposed algorithm is 3-fold. First, it integrates both chaos theory and the firefly algorithm to optimize SVR hyperparameters, whereas previous studies employ a genetic algorithm (GA) to optimize these parameters. Second, it uses a delay coordinate embedding method to reconstruct phase space dynamics. Third, it has high prediction accuracy due to its implementation of structural risk minimization (SRM). To show the applicability and superiority of the proposed algorithm, we selected the three most challenging stock market time series data from NASDAQ historical quotes, namely Intel, National Bank shares and Microsoft daily closed (last) stock price, and applied the proposed algorithm to these data.

Kosman, K, Talaei-Khoei, A, Ghapanchi, AH & Ray, P 2013, 'A Systematic Literature Review Approach To Clinical Trial Informatics Systems: Case of caBIG and its Clinical Trial', International Journal of Advanced Information Technologies (IJAIT), vol. 7, no. 1, pp. 84-98.
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An increased usage of clinical trial informatics systems will promote scientific institutions, benefit the worldwide research community, and assist in the rising trend of personalized medicine. This paper undertakes a systematic review to gain insight into existing studies on the Clinical Trial Informatics Systems (CTIS). In particular, we will focus on those articles that have worked on a special type of CTIS called the Cancer Biomedical Informatics Grid (caBIG), developed by the National Cancer Institute, and its Clinical Trial Management System (CTMS) workspace which uses Clinical Trials Suite software. Based on the 67 extracted studies from 2001-2011, we classified the literature into the 3 broad categories of product description, analysis of options, and user behaviour, each containing some sub-categories, and provided insight into each category. Moreover, this paper presents insightful recommendations for health institutions to enable them ensure that the adoption and implementation of a clinical trials informatics systems such as caBIG/CTMS will be satisfactory. Finally, this article presents 5 important gaps in the literature and calls for future research to fill those gaps.

Kozhevnikov, M, Elliott, J, Shephard, J & Gramann, K 2013, 'Neurocognitive and Somatic Components of Temperature Increases during g-Tummo Meditation: Legend and Reality', PLOS ONE, vol. 8, no. 3.
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Lei, S-IE, Chen, Y-C, Chen, H-T & Chang, C-F 2013, 'Interactive Physics-based Ink Splattering Art Creation', COMPUTER GRAPHICS FORUM, vol. 32, no. 7, pp. 147-156.
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Li, B, Chen, L, Zhu, X & Zhang, C 2013, 'Noisy but Non-malicious User Detection in Social Recommender Systems', World Wide Web, vol. 16, no. 5-6, pp. 677-699.
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Social recommender systems largely rely on user-contributed data to infer users' preference. While this feature has enabled many interesting applications in social networking services, it also introduces unreliability to recommenders as users are allowed to insert data freely. Although detecting malicious attacks from social spammers has been studied for years, little work was done for detecting Noisy but Non-Malicious Users (NNMUs), which refers to those genuine users who may provide some untruthful data due to their imperfect behaviors. Unlike colluded malicious attacks that can be detected by finding similarly-behaved user profiles, NNMUs are more difficult to identify since their profiles are neither similar nor correlated from one another. In this article, we study how to detect NNMUs in social recommender systems. Based on the assumption that the ratings provided by a same user on closely correlated items should have similar scores, we propose an effective method for NNMU detection by capturing and accumulating userâs âself-contradictionsâ, i.e., the cases that a user provides very different rating scores on closely correlated items. We show that self-contradiction capturing can be formulated as a constrained quadratic optimization problem w.r.t. a set of slack variables, which can be further used to quantify the underlying noise in each test user profile. We adopt three real-world data sets to empirically test the proposed method. The experimental results show that our method (i) is effective in real-world NNMU detection scenarios, (ii) can significantly outperform other noisy-user detection methods, and (iii) can improve recommendation performance for other users after removing detected NNMUs from the recommender system.

Li, J & Tao, D 2013, 'A Bayesian Hierarchical Factorization Model for Vector Fields', IEEE Transactions On Image Processing, vol. 22, no. 11, pp. 4510-4521.
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Factorization-based techniques explain arrays of observations using a relatively small number of factors and provide an essential arsenal for multi-dimensional data analysis. Most factorization models are, however, developed on general arrays of scalar v

Li, J & Tao, D 2013, 'Exponential Family Factors For Bayesian Factor Analysis', IEEE Transactions On Neural Networks And Learning Systems, vol. 24, no. 6, pp. 964-976.
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Expressing data as linear functions of a small number of unknown variables is a useful approach employed by several classical data analysis methods, e.g., factor analysis, principal component analysis, or latent semantic indexing. These models represent the data using the product of two factors. In practice, one important concern is how to link the learned factors to relevant quantities in the context of the application. To this end, various specialized forms of the factors have been proposed to improve interpretability. Toward developing a unified view and clarifying the statistical significance of the specialized factors, we propose a Bayesian model family. We employ exponential family distributions to specify various types of factors, which provide a unified probabilistic formulation. A Gibbs sampling procedure is constructed as a general computation routine. We verify the model by experiments, in which the proposed model is shown to be effective in both emulating existing models and motivating new model designs for particular problem settings.

Li, J & Tao, D 2013, 'Simple Exponential Family PCA', IEEE Transactions on Neural Networks and Learning Systems, vol. 24, no. 3, pp. 485-497.
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Principal component analysis (PCA) is a widely used model for dimensionality reduction. In this paper, we address the problem of determining the intrinsic dimensionality of a general type data population by selecting the number of principal components for a generalized PCA model. In particular, we propose a generalized Bayesian PCA model, which deals with general type data by employing exponential family distributions. Model selection is realized by empirical Bayesian inference of the model. We name the model as simple exponential family PCA (SePCA), since it embraces both the principal of using a simple model for data representation and the practice of using a simplified computational procedure for the inference. Our analysis shows that the empirical Bayesian inference in SePCA formally realizes an intuitive criterion for PCA model selection - a preserved principal component must sufficiently correlate to data variance that is uncorrelated to the other principal components. Experiments on synthetic and real data sets demonstrate effectiveness of SePCA and exemplify its characteristics for model selection.

Li, J, Bian, W, Tao, D & Zhang, C 2013, 'Learning Colours From Textures By Sparse Manifold Embedding', Signal Processing, vol. 93, no. 6, pp. 1485-1495.
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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 manual or limited automatic colour assignment involves intensive human

Li, J, Talaei-Khoei, A, Seale, H & Ray, P 2013, 'Health Care Provider Adoption of eHealth: Systematic Literature Review', Interactive Journal of Medical Research, vol. 2, no. 1, pp. 1-19.
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Background: eHealth is an application of information and communication technologies across the whole range of functions that affect health. The benefits of eHealth (eg, improvement of health care operational efficiency and quality of patient care) have previously been documented in the literature. Health care providers (eg, medical doctors) are the key driving force in pushing eHealth initiatives. Without their acceptance and actual use, those eHealth benefits would be unlikely to be reaped. Objective: To identify and synthesize influential factors to health care providers acceptance of various eHealth systems. Methods: This systematic literature review was conducted in four steps. The first two steps facilitated the location and identification of relevant articles. The third step extracted key information from those articles including the studies characteristics and results. In the last step, identified factors were analyzed and grouped in accordance with the Unified Theory of Acceptance and Use of Technology (UTAUT). Results: This study included 93 papers that have studied health care providers acceptance of eHealth. From these papers, 40 factors were identified and grouped into 7 clusters: (1) health care provider characteristics, (2) medical practice characteristics, (3) voluntariness of use, (4) performance expectancy, (5) effort expectancy, (6) social influence, and (7) facilitating or inhibiting conditions. Conclusions: The grouping results demonstrated that the UTAUT model is useful for organizing the literature but has its limitations. Due to the complex contextual dynamics of health care settings, our work suggested that there would be potential to extend theories on information technology adoption, which is of great benefit to readers interested in learning more on the topic. Practically, these findings may help health care decision makers proactively introduce interventions to encourage acceptance of eHealth and may also assist health policy maker...

Li, L, Xu, G, Yang, Z, Dolog, P, Zhang, Y & Kitsuregawa, M 2013, 'An efficient approach to suggesting topically related web queries using hidden topic model', World Wide Web, vol. 16, no. 3, pp. 273-297.
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Keyword-based Web search is a widely used approach for locating information on the Web. However, Web users usually suffer from the difficulties of organizing and formulating appropriate input queries due to the lack of sufficient domain knowledge, which greatly affects the search performance. An effective tool to meet the information needs of a search engine user is to suggest Web queries that are topically related to their initial inquiry. Accurately computing query-to-query similarity scores is a key to improve the quality of these suggestions. Because of the short lengths of queries, traditional pseudo-relevance or implicit-relevance based approaches expand the expression of the queries for the similarity computation. They explicitly use a search engine as a complementary source and directly extract additional features (such as terms or URLs) from the top-listed or clicked search results. In this paper, we propose a novel approach by utilizing the hidden topic as an expandable feature. This has two steps. In the offline model-learning step, a hidden topic model is trained, and for each candidate query, its posterior distribution over the hidden topic space is determined to re-express the query instead of the lexical expression. In the online query suggestion step, after inferring the topic distribution for an input query in a similar way, we then calculate the similarity between candidate queries and the input query in terms of their corresponding topic distributions; and produce a suggestion list of candidate queries based on the similarity scores. Our experimental results on two real data sets show that the hidden topic based suggestion is much more efficient than the traditional term or URL based approach, and is effective in finding topically related queries for suggestion.

Li, S-Y, Yang, C-H, Chen, S-A, Ko, L-W & Lin, C-T 2013, 'Fuzzy adaptive synchronization of time-reversed chaotic systems via a new adaptive control strategy', INFORMATION SCIENCES, vol. 222, pp. 486-500.
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Li, SY, Yang, CH, Ko, LW, Lin, CT & Ge, ZM 2013, 'Implementation on electronic circuits and RTR pragmatical adaptive synchronization: Time-reversed uncertain dynamical systems' analysis and applications', Abstract and Applied Analysis, vol. 2013, pp. 1-10.
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We expose the chaotic attractors of time-reversed nonlinear system, further implement its behavior on electronic circuit, and apply the pragmatical asymptotically stability theory to strictly prove that the adaptive synchronization of given master and slave systems with uncertain parameters can be achieved. In this paper, the variety chaotic motions of time-reversed Lorentz system are investigated through Lyapunov exponents, phase portraits, and bifurcation diagrams. For further applying the complex signal in secure communication and file encryption, we construct the circuit to show the similar chaotic signal of time-reversed Lorentz system. In addition, pragmatical asymptotically stability theorem and an assumption of equal probability for ergodic initial conditions (Ge et al., 1999, Ge and Yu, 2000, and Matsushima, 1972) are proposed to strictly prove that adaptive control can be accomplished successfully. The current scheme of adaptive control - by traditional Lyapunov stability theorem and Barbalat lemma, which are used to prove the error vector - approaches zero, as time approaches infinity. However, the core question - why the estimated or given parameters also approach to the uncertain parameters - remains without answer. By the new stability theory, those estimated parameters can be proved approaching the uncertain values strictly, and the simulation results are shown in this paper. © 2013 Shih-Yu Li et al.

Li, SY, Yang, CH, Lin, CT, Ko, LW & Chiu, TT 2013, 'Chaotic motions in the real fuzzy electronic circuits', Abstract and Applied Analysis, vol. 2013, pp. 1-8.
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Fuzzy electronic circuit (FEC) is firstly introduced, which is implementing Takagi-Sugeno (T-S) fuzzy chaotic systems on electronic circuit. In the research field of secure communications, the original source should be blended with other complex signals. Chaotic signals are one of the good sources to be applied to encrypt high confidential signals, because of its high complexity, sensitiveness of initial conditions, and unpredictability. Consequently, generating chaotic signals on electronic circuit to produce real electrical signals applied to secure communications is an exceedingly important issue. However, nonlinear systems are always composed of many complex equations and are hard to realize on electronic circuits. Takagi-Sugeno (T-S) fuzzy model is a powerful tool, which is described by fuzzy IF-THEN rules to express the local dynamics of each fuzzy rule by a linear system model. Accordingly, in this paper, we produce the chaotic signals via electronic circuits through T-S fuzzy model and the numerical simulation results provided by MATLAB are also proposed for comparison. T-S fuzzy chaotic Lorenz and Chen-Lee systems are used for examples and are given to demonstrate the effectiveness of the proposed electronic circuit. © 2013 Shih-Yu Li et al.

Liao, L-D, Chen, B-W, Tseng, KC, Ko, L-W, Wang, I-J, Chen, S-A, Chang, J-Y & Lin, C-T 2013, 'Design and Implementation of Wearable and Wireless Multi-Channel Brain-Computer Interface with the Novel Dry Sensors', Journal of Neuroscience and Neuroengineering, vol. 2, no. 5, pp. 477-484.
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Liao, S-H, Han, M-F, Chang, J-Y & Lin, C-T 2013, 'Study on Adaptive Least Trimmed Squares Fuzzy Neural Network', INTERNATIONAL JOURNAL OF FUZZY SYSTEMS, vol. 15, no. 3, pp. 338-346.
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Liaw, S, Rahimi, A, Ray, P, Taggart, J, Dennis, S, de Lusignan, S, Jalaludin, B, Yeo, A & Talaei-Khoei, A 2013, 'Towards an ontology for data quality in integrated chronic disease management: a realist review of the literature', International Journal Of Medical Informatics, vol. 82, no. 1, pp. 10-24.
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Purpose Effective use of routine data to support integrated chronic disease management (CDM) and population health is dependent on underlying data quality (DQ) and, for cross system use of data, semantic interoperability. An ontological approach to DQ is a potential solution but research in this area is limited and fragmented. Objective Identify mechanisms, including ontologies, to manage DQ in integrated CDM and whether improved DQ will better measure health outcomes. Methods A realist review of English language studies (January 2001March 2011) which addressed data quality, used ontology-based approaches and is relevant to CDM. Results We screened 245 papers, excluded 26 duplicates, 135 on abstract review and 31 on full-text review; leaving 61 papers for critical appraisal. Of the 33 papers that examined ontologies in chronic disease management, 13 defined data quality and 15 used ontologies for DQ. Most saw DQ as a multidimensional construct, the most used dimensions being completeness, accuracy, correctness, consistency and timeliness. The majority of studies reported tool design and development (80%), implementation (23%), and descriptive evaluations (15%). Ontological approaches were used to address semantic interoperability, decision support, flexibility of information management and integration/linkage, and complexity of information models. Conclusion DQ lacks a consensus conceptual framework and definition. DQ and ontological research is relatively immature with little rigorous evaluation studies published. Ontology-based applications could support automated processes to address DQ and semantic interoperability in repositories of routinely collected data to deliver integrated CDM. We advocate moving to ontology-based design of information systems to enable more reliable use of routine data to measure health mechanisms and impacts.

Liaw, ST, Rahimi, A, Ray, P, Taggart, J, Dennis, S, de Lusignan, S, Jalaludin, B, Yeo, AET & Talaei-Khoei, A 2013, 'Towards an ontology for data quality in integrated chronic disease management: A realist review of the literature (vol 82, pg 10, 2013)', INTERNATIONAL JOURNAL OF MEDICAL INFORMATICS, vol. 82, no. 2, pp. 139-139.
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Lim, CCW, Portmann, C, Tomamichel, M, Renner, R & Gisin, N 2013, 'Device-Independent Quantum Key Distribution with Local Bell Test', Physical Review X, vol. 3, pp. 1-11.
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Device-independent quantum key distribution (DIQKD) in its current design requires a violation of a Bell’s inequality between two parties, Alice and Bob, who are connected by a quantum channel. However, in reality, quantum channels are lossy and current DIQKD protocols are thus vulnerable to attacks exploiting the detection loophole of the Bell test. Here, we propose a novel approach to DIQKD that overcomes this limitation. In particular, we propose a protocol where the Bell test is performed entirely on two casually independent devices situated in Alice’s laboratory. As a result, the detection loophole caused by the losses in the channel is avoided

Lin, C-L, Jung, T-P, Chuang, S-W, Duann, J-R, Lin, C-T & Chiu, T-W 2013, 'Self-adjustments may account for the contradictory correlations between HRV and motion-sickness severity', INTERNATIONAL JOURNAL OF PSYCHOPHYSIOLOGY, vol. 87, no. 1, pp. 70-80.
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Lin, CT, Hsu, SC, Chou, KP, Siana, L & Yang, CT 2013, 'Real-time boosted vehicle detection deal with high detection rate using false alarm eliminating method', International Journal of Innovative Computing, Information and Control, vol. 9, no. 7, pp. 3039-3052.
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We present in this paper a high detection rate of Boosted vehicle detection. The positive database of Boosted training usually consists of similar contour or lighting of vehicle image, but in our work the training data is extracted from both daytime and evening images, it means different in lighting, and we are forced to stop Boosted training toward a high detection rate, which results in a relatively high false alarm rate. Therefore, the Boosted detector will detect vehicle candidate as much as possible. Moreover, we develop two false alarm eliminating methods to eliminate the false vehicle candidates. The algorithm consists of edge complexity for daytime case, and combination histogram matching and intensity complexity for evening case. Each case is chosen by automatic switcher algorithm. To provide real-time detection, we also proposed position based sliding window detector. The idea is based on sliding windows size selection relative to the position of vehicle candidate in an image. Thus, we do not need to apply various size of detector size as traditional Boosted algorithm. Finally, our experimental results show that our proposed system can operate in a real-world environment, while providing realtime detection. © 2013 ICIC International.

Lin, C-T, Hsu, S-C, Lee, J-F & Yang, C-T 2013, 'Boosted Vehicle Detection Using Local and Global Features', Journal of Signal and Information Processing, vol. 04, no. 03, pp. 243-252.
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This study presents a boosted vehicle detection system. It first hypothesizes potential locations of vehicles to reduce the computational costs by a statistic of the edge intensity and symmetry, then verifies the accuracy of the hypotheses using AdaBoost and Probabilistic Decision-Based Neural Network (PDBNN) classifiers, which exploit local and global features of vehicles, respectively. The combination of 2 classifiers can be used to learn the complementary relationship between local and global features, and it gains an extremely low false positive rate while maintaining a high detection rate. For the MIT Center for Biological & Computational Learning (CBCL) database, a 96.3% detection rate leads to a false alarm rate of approximately 0.0013%. The objective of this study is to extract the characteristic of vehicles in both local- and global-orientation, and model the implicit invariance of vehicles. This boosted approach provides a more effective solution to handle the problems encountered by conventional background-based detection systems. The experimental results of this study prove that the proposed system achieves good performance in detecting vehicles without background information. The implemented system also extract useful traffic information that can be used for further processing, such as tracking, counting, classification, and recognition.

Lin, C-T, Huang, K-C, Chuang, C-H, Ko, L-W & Jung, T-P 2013, 'Can arousing feedback rectify lapses in driving? Prediction from EEG power spectra', JOURNAL OF NEURAL ENGINEERING, vol. 10, no. 5.
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Lin, C-T, Tsai, S-F & Ko, L-W 2013, 'EEG-Based Learning System for Online Motion Sickness Level Estimation in a Dynamic Vehicle Environment', IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, vol. 24, no. 10, pp. 1689-1700.
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Lin, Q, Zhang, Y, Zhang, W & Lin, X 2013, 'Efficient general spatial skyline computation', World Wide Web, vol. 16, no. 3, pp. 247-270.
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With the emergence of location-aware mobile device technologies, communication technologies and GPS systems, the location based queries have attracted great attentions in the database literature. In many user recommendation web services, the spatial preference query is used to suggest the objects based on their spatial proximity with the facilities. In this paper, we study the problem of general spatial skyline (GSSKY) which can provide the minimal candidate set of the optimal solutions for any monotonic distance based spatial preference query. Efficient progressive algorithm called P-GSSKY is proposed to significantly reduce the number of non-promising objects in the computation. Moreover, we also propose spatial join based algorithm, called J-GSSKY, which can compute GSSKY efficiently in terms of I/O cost. The paper conducts a comprehensive performance study of the proposed techniques based on both real and synthetic data

Lin, Y-Y, Chang, J-Y & Lin, C-T 2013, 'Identification and Prediction of Dynamic Systems Using an Interactively Recurrent Self-Evolving Fuzzy Neural Network', IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, vol. 24, no. 2, pp. 310-321.
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Lin, Y-Y, Chang, J-Y, Pal, NR & Lin, C-T 2013, 'A Mutually Recurrent Interval Type-2 Neural Fuzzy System (MRIT2NFS) With Self-Evolving Structure and Parameters', IEEE TRANSACTIONS ON FUZZY SYSTEMS, vol. 21, no. 3, pp. 492-509.
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Liu, L, Chen, X, Luo, D, Lu, Y, Xu, G & Liu, M 2013, 'HSC: A spectral clustering algorithm combined with hierarchical method', Neural Network World, vol. 23, no. 6, pp. 499-521.
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Most of the traditional clustering algorithms are poor for clustering more complex structures other than the convex spherical sample space. In the past few years, several spectral clustering algorithms were proposed to cluster arbitrarily shaped data in various real applications. However, spectral clustering relies on the dataset where each cluster is approximately well separated to a certain extent. In the case that the cluster has an obvious inflection point within a non-convex space, the spectral clustering algorithm would mistakenly recognize one cluster to be different clusters. In this paper, we propose a novel spectral clustering algorithm called HSC combined with hierarchical method, which obviates the disadvantage of the spectral clustering by not using the misleading information of the noisy neighboring data points. The simple clustering procedure is applied to eliminate the misleading information, and thus the HSC algorithm could cluster both convex shaped data and arbitrarily shaped data more efficiently and accurately. The experiments on both synthetic data sets and real data sets show that HSC outperforms other popular clustering algorithms. Furthermore, we observed that HSC can also be used for the estimation of the number of clusters

Liu, S, Law, R, Rong, J, Li, G & Hall, J 2013, 'Analyzing changes in hotel customers' expectations by trip mode', INTERNATIONAL JOURNAL OF HOSPITALITY MANAGEMENT, vol. 34, pp. 359-371.
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Lu, J, Niu, L & Zhang, G 2013, 'A Situation Retrieval Model for Cognitive Decision Support in Digital Business Ecosystems', IEEE Transactions On Industrial Electronics, vol. 60, no. 3, pp. 1059-1069.
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This paper presents a novel situation retrieval (SR) model for supporting cognition-driven decision processes in digital business ecosystems. Cognitive decision support in digital ecosystems is concerned with decision makers cognitive processes. This study aims to facilitate cognitive decision support to decision makers on the basis of current business intelligence (BI) platform. Underlying foundations of the SR model are two types of mental constructs: situation awareness (SA) and mental models of decision makers and the model of naturalistic decision making (NDM). These mental constructs and NDM are integrated into the BI application framework. Our experiments showed that the SR model was playing a nontrivial role to help decision makers develop enhanced SA and reuse their past experience to make better decisions.

Lu, J, Shambour, QY, Xu, Y, Lin, Q & Zhang, G 2013, 'A web-based personalized business partner recommendation system using fuzzy semantic techniques', Computational Intelligence, vol. 29, no. 1, pp. 37-69.
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The web provides excellent opportunities to businesses in various aspects of development such as finding a business partner online. However, with the rapid growth of web information, business users struggle with information overload and increasingly find it difficult to locate the right information at the right time. Meanwhile, small and medium businesses (SMBs), in particular, are seeking one-to-one e-services from government in current highly competitive markets. How can business users be provided with information and services specific to their needs, rather than an undifferentiated mass of information? An effective solution proposed in this study is the development of personalized e-services. Recommender systems is an effective approach for the implementation of Personalized E-Service which has gained wide exposure in e-commerce in recent years. Accordingly, this paper first presents a hybrid fuzzy semantic recommendation (HFSR) approach which combines item-based fuzzy semantic similarity and item-based fuzzy collaborative filtering (CF) similarity techniques. This paper then presents the implementation of the proposed approach into an intelligent recommendation system prototype called Smart BizSeeker, which can recommend relevant business partners to individual business users, particularly for SMBs. Experimental results show that the HFSR approach can help overcome the semantic limitations of classical CF-based recommendation approaches, namely sparsity and new cold start item problems.

Lunghi, T, Kaniewski, J, Bussieres, F, Houlmann, R, Tomamichel, M, Kent, A, Gisin, N, Wehner, S & Zbinden, H 2013, 'Experimental Bit Commitment Based on Quantum Communication and Special Relativity', PHYSICAL REVIEW LETTERS, vol. 111, no. 18.
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Luo, Z, Hu, Z, Song, Y, Xu, Z & Lu, H 2013, 'Optimal Coordination of Plug-In Electric Vehicles in Power Grids With Cost-Benefit Analysis-Part I: Enabling Techniques', IEEE Transactions on Power Systems, vol. 28, no. 4, pp. 3546-3555.
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Plug-in electric vehicles (PEVs) appear to offer a promising option for mitigating greenhouse emission. However, uncoordinated PEV charging can weaken the reliability of power systems. The proper accommodation of PEVs in a power grid imposes many challenges on system planning and operations. This work aims to investigate optimal PEV coordination strategies with cost-benefit analysis. In Part I, we first present a new method to calculate the charging load of PEVs with a modified Latin hypercube sampling (LHS) method for handling the stochastic property of PEVs. We then propose a new two-stage optimization model to discover the optimal charging states of PEVs in a given day. Using this model, the peak load with charging load of PEVs is minimized in the first stage and the load fluctuation is minimized in the second-stage with peak load being fixed as the value obtained in the first stage. An algorithm based on linear mixed-integer programming is provided as a suitable solution method with fast computation. Finally, we present a new method to calculate the benefit and cost for a PEV charging and discharging coordination strategy from a social welfare approach. These methods are useful for developing PEV coordination strategies in power system planning and supporting PEV-related policy making.

Luo, Z, Hu, Z, Song, Y, Xu, Z & Lu, H 2013, 'Optimal Coordination of Plug-in Electric Vehicles in Power Grids With Cost-Benefit AnalysisPart II: A Case Study in China', IEEE Transactions on Power Systems, vol. 28, no. 4, pp. 3556-3565.
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Continuing with a set of enabling techniques for the optimal coordination of plug-in electric vehicles (PEVs) in Part I, we present a case study in this paper using techniques based on the data collected in the BeijingTianjinTangshan Region (BTTR) China to discover optimal PEV coordination strategies and assess the attractiveness of these strategies. In Part II, we first present the charging characteristics for different categories of PEVs in BTTR and predict the optimal seasonal daily loads with PEVs under different PEV penetration levels using a two-stage optimization model in both 2020 and 2030. The simulation results indicate that optimal PEV coordination effectively reduces the peak load and smooths the load curve. Finally, we present a cost-benefit analysis of optimal coordination strategies by taking a social welfare approach. The analysis shows that the optimal coordination strategies are beneficial in terms of the reduction in capital investment in power grid expansion and that the attractiveness of a coordination strategy is related to the coordination level. The results also show that the fully coordinated charging and vehicle to grid are not the most attractive strategies. This case study is useful for better understanding the costs and benefits of PEV coordination strategies and for supporting PEV-related decision and policy making from a power system planning perspective.

Marshall, P, Antle, A, van den Hoven, E & Rogers, Y 2013, 'Introduction to the special issue on the theory and practice of embodied interaction in HCI and interaction design', ACM Transactions on Computer-Human Interaction (TOCHI), vol. 20, no. 1, pp. 1-3.
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Theories of embodiment focus on how practical engagement and the structure of the body shape perception, experience, and cognition. They typically reject a view of human cognition as grounded in abstract information processing. The concept of embodied in

McDowell, K, Lin, C-T, Oie, KS, Jung, T-P, Gordon, S, Whitaker, KW, Li, S-Y, Lu, S-W & Hairston, WD 2013, 'Real-World Neuroimaging Technologies', IEEE ACCESS, vol. 1, pp. 131-149.
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McGregor, C 2013, 'Big Data in Neonatal Intensive Care', COMPUTER, vol. 46, no. 6, pp. 54-59.
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McGregor, C, Steadman, A, Percival, J & James, A 2013, 'Modelling health informatics capacity for neonatal intensive care patient journeys supported by interprofessional teams', International Journal of Biomedical Engineering and Technology, vol. 11, no. 3, pp. 301-317.
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Neonatal intensive care is a highly complex area of healthcare requiring coordinated care between multiple healthcare professionals; as a result, information flow within the Neonatal Intensive Care Unit (NICU) can be very complex and impact quality of care. This paper presents initial research findings based on the use of the patient journey modelling technique known as PaJMa to audit the current state of health informatics within NICUs in Canada. In this paper, a case study including three Ontario NICUs is utilised and their 'Investigations' processes are modelled using PaJMa. Copyright © 2013 Inderscience Enterprises Ltd.

Meng, HD, Wu, PF, Song, YC & Xu, GD 2013, 'Research of clustering algorithm based on different data field model', Advanced Materials Research, vol. 760-762, pp. 1925-1929.
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Data field clustering algorithm possesses dynamic characteristics compared with other clustering algorithms. By changing the parameters of the data field model, the results can be dynamically adjusted to meet the target of feature extraction and knowledge discovery in different scales, but the selection and construction of data field model can give rise to different clustering results. This paper presents the different effectiveness of clustering based on various of data field models and its parameters, provides with the scheme to chose the best data field model fitting to the characteristics of the data radiation, and verifies that the best clustering effectiveness can be achieved with the value of radial energy in the golden section. © (2013) Trans Tech Publications, Switzerland.

Mueller-Lennert, M, Dupuis, F, Szehr, O, Fehr, S & Tomamichel, M 2013, 'On quantum Renyi entropies: A new generalization and some properties', JOURNAL OF MATHEMATICAL PHYSICS, vol. 54, no. 12.
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Musial, K & Kazienko, P 2013, 'Social networks on the Internet', WORLD WIDE WEB-INTERNET AND WEB INFORMATION SYSTEMS, vol. 16, no. 1, pp. 31-72.
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Musial, K, Budka, M & Blysz, W 2013, 'Understanding the Other Side - The Inside Story of the INFER Project', Smart Innovation, Systems and Technologies, vol. 18, pp. 1-9.
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In the last few years, the collaboration between research institutions and industry has become a well established process. Transfer of Knowledge (ToK) is required to accelerate the development of both sides and to enable them to unlock their full potential. European Commission within the Marie Curie Industry and Academia Partnerships & Pathways (IAPP) programme supports the cooperation between these two sectors at the international scale by funding research projects that as one of the objectives aim at enhancing human mobility. IAPP projects offer people from different institutions the possibility to move sector and country in order to provide, absorb and implement new knowledge in a professional industrial-academic environment. In this paper, one of such projects is presented and both academia and industry perspectives in regard to opportunities and challenges in Transfer of Knowledge are described. Computational Intelligence Platform for Evolving and Robust Predictive Systems (INFER) is the IAPP project that serves as a case study for this paper. © Springer-Verlag Berlin Heidelberg 2013.

Musial, K, Budka, M & Juszczyszyn, K 2013, 'Creation and growth of online social network How do social networks evolve?', WORLD WIDE WEB-INTERNET AND WEB INFORMATION SYSTEMS, vol. 16, no. 4, pp. 421-447.
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Najaftorkaman, M, Ghapanchi, AH, Talaei-Khoei, A & Ray, P 2013, 'Recent Research Areas and Grand Challenges in Security of Electronic Medical Records', International Technology Management Review, vol. 3, no. 1, pp. 12-21.
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This study undertook a literature survey to provide a taxonomy that represents research areas of Electronic Medical Record (EMR). We identified the following areas of research and classified them into eight main categories: design and implementation, evaluation, adoption, impacts, medical research, integration, EMR data design and management, and policy and standards. Even though EMR improves care quality and efficiency in a positive way, some negative perceptions by the health user community (health professionals and health service managers) should not be neglected. By categorizing EMR research articles, we reveal a clear set of grand challenges of EMR in the future education and research in health informatics, biomedical engineering, and related areas. A big picture of EMR research areas presented in this study helps health community to find scientific methods for various grand challenges in EMR.

Nguyen, Q, Qian, Y, Huang, M & Zhang, J 2013, 'Tabuvis: A Tool For Visual Analytics Multidimensional Datasets', Science China Information Sciences, vol. 56, no. 5, pp. 1-12.
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This paper describes TabuVis, a light weight visual analytics system that provides a flexible, customizable and effective visualization for multidimensional data. Key aspects for visually analyzing data with multiple attributes are quality and appropriateness of the analytical platform whose presentation can be adjusted via domain experts. Our commercial-free and comprehensive prototype utilizes scatter-plot approach to support the visual analytics process. The system consists of multiple components enabling the complete analysis process, including data processing, automatic marks, customizable interactive visualization and filtering. We demonstrate the effectiveness of TabuVis on various case studies using medical and Oscars datasets.

Niazi, M, Ikram, N, Gill, AQ & Ul Hassan, MR 2013, 'Special Issue on 'Empirical Studies in Software Engineering'', IET SOFTWARE, vol. 7, no. 6, pp. 295-297.
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Niu, L, Lu, J, Zhang, G & Wu, D 2013, 'FACETS: A Cognitive Business Intelligence System', Information Systems, vol. 38, no. 6, pp. 835-862.
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A cognitive decision support system called FACETS was developed and evaluated based on the situation retrieval (SR) model. The aim of FACETS is to provide decision makers cognitive decision support in ill-structured decision situations. The design and de

Nizami, S, Green, JR & McGregor, C 2013, 'Implementation of artifact detection in critical care: A methodological review', IEEE Reviews in Biomedical Engineering, vol. 6, pp. 127-142.
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Artifact detection (AD) techniques minimize the impact of artifacts on physiologic data acquired in critical care units (CCU) by assessing quality of data prior to clinical event detection (CED) and parameter derivation (PD). This methodological review introduces unique taxonomies to synthesize over 80 AD algorithms based on these six themes: 1) CCU; 2) physiologic data source; 3) harvested data; 4) data analysis; 5) clinical evaluation; and 6) clinical implementation. Review results show that most published algorithms: a) are designed for one specific type of CCU; b) are validated on data harvested only from one OEM monitor; c) generate signal quality indicators (SQI) that are not yet formalized for useful integration in clinical workflows; d) operate either in standalone mode or coupled with CED or PD applications; e) are rarely evaluated in real-time; and f) are not implemented in clinical practice. In conclusion, it is recommended that AD algorithms conform to generic input and output interfaces with commonly defined data: 1) type; 2) frequency; 3) length; and 4) SQIs. This shall promote: a) reusability of algorithms across different CCU domains; b) evaluation on different OEM monitor data; c) fair comparison through formalized SQIs; d) meaningful integration with other AD, CED and PD algorithms; and e) real-time implementation in clinical workflows. © 2008-2011 IEEE.

Oberst, S, Lai, JCS & Marburg, S 2013, 'Guidelines for numerical vibration and acoustic analysis of disc brake squeal using simple models of brake systems', JOURNAL OF SOUND AND VIBRATION, vol. 332, no. 9, pp. 2284-2299.
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Pang, LX, Chawla, S, Liu, W & Zheng, Y 2013, 'On detection of emerging anomalous traffic patterns using GPS data', DATA & KNOWLEDGE ENGINEERING, vol. 87, pp. 357-373.
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Parvin, S, Hussain, FK & Hussain, OK 2013, 'Conjoint trust assessment for secure communication in cognitive radio networks', Mathematical And Computer Modelling, vol. 58, no. 5-6, pp. 1340-1350.
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With the rapid development of wireless communication, the growth of Cognitive Radio (CR) is increasing day by day. Because CR is flexible and operates on the wireless network, there are more security threats to CR technology than to the traditional radio environment. In addition, there is no comprehensive framework for achieving security in Cognitive Radio Networks (CRNs), and the role of trust for achieving security in CRNs has not been explored previously. Security vulnerability in cognitive radio technology is unavoidable due to the intrinsic nature of the technology, so it is critical to ensure system security in CRNs. The issue of secure communication in CRNs thus becomes more important than it is in conventional wireless networks. In this paper, we propose a conjoint trust assessment approach (combining trust assessment from the Primary User Network and the Secondary User Network) in a CRN to solve the security threats brought about by untrustworthy entities, such as selfish, malicious, and faultless nodes, and to ensure secure spectrum sharing in CRNs. A numerical analysis shows the feasibility of our proposed approach.

Parvin, S, Hussain, FK, Hussain, OK, Thein, T & Park, JS 2013, 'Multi-Cyber Framework for Availability Enhancement of Cyber Physical Systems', Computing, vol. 95, no. 10-11, pp. 927-948.
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With the rapid growth of wireless communication, the deployment of cyber-physical system (CPS) is increasing day by day. As a cyber physical system involves a tight coupling between the physical and computational components, it is critical to ensure that the system, apart from being secure, is available for both the cyber and physical processes. Traditional methods have generally been employed to defend an infrastructure system against physical threats. However, this does not guarantee that the availability of the system will always be high. In this paper, we propose a multi-cyber (computational unit) framework to improve the availability of CPS based on Markov model. We evaluate the effectiveness of our proposed framework in terms of availability, downtime, downtime cost and reliability of the CPS framework.

Raza, AN, Rajput, N & Safeer-e-Hussain, S 2013, 'Karachi Koalas 3D Simulation Soccer Team Team Description Paper for World RoboCup 2013'.

Redshaw, S, Harrison, K, Johnson, A & Chang, E 2013, 'Community nurses' perceptions of providing bereavement care', INTERNATIONAL JOURNAL OF NURSING PRACTICE, vol. 19, no. 3, pp. 344-350.
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Rehman, Z, Hussain, FK & Hussain, OK 2013, 'Frequency-based similarity measure for multimedia recommender systems', Multimedia Systems, vol. 19, no. 2, pp. 95-102.
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Personalized recommendation has become a pivotal aspect of online marketing and e-commerce as a means of overcoming the information overload problem. There are several recommendation techniques but collaborative recommendation is the most effective and widely used technique. It relies on either item-based or user-based nearest neighborhood algorithms which utilize some kind of similarity measure to assess the similarity between different users or items for generating the recommendations. In this paper, we present a new similarity measure which is based on rating frequency and compare its performance with the current most commonly used similarity measures. The applicability and use of this similarity measure from the perspective of multimedia content recommendation is presented and discussed

Ren, Y, Li, G & Zhou, W 2013, 'A learning method for Top-N recommendations with incomplete data', Social Network Analysis and Mining, vol. 3, no. 4, pp. 1135-1148.
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© 2013, Springer-Verlag Wien. In this paper, we tackle the incompleteness of user rating history in the context of collaborative filtering for Top-N recommendations. Previous research ignore a fact that two rating patterns exist in the user × item rating matrix and influence each other. More importantly, their interactive influence characterizes the development of each other, which can consequently be exploited to improve the modelling of rating patterns, especially when the user × item rating matrix is highly incomplete due to the well-known data sparsity issue. This paper proposes a Rating Pattern Subspace to iteratively re-optimize the missing values in each user’s rating history by modelling both the global and the personal rating patterns simultaneously. The basic idea is to project the user × item rating matrix on a low-rank subspace to capture the global rating patterns. Then, the projection of each individual user on the subspace is further optimized according to his/her own rating history and the captured global rating patterns. Finally, the optimized user projections are used to improve the modelling of the global rating patterns. Based on this subspace, we propose a RapSVD-L algorithm for Top-N recommendations. In the experiments, the performance of the proposed method is compared with the state-of-the-art Top-N recommendation methods on two real datasets under various data sparsity levels. The experimental results show that RapSVD-L outperforms the compared algorithms not only on the all items recommendations but also on the long tail item recommendations in terms of accuracy.

Ren, Y, Li, G, Zhang, J & Zhou, W 2013, 'Lazy collaborative filtering for data sets with missing values', IEEE Transactions on Cybernetics, vol. 43, no. 6, pp. 1822-1834.
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As one of the biggest challenges in research on recommender systems, the data sparsity issue is mainly caused by the fact that users tend to rate a small proportion of items from the huge number of available items. This issue becomes even more problematic for the neighborhood-based collaborative filtering (CF) methods, as there are even lower numbers of ratings available in the neighborhood of the query item. In this paper, we aim to address the data sparsity issue in the context of neighborhood-based CF. For a given query (user, item), a set of key ratings is first identified by taking the historical information of both the user and the item into account. Then, an auto-adaptive imputation (AutAI) method is proposed to impute the missing values in the set of key ratings. We present a theoretical analysis to show that the proposed imputation method effectively improves the performance of the conventional neighborhood-based CF methods. The experimental results show that our new method of CF with AutAI outperforms six existing recommendation methods in terms of accuracy. © 2013 IEEE.

Saberi, M, Mirtalaie, M, Hussain, FK, Azadeh, A, Hussain, O & Ashjari, B 2013, 'A granular computing-based approach to credit scoring modeling', Neurocomputing, vol. 122, no. 1, pp. 100-115.
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The credit card industry has been growing rapidly and thus huge numbers of consumers' credit data are collected by the credit department of the banks. The credit scoring managers often evaluate the consumer's credit with intuitive experience. However, wi

Szehr, O, Dupuis, F, Tomamichel, M & Renner, R 2013, 'Decoupling with unitary approximate two-designs', NEW JOURNAL OF PHYSICS, vol. 15.
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Tafavogh, S, Felix Navarro, KM, Catchpoole, DR & Kennedy, PJ 2013, 'Non-parametric and integrated framework for segmenting and counting neuroblastic cells within neuroblastoma tumor images', Medical & biological engineering & computing, vol. 51, no. 6, pp. 645-665.
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Neuroblastoma is a malignant tumor and a cancer in childhood that derives from the neural crest. The number of neuroblastic cells within the tumor provides significant prognostic information for pathologists. An enormous number of neuroblastic cells makes the process of counting tedious and error-prone. We propose a user interaction-independent framework that segments cellular regions, splits the overlapping cells and counts the total number of single neuroblastic cells. Our novel segmentation algorithm regards an image as a feature space constructed by joint spatial-intensity features of color pixels. It clusters the pixels within the feature space using mean-shift and then partitions the image into multiple tiles. We propose a novel color analysis approach to select the tiles with similar intensity to the cellular regions. The selected tiles contain a mixture of single and overlapping cells. We therefore also propose a cell counting method to analyse morphology of the cells and discriminate between overlapping and single cells. Ultimately, we apply watershed to split overlapping cells. The results have been evaluated by a pathologist. Our segmentation algorithm was compared against adaptive thresholding. Our cell counting algorithm was compared with two state of the art algorithms. The overall cell counting accuracy of the system is 87.65 %

Tang, J, Bian, W, Yu, N & Zhang, Y 2013, 'Intelligent processing techniques for semantic-based image and video retrieval', Neurocomputing, vol. 119, no. 1, pp. 1-2.
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Rapid advances in technology for capturing, processing, distributing, storing, and presenting visual data have resulted in a proliferation of image and video data in human lives. The multimedia research community has widely recognized the importance of searching images or videos from a large-scale corpus or the Internet. Intelligent processing techniques are the most useful tools to achieve this objective and the recent years have witnessed very significant contributions of intelligent algorithms in multimedia search. Intelligent information processing, such as machine learning techniques, knowledge discovery and data mining, computer vision and cognitive computation, natural language processing, and intelligent humanmachine interfaces, have great influence on extracting the semantic information for image and video data. These techniques light a way to make the semantic-based image/video retrieval come true. At least, they provide us a reasonable direction to touch the semantic retrieval. The goals of this special issue are three-fold: (1) introduce novel research in intelligent processing techniques for semantic-based image and video retrieval; (2) survey on the progress of this area in the past years; and (3) discuss new applications based on semantic-based image and video retrieval models.

Tang, J, Chen, L, King, I & Wang, J 2013, 'Introduction to Special section on Large-scale Data Mining', Data and Knowledge Engineering, vol. 87, pp. 355-356.
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Tomamichel, M & Haenggi, E 2013, 'The link between entropic uncertainty and nonlocality', JOURNAL OF PHYSICS A-MATHEMATICAL AND THEORETICAL, vol. 46, no. 5.
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Tomamichel, M & Hayashi, M 2013, 'A Hierarchy of Information Quantities for Finite Block Length Analysis of Quantum Tasks', IEEE TRANSACTIONS ON INFORMATION THEORY, vol. 59, no. 11, pp. 7693-7710.
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Tomamichel, M & Tan, VYF 2013, 'A Tight Upper Bound for the Third-Order Asymptotics for Most Discrete Memoryless Channels', IEEE TRANSACTIONS ON INFORMATION THEORY, vol. 59, no. 11, pp. 7041-7051.
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Tomamichel, M, Fehr, S, Kaniewski, J & Wehner, S 2013, 'A monogamy-of-entanglement game with applications to device-independent quantum cryptography', NEW JOURNAL OF PHYSICS, vol. 15.
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Van De Garde-Perik, E, Offermans, S, Van Boerdonk, K, Lenssen, KM & Van Den Hoven, E 2013, 'An analysis of input-output relations in interaction with smart tangible objects', ACM Transactions on Interactive Intelligent Systems, vol. 3, no. 2.
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This article focuses on the conceptual relation between the user's input and a system's output in interaction with smart tangible objects. Understanding this input-output relation (IO relation) is a prerequisite for the design of meaningful interaction. A meaningful IO relation allows the user to know what to do with a system to achieve a certain goal and to evaluate the outcome. The work discussed in this article followed a design research process in which four concepts were developed and prototyped. An evaluation was performed using these prototypes to investigate the effect of highly different IO relations on the user's understanding of the interaction. The evaluation revealed two types of IO relations differing in functionality and the number of mappings between the user and system actions. These two types of relations are described by two IO models that provide an overview of these mappings. Furthermore, they illustrate the role of the user and the influence of the system in the process of understanding the interaction. The analysis of the two types of IO models illustrates the value of understanding IO relations for the design of smart tangible objects. © 2013 ACM.

van den Hoven, E, van de Garde-Perik, E, Offermans, S, van Boerdonk, K & Lenssen, K 2013, 'Moving Tangible Interaction Systems to the Next Level', Computer, vol. 46, no. 8, pp. 70-76.
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Understanding tangible interactions foundational concepts can lead to systems with direct, integrated, and meaningful data control and representation.

Verma, P, Singh, R & Singh, AK 2013, 'A framework to integrate speech based interface for blind web users on the websites of public interest', Human-centric Computing and Information Sciences, vol. 3, no. 1, pp. 1-18.
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© 2013, Verma et al.; licensee Springer. Despite many assistive tools available for browsing the web, blind persons are not able to perform the tasks using internet that are done by persons without such disability. Even the futuristic social networking sites and other websites using the features of web 2.0 indicate a lesser accessible/responsible web. In this paper, we propose a framework, which can be used by the websites of public interest to make their important utilities better accessible and usable to blind web users. The approach is based on providing an alternate access system on the fly using one single website. The framework makes use of existing technologies like JavaScript, available speech APIs etc. and therefore provides a lightweight and robust solution to the accessibility problem. As a case study, we demonstrate the usefulness of the proposed framework by showing its working on a key functionality of the Indian Railways Reservation Website.

Vitanov, A, Dupuis, F, Tomamichel, M & Renner, R 2013, 'Chain Rules for Smooth Min- and Max-Entropies', IEEE TRANSACTIONS ON INFORMATION THEORY, vol. 59, no. 5, pp. 2603-2612.
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Wang, G, Zhou, W & Yang, LT 2013, 'Trust, security and privacy for pervasive applications', Journal of Supercomputing, vol. 64, no. 3, pp. 661-663.
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April 2013 Special section of the Journal of Supercomputer reviews high quality research papers that report the latest research achievements in trust, security and privacy for pervasive applications. The first paper, 'A Holistic Approach Examining RFID Design for Security and Privacy,' presents a holistic approach to ensure security and privacy for Radio Frequency Identification (RFID) systems. The second paper, 'Secure Localization and Location Verification in Wireless Sensor Networks: A Survey,' presents a survey on secure localization and location verification in wireless networks. Another paper, 'Requirements and Design for Neutral Trust Management Framework in Unstructured Networks,' designs a neutral trust management framework for MANETs, to ensure that users could obtain services free from discrimination or interference. One more paper, 'User Requirements-Aware Security Ranking in SSL Protocol, proposes a secret exchange algorithm for the Secure Socket Layer (SSL) handshake protocol.

Wang, X, Bian, W & Tao, D 2013, 'Grassmannian regularized structured multi-view embedding for image classification', IEEE Transactions On Image Processing, vol. 22, no. 7, pp. 2646-2660.
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Images are usually represented by features from multiple views, e.g., color and texture. In image classification, the goal is to fuse all the multi-view features in a reasonable manner and achieve satisfactory classification performance. However, the fea

Wen, S, Zhou, W, Zhang, J, Xiang, Y, Zhou, W & Jia, W 2013, 'Modeling propagation dynamics of social network worms', IEEE Transactions on Parallel and Distributed Systems, vol. 24, no. 8, pp. 1633-1643.
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Social network worms, such as email worms and facebook worms, pose a critical security threat to the Internet. Modeling their propagation dynamics is essential to predict their potential damages and develop countermeasures. Although several analytical models have been proposed for modeling propagation dynamics of social network worms, there are two critical problems unsolved: temporal dynamics and spatial dependence. First, previous models have not taken into account the different time periods of Internet users checking emails or social messages, namely, temporal dynamics. Second, the problem of spatial dependence results from the improper assumption that the states of neighboring nodes are independent. These two problems seriously affect the accuracy of the previous analytical models. To address these two problems, we propose a novel analytical model. This model implements a spatial-temporal synchronization process, which is able to capture the temporal dynamics. Additionally, we find the essence of spatial dependence is the spreading cycles. By eliminating the effect of these cycles, our model overcomes the computational challenge of spatial dependence and provides a stronger approximation to the propagation dynamics. To evaluate our susceptible-infectious-immunized (SII) model, we conduct both theoretical analysis and extensive simulations. Compared with previous epidemic models and the spatial-temporal model, the experimental results show our SII model achieves a greater accuracy. We also compare our model with the susceptible-infectious-susceptible and susceptible-infectious- recovered models. The results show that our model is more suitable for modeling the propagation of social network worms. © 1990-2012 IEEE.

Wu, J, Wang, J, Lu, H, Dong, Y & Lu, X 2013, 'Short Term Load Forecasting Technique Based On The Seasonal Exponential Adjustment Method And The Regression Model', Energy Conversion and Management, vol. 70, no. 1, pp. 1-9.
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For an energy-limited economy system, it is crucial to forecast load demand accurately. This paper devotes to 1-week-ahead daily load forecasting approach in which load demand series are predicted by employing the information of days before being similar to that of the forecast day. As well as in many nonlinear systems, seasonal item and trend item are coexisting in load demand datasets. In this paper, the existing of the seasonal item in the load demand data series is firstly verified according to the Kendall t correlation testing method. Then in the belief of the separate forecasting to the seasonal item and the trend item would improve the forecasting accuracy, hybrid models by combining seasonal exponential adjustment method (SEAM) with the regression methods are proposed in this paper, where SEAM and the regression models are employed to seasonal and trend items forecasting respectively. Comparisons of the quartile values as well as the mean absolute percentage error values demonstrate this forecasting technique can significantly improve the accuracy though models applied to the trend item forecasting are eleven different ones. This superior performance of this separate forecasting technique is further confirmed by the paired-sample T tests.

Wu, S-L, Liao, L-D, Lu, S-W, Jiang, W-L, Chen, S-A & Lin, C-T 2013, 'Controlling a Human-Computer Interface System With a Novel Classification Method that Uses Electrooculography Signals', IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, vol. 60, no. 8, pp. 2133-2141.
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Wu, Z, Xu, G, Lu, C, Chen, EX, Zhang, Y & Zhang, H 2013, 'Position-wise contextual advertising: Placing relevant ads at appropriate positions of a web page', Neurocomputing, vol. 120, no. 1, pp. 524-535.
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Web advertising, a form of online advertising, which uses the Internet as a medium to post product or service information and attract customers, has become one of the most important marketing channels. As one prevalent type of web advertising, contextual

Xu, G, Xu, YJ & Lee, W 2013, 'Guest editorial: social networks and social Web mining'.
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Xu, G, Yu, JX & Lee, W 2013, 'Social networks and social Web mining', World Wide Web-Internet And Web Information Systems, vol. 16, no. 5-6, pp. 541-544.
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Zhang, J, Chen, C, Xiang, Y, Zhou, W & Vasilakos, AV 2013, 'An effective network traffic classification method with unknown flow detection', IEEE Transactions on Network and Service Management, vol. 10, no. 2, pp. 133-147.
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Traffic classification technique is an essential tool for network and system security in the complex environments such as cloud computing based environment. The state-of-the-art traffic classification methods aim to take the advantages of flow statistical features and machine learning techniques, however the classification performance is severely affected by limited supervised information and unknown applications. To achieve effective network traffic classification, we propose a new method to tackle the problem of unknown applications in the crucial situation of a small supervised training set. The proposed method possesses the superior capability of detecting unknown flows generated by unknown applications and utilizing the correlation information among real-world network traffic to boost the classification performance. A theoretical analysis is provided to confirm performance benefit of the proposed method. Moreover, the comprehensive performance evaluation conducted on two real-world network traffic datasets shows that the proposed scheme outperforms the existing methods in the critical network environment. © 2004-2012 IEEE.

Zhang, J, Chen, C, Xiang, Y, Zhou, W & Xiang, Y 2013, 'Internet traffic classification by aggregating correlated naive bayes predictions', IEEE Transactions on Information Forensics and Security, vol. 8, no. 1, pp. 5-15.
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This paper presents a novel traffic classification scheme to improve classification performance when few training data are available. In the proposed scheme, traffic flows are described using the discretized statistical features and flow correlation information is modeled by bag-of-flow (BoF). We solve the BoF-based traffic classification in a classifier combination framework and theoretically analyze the performance benefit. Furthermore, a new BoF-based traffic classification method is proposed to aggregate the naive Bayes (NB) predictions of the correlated flows. We also present an analysis on prediction error sensitivity of the aggregation strategies. Finally, a large number of experiments are carried out on two large-scale real-world traffic datasets to evaluate the proposed scheme. The experimental results show that the proposed scheme can achieve much better classification performance than existing state-of-the-art traffic classification methods. © 2005-2012 IEEE.

Zhang, J, Huang, M & Hoang, DB 2013, 'Visual analytics for intrusion detection in spams', International Journal Grid and Utility Computing Vol X No X 20XX, vol. 4, no. 2/3, pp. 178-186.
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Spam email attacks are increasing at an alarming rate and have become more and more cunning in nature. This has necessitated the need for visual spam email analysis within an intrusion detection system to identify these attacks. The challenges are how to increase the accuracy of detection and how to visualise large volumes of spam email to better understand the analysis results and identify email attacks. This paper proposes a DensityWeight model that is to strengthen and extend the system capacity for analysis of network attacks in spam emails, including DDoS attacks. An interactive visual clustering method DATU is introduced to classify and display spam emails. The experimental results have shown that the proposed new model has improved the accuracy of intrusion detection and provides a better understanding of the nature of spam email attacks on though the network.

Zhang, J, Xiang, Y, Wang, Y, Zhou, W, Xiang, Y & Guan, Y 2013, 'Network traffic classification using correlation information', IEEE Transactions on Parallel and Distributed Systems, vol. 24, no. 1, pp. 104-117.
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Traffic classification has wide applications in network management, from security monitoring to quality of service measurements. Recent research tends to apply machine learning techniques to flow statistical feature based classification methods. The nearest neighbor (NN)-based method has exhibited superior classification performance. It also has several important advantages, such as no requirements of training procedure, no risk of overfitting of parameters, and naturally being able to handle a huge number of classes. However, the performance of NN classifier can be severely affected if the size of training data is small. In this paper, we propose a novel nonparametric approach for traffic classification, which can improve the classification performance effectively by incorporating correlated information into the classification process. We analyze the new classification approach and its performance benefit from both theoretical and empirical perspectives. A large number of experiments are carried out on two real-world traffic data sets to validate the proposed approach. The results show the traffic classification performance can be improved significantly even under the extreme difficult circumstance of very few training samples. © 2012 IEEE.

Zhang, J, Xiang, Y, Zhou, W & Wang, Y 2013, 'Unsupervised traffic classification using flow statistical properties and IP packet payload', Journal of Computer and System Sciences, vol. 79, no. 5, pp. 573-585.
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In network traffic classification, "unknown applications" is a difficult problem unsolved. Conventional supervised classification methods classify any traffic flow into predefined classes, while cannot handle unknown applications without corresponding supervised data. Some unsupervised clustering algorithms, such as k-means, have been applied to group traffic flows automatically, but a large number of resulting clusters are unable to correctly represent a small number of real applications. To address the problem of unknown applications, we propose a novel unsupervised approach which has the capability to discover application-based traffic classes and classify traffic flows according to their generation applications. In the proposed approach, flow statistical properties and IP packet payload are used in combination to discover traffic classes in the training stage. We introduce a bag-of-words (BoW) model to represent the content of clusters constructed by using flow statistical features, and apply the latent semantic analysis (LSA) to aggregate similar traffic clusters based on their payload content. In the testing stage, only flow statistical features are used to classify traffic flows, that can protect user privacy and deal with known encrypted applications without inspecting IP packets. A number of experiments are carried out on a real-world traffic dataset to demonstrate the effectiveness and robustness of the proposed approach. © 2012 Elsevier Inc.

Zhang, J, Ye, L, Xiang, Y & Zhou, W 2013, 'Robust image retrieval with hidden classes', Computer Vision and Image Understanding, vol. 117, no. 6, pp. 670-679.
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For the purpose of content-based image retrieval (CBIR), image classification is important to help improve the retrieval accuracy and speed of the retrieval process. However, the CBIR systems that employ image classification suffer from the problem of hidden classes. The queries associated with hidden classes cannot be accurately answered using a traditional CBIR system. To address this problem, a robust CBIR scheme is proposed that incorporates a novel query detection technique and a self-adaptive retrieval strategy. A number of experiments carried out on the two popular image datasets demonstrate the effectiveness of the proposed scheme. © 2013 Elsevier Inc.

Zhang, W, Lin, X, Zhang, Y, Wang, W, Zhu, G & Yu, JX 2013, 'Probabilistic Skyline Operator over Sliding Windows', Information Systems, vol. 38, no. 8, pp. 1212-1233.
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Skyline computation has many applications including multi-criteria decision making. In this paper, we study the problem of efficiently computing the skyline over sliding windows on uncertain data elements against probability thresholds. Firstly, we characterize the properties of elements to be kept in our computation. Then, we show the size of dynamically maintained candidate set and the size of skyline. Novel, efficient techniques are developed to process continuous probabilistic skyline queries over sliding windows. Finally, we extend our techniques to cover the applications where multiple probability thresholds are given, top-k skyline data objects are retrieved, or elements have individual life-spans. Our extensive experiments demonstrate that the proposed techniques are very efficient and can handle a high-speed data stream in real time.

Zhang, Z, Lin, H, Liu, K, Wu, D, Zhang, G & Lu, J 2013, 'A Hybrid Fuzzy-based Personalized Recommender System For Telecom Products/services', Information Sciences, vol. 235, no. 1, pp. 117-129.
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The Internet creates excellent opportunities for businesses to provide personalized online services to their customers. Recommender systems are designed to automatically generate personalized suggestions of products/services to customers. Because various uncertainties exist within both product and customer data, it is a challenge to achieve high recommendation accuracy. This study develops a hybrid recommendation approach which combines user-based and item-based collaborative filtering techniques with fuzzy set techniques and applies it to mobile product and service recommendation. It particularly implements the proposed approach in an intelligent recommender system software called Fuzzy-based Telecom Product Recommender System (FTCP-RS). Experimental results demonstrate the effectiveness of the proposed approach and the initial application shows that the FTCP-RS can effectively help customers to select the most suitable mobile products or services

Zong, Y, Jin, P, Xu, G & Guo, Y 2013, 'Local centrality information passing clustering algorithm for tags', Harbin Gongcheng Daxue Xuebao/Journal of Harbin Engineering University, vol. 34, no. 4, pp. 499-504.
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In recent years, most of the proposed tag clustering algorithms directly deal with the tag data by using traditional clustering algorithms, such as: K-means or Single-linkage devices. Nevertheless, the inherent drawbacks of using these traditional clustering algorithms have badly influenced the quality of tag clustering. In this paper, a clustering algorithm named local centrality information passing clustering (LCIPC) was proposed in an attempt to find out how to achieve high quality tag clustering results. First, we utilized the LCIPC, to construct a KNN directed neighbor graph G based on the similarities of the tag's; secondly, the local centrality value of every tag was calculated by using a KNN kernel density estimator; and thirdly, the local centrality value was passed onto the graph G by running a random walk method to generate global centrality rank listings. Eventually, tag clustering results were created based on global centrality ranking list by using an in-depth search first algorithm. The experimental results conducted utilizing three real world datasets indicate that the proposed LCIPC method has the ability of finding high quality tag clustering results.

Zong, Y, Jin, P, Xu, G & Pan, R 2013, 'A clustering algorithm based on local accumulative knowledge', Journal of Computers (Finland), vol. 8, no. 2, pp. 365-371.
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Clustering as an important unsupervised learning technique is widely used to discover the inherent structure of a given data set. For clustering is depended on applications, researchers use different models to defined clustering problems. Heuristic clustering algorithm is an efficient way to deal with clustering problem defined by combining optimization model, but initialization sensitivity is an inevitable problem. In the past decades, a lot of methods have been proposed to deal with such problem. In this paper, on the contrary, we take the advantage of the initialization sensitivity to design a new clustering algorithm. We, firstly, run K-means, a widely used heuristic clustering algorithm, on data set for multiple times to generate several clustering results; secondly, propose a structure named Local Accumulative Knowledge (LAKE) to capture the common information of clustering results; thirdly, execute the Single-linkage algorithm on LAKE to generate a rough clustering result; eventually, assign the rest data objects to the corresponding clusters. Experimental results on synthetic and real world data sets demonstrate the superiority of the proposed approach in terms of clustering quality measures. © 2013 ACADEMY PUBLISHER.

Abidi, SS, Williams, M & Johnston, BG 2013, 'Human pointing as a robot directive', ACM/IEEE International Conference on Human-Robot Interaction, ACM/IEEE International Conference on Human-Robot Interaction, IEEE, Tokyo, Japan, pp. 67-68.
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People are accustomed to directing other people's attention using pointing gestures. People enact and interpret pointing commands often and effortlessly. If robots understand human intentions (e.g. as encoded in pointing-gestures), they can reach higher

Adak, C 2013, 'Gabor Filter and Rough Clustering Based Edge Detection', 2013 INTERNATIONAL CONFERENCE ON HUMAN COMPUTER INTERACTIONS (ICHCI), International Conference on Human Computer Interactions (ICHCI), IEEE, Chennai, INDIA.

Adak, C 2013, 'Unsupervised Text Extraction from G-Maps', 2013 INTERNATIONAL CONFERENCE ON HUMAN COMPUTER INTERACTIONS (ICHCI), International Conference on Human Computer Interactions (ICHCI), IEEE, Chennai, INDIA.

Adak, C & Chaudhuri, BB 2013, 'Extraction of doodles and drawings from manuscripts', Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pp. 515-520.
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In this paper we propose an approach to separate the non-texts from texts of a manuscript. The non-texts are mainly in the form of doodles and drawings of some exceptional thinkers and writers. These have enormous historical values due to study on those writers' subconscious as well as productive mind. We also propose a computational approach to recover the struck-out texts to reduce human effort. The proposed technique has a preprocessing stage, which removes noise using median filter and segments object region using fuzzy c-means clustering. Now connected component analysis finds the major portions of non-texts, and window examination eliminates the partially attached texts. The struck-out texts are extracted by eliminating straight lines, measuring degree of continuity, using some morphological operations. © Springer-Verlag 2013.

Ahadi, A & Lister, RF 2013, 'Geek Genes, Prior Knowledge, Stumbling Points and Learning Edge Momentum: Parts of the One Elephant?', Proceedings of the 2013 ACM Conference on International Computing Education Research ICER, ACM Conference on International Computing Education Research, ACM, San Diego, CA, USA, pp. 123-128.
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ABSTRACT: Computing academics report bimodal grade distributions in their CS1 classes. Some academics believe that such a distribution is due to their being an innate talent for programming, a geek gene, which some students have, while other students do not have it. Robins introduced the concept of learning edge momentum, which offers an alternative explanation for the purported bimodal grade distribution. In this paper, we analyze empirical data from a real introductory programming class, looking for evidence of geek genes, learning edge momentum and other possible factors.

Aljaafreh, AO, Gill, AQ, Al-Ani, A, Al-adaileh, RM & Alzoubi, YI 2013, 'Factors Influencing Customer's Initial Trust of Internet Banking Services in the Jordanian Context', 22nd IBIMA Conference, International Business Information Management, IBIM, Rome, Italy, pp. 281-288.
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Internet banking services (IBS) offer many benefits to customers and banks. IBS have widely adopted and used in developed countries, however IBS adoption in developing countries such as Jordan is still low. Lack of customer trust is considered as the most important impediment to the use of IBS in developing countries. The aim of this study is to investigate and identify the factors that influence customers initial trust of IBS in the Jordanian context. This paper adopts the qualitative literature survey approach and reports two main categories: Human category and Information Technology category. Human category includes: personality- based trust, cognition-based trust (Reputation), Institutional-based trust (structural assurance), social factors (culture) and supporting factors (relative advantages). Information Technology category includes: website factors (security, privacy, and general online experiences)). We argue that these factors can be useful for organisations in understanding and addressing customers initial trust about IBS in the Jordanian context.

Al-Sharawneh, JA, Sinnappan, S & Williams, M 2013, 'Credibility-based twitter social network analysis', Lecture Notes in Computer Science, Asia Pacific Web Conference, Springer, Sydney, Australia, pp. 323-331.
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Social Network (SN) members in Twitter communicate in varied contexts such as crisis. Formations within social networks are unique as some members have more influence over other members; members with more influence are known as leaders or pioneers. Findi

Bakker, S, van den Hoven, E & Eggen, B 2013, 'FireFlies: Physical Peripheral Interaction Design for the Everyday Routine of Primary School Teachers', Proceedings of the 7th International Conference on Tangible, Embedded and Embodied Interaction (TEI'13), Tangible, Embedded, and Embodied Interaction, ACM, Barcelona, Spain, pp. 57-64.
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This paper presents a research-through-design study into interactive systems for a primary school setting to support teachers' everyday tasks. We developed an open-ended interactive system called FireFlies, which is intended to be interacted with in the periphery of the teacher's attention and thereby become an integral part of everyday routines. FireFlies uses light-objects and audio as a (background) information display. Furthermore, teachers can manipulate the light and audio through physical interaction. A working prototype of FireFlies was deployed in four different classrooms for six weeks. Qualitative results reveal that all teachers found a relevant way of working with FireFlies, which they applied every day of the evaluation. After the study had ended and the systems were removed from the schools, the teachers kept reaching for the devices and mentioned they missed FireFlies, which shows that it had become part of their everyday routine.

Bakker, S, Van Den Hoven, E & Eggen, E 2013, 'FireFlies: Physical peripheral interaction design for the everyday routine of primary school teachers', TEI 2013 - Proceedings of the 7th International Conference on Tangible, Embedded and Embodied Interaction, pp. 57-64.
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This paper presents a research-through-design study into interactive systems for a primary school setting to support teachers' everyday tasks. We developed an open-ended interactive system called FireFlies, which is intended to be interacted with in the periphery of the teacher's attention and thereby become an integral part of everyday routines. FireFlies uses light-objects and audio as a (background) information display. Furthermore, teachers can manipulate the light and audio through physical interaction. A working prototype of FireFlies was deployed in four different classrooms for six weeks. Qualitative results reveal that all teachers found a relevant way of working with FireFlies, which they applied every day of the evaluation. After the study had ended and the systems were removed from the schools, the teachers kept reaching for the devices and mentioned they missed FireFlies, which shows that it had become part of their everyday routine. Copyright 2013 ACM.

Baro, EN, Oberst, S, Lai, JCS & Evans, TA 2013, 'A signal processing method for extracting vibration signals due to ants' activities', 42nd International Congress and Exposition on Noise Control Engineering 2013, INTER-NOISE 2013: Noise Control for Quality of Life, International Congress and Exposition on Noise Control Engineering, Innsbruck, Austria, pp. 3631-3640.
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Many software algorithms have been developed to track ants by analysing recorded videos. On the other hand, the feasibility of using vibrations measured at the substrate to classify ants' behaviour has not been examined before. A method is developed to separate vibrations owing to ants' activities from the substrate's response through a filtering/de-convolution procedure. This involves estimating the frequency response of the substrate and applying wavelet analysis to the measured vibrations. A number of responses due to ants' behaviours have been observed: Ants shaking, falling, carrying stones, walking, scratching/biting, tapping hind legs, grooming, and antennation/feeding. Vibrations produced by ants falling, carrying stones, walking and scratching/biting are measurable (i.e, above background noise levels). The proposed method is shown to be successful in classifying activities due to ants falling, ants carrying stones and to a lesser extent ants' scratching/biting. With further refinement, it seems feasible to use vibrations and the proposed algorithm to measure ants' behaviours in bioassays. Copyright© (2013) by Austrian Noise Abatement Association (OAL).

Behbood, V, Lu, J & Zhang, G 2013, 'Text categorization by fuzzy domain adaptation', 2013 IEEE International Conference on Fuzzy Systems, IEEE International Conference on Fuzzy Systems, IEEE, Hyderabad, India, pp. 1841-1848.
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Machine learning methods have attracted attention of researches in computational fields such as classification/categorization. However, these learning methods work under the assumption that the training and test data distributions are identical. In some real world applications, the training data (from the source domain) and test data (from the target domain) come from different domains and this may result in different data distributions. Moreover, the values of the features and/or labels of the data sets could be non-numeric and contain vague values. In this study, we propose a fuzzy domain adaptation method, which offers an effective way to deal with both issues. It utilizes the similarity concept to modify the target instances' labels, which were initially classified by a shift-unaware classifier. The proposed method is built on the given data and refines the labels. In this way it performs completely independently of the shift-unaware classifier. As an example of text categorization, 20Newsgroup data set is used in the experiments to validate the proposed method. The results, which are compared with those generated when using different baselines, demonstrate a significant improvement in the accuracy

Berry, RA 2013, 'Representational systems with tangible and graphical elements', 2013 IEEE International Symposium on Mixed and Augmented Reality, IEEE International Symposium on Mixed and Augmented Reality, IEEE, Adelaide, Australia, pp. 1-4.
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This research centres on the development of a number of prototype interactive systems, each of which uses a tangible means of representation and manipulation of musical elements in musical composition. Data gathered through collaborative prototyping and user studies is analysed using grounded theory methods. The resultant contribution to knowledge includes theory, design criteria and guidelines specific to tangible representations of music. This knowledge will be useful for future design of systems that use tangible representations, particularly for making music. The prototypes themselves also serve as a form of knowledge and as creative works

Bommes, D, Lévy, B, Pietroni, N, Puppo, E, Silva, C, Tarini, M & Zorin, D 2013, 'Quad-mesh generation and processing: A survey', Computer Graphics Forum, pp. 51-76.

Bressan, NA, James, A & McGregor, C 2013, 'Integration of Drug Dosing Data with Physiological Data Streams using a Cloud Computing Paradigm', 2013 35TH ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC), 35th Annual International Conference of the IEEE-Engineering-in-Medicine-and-Biology-Society (EMBC), IEEE, Osaka, JAPAN, pp. 4175-4178.

Chan, J, Liu, W, Kan, A, Leckie, C & Bailey, J 2013, 'Discovering latent blockmodels in sparse and noisy graphs using non-negative matrix factorisation', International Conference on Information and Knowledge Management, Proceedings, pp. 811-816.
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Blockmodelling is an important technique in social network analysis for discovering the latent structure in graphs. A blockmodel partitions the set of vertices in a graph into groups, where there are either many edges or few edges between any two groups. For example, in the reply graph of a question and answer forum, blockmodelling can identify the group of experts by their many replies to questioners, and the group of questioners by their lack of replies among themselves but many replies from experts. Non-negative matrix factorisation has been successfully applied to many problems, including blockmodelling. However, these existing approaches can fail to discover the true latent structure when the graphs have strong background noise or are sparse, which is typical of most real graphs. In this paper, we propose a new non-negative matrix factorisation approach that can discover blockmodels in sparse and noisy graphs. We use synthetic and real datasets to show that our approaches have much higher accuracy and comparable running times. Copyright 2013 ACM.

Cheema, MA, Lin, X, Zhang, W & Zhang, Y 2013, 'A safe zone based approach for monitoring moving skyline queries', Proceedings of the 16th International Conference on Extending Database Technology, Extending Database Technology, ACM, Genoa, Italy, pp. 275-286.
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Given a set of criterions, an object o dominates another object ó if o is more preferable than ó according to every criterion. A skyline query returns every object that is not dominated by any other object. In this paper, we study the problem of continuously monitoring a moving skyline query where one of the criterions is the distance between the objects and the moving query. We propose a safe zone based approach to address the challenge of efficiently updating the results as the query moves. A safe zone is the area such that the results of a query remain unchanged as long as the query lies inside this area. Hence, the results are required to be updated only when the query leaves its safe zone. Although the main focus of this paper is to present the techniques for Euclidean distance metric, the proposed techniques are applicable to any metric distance (e.g., Manhattan distance, road network distance). We present several non-trivial optimizations and propose an efficient algorithm for safe zone construction. Our experiments demonstrate that the cost of our safe zone based approach is reasonably close to a lower bound cost and is three orders of magnitude lower than the cost of a naïve algorithm.

Chen, H, Zhang, G & Lu, J 2013, 'A Time-Series-Based Technology Intelligence Framework by Trend Prediction Functionality', 2013 IEEE International Conference on Systems, Man, and Cybernetics, IEEE International Conference on Systems, Man and Cybernetics, IEEE, Manchester, UK, pp. 3477-3482.
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Technology Intelligence (TI) indicates the concept and applications that transform data hidden in patents or scientific literature into technical insight for technology development planning and strategies formulation. Although much effort has been put into technology trend analysis in existing research, the majority of the results are still obtained from expert opinions on the basis of historical trends presented by content-based Technology Intelligence tools. To improve this situation, this paper proposes a time-series-based framework for TI that enables the system to be more effective when dealing with trend prediction requirements. Time-series analysis module is first applied in TI framework to process patent time series for technology trend predictions in a real sense, at the same time overcome the problem that prediction of future data points' values is insufficient to support TI construction. Based on explicit patent attributes and unknown patterns learned from the historical data, the framework combines the "trend" and "content" knowledge by analyzing both time-related property and semantic attributes of patent data, to support technology development planning more efficiently and satisfactorily. A case study is presented to demonstrate the validity of trend prediction functionality, which is the emphasis of the whole framework

Chen, HC, Skarmeta Gómez, AF & Hussain, F 2013, 'Welcome message from CISIS 2013 program committee co-chairs', Proceedings - 2013 7th International Conference on Complex, Intelligent, and Software Intensive Systems, CISIS 2013.
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Chen, S & Williams, M 2013, 'Grounding Privacy-by-Design for Information Systems', Pacific Asia Conference on Information Systems (PACIS), Pacific Asia Conference on Information Systems, AIS Electronic Library, Jeju Island, Korea.
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The Privacy-by-Design approach has gained an increasing acceptance for privacy management in the privacy community. However, there is still a research gap in methodologies for implementing this approach and a need to develop frameworks and systems to support Privacy-by-Design practice. In an attempt to bridge this gap, this paper uncovers hidden issues of the Privacy-by-Design approach as a means to derive privacy requirements for implementing information systems with privacy embedded by design.

Chen, X, Zhang, J, Xiang, Y & Zhou, W 2013, 'Traffic identification in semi-known network environment', Proceedings - 16th IEEE International Conference on Computational Science and Engineering, CSE 2013, pp. 572-579.
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Network traffic classification has attracted more and more attentions from both academia and industry. It has been widely adopted in network management and security, such as QoS measurements. Due to rapid emergence of new applications in current network environment, it is impractical for a classification system to obtain full knowledge of a network environment. A big challenge to the identification of interested traffic comes from semi-known network environment, in which some emerging applications are not recognized by the classification system yet. In this paper, we proposed a new framework of Traffic Identification with Unknown Discovery (TIUD) by innovatively combining supervised and unsupervised machine learning techniques to meet the challenge. The proposed TIUD framework has the capability to accurately identify the interested traffic in semiknown network environment. The proposed framework is fully evaluated on a large real-world traffic dataset, with a comparison with three state-of-the-art traffic classification methods. The experimental results yield a outstanding performance of the proposed framework. © 2013 IEEE.

Chuang, C-H, Lin, Y-P, Ko, L-W, Jung, T-P & Lin, C-T 2013, 'Automatic design for independent component analysis based brain-computer interfacing.', 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, Osaka, Japan, pp. 2180-2183.
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This study proposes a new framework, independent component ensemble, to leverage the acquired knowledge into a truly automatic and on-line EEG-based brain-computer interfacing (BCI). The envisioned design includes: (1) independent source recover using independent component analysis (ICA) (2) automatic selection of the independent components of interest (ICi) associated with human behaviors; (3) multiple classifiers with a parallel constructing and processing structure; and (4) a simple fusion scheme to combine the decisions from multiple classifiers. Its implications in BCI are demonstrated through a sample application: cognitive-state monitoring of participants performing a realistic sustained-attention driving task. Empirical results showed the proposed ensemble design could provide an improvement of 7% ~ 15% in overall accuracy for the classification of the arousal state and the driving performance. In summary, constructing ICi-ensemble classifiers and combining their outputs demonstrates a practical option for ICA-based BCIs to reduce the risk of not obtaining any desired independent source or selecting an inadequate component. Most importantly, the ensemble design for integrating information across multiple brain areas creates potentials for developing more complicated BCIs for real world applications.

Cuzzocrea, A, Moussa, R & Xu, G 2013, 'OLAP*: Effectively and Efficiently Supporting Parallel OLAP over Big Data', Lecture Notes in Computer Science, International Conference on Model and Data Engineering, Springer Berlin / Heidelberg, Amantea, Italy, pp. 38-49.
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In this paper, we investigate solutions relying on data partitioning schemes for parallel building of OLAP data cubes, suitable to novel Big Data environments, and we propose the framework OLAP*, along with the associated benchmark TPC-H*d, a suitable transformation of the well-known data warehouse benchmark TPC-H. We demonstrate through performance measurements the efficiency of the proposed framework, developed on top of the ROLAP server Mondrian

Da'ana, MY & Huang, M 2013, 'Visual Sensitivity Analysis in Real Estate Prediction System', Proceedings of 10th International Conference on Computer Graphics, Imaging and Visualization, International Conference Computer Graphics, Imaging and Visualization, IEEE CS Press, Macau, China, pp. 100-105.
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Visual Sensitivity analysis has proven its feasibility in data exploration and exposing relationships between the variables in the model. However, it lacks the ability of user direct interaction of outputs. To overcome this drawback for this interdisciplinary field, in this paper we introduce a novel approach of integrating an interactive visualization and a sensitivity analysis method into a visual interactive sensitivity analysis environment. This environment is applied to a property prediction system. The interactive visualization will facilitate user interaction with the sensitivity analysis method to adjust the outputs of the analysis procedure. The results are presented graphically to the non-expert users without the need to a prior knowledge of the sensitivity analysis method being used. Additionally, all the results that the non-expert is presented with, are all compiled together and presented to an expert user for further analysis by means of multidimensional scatter plots.

Delgrande, J, Peppas, P & Woltran, S 2013, 'AGM-style belief revision of logic programs under answer set semantics', Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), International Conference on Logic Programming and Non-monotonic Reasoning, Springer, Corunna, Spain, pp. 264-276.
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In the past few years, several approaches for revision (and update) of logic programs have been studied. None of these however matched the generality and elegance of the original AGM approach to revision in classical logic. One particular obstacle is the underlying nonmonotonicity of the semantics of logic programs. Recently however, specific revision operators based on the monotonic concept of SE-models (which underlies the answer-set semantics of logic programs) have been proposed. Basing revision of logic programs on sets of SE-models has the drawback that arbitrary sets of SE-models may not necessarily be expressed via a logic program. This situation is similar to the emerging topic of revision in fragments of classical logic. In this paper we show how nonetheless classical AGM-style revision can be extended to various classes of logic programs using the concept of SE-models. That is, we rephrase the AGM postulates in terms of logic programs, provide a semantic construction for revision operators, and then in a representation result show that these approaches coincide. This work is interesting because, on the one hand it shows how the AGM approach can be extended to a seemingly nonmonotonic framework, while on the other hand the formal characterization may provide guiding principles for the development of specific revision operators. © 2013 Springer-Verlag.

Dong, H, Hussain, FK & Chang, E 2013, 'UCOSAIS: A Framework for User-Centered Online Service Advertising Information Search', Proceedings of the 14th International Conference on Web Information Systems Engineering, International Conference on Web Information Systems Engineering, Springer Verlag, Nanjing, China, pp. 267-276.
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The emergence of Internet advertising brings about an economic and efficient marketing means for small and medium enterprises in service industries. Every day, massive service advertising information is published over the Internet. Nevertheless, on the other side, service consumers find it difficult to quickly and precisely retrieve their desired services. This problem is partly caused by the ubiquitous, heterogeneous, and ambiguous nature of online service advertising information. In this paper, we propose a systematic framework – UCOSAIS – for online service advertising information search. Inspired by the philosophy of user-centered design, this framework comprises an ontology-learning-based focused crawler for service information discovery and classification, a faceted semantic search component for service concept selection, and a user-click-based similarity computing component for service concept ranking adjustment.

Esteves, A, van den Hoven, E & Oakley, I 2013, 'Physical Games or Digital Games? Comparing Support for Mental Projection in Tangible and Virtual Representations of a Problem-Solving Task', Proceedings of 7th International Conference on Tangible, Embedded and Embodied Interaction (TEI'13), Tangible, Embedded, and Embodied Interaction, ACM, Barcelona, Spain, pp. 167-174.
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This paper explores how different interfaces to a problem solving task affect how users perform it. Specifically, it focuses on a customized version of the game of Four-in-arow and compares play on a physical, tangible game board with that conducted in mouse and touch-screen driven virtual versions. This is achieved through a repeated measures study involving a total of 36 participants and which explicitly assesses aspects of cognitive work through measures of time task, subjective workload, the projection of mental constructs onto external structures and the occurrence of explanatory epistemic actions. The results highlight the relevance of projection and epistemic action to this problem-solving task and suggest that the different interface forms afford instantiation of these activities in different ways. The tangible version of the system supports the most rapid execution of these actions and future work on this topic should explore the unique advantages of tangible interfaces in supporting epistemic actions.

Felix Navarro, KM, Gay, VC, Golliard, L, Johnston, BG, Leijdekkers, P, Vaughan, EP, Wang, T & Williams, M 2013, 'SocialCycle What Can a Mobile App Do To Encourage Cycling', 38th IEEE Conference on Local Computer Networks (LCN 2013) and Workshops, IEEE Conference on Local Computer Networks, IEEE Computer Society, Sydney Australia, pp. 24-30.
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Traffic congestion presents significant enviromnental, social and economic costs. Encouraging people to cycle and use other fonns of alternate transportation is one important aspect of addressing these problems. However, many city councils face significant difficulties in educating citizens and encouraging them to fonn new habits around these alternate fonns of transport. Mobile devices present a great opportunity to effect such positive behavior change. In this paper we discuss the results of a survey aimed at understanding how mobile devices can be used to encourage cycling and/or improve the cycling experience. We use the results of the survey to design and develop a mobile app called SocialCycle, which purpose is to encourage users to start cycling and to increase the number of trips that existing riders take by bicycle

Feng, X, Zhang, W, Zhao, X, Zhang, Y & Gao, Y 2013, 'Probabilistic k-skyband operator over sliding windows', Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), International Conference on Web-Age Information Management, Springer, Beidaihe, China, pp. 190-202.
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Given a set of data elements in a d-dimensional space, a k-skyband query reports the set of elements which are dominated by at most k - 1 other elements in. k-skyband query is a fundamental query type in data analyzing as it keeps a minimum candidate set for all top-k ranking queries where the ranking functions are monotonic. In this paper, we study the problem of k-skyband over uncertain data streams following the possible world semantics where each data element is associated with an occurrence probability. Firstly, a dynamic programming based algorithm is proposed to identify k-skyband results for a given set of uncertain elements regarding a pre-specified probability threshold. Secondly, we characterize the minimum set of elements to be kept in the sliding window to guarantee correct computing of k-skyband. Thirdly, efficient update techniques based on R-tree structures are developed to handle frequent updates of the elements over the sliding window. Extensive empirical studies demonstrate the efficiency and effectiveness of our techniques. © 2013 Springer-Verlag Berlin Heidelberg.

Feng, X, Zhao, X, Gao, Y & Zhang, Y 2013, 'Probabilistic top-k dominating query over sliding windows', Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Joint International Conference on Asia-Pacific Web Conference (APWeb)/Web-Age Information Management (WAIM), Springer, Sydney, NSW, Australia, pp. 782-793.
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Probabilistic queries on uncertain data have been intensively investigated lately. Top-k dominating query is important in many applications, e.g., decision making, as it offers choices which are better than the most of others. In this paper, we study the problem of probabilistic top-k dominating query over sliding windows. An efficient algorithm is developed to compute the exact solution. Extensive experiments are conducted to demonstrate the efficiency and effectiveness of the algorithm. © 2013 Springer-Verlag.

Ferguson, S 2013, 'Sonifying every day: Activating everyday interactions for ambient sonification systems', Website Proceedings of the 2013 International Conference on Auditory Display, International Conference on Auditory Display, Lodz University of Technology Press, Lodz, Poland, pp. 77-84.
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Sonifying every day: Activating everyday interactions for ambient sonification systems

Ferguson, S, Emery, S, Lee, D, Cabrera, D & McPherson, GE 2013, 'A comparison between continuous categorical emotion responses and stimulus loudness parameters', 4th International Conference on Information, Intelligence, Systems and Applications, International Conference on Information, Intelligence, System and Applications, IEEE, Piraeus, Greece.
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This paper investigates the use of psychoacoustic loudness analysis as a method for determining the likely emotional responses of listeners to musical excerpts. 19 excerpts of music were presented to 86 participants (7 randomly chosen excerpts per participant) who were asked to rate the emotion category using the emotion-clock-face continuous response interface. The same excerpts were analysed with a loudness model, and time series results were summarised as both loudness median and standard deviation. Comparisons indicate that the median and standard deviation of loudness plays an important role in determining the emotion category responses.

Ferguson, S, Johnston, AJ & Martin, AG 2013, 'A corpus-based method for controlling guitar feedback', Proceedings of the International Conference on New Interfaces for Musical Expression, New Interfaces for Musical Expression, Korea Advance Institute of Science and Technology, Daejeon & Seoul, Korea Republic, pp. 541-546.
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The use of feedback created by electric guitars and amplifiers is problematic in musical settings. For example, it is difficult for a performer to accurately obtain specific pitch and loudness qualities. This is due to the complex relationship between these quantities and other variables such as the string being fretted and the positions and orientations of the guitar and amplifier. This research investigates corpus-based methods for controlling the level and pitch of the feedback produced by a guitar and amplifier. A guitar-amplifier feedback system was built in which the feedback is manipulated using (i) a simple automatic gain control system, and (ii) a band-pass filter placed in the signal path. A corpus of sounds was created by recording the sound produced for various combinations of the parameters controlling these two components. Each sound in the corpus was analysed so that the control parameter values required to obtain particular sound qualities can be recalled in the manner of concatenative sound synthesis. As a demonstration, a recorded musical target phrase is recreated on the feedback system.

Ferguson, S, Nagai, Y, Hewett, T, Yi-Luen Do, E, Dow, S, Ox, J, Smith, S, Nishimoto, K & Tan, C 2013, 'Proceedings of the 9th ACM Conference on Creativity & Cognition', Proceedings of the 9th ACM Conference on Creativity & Cognition, ACM, Sydney, NSW, Australia.

Fidge, CF, Hogan, J & Lister, RF 2013, 'What vs. How: Comparing Students Testing and Coding Skills', Volume 136 - Fifteenth Australasian Computing Education Conference, Australasian Computing Education Conference, Australian Computer Society Inc, Adelaide, Australia, pp. 97-106.
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Abstract: The well-known difficulties students exhibit when learning to program are often characterised as either difficulties in understanding the problem to be solved or difficulties in devising and coding a computational solution. It would therefore be helpful to understand which of these gives students the greatest trouble. Unit testing is a mainstay of large-scale software development and maintenance. A unit test suite serves not only for acceptance testing, but is also a form of requirements specification, as exemplified by agile programming methodologies in which the tests are developed before the corresponding program code. In order to better understand studentsâ conceptual difficulties with programming, we conducted a series of experiments in which students were required to write both unit tests and program code for non-trivial problems. Their code and tests were then assessed separately for correctness and âcoverageâ, respectively. The results allowed us to directly compare studentsâ abilities to characterise a computational problem, as a unit test suite, and develop a corresponding solution, as executable code. Since understanding a problem is a pre-requisite to solving it, we expected studentsâ unit testing skills to be a strong predictor of their ability to successfully implement the corresponding program. Instead, however, we found that studentsâ testing abilities lag well behind their coding skills.

Fitzgerald, S, Hanks, B, Lister, RF, McCauley, R & Murphy, L 2013, 'What Are We Thinking When We Grade Programs?', SIGCSE '13: 44th ACM Technical Symposium on Computer Science Education, ACM Technical Symposium on Computer Science Education (SIGCSE), ACM, Denver, Colorado, USA, pp. 471-476.
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Abstract: This paper reports on a mixed methods study which examines how four experienced instructors approached the grading of a programming problem. Two instructors used a detailed, analytic approach and two instructors employed a holistic approach. One instructor exhibited elements of a primary trait approach. Even though the four instructors used different grading scales and philosophies, their raw scores were highly correlated (Spearmanâs rho of .81) supporting the conclusion that experienced instructors usually agree on whether a program is âvery goodâ or âvery badâ. Clearly there is no single right way to grade programs. Further discourse should be encouraged for the benefit of both educators and students.

Fu, B, Xu, G, Wang, Z & Cao, L 2013, 'Leveraging Supervised Label Dependency Propagation for Multi-label Learning', 2013 IEEE 13th International Conference on Data Mining, IEEE International Conference on Data Mining, IEEE, Dallas, TX, USA, pp. 1061-1066.
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Exploiting label dependency is a key challenge in multi-label learning, and current methods solve this problem mainly by training models on the combination of related labels and original features. However, label dependency cannot be exploited dynamically and mutually in this way. Therefore, we propose a novel paradigm of leveraging label dependency in an iterative way. Specifically, each label's prediction will be updated and also propagated to other labels via an random walk with restart process. Meanwhile, the label propagation is implemented as a supervised learning procedure via optimizing a loss function, thus more appropriate label dependency can be learned. Extensive experiments are conducted, and the results demonstrate that our method can achieve considerable improvements in terms of several evaluation metrics.

Furqan, F & Hoang, DB 2013, 'WFICC: A new mechanism for provision of QoS and Congestion Control in WiMAX', 2013 IEEE 10th Consumer Communications and Networking Conference, CCNC 2013, IEEE Consumer Communications and Networking Conference, IEEE, Las Vegas, USA, pp. 552-558.
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In WiMAX architecture the base station lacks the mechanisms to avoid it from being overloaded, which can lead to degradation in the Quality of service (QoS) experienced by the users in the cell, as the large queue at buffer risk high delays and buffer ov

Furqan, F & Hoang, DB 2013, 'Wireless Fair Intelligent Admission Control -- WFIAC', Advanced Information Networking and Applications, International Conference on Advanced Information Networking and Applications (was ICOIN), IEEE, Barcelona, Spain, pp. 1001-1008.
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In next generation wireless networks like WiMAX, a dynamic Call Admission Control (CAC) plays an important role to ensure Quality of Service (QoS) of existing users and to efficiently utilize network resources. We propose a predictive CAC namely Wireless Fair Intelligent Admission Control (WFIAC) that admits or rejects a new incoming connection base on resource availability and load in the network. The proposed CAC works in conjunction to a load control module namely WiMAX Fair Intelligent Congestion Control (WFICC) to determine load in network. The proposed CAC is based on bandwidth borrowing and degradation of over provisioned connections in order to minimize blocking probability and to maximize resource utilization in the network. Once the network load reduces, WFICC upgrades the bandwidth allocated to connections that have data to send. So, WFIAC along with WFICC ensures the network operates around a target operating point to guarantee QoS to end users. A detailed and comprehensive simulation is performed in ns-2 to show the efficiency of the proposed CAC scheme in terms of blocking probability of different service classes and QoS provisioning to existing connections when the network is in congested and non congested state.

Gao, L, Li, M, Zhou, W & Shi, W 2013, 'Anonymous data forwarding in human associated delay tolerant networks', Proceedings - International Conference on Distributed Computing Systems, pp. 17-21.
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Human associated delay-tolerant networks (HDTNs) are new networks for DTNs, where mobile devices are associated with humans and demonstrate social-related communication characteristics. As most of recent works use the social attributes to study the date forwarding in HDTNs and these attributes are critical for the data provider, how to use the anonymous attributes becomes a serious issue. In this paper, we propose a three-dimensional coordinate model by using the anonymous attributes to perform the data forwarding. We use MIT reality dataset, which is a human associated mobile network trace file, to simulate our model. The results of simulations show that the proposed model can use the anonymous attributes to achieve a high data forwarding performance. © 2013 IEEE.

Gao, L, Li, M, Zhou, W & Shi, W 2013, 'Privacy protected data forwarding in human associated delay tolerant networks', Proceedings - 12th IEEE International Conference on Trust, Security and Privacy in Computing and Communications, TrustCom 2013, pp. 586-593.
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Human associated delay-tolerant networks (HDTNs) are new networks for DTNs, where mobile devices are associated with humans and demonstrate social related communication characteristics. As most of recent works use real social trace files to study the date forwarding in HDTNs, the privacy protection becomes a serious issue. Traditional privacy protections need to keep the attributes semantics, such as data mining and information retrieval. However, in HDTNs, it is not necessary to keep these meaningful semantics. In this paper, instead, we propose to anonymize the original data by coding to preserve individual's privacy and apply Privacy Protected Data Forwarding (PPDF) model to select the top N nodes to perform the multicast. We use both MIT Reality and Infocom 06 datasets, which are human associated mobile network trace file, to simulate our model. The results of our simulations show that this method can achieve a high data forwarding performance while protect the nodes' privacy as well. © 2013 IEEE.

Gill, AQ 2013, 'Towards the Development of an Adaptive Enterprise Service System Model', Americas Conference on Information Systems (AMCIS 2013), Americas Conference on Information Systems, AIS, Chicago, IL, USA, pp. 1-9.
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The continuous adaptation of modern enterprises is largely dependent on their underlying adaptive enterprise architecture capability. However, the establishment of an adaptive enterprise architecture capability requires defining the enterprise context before actually commissioning any enterprise architecture or adaptation work. This paper presents the adaptive enterprise service system (AESS) model based on the Design Science research method and Theory Triangulation approach. The AESS integrates the enterprise context perspectives from three well-known theories of agility, (agent) system, and service science. The AESS model, as a part of the large adaptive enterprise architecture toolkit, defines a modern enterprise as an adaptive enterprise service system. The adaptive enterprise service system is a multi-agent system of service systems that exhibits agility and focuses on the emerging service-centric view as opposed to a traditional product-centric view. The service-centric view of an enterprise is critical for establishing the adaptive enterprise architecture capability for handling complex enterprise transformations.

Given-Wilson, T, Huang, F & Jay, B 2013, 'Multi-polymorphic programming in bondi', Proceedings of the ACM SIGPLAN International Conference on Functional Programming, ICFP, pp. 53-60.
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The bondi programming language is multi-polymorphic, in that it supports four polymorphic programming styles within a small core of computation, namely a typed pattern calculus. bondi's expressive power is illustrated by considering the problem of assigning reviewers to a paper. As the context generalises from a committee to a committee with additional reviewers, to a conference, to a federation or confederation, the solution incorporates polymorphism familiar from the functional, generic functional, relational, path-based, and object-oriented programming styles, respectively. These experiments show that multi-polymorphic programming is both practical and desirable. Copyright © 2013 ACM.

Gluga, R, Kay, J & Lister, RF 2012, 'Progoss: Mastering the Curriculum', Australian Conference on Science and Mathematics Education (ACSME2012), Australian Conference on Science and Mathematics Education, UniServe Science, Sydney, Australia, pp. 92-98.
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Abstract: In education, we need to design effective degree programs of study that meet authoritative curricula guidelines. This is challenging because of the size of the curriculum and complexity of degree program structures. When dealing with data of this size and complexity, traditional spreadsheets are a clumsy way of storing the data. A database is a better option, especially when the database is accessible over the web. We created ProGoSs to effectively tackle this complexity. ProGoSs is a web-based system that maps curricula learning goals and mastery levels to individual assessment tasks across entire degree programs. ProGoSs enables academics to answer important questions such as: Does our degree teach the essential core defined in a recommended curriculum? Where in our degree are particular parts of the recommended curriculum taught? Does our degree ensure a solid progression in building skills? Where and how do we assess the learning achieved by bare-pass students on particular parts of the recommended curriculum? We present the design and implementation of ProGoSs and report on its evaluation by mapping multiple programming subjects from multiple universities to the ACM/IEEE Computer Science 2013 topics and learning objectives. This includes a mapping to various levels of Bloomâs Taxonomy to capture mastery.

Gluga, R, Kay, J, Lister, RF, simon, S, Charleston, M, Harland, J & Teague, D 2013, 'A conceptual model for reflecting on expected learning vs. demonstrated student performance', Computing Education 2013, Australasian Computing Education Conference, Australian Computer Society Inc, Adelaide, Australia, pp. 77-86.
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Abstract: Educators are faced with many challenging questions in designing an effective curriculum. What prerequisite knowledge do students have before commencing a new subject? At what level of mastery? What is the spread of capabilities between bare-passing students vs. the top-performing group? How does the intended learning specication compare to student performance at the end of a subject? In this paper we present a conceptual model that helps in answering some of these questions. It has the following main capabilities: capturing the learning specification in terms of syllabus topics and outcomes; capturing mastery levels to model progression; capturing the minimal vs. aspirational learning design; capturing condence and reliability metrics for each of these mappings; and annally, comparing and reflecting on the learning speciffcation against actual student performance. We present a web-based implementation of the model, and validate it by mapping the final exams from four programming subjects against the ACM/IEEE CS2013 topics and outcomes, using Bloom's Taxonomy as the mastery scale. We then import the itemised exam grades from 632 students across the four subjects and compare the demonstrated student performance against the expected learning for each of these. Key contributions of this work are the validated conceptual model for capturing and comparing expected learning vs. demonstrated performance, and a web-based implementation of this model, which is made freely available online as a community resource.

Guo, Y, Jin, J, Zhu, JG & Lu, HY 2013, 'Performance Analysis of a Linear Motor with HTS Bulk Magnets for Driving a Prototype HTS Maglev Vehicle', Applied Mechanics and Materials – Linear Drives for Industry Applications XI, Linear Drives for Industry Applications, Trans Tech Publications, Hangzhou, China, pp. 33-37.
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This paper presents the performance analysis of a linear synchronous motor which employs high-temperature superconducting (HTS) bulk magnets on the mover and normal copper windings on the stator. The linear motor is designed to drive a prototype HTS maglev vehicle in which the mover is suspended by the levitation force between HTS bulks on the mover and permanent magnets on the ground. Finite element magnetic field analysis is conducted to calculate the major parameters of the linear motor and an equation is derived to calculate the electromagnetic thrust force. Theoretical calculations are verified by the measured results on the prototype.

Guo, Y, Zeng, J, Zhu, J, Lu, H & Jin, J 2013, 'B-H Relations of Magnetorheological Fluid under 2-D Rotating Magnetic Field Excitation', Proceedings of 2013 IEEE International Conference on Applied Superconductivity and Electromagnetic Devices, IEEE International Conference on Applied Superconductivity and Electromagnetic Devices, IEEE, Biejing, China, pp. 94-97.
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This paper presents the investigation of the B-H relations of a magnetorheological (MR) fluid under one-dimensional (1-D) alternating and two-dimensional (2-D) rotating magnetic field excitations where B is magnetic flux density and H is magnetic field strength. The measurement is carried out by using a single sheet tester with an MR fluid sample. The measurement principle and structure of the testing system are described. The calibration of the B and H sensing coils are also reported. The relations between B and H on the MR fluid sample under 2-D rotating magnetic field excitations have been measured and compared with the results under 1-D excitations showing that the B-H relations under 2-D excitations are significantly different from the 1-D case. These data would be useful for design and analysis of MR smart structures like MR dampers.

Gupta, A, Kayal, N & Qiao, Y 2013, 'Random Arithmetic Formulas can be Reconstructed Efficiently', 2013 IEEE CONFERENCE ON COMPUTATIONAL COMPLEXITY (CCC), 28th Annual IEEE Conference on Computational Complexity (CCC), IEEE, Palo Alto, CA, pp. 1-9.
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Hausen, D, Bakker, S, van den Hoven, E, Butz, A & Eggen, B 2013, 'Peripheral Interaction: Embedding HCI in Everyday Life', Human-Computer interaction - Interact 2013 - 14th IFIP TC 13 International Conference Cape Town, South Africa, September 2013 Proceedings, Part IV, International Federation for Information Processing Technical Committee 13 on Human-Computer Interaction, Springer, Capetown, South Africa, pp. 782-782.
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The comparison of actions in the physical world with actions on interactive devices reveals a remarkable difference. In daily life we easily perform several tasks in parallel, for example when drinking coffee while reading, drinking may be in the periphery of the attention. Contrarily, we usually have to focus our attention on each digital device we interact with. In recent years, the concept of interacting with computing technology in the background or periphery of the users attention is gaining traction. We call this direction Peripheral Interaction, and see it as a very promising approach to fluently embedding the increasing number of interactive devices into our everyday lives. The workshop is intended to encourage hands-on explorations and discussion about the definition of Peripheral Interaction, its design space and suitable evaluation strategies. Albrecht Schmidt will give a keynote, entitled Creating Seamless transitions between Central and Peripheral User Interfaces. While the term Peripheral Interaction is not (yet) widely adopted, several design disciplines already address different aspects of the core ideas of Peripheral Interaction (e.g. ambient information systems, ubiquitous computing, implicit interaction, eyes-free interaction, calm technology). We want to sharpen the focus for Peripheral Interaction by offering a platform for exchange of knowledge and community building to establish a network around Peripheral Interaction for further collaboration. This workshop invites researchers and practitioners from different disciplines (e.g. computer science, interaction design, interactive arts, psychology, cognitive science, product design and social science), to share their experiences with human-computer interaction for the everyday routine, and aims to lay the foundations for a structured exploration of the new interaction paradigm of Peripheral Interaction. More information about the workshop is available at the workshops website www.peripheralinte...

Homayounfard, H, Kennedy, PJ & Braun, RM 2013, 'NARGES: Prediction Model for Informed Routing in a Communications Network', Advances in Knowledge Discovery and Data Mining (LNCS), Pacific-Asia Conference on Knowledge Discovery and Data Mining, Springer, Gold Coast, QLD, Australia, pp. 327-338.
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There is a dependency between packet-loss and the delay and jitter time-series derived from a telecommunication link. Multimedia applications such as Voice over IP (VoIP) are sensitive to loss and packet recovery is not a merely efficient solution with the increasing number of Internet users. Predicting packet-loss from network dynamics of past transmissions is crucial to inform the next generation of routers in making smart decisions. This paper proposes a hybrid data mining model for routing management in a communications network, called NARGES. The proposed model is designed and implemented for predicting packet-loss based on the forecasted delays and jitters. The model consists of two parts: a historical symbolic time-series approximation module, called HDAX, and a Multilayer Perceptron (MLP). It is validated with heterogeneous quality of service (QoS) datasets, namely delay, jitter and packet-loss time-series. The results show improved precision and quality of prediction compared to autoregressive moving average, ARMA.

Hu, L, Cao, J, Xu, G, Cao, L, Gu, Z & Zhu, C 2013, 'Personalized recommendation via cross-domain triadic factorization', Proceedings of the 22nd international conference on World Wide Web WWW'13, International World Wide Web Conference, ACM, Rio de Janeiro, Brazil, pp. 595-606.
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Collaborative filtering (CF) is a major technique in recommender systems to help users find their potentially desired items. Since the data sparsity problem is quite commonly encountered in real-world scenarios, Cross-Domain Collaborative Filtering (CDCF) hence is becoming an emerging research topic in recent years. However, due to the lack of sufficient dense explicit feedbacks and even no feedback available in users' uninvolved domains, current CDCF approaches may not perform satisfactorily in user preference prediction. In this paper, we propose a generalized Cross Domain Triadic Factorization (CDTF) model over the triadic relation user-item-domain, which can better capture the interactions between domain-specific user factors and item factors. In particular, we devise two CDTF algorithms to leverage user explicit and implicit feedbacks respectively, along with a genetic algorithm based weight parameters tuning algorithm to trade off influence among domains optimally. Finally, we conduct experiments to evaluate our models and compare with other state-of-the-art models by using two real world datasets. The results show the superiority of our models against other comparative models

Hu, L, Cao, J, Xu, G, Wang, J, Gu, Z & Cao, L 2013, 'Cross-Domain Collaborative Filtering via Bilinear Multilevel Analysis', Proceedings of the 23rd International Joint Conference on Artificial Intelligence, International Joint Conference on Artificial Intelligence, IJCAI/AAAI, Beijing, China, pp. 2626-2632.
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Cross-domain collaborative filtering (CDCF), which aims to leverage data from multiple domains to relieve the data sparsity issue, is becoming an emerging research topic in recent years. However, current CDCF methods that mainly consider user and item factors but largely neglect the heterogeneity of domains may lead to improper knowledge transfer issues. To address this problem, we propose a novel CDCF model, the Bilinear Multilevel Analysis (BLMA), which seamlessly introduces multilevel analysis theory to the most successful collaborative filtering method, matrix factorization (MF). Specifically, we employ BLMA to more efficiently address the determinants of ratings from a hierarchical view by jointly considering domain, community, and user effects so as to overcome the issues caused by traditional MF approaches. Moreover, a parallel Gibbs sampler is provided to learn these effects. Finally, experiments conducted on a real-world dataset demonstrate the superiority of the BLMA over other state-of-the-art methods.

Hu, Z, Zhang, S, Zhang, F & Lu, H 2013, 'SCUC with battery energy storage system for peak-load shaving and reserve support', IEEE Power and Energy Society General Meeting, IEEE Power and Energy Society General Meeting, IEEE, Vancouver, BC, Canada.
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This paper aims to investigate the benefit of deploying battery energy storage system (BESS) in a power system for reducing production cost, shaving peak-load and providing reserve support. A BESS model is built which takes into account the charging and discharging efficiencies, charging/discharging power limits, and reserve capacity limits. This model is incorporated into the security-constrained unit commitment (SCUC) problem. The new SCUC problem is solved to optimally allocate the charging and discharging power and reserve capacity of each BESS. Tests are carried out on the IEEE 24-bus system and simulation results show that lower operational cost can be achieved by using BESS for both peak-load shaving/shifting and reserve support. © 2013 IEEE.

Hua, J & Huang, M 2013, 'Improving the Quality of Clustered Graph Drawing through a Dummy Element Approach', Proceedings of Computer Graphics, Imaging and Visualization (CGIV), 2013 10th International Conference, International Conference on Computer Graphics, Imaging and Visualization, IEEE, Macau, China, pp. 88-92.
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Clustered graphs have been widely consisted in Graph Drawing to overcome the problem of drawing large (or huge) graphs with thousands, or perhaps millions of nodes. Force-directed algorithm is one of the available approaches to draw such graphs with good layouts. However, the force directed methods are often produce very different layout outcomes based on different clustering algorithms that greatly affect the quality of the final result. In this paper, we propose a 'dummy element' approach for drawing clustered graphs by using the traditional force-directed algorithm. Our approach attempts to maximize the satisfaction of aesthetics in graph drawing. The experimental results shown that our new method can reduce the side effects on choosing different clustering methods and improve the quality of final layouts.

Huang, CS, Lin, CL, Ko, LW, Liu, SY, Sua, TP & Lin, CT 2013, 'A hierarchical classification system for sleep stage scoring via forehead EEG signals', Proceedings of the 2013 IEEE Symposium on Computational Intelligence, Cognitive Algorithms, Mind, and Brain, CCMB 2013 - 2013 IEEE Symposium Series on Computational Intelligence, SSCI 2013, IEEE Symposium on Computational Intelligence, Cognitive Algorithms, Mind, and Brain (CCMB), IEEE, Singapore, pp. 1-5.
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The study adopts the structure of hierarchical classification to develop an automatic sleep stage classification system using forehead (Fpl and Fp2) EEG signals. The hierarchical classification consists of a preliminary wake detection rule, a novel feature extraction method based on American Academy of Sleep Medicine (AASM) scoring manual, feature selection methods and SVM. After estimating the preliminary sleep stages, two adaptive adjustment schemes are applied to adjust the preliminary sleep stages and provide the final estimation of sleep stages. Clinical testing reveals that the proposed automatic sleep stage classification system is about 77% accuracy and 67% kappa for individual 10 normal subjects. This system could provide the possibility of long term sleep monitoring at home and provide a preliminary result of sleep stages so that doctor could decide if a patient needs to have a detailed diagnosis using Polysomnography (PSG) system in a sleep laboratory of hospital. © 2013 IEEE.

Huang, CS, Lin, CL, Ko, LW, Wang, YK, Liang, JW & Lin, CT 2013, 'Automatic sleep stage classification GUI with a portable EEG device', Communications in Computer and Information Science, pp. 613-617.
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In this study, a developed automatic sleep stage classification system with a portable EEG recording device, (Mindo-4s) is implemented by JAVA-based sleep graphical user interface (GUI) in android platform. First, the parameters of the developed sleep stage classification system, including extracting effective sleep features and a hierarchical classification structure consisting of preliminary wake detection rule, adaptive adjustment scheme, and support vector machine, were trained by our existing sleep database, which collected using polysomnogram (PSG), in MATLAB program. Finally, this classification system would be reedited by JAVA language, and the corresponding JAVA-based sleep GUI software was working in android platform and Mindo-4s. The connection between JAVA-based sleep GUI software and the portable Mindo-4s was through Bluetooth communication. The performance of this JAVA-based sleep GUI can reach 72.43% average accuracy comparing to the result from manual scoring. This JAVA-based sleep GUI can on-line display, record and analyze the forehead EEG signals simultaneously. After sleep, the user can received a complete sleep report, including sleep efficiency, sleep stage distribution, from JAVA-based sleep GUI. Thus, this system can provide a preliminary result in sleep quality estimation, and help the sleep doctor to decide someone needs to have a complete PSG testing in hospital. Using this system is more convenient for long-term and home-based daily caring than traditional PSG measurement. © Springer-Verlag Berlin Heidelberg 2013.

Huang, CS, Lin, CL, Ko, LW, Wang, YK, Liang, JW & Lin, CT 2013, 'Automatic Sleep Stage Classification GUI with a Portable EEG Device', International Conference on Human-Computer Interaction, Springer, Las Vegas, NV, USA, pp. 613-617.
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In this study, a developed automatic sleep stage classification system with a portable EEG recording device, (Mindo-4s) is implemented by JAVA-based sleep graphical user interface (GUI) in android platform. First, the parameters of the developed sleep stage classification system, including extracting effective sleep features and a hierarchical classification structure consisting of preliminary wake detection rule, adaptive adjustment scheme, and support vector machine, were trained by our existing sleep database, which collected using polysomnogram (PSG), in MATLAB program. Finally, this classification system would be reedited by JAVA language, and the corresponding JAVA-based sleep GUI software was working in android platform and Mindo-4s. The connection between JAVA-based sleep GUI software and the portable Mindo-4s was through Bluetooth communication. The performance of this JAVA-based sleep GUI can reach 72.43% average accuracy comparing to the result from manual scoring. This JAVA-based sleep GUI can on-line display, record and analyze the forehead EEG signals simultaneously. After sleep, the user can received a complete sleep report, including sleep efficiency, sleep stage distribution, from JAVA-based sleep GUI. Thus, this system can provide a preliminary result in sleep quality estimation, and help the sleep doctor to decide someone needs to have a complete PSG testing in hospital. Using this system is more convenient for long–term and home-based daily caring than traditional PSG measurement.

Huang, CS, Lin, CL, Yang, WY, Ko, LW, Liu, SY & Lin, CT 2013, 'Applying the fuzzy C-means based dimension reduction to improve the sleep classification system', IEEE International Conference on Fuzzy Systems, IEEE International Conference on Fuzzy Systems, IEEE, Hyderabad, India.
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Having a well sleep quality is important factor in our daily life. The evaluation of sleep stages has become an important issue due to the distribution of sleep stages across a whole night relates to sleep quality. This study aims to propose a sleep classification system, consists of a preliminary wake detection rule, sleep feature extraction, fuzzy c-means based dimension reduction, support vector machine with radial basis function kernel, and adaptive adjustment scheme, with only FP1 and FP2 electroencephalography. Compared with the results from the sleep technologist, the average accuracy and Kappa coefficient of the proposed sleep classification system is 70.92% and 0.6130, respectively, for individual 10 normal subjects. Thus, the proposed sleep classification system could provide a preliminary report of sleep stages to assistant doctors to make decision if a patient needs to have a detailed testing in a sleep laboratory. © 2013 IEEE.

Hussain, FK 2014, 'An Enhanced Mental Model Elicitation Technique to Improve Mental Model Accuracy', Proceedings of the 20th International Conference on Neural Information Processing, International Conference on Neural Information Processing, Springer Verlag, Daegu, Korea, pp. 82-89.

Ilsar, A, Havryliv, M & Johnston, AJ 2013, 'The AirSticks: a new interface for electronic percussion', Proceedings of the Sound and Music Computing Conference 2013, Sound and Music Computing Conference, KTH Royal Institute of Technology Stockholm, Stockholm, Sweden, pp. 220-226.
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This paper documents the early developments of a new interface for electronic percussionists. The interface is designed to allow the composition, improvisation and performance of live percussive electronic music using hand, finger, foot and head movements captured by various controllers. This paper provides a background to the field of electronic percussion, outlines the artistic motivations behind the project, and describes the technical nature of the work completed so far. This includes the development of software, the combination of existing controllers and senses, and an example mapping of movement to sound.

Islam, R, Guo, Y, Zhu, J, Lu, H & Jin, J 2013, 'Medium-Frequency-Link Power Conversion for High Power Density Renewable Energy Systems', 2013 IEEE International Conference on Applied Superconductivity and Electromagnetic Devices, IEEE International Conference on Applied Superconductivity and Electromagnetic Devices, IEEE, Beijing, China, pp. 102-106.
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Recent advances in solid-state semiconductors and magnetic materials have provided the impetus for medium frequency-link based medium voltage power conversion systems, which would be a possible solution to reducing the weight and volume of renewable power generation systems. To verify this new concept, in this paper, a laboratory prototype of 1.26 kVA medium-frequency-link power conversion system is developed for a scaled down 1 kV grid applications. The design and implementation of the prototyping, test platform, and the experimental results are analyzed and discussed. It is expected that the proposed new technology would have a great potential for future renewable and smart grid applications.

Jay, B & Vergara, J 2013, 'Growing a Language in Pattern Calculus', Theoretical Aspects of Software Engineering (TASE), 2013 International Symposium on, IEEE, pp. 233-240.

Jiang, J, Lu, J, Zhang, G & Long, G 2013, 'Optimal cloud resource auto-scaling for web applications', 2013 13th IEEE/ACM International Symposium on Cluster, Cloud, and Grid Computing, IEEE, pp. 58-65.
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Johnston, AJ 2013, 'Fluid Simulation as Full Body Audio-Visual Instrument', Proceedings of the International Conference on New Interfaces for Musical Expression, New Interfaces for Musical Expression, Korea Advance Institute of Science and Technology, Daejeon & Seoul, Korea Republic, pp. 132-135.
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This paper describes an audio-visual performance system based on real-time fluid simulation. The aim is to provide a rich environment for works which blur the boundaries between dance and instrumental performance-and sound and visuals-while maintaining transparency for audiences and new performers.

Kajdanowicz, T, Michalski, R, Musial, K & Kazienko, P 2013, 'Active Learning and Inference Method for Within Network Classification', 2013 IEEE/ACM INTERNATIONAL CONFERENCE ON ADVANCES IN SOCIAL NETWORKS ANALYSIS AND MINING (ASONAM), IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), IEEE, Niagara Falls, CANADA, pp. 1299-1306.

Kamaleswaran, R, Thommandram, A, Zhou, Q, Eklund, M, Cao, Y, Wang, WP & McGregor, C 2013, 'Cloud framework for real-time synchronous physiological streams to support rural and remote critical care', Proceedings of CBMS 2013 - 26th IEEE International Symposium on Computer-Based Medical Systems, pp. 473-476.
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We present a method for transmission and processing of real-time trans-continental medical data streams. We apply fundamentals of existing network technologies to create a secure tunnel from a remote hospital through an open-network to the Artemis Cloud. We capture and store incoming 1Hz data stream in our real-time event stream processor to allow for online real-time monitoring of the patient status. The contributions of this paper extend the Critical Care as a Service paradigm by incorporating remote monitoring centers. The results establish feasibility of the system to support real-time monitoring. However, existing protocols were required significant optimization to account for variability in throughput and availability of the network. © 2013 IEEE.

Kamaleswaran, R, Thommandram, A, Zhou, Q, Eklund, M, Cao, Y, Wang, WP & McGregor, C 2013, 'Cloud framework for real-time synchronous physiological streams to support rural and remote Critical Care', Proceedings - IEEE Symposium on Computer-Based Medical Systems, pp. 473-476.
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We present a method for transmission and processing of real-time trans-continental medical data streams. We apply fundamentals of existing network technologies to create a secure tunnel from a remote hospital through an open-network to the Artemis Cloud. We capture and store incoming 1Hz data stream in our real-time event stream processor to allow for online real-time monitoring of the patient status. The contributions of this paper extend the Critical Care as a Service paradigm by incorporating remote monitoring centers. The results establish feasibility of the system to support real-time monitoring. However, existing protocols were required significant optimization to account for variability in throughput and availability of the network. © 2013 IEEE.

Kaur, P, Goyal, ML & Lu, J 2013, 'A Proficient and Dynamic Bidding Agent for Online Auctions', Lecture Notes in Computer Science, International Workshop on Agents and Data Mining Interaction, Springer, Valencia, Spain, pp. 178-190.
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E-consumers face biggest challenge of opting for the best bidding strategies for competing in an environment of multiple and simultaneous online auctions for same or similar items. It becomes very complicated for the bidders to make decisions of selecting which auction to participate in, place single or multiple bids, early or late bidding and how much to bid. In this paper, we present the design of an autonomous dynamic bidding agent (ADBA) that makes these decisions on behalf of the buyers according to their bidding behaviors. The agent develops a comprehensive method for initial price prediction and an integrated model for bid forecasting. The initial price prediction method selects an auction to participate in and then predicts its closing price (initial price). Then the bid forecasting model forecasts the bid amount by designing different bidding strategies followed by the late bidders. The experimental results demonstrated improved initial price prediction outcomes by proposing a clustering based approach. Also, the results show the proficiency of the bidding strategies amongst the late bidders with desire for bargain

Kellihan, B, Doty, TJ, Hairston, WD, Canady, J, Whitaker, KW, Lin, CT, Jung, TP & McDowell, K 2013, 'A real-world neuroimaging system to evaluate stress', Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), International Conference on Augmented Cognition, Springer, Las Vegas, NV, USA, pp. 316-325.
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While the laboratory setting offers researchers a great deal of experimental control, this environment also limits how generalizable the results are to the real world. This is particularly true when studying the multifaceted phenomenon of stress, which often relies on personal experience, a dimension that is difficult to reproduce in the laboratory setting. This paper describes a novel, multi-aspect real-world integrated neuroimaging system (MARIN) optimized to study physiological phenomena in the real-world and particularly suited to the study of stress. This system integrates neurological data from a gel-free, wireless EEG device with physiological data from wireless cardiac and skin conductance sensors, as well as self-reports of activity and stress. Coordination of the system is managed through an Android handheld mobile device that also logs salient events and presents inventories for subjective reports of stress. The integration of these components creates a rich, multimodal dataset with minimal interference to the user's daily life, and these data will guide the further understanding of neurological mechanisms of stress. © 2013 Springer-Verlag Berlin Heidelberg.

Khoo, IH, Reddy, HC, Van, LD & Lin, CT 2013, 'Design of 2-D digital filters with almost quadrantal symmetric magnitude response without 1-D separable denominator factor constraint', Midwest Symposium on Circuits and Systems, IEEE International Midwest Symposium on Circuits and Systems (MWSCAS), IEEE, Columbus, OH, USA, pp. 999-1002.
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A design approach is presented for 2-D digital filters possessing approximate quadrantal magnitude symmetry without the constraint of the denominator having only 1-D separable factors. To ensure the BIBO stability of the filter, the planar least square inverse stabilization approach is employed. It is illustrated through design examples that the proposed approach results in filters with sharper transition band and lower error relative to the given filter specifications. Also, for certain cases, it is shown that a lower order non-separable denominator design can achieve the same result as a higher order separable denominator design, thus providing savings in the number of multipliers. Finally, 2-D VLSI realizations without global broadcast are presented for the optimized transfer function with non-separable denominator factors and approximate quadrantal symmetry. © 2013 IEEE.

Ko, LW, Chuang, CH, Huang, CS, Chen, YH, Lu, SW, Liao, LD, Chang, WT & Lin, CT 2013, 'Real-time vigilance estimation using mobile wireless mindo EEG device with spring-loaded sensors', Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), International Conference on Augmented Cognition, Springer, Las Vegas, NV, USA, pp. 450-458.
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Monitoring the neurophysiological activities of human brain dynamics in an operational environment poses a severe measurement challenge using current laboratory-oriented biosensor technology. The goal of this research is to design, develop and test the wearable and wireless dry-electrode EEG human-computer interface (HCI) that can allow assessment of brain activities of participants actively performing ordinary tasks in natural body positions and situations within a real operational environment. Its implications in HCI were demonstrated through a sample application: vigilance-state prediction of participants performing a realistic sustained-attention driving task. Besides, this study further developed an online signal processing for extracting EEG features and assessing cognitive performance. We demonstrated the feasibility of using dry EEG sensors and miniaturized supporting hardware/software to continuously collect EEG data recorded from hairy sites (i.e., occipital region) in a realistic VR-based dynamic driving simulator. © 2013 Springer-Verlag Berlin Heidelberg.

Ko, LW, Lai, KL, Huang, PH, Lin, CT & Wang, SJ 2013, 'Steady-state visual evoked potential based classification system for detecting migraine seizures', International IEEE/EMBS Conference on Neural Engineering, NER, International IEEE Engineering-in-Medicine-and-Biology-Society (EMBS) Conference on Neural Engineering (NER), IEEE, San Diego, CA, USA, pp. 1299-1302.
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The recurrent migraine attacks between interictal phenomenon is triggered by the migraineurs' brain lacking for habituation, due to the stimulations from the outside world that increase the excitability of brain activity, which have been considered as the possible reasons for migraine seizure. The variation of habituation level within the migraine cycle is proposed to be a critical symptom to describe the physiological states of migraine headache. This study proposed Steady-State Visual Evoked Potentials (SSVEP) examination to utilize habituation for classifying the different physiologic states of migraine cycle, and implement a classification system to determine different migraine states. The developed system may be extended to detect migraine seizure, and provide an opportunity to a clinically individual-based headache monitoring program, aiming for early migraine detection. © 2013 IEEE.

Ko, LW, Lee, HC, Tsai, SF, Shih, TC, Chuang, YT, Huang, HL, Ho, SY & Lin, CT 2013, 'EEG-based motion sickness classification system with genetic feature selection', Proceedings of the 2013 IEEE Symposium on Computational Intelligence, Cognitive Algorithms, Mind, and Brain, CCMB 2013 - 2013 IEEE Symposium Series on Computational Intelligence, SSCI 2013, IEEE Symposium on Computational Intelligence, Cognitive Algorithms, Mind, and Brain (CCMB), IEEE, Simgapore, pp. 158-164.
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People tend to get motion sickness on a moving boat, train, airplane, car, or amusement park rides. Many previous studies indicated that motion sickness sometimes led to traffic accidents, so it becomes an important issue in our daily life. In this study, we designed a VR-based motion-sickness platform with a 32-channel EEG system and a joystick which is used to report the motion sickness level (MSL) in real time during experiments. The results show it is feasible to estimate subject's MSL based on re-sampling frequency band proved by the high test accuracy. A comparison between general prediction models (such as LDA, QDA, KNN) and IBCGA shows that the IBCGA can be effectively increase the accuracy. In this paper, an extended-IBCGA (e-IBCGA) is proposed and it provides more accuracy than the prior-art research. The test results show that e-IBCGA increases at least 10% to 20% test accuracy in 6 subjects. © 2013 IEEE.

Koreshoff, TJ, Leong, T & Robertson, TJ 2013, 'Approaching a human-centred Internet of Things', Proceedings of the 25th Australian Computer-Human Interaction Conference OzCHI13, Australian Computer Human Interaction Conference, ACM, Flinders University, Adelaide, Australia, pp. 363-366.
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This paper surveys recent Internet of Things (IoT) related HCI literature, and examines it in light of a comprehensive framework by Atzori et al. (2010). Mapping HCI literature to this framework helped us understand the extend and the focus of IoT related HCI efforts, including a lack of HCI engagement with deeper human-centred perspectives of the IoT. It also revealed HCI considerations for the IoT which we added to the framework.

Koreshoff, TJ, Robertson, TJ & Leong, T 2013, 'Internet of Things: a review of literature and products', Proceedings of the 25th Australian Computer-Human Interaction Conference, Australian Computer Human Interaction Conference, ACM, Flinders University, Adelaide, Australia, pp. 335-344.
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This paper offers an HCI perspective on the emergent agenda of the Internet of Things (IoT). The purpose is to provide insights and resources for how HCI could engage productively with the IoT agenda while it is still evolving and being realised.

Kulkarni, R, Qiao, Y & Sun, X 2013, 'Any monotone property of 3-uniform hypergraphs is weakly evasive', LNCS - Theory and Applications of Models of Computation - Proceedings of the10th International Conference, TAMC 2013, Theory and Applications of Models of Computation, Springer, Hong Kong, pp. 224-235.
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Our proof combines the combinatorial approach of Rivest and Vuillemin with the topological approach of Kahn, Saks, and Sturtevant. Interestingly, our proof makes use of Vinogradovs Theorem (weak Goldbach Conjecture), inspired by its recent use by Babai et. al. [1] in the context of the topological approach. Our work leaves the generalization to k-uniform hypergraphs as an intriguing open question.

Leong, T & Wright, P 2013, 'Revisiting social practices surrounding music', Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, SIGCHI Conference on Human Factors in Computing Systems, ACM, Paris, France, pp. 951-960.
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Music shapes our social lives. While previous research has provided a foundational understanding of the social affordances surrounding people's interactions with music, there is a need to update this understanding in light of recent key developments in o

Leong, T & Wright, P 2013, 'Understanding 'Tingle' in Opera Performances', Proceedings of the 25th Australian Computer-Human Interaction Conference, Australian Computer Human Interaction Conference, ACM, Flinders University, Adelaide, Australia, pp. 43-52.
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With HCI venturing more into designing for the cultural and entertaining domain, researchers are engaging with experimental designs, and technical interventions to understand how to best consider new technologies for this domain. This paper focuses on audience experience. It presents approaches as to how the HCI community can better support audiences' encounters with deeply engaging peak experiences that are intense, memorable and personally engaging experiences in live performances.

Li, F, Xu, G, Cao, L, Fan, X & Niu, Z 2013, 'CGMF: Coupled Group-Based Matrix Factorization for Recommender System', Lecture Notes in Computer Science, International Conference on Web Information Systems Engineering, Springer, Nanjing, China, pp. 289-298.
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With the advent of social influence, social recommender systems have become an active research topic for making recommendations based on the ratings of the users that have close social relations with the given user. The underlying assumption is that a users taste is similar to his/her friends in social networking. In fact, users enjoy different groups of items with different preferences. A user may be treated as trustful by his/her friends more on some specific rather than all groups. Unfortunately, most of the extant social recommender systems are not able to differentiate users social influence in different groups, resulting in the unsatisfactory recommendation results. Moreover, most extant systems mainly rely on social relations, but overlook the influence of relations between items. In this paper, we propose an innovative coupled group-based matrix factorization model for recommender system by leveraging the user and item groups learned by topic modeling and incorporating couplings between users and items and within users and items. Experiments conducted on publicly available data sets demonstrate the effectiveness of our approach.

Li, J & Tao, D 2013, 'A Bayesian factorised covariance model for image analysis', International Joint Conference on Artificial Intelligence, International Joint Conference on Artificial Intelligence, AAAI, Beijing, China, pp. 1465-1471.
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Li, J, Wang, J & Huang, M 2013, 'Exploiting the Relationship between Keywords for Effective XML Keyword Search', Lecture Notes in Computer Science, International Conference on Advances in Databases and Information Systems, Springer Berlin Heidelberg, Genoa, Italy, pp. 232-245.
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xml keyword search provides a simple and user-friendly way of retrieving data from xml databases, but the ambiguities of keywords make it difficult to effectively answer keyword queries. In this paper, we tackle the keyword ambiguity problem by exploiting the relationship between keywords in a query. We propose an approach which infers and ranks a set of likely search intentions. Extensive experiments verified the better effectiveness of our approach than existing systems.

Li, L, Chen, X & Xu, G 2013, 'Suggestions for fresh search queries by mining mircoblog topics', Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), International Workshop on Behavior and Social Informatics, Springer, Gold Coast, QLD, Australia, pp. 214-223.
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Query suggestion of Web search has been an effective approach to help users quickly express their information need and more accurately get the information they need. All major web-search engines and most proposed methods that suggest queries rely on query logs of search engine to determine possible query suggestions. However, for search systems, it is much more difficult to effectively suggest relevant queries to a fresh search query which has no or few historical evidences in query logs. In this paper, we propose a suggestion approach for fresh queries by mining the new social network media, i.e, mircoblog topics. We leverage the comment information in the microblog topics to mine potential suggestions. We utilize word frequency statistics to extract a set of ordered candidate words. As soon as a user starts typing a query word, words that match with the partial user query word are selected as completions of the partial query word and are offered as query suggestions. We collect a dataset from Sina microblog topics and compare the final results by selecting different suggestion context source. The experimental results clearly demonstrate the effectiveness of our approach in suggesting queries with high quality. Our conclusion is that the suggestion context source of a topic consists of the tweets from authenticated Sina users is more effective than the tweets from all Sina users. © Springer International Publishing Switzerland 2013.

Li, SY, Ko, LW, Lin, CT, Tam, LM, Chen, HK & Lao, SK 2013, 'System modeling and synchronization of nonlinear chaotic systems with uncertainty and disturbance by innovative fuzzy modeling strategy', IEEE International Conference on Fuzzy Systems, IEEE International Conference on Fuzzy Systems, IEEE, Hyderabad, India.
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In this paper, an application of the innovative fuzzy model [1] is applied to simulate and synchronize two classical Sprott chaotic systems with unknown noise and disturbance. In traditional Takagi-Sugeno fuzzy (T-S fuzzy) model, there will be 2 N linear subsystems (according to 2 N fuzzy rules) and m × 2 N equations in the T-S fuzzy system, where N is the number of minimum nonlinear terms and m is the order of the system. Through the new fuzzy model, a complicated nonlinear system is linearized to a simple form - linear coupling of only two linear subsystems and the numbers of fuzzy rules can be reduced from 2 N to 2 × N. The fuzzy equations become much simpler. There are two Sprott systems in numerical simulations to show the effectiveness and feasibility of new model. © 2013 IEEE.

Li, X, Zhang, L, Chen, E, Zong, Y & Xu, G 2013, 'Mining Frequent Patterns in Print Logs with Semantically Alternative Labels', Lecture Notes in Computer Science, International Conference on Advanced Data Mining and Applications, Springer Berlin / Heidelberg, Hangzhou, pp. 107-119.
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It is common today for users to print the informative information from webpages due to the popularity of printers and internet. Thus, many web printing tools such as Smart Print and PrintUI are developed for online printing. In order to improve the users printing experience, the interaction data between users and these tools are collected to form a so-called print log data, where each record is the set of urls selected for printing by a user within a certain period of time. Apparently, mining frequent patterns from these print log data can capture user intentions for other applications, such as printing recommendation and behavior targeting. However, mining frequent patterns by directly using url as item representation in print log data faces two challenges: data sparsity and pattern interpretability. To tackle these challenges, we attempt to leverage delicious api (a social bookmarking web service) as an external thesaurus to expand the semantics of each url by selecting tags associated with the domain of each url. In this setting, the frequent pattern mining is employed on the tag representation of each url rather than the url or domain representation. With the enhancement of semantically alternative tag representation, the semantics of url is substantially improved, thus yielding the useful frequent patterns. To this end, in this paper we propose a novel pattern mining problem, namely mining frequent patterns with semantically alternative labels, and propose an efficient algorithm named PaSAL (Frequent Patterns with Semantically Alternative Labels Mining Algorithm) for this problem. Specifically, we propose a new constraint named conflict matrix to purify the redundant patterns to achieve a high efficiency. Finally, we evaluate the proposed algorithm on a real print log data.

Liang, J, Hua, J, Huang, M, Nguyen, Q & Simoff, SJ 2012, 'Rectangle orientation in area judgment task for treemap design', The 24th Australian Computer-Human Interaction Conference, OzCHI '12, Australian Computer Human Interaction Conference, ACM Press, Melbourne, VIC, Australia, pp. 349-352.
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Prior works on treemaps have mainly focused on developing the new layouts. The existing treemaps generated from various algorithms require careful examination on design parameter. However, current research does not provide usability studies of treemap guidelines on effectiveness of design parameters. Hence, selecting the most effective parameter for certain type of task is primarily based on intuition preference of visualization designer. For example, in the existing research, there is insufficient guidance on orientation for treemap design yet. Therefore, the impact of orientation remains unclear in visual analysis tasks performance. The contribution of this paper is to assess the effect of orientation in visual data analysis process so that we will further investigate treemap design guidance

Liang, J, Nguyen, Q, Simoff, SJ & Huang, M 2013, 'Visualizing large trees with divide & conquer partition', Proceedings of the 6th International Symposium on Visual Information Communication and Interaction, International Symposium on Visual Information Communication and Interaction, ACM, Tianjin, China, pp. 79-87.
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While prior works on enclosure approach, guarantees the space utilization of a single geometrical area, mostly rectangle, this paper proposes a flexible enclosure tree layout method for partitioning various polygonal shapes that break through the limitation of rectangular constraint. Similar to Treemap techniques, it uses enclosure to divide display space into smaller areas for its sub-hierarchies. The algorithm can partition a polygonal shape or even an arbitrary shape into smaller polygons, rotated rectangles or vertical-horizontal rectangles. The proposed method and implementation algorithms provide an effective interactive visualization tool for partitioning large hierarchical structures within a confined display area with different shapes for real-time applications. We demonstrated the effective of the new method with a case study, an automated evaluation and a usability study.

Liao, LD, Chen, YY, Lin, CT & Li, ML 2013, 'Functional photoacoustic micro-imaging of cerebral hemodynamic changes in single blood vessels after photo-induced brain stroke', Progress in Biomedical Optics and Imaging - Proceedings of SPIE, Conference on Photons Plus Ultrasound - Imaging and Sensing/Photonics West BiOS Symposium, SPIE, San Francisco, CA.
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Studying the functional hemodynamic roles of individual cerebral cortical arterioles in maintaining both the structure and function of cortical regions during and after brain stroke in small animals is an important issue. Recently, functional photoacoustic microscopy (fPAM) has been proved as a reliable imaging technique to probe the total hemoglobin concentration (HbT), cerebral blood volume (CBV) and hemoglobin oxygen saturation (SO 2 ) in single cerebral blood vessels of rats. Here, we report the application of fPAM associated with electrophysiology recordings to investigating functional hemodynamic changes in single cortical arterioles of rats with electrical forepaw stimulation after photo-induced ischemic stroke. Because of the weak optical focusing nature of our fPAM system, photo-induced ischemic stroke targeting single cortical arterioles can be easily conducted with simple adaptation. Functional HbT, CBV and SO 2 changes associated with the induced stroke in selected arterioles from the anterior cerebral artery system were imaged with 36 x 65-μm spatial resolution. Experimental results showed that after photo-occlusion of a single arteriole, the functional changes of nearby arterioles in cerebral cortex only can be observed immediately after the stroke. After a few minutes of stroke onset, there are no significant functional changes under the forepaw stimulation, suggesting that alternate blood flow routes are not actively recruited. The fPAM with electrophysiology recordings complements existing imaging techniques and has the potential to offer a favorable tool for explicitly studying cerebral hemodynamics in small animal models of photo-indcued ischemic stroke. © 2013 Copyright SPIE.

Liao, S-H, Chang, J-Y & Lin, C-T 2013, 'Study on Least Trimmed Absolute Deviations Artificial Neural Network', 2013 INTERNATIONAL CONFERENCE ON FUZZY THEORY AND ITS APPLICATIONS (IFUZZY 2013), International Conference on Fuzzy Theory and Its Applications (iFUZZY), IEEE, Taipei, TAIWAN, pp. 156-160.

Lin, CT, Chuang, CH, Huang, CS, Chen, YH & Ko, LW 2013, 'Real-time assessment of vigilance level using an innovative Mindo4 wireless EEG system', Proceedings - IEEE International Symposium on Circuits and Systems, International Symposium on Circuits and Systems Nano-Bio Circuit Fabrics and Systems (ISCAS), IEEE, Beijing, China, pp. 1528-1531.
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Monitoring the neurophysiological activities of driver in an operational environment poses a severe measurement challenge using a current laboratory-oriented biosensor technology. The aims of this research are to 1) introduce a dry and wireless EEG system used for conveniently recording EEG signals from forehead regions, 2) propose an effective system for processing EEG recordings and translating them into the vigilance level, and 3) implement the proposed system with a JAVA-based graphical user interface (GUI) for online analysis. To validate the performance of the proposed system, this study recruited eight voluntary subjects to participate a 90-min sustained-attention driving task in a virtual-realistic driving environment. Physiological evidence obtained from the power spectral analysis showed that the dry EEG system could distinguish an alert EEG from a drowsy EEG by evaluating the spectral dynamics of delta and alpha activities. Furthermore, the experimental result of the comparison of the prediction performance using four forehead electrode sites (AF8, FP2, FP1, and AF7) implied that a single-electrode EEG signal used in the mobile and wireless EEG system is able to obtain a high prediction accuracy (∼93%). Taken together, the proposed system applied a dry-EEG device combined with an effective algorithm can be a promising technology for real driving applications. © 2013 IEEE.

Lin, C-T, Prasad, M & Chang, J-Y 2013, 'Designing Mamdani Type Fuzzy Rule Using a Collaborative FCM Scheme', 2013 INTERNATIONAL CONFERENCE ON FUZZY THEORY AND ITS APPLICATIONS (IFUZZY 2013), International Conference on Fuzzy Theory and Its Applications (iFUZZY), IEEE, Taipei, TAIWAN, pp. 279-282.

Lin, CT, Wang, YK, Fan, JW & Chen, SA 2013, 'The influence of acute stress on brain dynamics', Proceedings of the 2013 IEEE Symposium on Computational Intelligence, Cognitive Algorithms, Mind, and Brain, CCMB 2013 - 2013 IEEE Symposium Series on Computational Intelligence, SSCI 2013, IEEE Symposium on Computational Intelligence, Cognitive Algorithms, Mind, and Brain (CCMB), IEEE, Singapore, pp. 6-10.
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Living under high stress may be unhealthy. This study explores electroencephalography (EEG) correlated with stressful circumstances by using the task-switching paradigm with feedback information. According to the behavioral and physiological evidence, acute stress created by this paradigm affected the performance of participants. Under stress, the participants responded quickly and inaccurately. The EEG results correlated with acute stress were found in the frontal midline cortex, especially on the theta and alpha bands. These specific factors are considered importance features for detecting the influence of stress by applying various machine-learning methods and neuro-fuzzy systems. This comprehensive study can provide knowledge for studying stress and designing Brain-Computer Interface (BCI) systems in the future. © 2013 IEEE.

Lin, CT, Wu, SL, Jiang, WL, Liang, JW & Chen, SA 2013, 'A wireless Electrooculography-based human-computer interface for baseball game', ICICS 2013 - Conference Guide of the 9th International Conference on Information, Communications and Signal Processing, International Conference on Information, Communications and Signal Processing, IEEE, Taiwan.
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Gaming control becomes popular based on the development of human-computer interface (HCI). Among many kinds of physiological signals, Electrooculography (EOG) signal is more stable which can be used to control HCI systems based on eye movement detection and signal processing methods. However, there are currently no effective multi-directional classification methods for monitoring eye movements. In addition, many EOG-based HCI systems have been developed with traditional wet electrodes. Those traditional electrodes require conductive gel and skin preparation on some users. Here, we describe a signal processing method used in a wireless EOG-based HCI system with dry electrodes for detecting eye movements to have 9 options. This system includes wireless EOG signal acquisition device, dry electrodes and an EOG signal processing algorithm. The EOG signal processing algorithm is based on 9 options of eye movement and blink signals. The results demonstrated an application of baseball game control using the proposed wireless HCI system. This system provides an effective and convenient method for eye movement detection. © 2013 IEEE.

Lin, Q, Zhang, Y, Zhang, W & Lin, X 2013, 'AVR-Tree: Speeding Up the NN and ANN Queries on Location Data', LNCS - Database Systems for Advanced Applications - Proceedings, Part I of the 18th International Conference on Database Systems for Advanced Applications, Database Systems for Advanced Applications, Springer, China, pp. 116-130.
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In the paper, we study the problems of nearest neighbor queries (NN) and all nearest neighbor queries (ANN) on location data, which have a wide range of applications such as Geographic Information System (GIS) and Location based Service (LBS). We propose a new structure, termed AVR-Tree, based on the R-tree and Voronoi diagram techniques. Compared with the existing indexing techniques used for NN and ANN queries on location data, AVR-Tree can achieve a better trade-off between the pruning effectiveness and the index size for NN and ANN queries. We also conduct a comprehensive performance evaluation for the proposed techniques based on both real and synthetic data, which shows that AVR-Tree based NN and ANN algorithms achieve better performance compared with their best competitors in terms of both CPU and I/O costs.

Lin, YY, Chang, JY & Lin, CT 2013, 'An interval type-2 neural fuzzy inference system (IT2NFIS) with compensatory operator', Proceedings of the 2013 Joint IFSA World Congress and NAFIPS Annual Meeting, IFSA/NAFIPS 2013, Joint IFSA World Congress and NAFIPS Annual Meeting (IFSA/NAFIPS), IEEE, Edmonton, AB, Canada, pp. 884-889.
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In this paper, an interval type-2 neural fuzzy system (IT2NFIS) with compensatory operator is proposed for system modeling. The IT2NFIS uses type-2 fuzzy sets in the premise clause in order to effectively handle the uncertainties in terms of data and information. The premise part of each compensatory fuzzy rule is an interval type-2 fuzzy set in the IT2NFIS, where compensatory operation is able to adaptively adjust fuzzy membership functions and to dynamically optimize fuzzy operations. The consequent part in the IT2NFIS consists of the Takagi-Sugeno-Kang (TSK) type that is a linear combination of exogenous input variables. Initially the rule base in the IT2NFIS is empty. All rules generated are based on on-line type-2 fuzzy clustering. All free weights are learned by a gradient descent algorithm to improve the learning performance. Simulation results show that our approach yields smaller root mean squared errors than its rivals. © 2013 IEEE.

Liu, C, Chen, L & Zhang, C 2013, 'Mining Probabilistic Representative Frequent Patterns From Uncertain Data', The 13th SIAM International Conference on Data Mining (SDM 2013), SIAM International Conference on Data Mining, SIAM / Omnipress, Austin, Texas, USA, pp. 1-9.
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Probabilistic frequent pattern mining over uncertain data has received a great deal of attention recently due to the wide applications of uncertain data. Similar to its counterpart in deterministic databases, however, probabilistic frequent pattern mining suffers from the same problem of generating an exponential number of result patterns. The large number of discovered patterns hinders further evaluation and analysis, and calls for the need to find a small number of representative patterns to approximate all other patterns. This paper formally defines the problem of probabilistic representative frequent pattern (P-RFP) mining, which aims to find the minimal set of patterns with sufficiently high probability to represent all other patterns. The problem's bottleneck turns out to be checking whether a pattern can probabilistically represent another, which involves the computation of a joint probability of supports of two patterns. To address the problem, we propose a novel and efficient dynamic programming-based approach. Moreover, we have devised a set of effective optimization strategies to further improve the computation efficiency. Our experimental results demonstrate that the proposed P-RFP mining effectively reduces the size of probabilistic frequent patterns. Our proposed approach not only discovers the set of P-RFPs efficiently, but also restores the frequency probability information of patterns with an error guarantee.

Liu, C, Chen, L & Zhang, C 2013, 'Summarizing Probabilistic Frequent Patterns: A Fast Approach', Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining (KDD13), ACM International Conference on Knowledge Discovery and Data Mining, ACM, Chicago, Illinois USA, pp. 527-535.
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Mining probabilistic frequent patterns from uncertain data has received a great deal of attention in recent years due to the wide applications. However, probabilistic frequent pattern mining suffers from the problem that an exponential number of result patterns are generated, which seriously hinders further evaluation and analysis. In this paper, we focus on the problem of mining probabilistic representative frequent patterns (P-RFP), which is the minimal set of patterns with adequately high probability to represent all frequent patterns. Observing the bottleneck in checking whether a pattern can probabilistically represent another, which involves the computation of a joint probability of the supports of two patterns, we introduce a novel approximation of the joint probability with both theoretical and empirical proofs. Based on the approximation, we propose an Approximate P-RFP Mining (APM) algorithm, which effectively and efficiently compresses the set of probabilistic frequent patterns. To our knowledge, this is the first attempt to analyze the relationship between two probabilistic frequent patterns through an approximate approach. Our experiments on both synthetic and real-world datasets demonstrate that the APM algorithm accelerates P-RFP mining dramatically, orders of magnitudes faster than an exact solution. Moreover, the error rate of APM is guaranteed to be very small when the database contains hundreds transactions, which further affirms APM is a practical solution for summarizing probabilistic frequent patterns.

Ma, J, Lin, H, Lu, J & Zhang, G 2013, 'A hybrid model for migrating customer segmentation with missing attributes', 2013 Joint IFSA World Congress NAFIPS Annual Meeting (IFSA/NAFIPS), Joint IFSA World Congress NAFIPS Annual Meeting, IEEE, Edmonton, Canada, pp. 825-830.
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Due to missing attributes in an enterprise's database, migrating customer segmentation results from external dataset to enterprise database in difficult. In this paper, a hybrid model, called HMCS model, is presented. This model artificially generates values of missing attributes based on external dataset and populates them to enterprise database. Based on this model, an application in a telecom application is reported. Application indicates the presented model can produce acceptable segmentation results on the enterprise dataset which is with missing attributes.

Mans, B & Mathieson, L 2013, 'On the treewidth of dynamic graphs', Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pp. 349-360.
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Dynamic graph theory is a novel, growing area that deals with graphs that change over time and is of great utility in modelling modern wireless, mobile and dynamic environments. As a graph evolves, possibly arbitrarily, it is challenging to identify the graph properties that can be preserved over time and understand their respective computability. In this paper we are concerned with the treewidth of dynamic graphs. We focus on metatheorems, which allow the generation of a series of results based on general properties of classes of structures. In graph theory two major metatheorems on treewidth provide complexity classifications by employing structural graph measures and finite model theory. Courcelle's Theorem gives a general tractability result for problems expressible in monadic second order logic on graphs of bounded treewidth, and Frick & Grohe demonstrate a similar result for first order logic and graphs of bounded local treewidth. We extend these theorems by showing that dynamic graphs of bounded (local) treewidth where the length of time over which the graph evolves and is observed is finite and bounded can be modelled in such a way that the (local) treewidth of the underlying graph is maintained. We show the application of these results to problems in dynamic graph theory and dynamic extensions to static problems. In addition we demonstrate that certain widely used dynamic graph classes naturally have bounded local treewidth. © 2013 Springer-Verlag Berlin Heidelberg.

Marcias, G, Pietroni, N, Panozzo, D, Puppo, E & Sorkine-Hornung, O 2013, 'Animation-aware quadrangulation', Proceedings of the Eleventh Eurographics/ACMSIGGRAPH Symposium on Geometry Processing, Eurographics Association, pp. 167-175.

McGregor, C 2013, 'A platform for real-time online health analytics during spaceflight', IEEE Aerospace Conference Proceedings.
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Monitoring the health and wellbeing of astronauts during spaceflight is an important aspect of any manned mission. To date the monitoring has been based on a sequential set of discontinuous samplings of physiological data to support initial studies on aspects such as weightlessness, and its impact on the cardiovascular system and to perform proactive monitoring for health status. The research performed and the real-time monitoring has been hampered by the lack of a platform to enable a more continuous approach to real-time monitoring. While any spaceflight is monitored heavily by Mission Control, an important requirement within the context of any spaceflight setting and in particular where there are extended periods with a lack of communication with Mission Control, is the ability for the mission to operate in an autonomous manner. This paper presents a platform to enable real-time astronaut monitoring for prognostics and health management within space medicine using online health analytics. The platform is based on extending previous online health analytics research known as the Artemis and Artemis Cloud platforms which have demonstrated their relevance for multi-patient, multi-diagnosis and multi-stream temporal analysis in real-time for clinical management and research within Neonatal Intensive Care. Artemis and Artemis Cloud source data from a range of medical devices capable of transmission of the signal via wired or wireless connectivity and hence are well suited to process real-time data acquired from astronauts. A key benefit of this platform is its ability to monitor their health and wellbeing onboard the mission as well as enabling the astronaut's physiological data, and other clinical data, to be sent to the platform components at Mission Control at each stage when that communication is available. As a result, researchers at Mission Control would be able to simulate, deploy and tailor predictive analytics and diagnostics during the same spaceflight for...

McGregor, C, James, A, Eklund, M, Sow, D, Ebling, M & Blount, M 2013, 'Real-time Multidimensional Temporal Analysis of Complex High Volume Physiological Data Streams in the Neonatal Intensive Care Unit', MEDINFO 2013: PROCEEDINGS OF THE 14TH WORLD CONGRESS ON MEDICAL AND HEALTH INFORMATICS, PTS 1 AND 2, 14th World Congress on Medical and Health Informatics (MEDINFO), IOS PRESS, Copenhagen, DENMARK, pp. 362-366.
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Mearns, HK & Leaney, JR 2013, 'The Use of Autonomic Management in Multi-provider Telecommunication Services', 2013 20th IEEE International Conference and Workshops on the Engineering of Computer Based Systems, IEEE International Conference and Workshops on the Engineering of Computer Based Systems, IEEE, Scottsdale, USA, pp. 129-138.
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The continuing expansion of telecommunication service domains, from Quality of Service guaranteed connectivity to ubiquitous cloud environments, has introduced an ever increasing level of complexity in the field of service management. This complexity arises not only from the sheer variability in service requirements but also through the required but ill-defined interaction of multiple organisations and providers. As a result of this complexity and variability, the provisioning and performance of current services is adversely affected, often with little or no accountability to the users of the service.This exposes a need for total coverage in the management of such complex services, a system which provides for service responsibility. Service responsibility is defined as the provisioning of service resilience and the judgement of service risk across all the service components. To be effective in responsible management for current complex services, any framework must be able to interact with multiple providers and management systems. The CARMA framework upon which we are working, aims to fulfil these requirements through a multi-agent system, that is based in a global market, and can negotiate and be responsible for multiple complex services.

Memon, T, Lu, J & Hussain, FK 2013, 'An Enhanced Mental Model Elicitation Technique to Improve Mental Model Accuracy', Lecture Notes in Computer Science, International Conference on Neural Information Processing, Springer, Daegu, South Korea, pp. 82-89.
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The causal mental model representation has been used extensively in decision support. Due to limited information requirements of this representation, that is concepts and relationships, the users are required to articulate only the mental models, without invoking the corresponding experiential knowledge stored in associative memory. The elicitation of mental models without being endorsed by experiential knowledge may lead to inaccurate, invalidated or biased mental models, and espoused theories, being stored for decision making. We introduce SDA articulation/ elicitation cycle, which invokes a users associative memory during the articulation/elicitation process to validate mental models. It is argued in this paper that by engaging associative memory during the mental model articulation/elicitation process, the accuracy and validity of mental models can be improved, the biases can be reduced, and the theories-in-use can be elicited rather than the espoused theories. A case study is presented to demonstrate the working and contributions of the SDA articulation/elicitation cycle.

Memon, T, Lu, J, Hussain, FK & Rauniyar, RK 2013, 'Subject-Oriented Semantic Knowledge Warehouse (SSKW) to Support Cognitive DSS', Lecture Notes in Computer Science, International Conference on Cooperative Information Systems, Springer, Graz, Austria, pp. 291-299.
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The communication between cognitive DSS and data warehouse tends to be inefficient due to their contradictory knowledge/data oriented nature. Data-to-knowledge conversion requires specialized techniques, whereas knowledge-to-data conversion results in loss of knowledge. To address these issues, a subject-oriented semantic knowledge warehouse (SSKW) is proposed, to provide relevant and precise knowledge to CDSS. The SSKW consists of: a) object/process/event/relationship (OPER) model to store domain knowledge in a unified fashion; and, b) a subjective view database, containing opinions of stakeholders about various OPER knowledge elements. A case study to compare the performance of the SSKW-based CDSS against a DW-based CDSS is presented. The results show that SSKW improves communication efficiency, provides relevant and precise domain knowledge to CDSS in less decision cycles, minimizes the loss of knowledge, and helps decision maker to quickly grasp the decision situation through its human-centric nature.

Meng, Q & Kennedy, PJ 2013, 'Discovering Influential Authors in Heterogeneous Academic Networks by a Co-ranking Method', Proceedings of the 22nd ACM International Conference on Information and Knowledge Management, ACM International Conference on Information and Knowledge Management, Association for Computing Machinery, San Francisco, California, USA, pp. 1029-1036.
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Research in ranking networked entities is widely applicable to many problems such as optimizing search engines, building recommendation systems and discovering influential nodes in social networks. However, many famous ranking approaches like PageRank are limited to solving this problem in homogeneous networks and are not applicable to heterogeneous networks. Faced with this problem, we propose a co--ranking method to evaluate scientific publications and authors. This novel approach is a flexible framework based on a set of customized rules taking into account both topological features of networks and the included citations. The approach ranks authors and publications iteratively and uses the results of each round to reinforce the ranks of authors and publications. Unlike traditional approaches to assessing publication, which require a great number of citations, our method lowers this requirement. This co--ranking approach has been validated using data collected from DBLP and CiteSeer, and the results suggest that it is effective and efficient in ranking authors and publications based on limited numbers of citations in heterogeneous networks and that it has fast convergence.

Moonsamy, V, Rong, J, Liu, S, Li, G & Batten, L 2013, 'Contrasting Permission Patterns between Clean and Malicious Android Applications', Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, International Conference on Security and Privacy for Communication Networks, Springer, Sydney, Australia, pp. 69-85.
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The Android platform uses a permission system model to allow users and developers to regulate access to private information and system resources required by applications. Permissions have been proved to be useful for inferring behaviors and characteristics of an application. In this paper, a novel method to extract contrasting permission patterns for clean and malicious applications is proposed. Contrary to existing work, both required and used permissions were considered when discovering the patterns. We evaluated our methodology on a clean and a malware dataset, each comprising of 1227 applications. Our empirical results suggest that our permission patterns can capture key differences between clean and malicious applications, which can assist in characterizing these two types of applications.

Musial, K, Gabrys, B & Buczko, M 2013, 'What kind of network are you? - Using local and global characteristics in network categorisation tasks', 2013 IEEE/ACM INTERNATIONAL CONFERENCE ON ADVANCES IN SOCIAL NETWORKS ANALYSIS AND MINING (ASONAM), IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), IEEE, Niagara Falls, CANADA, pp. 1366-1373.

Naderpour, M, Lu, J & Zhang, G 2013, 'A Fuzzy Dynamic Bayesian Network-Based Situation Assessment Approach', The Proceeding of IEEE International Conference on Fuzzy Systems, IEEE International Conference on Fuzzy Systems, IEEE, Hyderabad, India, pp. 1-8.
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Situation awareness (SA), a state in the mind of a human, is essential to conduct decision-making activities. It is about the perception of the elements in the environment, the comprehension of their meaning, and the projection of their status in the near future. Two decades of investigation and analysis of accidents have showed that SA was behind of many serious large-scale technological systems accidents. This emphasizes the importance of SA support systems development for complex and dynamic environments. This paper presents a fuzzy dynamic Bayesian network-based situation assessment approach to support the operators in decision making process in hazardous situations. The approach includes a dynamic Bayesian network-based situational network to model the hazardous situations where the existence of the situations can be inferred by sensor observations through the SCADA monitoring system using a fuzzy quantizer method. In addition to generate the assessment result, a fuzzy risk estimation method is proposed to show the risk level of situations. Ultimately a hazardous environment from U.S. Chemical Safety Board investigation reports has been used to illustrate the application of proposed approach.

Natgunanathan, I, Xiang, Y, Elbadry, SSM, Zhou, W & Xiang, Y 2013, 'Analysis of a patchwork-based audio watermarking scheme', Proceedings of the 2013 IEEE 8th Conference on Industrial Electronics and Applications, ICIEA 2013, pp. 900-905.
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Recently, a patchwork-based audio watermarking scheme has been proposed in [1], which embeds watermarks by modifying the means of absolute-valued discrete cosine transform (DCT) coefficients corresponding to suitable fragments. This audio watermarking scheme is more robust to common attacks than the existing counterparts. In this paper, we presents a detailed analysis of this audio watermarking scheme. We first derive a probability density function (pdf) of a random variable corresponding to the mean of an absolute-valued DCT fragment. Then, based on the obtained pdf, we show how watermarking parameters affect the performance of the concerned audio watermarking scheme. The analysis result provides a guideline for the selection of watermarking parameters. The effectiveness of our analysis is verified by simulations using a large number of real-world audio segments. © 2013 IEEE.

Niazi, MK, Mahmood, S, Alshayeb, M, Baqai, AA & Gill, AQ 2013, 'Motivators of Adopting Social Computing in Global Software Development: Initial Results', Proceedings of the World Congress on Engineering 2013 Vol I, World Congress on Engineering, IAENG, London, U.K, pp. 1-5.
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Abstract context: Real-time collaboration is critical for developing high quality software systems at low cost in a geographically distributed Global Software Development (GSD) environment. It is anticipated that emerging Social Computing tools can play an important role in facilitating realtime effective collaboration among teams working in the GSD. Objective: The objective of this research paper is to identify motivators for adopting social computing in GSD organizations. Method: We adopted a Systematic Literature Review (SLR) approach by applying customized search strings derived from our research questions. Results: We have identified factors such as real-time communication and coordination, information sharing, knowledge acquisition and expert feedback as key motivators for adoption of social computing in GSD. Conclusion: Based on the SLR results, we suggest that GSD organizations should embrace social computing as a tool for real-time collaboration between distributed GSD teams. The results of this initial study also suggest the need for developing the social computing strategies and policies to guide the effective social computing adoption by GSD teams.

Novianto, R, Johnston, BG & Williams, M 2013, 'Habituation and sensitisation learning in ASMO cognitive architecture', Lecture Notes in Computer Science, International Conference on Social Robotics (ICSR), Springer International Publishing, Bristol, United Kingdom, pp. 249-259.
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As social robots are designed to interact with humans in unstructured environments, they need to be aware of their surroundings, focus on significant events and ignore insignificant events in their environments. Humans have demonstrated a good example of adaptation to habituate and sensitise to significant and insignificant events respectively. Based on the inspiration of human habituation and sensitisation, we develop novel habituation and sensitisation mechanisms and include these mechanisms in ASMO cognitive architecture. The capability of these mechanisms is demonstrated in the `Smokey robot companion experiment. Results show that Smokey can be aware of their surroundings, focus on significant events and ignore insignificant events. ASMOs habituation and sensitisation mechanisms can be used in robots to adapt to the environment. It can also be used to modify the interaction of components in a cognitive architecture in order to improve agents or robots performances.

Oberst, S & Lai, JCS 2013, 'The role of pad-mode instabilities in disc brake squeal', 20th International Congress on Sound and Vibration 2013, ICSV 2013, International Congress on Sound and Vibration, Bangkok, Thailand, pp. 2861-2868.
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Automotive disc brake squeal remains an economically significant and technically challenging problem to solve, owing to customer complaints' associated warranty costs and the many interacting parameters. While industrial practice aims at identifying unstable vibration modes using complex eigenvalue analysis, in this paper, we show how to identify pad-mode instabilities using vibration forced response analysis complemented by acoustic radiation calculations for simplified brake systems in the form of a pad-on-plate model. Our recent results indicate that pad-mode instabilities might trigger so-called instantaneous mode squeal without the necessity of mode coupling. Pad-mode instabilities, which complex eigenvalue analysis fails to detect, are revealed by the dissipated energy spectrum at frequencies where the dissipated energy is negative (i.e. providing energy instead of dissipating energy). Pad-modes seem to radiate locally higher sound pressure depending on the phase shift between the structural vibration and the sound pressure while exciting the underlying plate's or disc's modes. Pad-mode instabilities are shown to be one mechanism of brake squeal. In order to identify pad-mode instabilities, it is beneficial to perform a full range of vibration analysis which includes complex eigenvalue value analysis, forced response and dissipated energy spectra as well as acoustic radiation calculations for a range of different parameters such as friction coefficient, operating pressure, temperature and contact conditions.

Oberst, SM & Lai, J 2013, 'The role of pad-modes and nonlinearity in instantaneous mode squeal', Proceedings of Meetings on Acoustics, Meetings on Acoustics.
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Disc brake squeal is a major source of customer dissatisfaction and related warranty costs for automobile manufacturers. Although mode coupling is recognised as a mechanism often found in squealing brakes, recent research results show that friction induced pad-mode instabilities could be the cause of instantaneous mode squeal reported in the literature. In this paper, the nonlinear characteristics of instantaneous mode squeal initiated by pad-mode instabilities are studied by analysing phase space plots of vibrations and sound pressure for a numerical model of a pad-on-plate system as the friction coefficient increases. Results show tat as the friction coefficient increases from 0.05 to 0.65, attractors of vibration in the phase space transits from limit cycle to quasi-periodic, showing signs of approaching chaotic behaviour. It is shown here that the correlation of the sound pressure behaviour in the phase-space with structural vibration is crucial to understanding the role of pad modes and nonlinearity in instantaneous mode squeal. © 2013 Acoustical Society of America.

Palmas, G, Pietroni, N, Cignoni, P & Scopigno, R 2013, 'A computer-assisted constraint-based system for assembling fragmented objects', Digital Heritage International Congress (DigitalHeritage), 2013, IEEE, pp. 529-536.

Peeters, M, Megens, C, van den Hoven, E, Hummels, C & Brombacher, A 2013, 'Social Stairs: taking the Piano Staircase towards long-term behavioral change', Lecture Notes in Computer Science, International Conference on Persuasive Technology, Springer, Sydney, NSW, Australia, pp. 174-179.
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Abstract. This paper addresses the development of Social Stairs, an intelli-gent musical staircase to change peoples behavior in the long-term to take the stairs in favor of the elevator. Through designing with the Experiential Design Landscape (EDL) method, a design opportunity was found that social engage-ment encouraged people to take the stairs at work in favor of the elevator. To encourage this social behavior, people who involved each other and worked to-gether whilst using the Social Stairs were treated with more diverse orchestral chimes that echoed up the stairwell. In this paper we reflect on the differences between the persuasive system of the well-known Piano Staircase and the So-cial Stairs. We report on the deployment of the Social Stairs for a period of three weeks in the public space within the university community and identify opportunities for triggering intrinsic motivation, social engagement and how to keep people involved in the long-term.

Pisan, Y, Garcia Marin, JA & Felix Navarro, KM 2013, 'Improving Lives: Using Microsoft Kinect to Predict the Loss of Balance for Elderly Users under Cognitive Load', Proceedings of the Ninth Australasian Conference on Interactive Entertainment, Interactive Entertainment, ACM Press, Melbourne, Australia, pp. 1-4.
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Among older adults, falling down while doing everyday tasks is the leading cause for injuries, disabilities and can even result in death. Furthermore, even when no injury has occurred the fear of falling can result in loss of confidence and independence. The two major factors in the loss of balance is weakening of the muscles and reduced cognitive skills. While exercise programmes can reduce the risk of falling by 40%, patient compliance with these programmes is low. We present the Microsoft-Kinect based step training program system that we have developed specifically for elderly patients. The program measures physical health and cognitive abilities and incorporates an individualized adaptive program for improvements. The real-time data obtained from the program is similar to clinical evaluations typically conducted by doctors and the game-like exercises result in increased adherence to the exercise regimes

Prasad, M, Lin, CT, Yang, CT & Saxena, A 2013, 'Vertical collaborative fuzzy C-means for multiple EEG data sets', Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), International Conference on Intelligent Robotics and Applications, Springer, Busan, South Korea, pp. 246-257.
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Vertical Collaborative Fuzzy C-Means (VC-FCM) is a clustering method that performs clustering on a data set of having some set of patterns with the collaboration of some knowledge which is obtained from other data set having the same number of features but different set of patterns. Uncertain relationship lies in data between the data sets as well as within a dataset. Practically data of the same group of objects are usually stored in different datasets; in each data set, the data dimensions are not necessarily the same and unreal data may exist. Fuzzy clustering of a single data set would bring about less reliable results. And these data sets cannot be integrated for some reasons. An interesting application of vertical clustering occurs when dealing with huge data sets. Instead of clustering them in a single pass, we split them into individual data sets, cluster each of them separately, and reconcile the results through the collaborative exchange of prototypes. Vertical collaborative fuzzy C-Means is a useful tool for dealing collaborative clustering problems where a feature space is described in different pattern-sets. In this paper we use collaborative fuzzy clustering, first we cluster each data set individually and then optimize in accordance with the dependency of these datasets is adopted so as to improve the quality of fuzzy clustering of a single data set with the help of other data sets, taking personal privacy and security of data into consideration. © 2013 Springer-Verlag Berlin Heidelberg.

Qiao, Y, Sun, X & Yu, N 2013, 'Determinantal Complexities and Field Extensions', LNCS - Algorithms and Computation - Proceedings of the 24th International Symposium, ISAAC 2013, International Symposium on Algorithms and Computation, Springer, Hong Kong, pp. 119-129.
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Let F be a field of characteristic ??2. The determinantal complexity of a polynomial P?F[x1,,xn] is defined as the smallest size of a matrix M whose entries are linear polynomials of x i s over F, such that P=det(M) as polynomials in F[x1,,xn]. To determine the determinantal complexity of the permanent polynomial is a long-standing open problem. Let K be an extension field of F; then P can be viewed as a polynomial over K. We are interested in the comparison between the determinantal complexity of P over K (denoted as dcK(P)), and that of P over F (denoted as dcF(P)). It is clear that dcK(P)=dcF(P), and the question is whether strict inequality can happen. In this note we consider polynomials defined over Q.

Raduescu, C & Gill, AQ 2012, 'Handling the Complexity of ISD Projects with Agile Methods: A Conceptual Foundation', Proceedings of the 2012 International Conference on Information Systems Development, International Conference on Information Systems Development, Springer, Prato Centre, Italy, pp. 417-427.
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Traditional approaches to software and information systems development (ISD) cannot fulfill the challenges presented by the complexity inherent in todays dynamic and changing environments. In this study we argue that ISD projects are socially complex endeavors and suggest that agile development methods display characteristics that justify them as being appropriate for such project environments. We suggest that one theory that justifies the appropriateness of agile methods in such contexts is the complex adaptive systems (CAS) theory. We first argue that ISD projects can be treated as CAS, and second, we assess the alignment between CAS characteristics and agile methods principles. We therefore propose and discuss a preliminary conceptual foundation for handling the complexity of ISD projects with agile methods. Our future research directions seek to investigate the applicability of specific agile methods and develop a comprehensive framework that will offer a validated theoretical justification of better approaches to manage complex ISD projects in practice.

Raffe, WL, Zambetta, F & Li, X 2013, 'Neuroevolution of content layout in the PCG: Angry bots video game', 2013 IEEE Congress on Evolutionary Computation, CEC 2013, IEEE Congress on Evolutionary Computation, IEEE, Cancun, Mexico, pp. 673-680.
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This paper demonstrates an approach to arranging content within maps of an action-shooter game. Content here refers to any virtual entity that a player will interact with during game-play, including enemies and pick-ups. The content layout for a map is indirectly represented by a Compositional Pattern-Producing Networks (CPPN), which are evolved through the Neuroevolution of Augmenting Topologies (NEAT) algorithm. This representation is utilized within a complete procedural map generation system in the game PCG: Angry Bots. In this game, after a player has experienced a map, a recommender system is used to capture their feedback and construct a player model to evaluate future generations of CPPNs. The result is a content layout scheme that is optimized to the preferences and skill of an individual player. We provide a series of case studies that demonstrate the system as it is being used by various types of players. © 2013 IEEE.

Ramezani, F, Hussain, FK & Lu, J 2013, 'A Fuzzy Predictable Load Balancing Approach in Cloud Computing', Proceedings of the International Conference on Grid & Cloud Computing and Applications GCA'13, International Conference on Grid & Cloud Computing and Applications, WorldComp, Las Vegas, Nevada, USA.
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Cloud computing is a new paradigm for hosting and delivering services on demand over the internet where users access services. It is an example of an ultimately virtualized system, and a natural evolution for data centers that employ automated systems management, workload balancing, and virtualization technologies. Live virtual machine (VM) migration is a technique to achieve load balancing in cloud environment by transferring an active overload VM from one physical host to another one without disrupting the VM. In this study, to eliminate whole VM migration in load balancing process, we propose a Fuzzy Predictable Load Balancing (FPLB) approach which confronts with the problem of overload VM, by assigning the extra tasks from overloaded VM to another similar VM instead of whole VM migration. In addition, we propose a Fuzzy Prediction Method (FPM) to predict VMs migration time. This approach also contains a multi-objective optimization model to migrate these tasks to a new VM host. In proposed FPLB approach there is no need to pause VM during migration time. Furthermore, considering this fact that VM live migration contrast to tasks migration takes longer to complete and needs more idle capacity in host physical machine (PM), the proposed approach will significantly reduce time, idle memory and cost consumption.

Ramezani, F, Lu, J & Hussain, FK 2013, 'An Online Fuzzy Decision Support System for Resource Management in Cloud Environments', Proceedings of the 2013 Joint IFSA World Congress and NAFIPS Annual Meeting (IFSA/NAFIPS), Joint IFSA World Congress and NAFIPS Annual Meeting, IEEE, Edmonton, Canada, pp. 754-760.
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Cloud computing is a large-scale distributed computing paradigm driven by economies of scale, in which a pool of abstracted, virtualized, dynamically-scalable, managed computing power, storage, platforms, and services are delivered on demand to external customers over the Internet. Although a significant amount of studies have been developed to optimize resource management and task scheduling in cloud computing, none of them considered the impact of task scheduling patterns on resource management and vice versa. To overcome this drawback, and considering the lack of resources in cloud environments and growing customer demands for cloud services, this paper proposes an Online Resource Management Decision Support System (ORMDSS) that addresses both tasks scheduling and resource management optimization in a unique system. In addition, ORMDSS contains a fuzzy prediction method for predicting VM workload patterns and VM migration time by applying neural networks and fuzzy expert systems. This ORMDSS helps cloud providers to automatically allocate scare resources to the applications and services in an optimal way. It is expected that the ORMDSS not only increases cloud utilization and QoS, but also decreases cost and response time.

Ramezani, F, Lu, J & Hussain, FK 2013, 'Task Scheduling Optimization in Cloud Computing Applying Multi-Objective Particle Swarm Optimization', Lecture Notes in Computer Science, IEEE International Conference on Service-Oriented Computing and Applications, Springer, Berlin, Germany, pp. 237-251.
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Optimizing the scheduling of tasks in a distributed heterogeneous computing environment is a nonlinear multi-objective NP-hard problem which is playing an important role in optimizing cloud utilization and Quality of Service (QoS). In this paper, we develop a comprehensive multi-objective model for optimizing task scheduling to minimize task execution time, task transferring time, and task execution cost. However, the objective functions in this model are in conflict with one another. Considering this fact and the supremacy of Particle Swarm Optimization (PSO) algorithm in speed and accuracy, we design a multi-objective algorithm based on multi-objective PSO (MOPSO) method to provide an optimal solution for the proposed model. To implement and evaluate the proposed model, we extend Jswarm package to multi-objective Jswarm (MO-Jswarm) package. We also extend Cloudsim toolkit applying MO-Jswarm as its task scheduling algorithm. MO-Jswarm in Cloudsim determines the optimal task arrangement among VMs according to MOPSO algorithm. The simulation results show that the proposed method has the ability to find optimal trade-off solutions for multi-objective task scheduling problems that represent the best possible compromises among the conflicting objectives, and significantly increases the QoS.

Ramezani, F, Lu, J & Hussain, FK 2013, 'Task Scheduling Optimization in Cloud Computing Applying Multi-Objective Particle Swarm Optimization', Proceedings of the 11th International Conference on Service-Oriented Computing, 11th International Conference on Service-Oriented Computing, Springer Verlag, Berlin, Germany, pp. 237-251.
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Raza, S, Haider, S & Williams, M 2013, 'Robot reasoning using first order bayesian networks', Lecture Notes in Computer Science, International Symposium on Integrated Uncertainty in Knowledge Modelling and Decision Making, Springer, Beijing, China, pp. 1-12.
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This study presents the application of first-order Bayesian Networks (FOBN) to model and reason in domains with complex relational and rich probabilistic structures. The FOBN framework used in this study is 'multi-entity Bayesian networks (MEBN). MEBN ha

Rehman, Z, Hussain, FK, Hussain, O & Singh, J 2013, 'Is There Self-Similarity in Cloud QoS Data?', 2013 IEEE 10th International Conference on e-Business Engineering, IEEE International Conference on e-Business Engineering, IEEE Computer Society, Coventry, UK, pp. 76-81.
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Monitoring and forecasting of QoS of cloud services is becoming increasingly important with increasing use of cloud computing. Cloud service selection, SLA compliance, service migration and many other areas in current cloud computing research rely on QoS data collected thorough cloud service monitoring. In this paper we have presented the results of our experiments for estimating the self-similarity in cloud service QoS data.

Rehman, Z, Hussain, OK & Hussain, FK 2013, 'Multi-criteria IaaS Service Selection Based on QoS History', 2013 IEEE 27th International Conference on Advanced Information Networking and Applications (AINA), International Conference on Advanced Information Networking and Applications (was ICOIN), IEEE, Barcelona, Spain, pp. 1129-1135.
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The growing number of cloud services have made service selection a challenging decision-making problem by providing wide ranging choices for cloud service consumers. This necessitates the use of formal decision making methodologies to assist a decision maker in selecting the service that best fulfils the user's requirements. In this paper, we present a cloud service selection methodology that utilizes QoS history over different time periods, performs Multi-Criteria Decision Analysis to rank all cloud services in each time period in accordance with user preferences before aggregating the results to determine the overall service rank of all the available services for cloud service selection.

Reitsma, L, Smith, A & van den Hoven, E 2013, 'StoryBeads: Preserving Indigenous Knowledge through Tangible Interaction Design', Proceedings of Culture and Computing 2013, International Conference on Culture and Computing, IEEE Computer Society, Kyoto, Japan, pp. 79-85.
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This paper addresses the need to preserve culturally unique knowledge for future generations. This user-centered design-research case study focused on preserving Indigenous Knowledge (IK) of the South-African BaNtwane culture, specifically focusing on their rich beadwork and oral traditions. Our approach allows for design research in a scenario where the community is represented by a few prominent members, simultaneously making provision for the incorporation of modern technology in a society trailing in technology adoption. The study resulted in a recording device that fits the target group's oral tradition and is based on a concept in which oral stories are recorded and associated with tangible beads that can be incorporated into traditional beadwork. The device and interaction design embraces the culture's aesthetics and existing IK mechanisms.

Ren, Y, Li, G & Zhou, W 2013, 'Recommendation techniques based on off-line data processing a multifaceted survey', Proceedings - 2013 9th International Conference on Semantics, Knowledge and Grids, SKG 2013, pp. 6-13.
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Recommendations based on off-line data processing has attracted increasing attention from both research communities and IT industries. The recommendation techniques could be used to explore huge volumes of data, identify the items that users probably like, and translate the research results into real-world applications, etc. This paper surveys the recent progress in the research of recommendations based on off-line data processing, with emphasis on new techniques (such as context-based recommendation, temporal recommendation), and new features (such as serendipitous recommendation). Finally, we outline some existing challenges for future research. © 2013 IEEE.

Ren, Y, Li, G, Zhang, J & Zhou, W 2013, 'AdaM: Adaptive-Maximum imputation for neighborhood-based collaborative filtering', Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2013, pp. 628-635.
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In the context of collaborative filtering, the well-known data sparsity issue makes two like-minded users have little similarity, and consequently renders the κ nearest neighbour rule inapplicable. In this paper, we address the data sparsity problem in the neighbourhood-based CF methods by proposing an Adaptive-Maximum imputation method (AdaM). The basic idea is to identify an imputation area that can maximize the imputation benefit for recommendation purposes, while minimizing the imputation error brought in. To achieve the maximum imputation benefit, the imputation area is determined from both the user and the item perspectives; to minimize the imputation error, there is at least one real rating preserved for each item in the identified imputation area. A theoretical analysis is provided to prove that the proposed imputation method outperforms the conventional neighbourhood-based CF methods through more accurate neighbour identification. Experiment results on benchmark datasets show that the proposed method significantly outperforms the other related state-of-the-art imputation-based methods in terms of accuracy. Copyright 2013 ACM.

Ren, Y, Zhu, T, Li, G & Zhou, W 2013, 'Top-N recommendations by learning user preference dynamics', Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pp. 390-401.
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In a recommendation system, user preference patterns and the preference dynamic effect are observed in the user x item rating matrix. However, their value has barely been exploited in previous research. In this paper, we formalize the preference pattern as a sparse matrix and propose a Preference Pattern Subspace to iteratively model the personal and the global preference patterns with an EM-like algorithm. Furthermore, we propose a PrepSVD-I algorithm by transforming the Top-N recommendation as a pairwise preference learning process. Experiment results show that the proposed PrepSVD-I algorithm significantly outperforms the state-of-the-art Top-N recommendation algorithms. © Springer-Verlag 2013.

Sanders, K, Ahmadzadeh, M, Clear, T, Edwards, S, goldweber, M, Johnson, C, Lister, RF, McCartney, R, Patitsas, E & Spacco, J 2013, 'The Canterbury QuestionBank: building a repository of multiple-choice CS1 and CS2 questions', Proceedings of the ITiCSE working group reports conference on Innovation and technology in computer science education-working group reports, Annual Conference on Innovation and Technology in Computer Science Education, ACM, Canterbury, Kent, United Kingdom, pp. 33-51.
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Abstract: In this paper, we report on an ITiCSE-13 Working Group that developed a set of 654 multiple-choice questions on CS1 and CS2 topics, the Canterbury QuestionBank. We describe the questions, the metadata we investigated, and some preliminary investigations of possible research uses of the QuestionBank. The QuestionBank is publicly available as a repository for computing education instructors and researchers.

Sasaki, N, Chen, HT, Sakamoto, D & Igarashi, T 2013, 'Facetons: Face primitives with adaptive bounds for building 3D architectural models in virtual environment', Proceedings of the ACM Symposium on Virtual Reality Software and Technology, VRST, CM Symposium on Virtual Reality Software and Technology, pp. 77-82.
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We present faceton, a geometric modeling primitive designed for building architectural models, using a six degrees of freedom (DoF) input device in a virtual environment (VE). A faceton is given as an oriented point floating in the air and defines a plane of infinite extent passing through the point. The polygonal mesh model is constructed by taking the intersection of the planes associated with the facetons. With the simple drag-and-drop and group interaction of faceton, users can easily create 3D architecture models in the VE. The faceton primitive and its interaction reduce the overhead associated with standard polygonal mesh modeling in VE, where users have to manually specify vertexes and edges which could be far away. The faceton representation is inspired by the research on boundary representations (B-rep) and constructive solid geometry (CSG), but it is driven by a novel adaptive bounding algorithm and is specifically designed for the 3D modeling activities in an immersive virtual environment. Copyright © 2013 ACM.

Schubert, E, Ferguson, S, Farrar, N, Taylor, D & McPherson, GE 2012, 'The Six Emotion-Face Clock as a Tool for Continuously Rating Discrete Emotional Responses to Music', From Sounds to Music and Emotions (LNCS), CMMR: International Symposium on Computer Music Modeling and Retrieval, Springer, 9th International Symposium, pp. 1-18.
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Recent instruments measuring continuous self-reported emotion responses to music have tended to use dimensional rating scale models of emotion such as valence (happy to sad). However, numerous retrospective studies of emotion in music use checklist style responses, usually in the form of emotion words, (such as happy, angry, sad) or facial expressions. A response interface based on six simple sketch style emotion faces aligned into a clock-like distribution was developed with the aim of allowing participants to quickly and easily rate emotions in music continuously as the music unfolded. We tested the interface using six extracts of music, one targeting each of the six faces: `Excited (at 1 oclock), `Happy (3), `Calm (5), `Sad (7), `Scared (9) and `Angry (11). 30 participants rated the emotion expressed by these excerpts on our `emotion-face-clock. By demonstrating how continuous category selections (votes) changed over time, we were able to show that (1) more than one emotion-face could be expressed by music at the same time and (2) the emotion face that best portrayed the emotion the music conveyed could change over time, and (3) the change could be attributed to changes in musical structure. Implications for research on orientation time and mixed emotions are discussed.

Schubert, P & Williams, SP 2013, 'The concept of Social business: Oxymoron or sign of a changing work culture?', 26th Bled eConference - eInnovations: Challenges and Impacts for Individuals, Organizations and Society, Proceedings, pp. 222-235.
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The article discusses the source and pertinence of the term "Social Business". We present the findings from a study of projects that are in the early stages of adoption of Social Software in organisations. Using a qualitative research approach we examine real-world cases of implementations of integrated Enterprise Collaboration Systems. 16 existing cases (desk research) and three new cases (field research) are analysed and the findings are compared and aggregated. We apply the 8C Model as an analytical lens to guide the coding of the case data. The study's results reveal the relations between the different concepts (features, components, collaboration scenarios) that can be identified in the cases. The findings show that the most popular usage scenarios of the software are not very "social" but support people in their daily joint work with a focus on getting the job done. The study also reveals possible beneficial factors for the adoption of Social Software such as improved personal information management, mobile devices and unified communication, and better workspace and presence awareness.

Sharma, N, Chanda, S, Pal, U & Blumenstein, M 2013, 'Word-wise script identification from video frames', Proceedings of the International Conference on Document Analysis and Recognition, ICDAR, International Conference on Document Analysis and Recognition (ICDAR), IEEE, Washington, DC, USA, pp. 867-871.
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Script identification is an essential step for the efficient use of the appropriate OCR in multilingual document images. There are various techniques available for script identification from printed and handwritten document images, but script identification from video frames has not been explored much. This paper presents a study of some pre-processing techniques and features for word-wise script identification from video frames. Traditional features, namely Zernike moments, Gabor and gradient, have performed well for handwritten and printed documents having simple backgrounds and adequate resolution for OCR. Video frames are mostly coloured and suffer from low resolution, blur, background noise, to mention a few. In this paper, an attempt has been made to explore whether the traditional script identification techniques can be useful in video frames. Three feature extraction techniques, namely Zernike moments, Gabor and gradient features, and SVM classifiers were considered for analyzing three popular scripts, namely English, Bengali and Hindi. Some pre-processing techniques such as super resolution and skeletonization of the original word images were used in order to overcome the inherent problems with video. Experiments show that the super resolution technique with gradient features has performed well, and an accuracy of 87.5% was achieved when testing on 896 words from three different scripts. The study also reveals that the use of proper pre-processing approaches can be helpful in applying traditional script identification techniques to video frames. © 2013 IEEE.

Sharma, N, Shivakumara, P, Pal, U, Blumenstein, M & Tan, CL 2013, 'A new method for character segmentation from multi-oriented video words', Proceedings of the International Conference on Document Analysis and Recognition, ICDAR, International Conference on Document Analysis and Recognition (ICDAR), IEEE, USA, pp. 413-417.
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This paper presents a two-stage method for multi-oriented video character segmentation. Words segmented from video text lines are considered for character segmentation in the present work. Words can contain isolated or non-touching characters, as well as touching characters. Therefore, the character segmentation problem can be viewed as a two stage problem. In the first stage, text cluster is identified and isolated (non-touching) characters are segmented. The orientation of each word is computed and the segmentation paths are found in the direction perpendicular to the orientation. Candidate segmentation points computed using the top distance profile are used to find the segmentation path between the characters considering the background cluster. In the second stage, the segmentation results are verified and a check is performed to ascertain whether the word component contains touching characters or not. The average width of the components is used to find the touching character components. For segmentation of the touching characters, segmentation points are then found using average stroke width information, along with the top and bottom distance profiles. The proposed method was tested on a large dataset and was evaluated in terms of precision, recall and f-measure. A comparative study with existing methods reveals the superiority of the proposed method. © 2013 IEEE.

Smith, S, Gill, AQ, Hasan, H & Ghobadi, S 2013, 'An Enterprise Architecture Driven Approach to Virtualisation', Pacific Asia Conference on Information Systems (PACIS 2013) Conference Proceedings Website, Pacific Asia Conference on Information Systems, AIS, Seogwipo City, Jeju-do, Korea, pp. 1-13.
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Organisations have shown a significant interest in the adoption of virtualisation technology for improving the efficiency of their Data Centres (DC) from both the resource performance and cost efficiency viewpoints. By improving the efficiency of data centres we can sustainably manage their impact on the environment by controlling their energy consumption. The intentions are clear but how best to approach to Data Centre virtualisation is not. This paper proposes an integrated Enterprise Architecture and Information Infrastructure (EAII) driven approach to guide the Data Centre virtualisation. The EAII approach has been developed based on the review and analysis of well-known The Open Group Architecture Framework (TOGAF) and Information Infrastructure (II) model. The proposed integrated EAII approach seems appropriate to guide and align business strategy and virtualisation implementation for data centres of any size in any industry vertical.

Sriyanyong, P & Lu, H 2013, 'Implementation and Comparison of PSO-Based Algorithms for Multi-Modal Optimization Problems', Proceedings of 2013 International Symposium on Computational Models for Life Sciences vol 1559, Issue 1, International Symposium on Computational Models for Life Sciences, AIP publishing, Sydney, Australia, pp. 165-174.
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This paper aims to compare the global search capability and overall performance of a number of Particle Swarm Optimization (PSO) based algorithms in the context solving the Dynamic Economic Dispatch (DED) problem which takes into account the operation limitations of generation units such as valve-point loading effect as well as ramp rate limits. The comparative study uses six PSO-based algorithms including the basic PSO and hybrid PSO algorithms using a popular benchmark test IEEE power system which is 10-unit 24-hour system with non-smooth cost functions. The experimental results show that one of the hybrid algorithms that combines the PSO with both inertia weight and constriction factor, and the Gaussian mutation operator (CBPSO-GM) is promising in achieving the near global optimal of a non-linear multi-modal optimization problem, such as the DED problem under the consideration

Sui, Y, Li, Y & Xue, J 2013, 'Query-directed adaptive heap cloning for optimizing compilers', Proceedings of the 2013 IEEE/ACM International Symposium on Code Generation and Optimization, CGO 2013.
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Andersen's pointer analysis becomes more precise when applied with full heap cloning but unscalable for large, heap-intensive programs. In contrast, k-callsite-sensitive heap cloning can be faster but less precise for some programs. In this paper, we make one step forward by enhancing Andersen's analysis with QUery-Directed Adaptive (QUDA) heap cloning for optimizing compilers. The novelty of our analysis, called QUDA, lies in performing k-callsite-sensitive heap cloning iteratively, starting with k = 0 (without heap cloning), so that an abstract heap object is cloned at iteration k = i + 1 only if some mayalias queries that are not answered positively at iteration k = i may now be answered more precisely. QUDA, which is implemented in Open64, has the same precision as the state-of-the-art, FULCRA, a version of QUDA with exhaustive heap cloning, but is significantly more scalable. For 10 SPEC2000 C benchmarks and 5 C applications (totalling 840 KLOC) evaluated, QUDA takes only 4+ minutes but exhaustive heap cloning takes 42+ minutes to complete. QUDA takes only 75.1 % of the time that Open64 takes on average to compile these 15 programs under '-O2'. © 2013 IEEE.

Sundaresan, S, Doss, R & Zhou, W 2013, 'Offline grouping proof protocol for RFID systems', International Conference on Wireless and Mobile Computing, Networking and Communications, pp. 247-252.
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Several grouping proof protocols have been proposed over the years but they are either found to be vulnerable to certain attacks or do not comply with EPC Class-1 Gen-2 (C1G2) standard because they use hash functions or other complex encryption schemes. Also, synchronization of keys, forward security, proving simultaneity, creating dependence, detecting illegitimate tags, eliminating unwanted tag processing and denial-of-proof (DoP) attacks have not been fully addressed by many. Our protocol addresses these important gaps and is based on Quadratic Residues property where the tags are only required to use XOR, 128-bit Pseudo Random Number Generators (PRNG) and Modulo (MOD) operations which can be easily implemented on low-cost passive tags and hence achieves EPC C1G2 compliance. © 2013 IEEE.

Sundaresan, S, Doss, R & Zhou, W 2013, 'RFID tags - Grouping proof with forward security', 2013 IEEE International Conference on RFID-Technologies and Applications, RFID-TA 2013.
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Several grouping proof protocols have been proposed over the years but they are either found to be vulnerable to certain attacks or do not comply with EPC Class-1 Gen-2 (C1G2) standard because they use hash functions or other complex encryption schemes. Among other requirements, synchronization of keys, forward security, dependence, detecting illegitimate tags, eliminating unwanted tag processing and denial-of-proof (DoP) attacks have not been fully addressed by many. Our protocol addresses these important gaps and is based on simple XOR encryption and 128-bit Pseudo Random Number Generators (PRNG), operations that are easily implemented on low-cost passive tags and hence achieves EPC C1G2 compliance. © 2013 IEEE.

Sundaresan, S, Doss, R & Zhou, W 2013, 'Secure ownership transfer in multi-tag/multi-owner passive RFID systems', GLOBECOM - IEEE Global Telecommunications Conference, pp. 2891-2896.
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In this paper we propose a secure ownership transfer protocol for a multi-tag and multi-owner RFID environment. Most of the existing work in this area do not comply with the EPC Global Class-1 Gen-2 (C1G2) standard since they use expensive hash operations or sophisticated encryption schemes that cannot be implemented on low-cost passive tags that are highly resource constrained. Our work aims to fill this gap by proposing a protocol based on simple XOR and 128-bit Pseudo Random Number Generators (PRNG), operations that can be easily implemented on low-cost passive RFID tags. The protocol thus achieves EPC C1G2 compliance while meeting the security requirements. Also, our protocol provides additional protection using a blind-factor to prevent tracking attacks. © 2013 IEEE.

Tafavogh, S, Felix Navarro, KM, Catchpoole, DR & Kennedy, PJ 2013, 'Segmenting Neuroblastoma Tumor Images and Splitting Overlapping Cells Using Shortest Paths between Cell Contour Convex Regions', Lecture Notes in Computer Science, Artificial Intelligence in Medicine in Europe, Elsevier, Murcia, Spain, pp. 171-175.
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Neuroblastoma is one of the most fatal paediatric cancers. One of the major prognostic factors for neuroblastoma tumour is the total number of neuroblastic cells. In this paper, we develop a fully automated system for counting the total number of neuroblastic cells within the images derived from Hematoxylin and Eosin stained histological slides by considering the overlapping cells. We finally propose a novel multi-stage cell counting algorithm, in which cellular regions are extracted using an adaptive thresholding technique. Overlapping and single cells are discriminated using morphological differences. We propose a novel cell splitting algorithm to split overlapping cells into single cells using the shortest path between contours of convex regions

Tan, C, Johnston, AJ, Ballard, KJ, Ferguson, S & Perera-Schulz, D 2013, 'sPeAK-MAN: towards popular gameplay for speech therapy', Proceedings of 9th Australasian Conference on Interactive Entertainment IE'13, Interactive Entertainment, ACM, Melbourne, VIC, Australia, pp. 1-4.
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Current speech therapy treatments are not easily accessible to the general public due to cost and demand. Therapy sessions are also laborious and maintaining motivation of patients is hard. We propose using popular games and speech recognition technology for speech therapy in an individualised and accessible manner. sPeAK-MAN is a Pac-Man-like game with a core gameplay mechanic that incorporates vocalisation of words generated from a pool commonly used in clinical speech therapy sessions. Other than improving engagement, sPeAK-MAN aims to provide real-time feedback on the vocalisation performance of patients. It also serves as an initial prototype to demonstrate the possibilities of using familiar popular gameplay (instead of building one from scratch) for rehabilitation purposes.

Teague, D, Corney, M, Ahadi, A & Lister, RF 2013, 'A Qualitative Think Aloud Study of the Early Neo-Piagetian Stages of Reasoning in Novice Programmers', Volume 136 - Fifteenth Australasian Computing Education Conference, Australasian Computing Education Conference, Australian Computer Society Inc, Adelaide, Australia, pp. 87-96.
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Abstract: Recent research indicates that some of the difficulties faced by novice programmers are manifested very early in their learning. In this paper, we present data from think aloud studies that demonstrate the nature of those difficulties. In the think alouds, novices were required to complete short programming tasks which involved either hand executing ("tracing") a short piece of code, or writing a single sentence describing the purpose of the code. We interpret our think aloud data within a neo-Piagetian framework, demonstrating that some novices reason at the sensorimotor and preoperational stages, not at the higher concrete operational stage at which most instruction is implicitly targeted.

Thommandram, A, Eklund, JM & McGregor, C 2013, 'Detection of Apnoea from Respiratory Time Series Data Using Clinically Recognizable Features and kNN Classification', 2013 35TH ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC), 35th Annual International Conference of the IEEE-Engineering-in-Medicine-and-Biology-Society (EMBC), IEEE, Osaka, JAPAN, pp. 5013-5016.

Thommandram, A, Pugh, JE, Eklund, JM, McGregor, C & James, AG 2013, 'Classifying Neonatal Spells Using Real-Time Temporal Analysis of Physiological Data Streams: Algorithm Development', 2013 IEEE POINT-OF-CARE HEALTHCARE TECHNOLOGIES (PHT), 1st IEEE-EMBS Special Topic Conference on Point-of-Care (POCT) Healthcare Technologies (PHT), IEEE, Bangalore, INDIA, pp. 240-243.

Tomamichel, M & Tan, VYF 2013, 'A tight upper bound for the third-order asymptotics of discrete memoryless channels', IEEE International Symposium on Information Theory - Proceedings, IEEE International Symposium on Information Theory, pp. 1536-1540.
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This paper shows that the logarithm of the ε-error capacity (average error probability) for n uses of a discrete memoryless channel with positive conditional information variance at every capacity-achieving input distribution is upper bounded by the normal approximation plus a term that does not exceed 1/2 log n + O(1). © 2013 IEEE.

Tomamichel, M & Tan, VYF 2013, 'ε-Capacity and strong converse for channels with general state', Information Theory Workshop (ITW), 2013 IEEE, IEEE Information Theory Workshop (ITW), IEEE, Seville, Spain.
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We consider state-dependent memoryless channels with general state available at both encoder and decoder. We establish the ε-capacity and the optimistic ε-capacity. This allows us to prove a necessary and sufficient condition for the strong converse to hold. We also provide a simpler sufficient condition on the first- and second-order statistics of the state process that ensures that the strong converse holds.

Tomamichel, M, Fehr, S, Kaniewski, J & Wehner, S 2013, 'One-sided device-independent QKD and position-based cryptography from monogamy games', Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), International Conference on the Theory and Application of Cryptographic Techniques, Springer, Athens, Greece, pp. 609-625.
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A serious concern with quantum key distribution (QKD) schemes is that, when under attack, the quantum devices in a real-life implementation may behave differently than modeled in the security proof. This can lead to real-life attacks against provably secure QKD schemes. In this work, we show that the standard BB84 QKD scheme is one-sided device-independent. This means that security holds even if Bob's quantum device is arbitrarily malicious, as long as Alice's device behaves as it should. Thus, we can completely remove the trust into Bob's quantum device for free, without the need for changing the scheme, and without the need for hard-to-implement loophole-free violations of Bell inequality, as is required for fully (meaning two-sided) device-independent QKD. For our analysis, we introduce a new quantum game, called a monogamy-of-entanglement game, and we show a strong parallel repetition theorem for this game. This new notion is likely to be of independent interest and to find additional applications. Indeed, besides the application to QKD, we also show a direct application to position-based quantum cryptography: we give the first security proof for a one-round position-verification scheme that requires only single-qubit operations. © 2013 International Association for Cryptologic Research.

Valuvanathorn, S, Nitsuwa, S & Huang, M 2011, 'Multi-Feature Face Recognition based on 2D-PCA and SVM', The Era of Interactive Media, Pacific-Rim Conference on Multimedia, Springer, Sydney, pp. 65-76.
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Identification and authentication by face recognition mainly use global face features. However, the recognition accuracy rate is still not high enough. This research aims to develop a method to increase the efficiency of recognition using global-face feature and local-face feature with four parts: the left-eye, right-eye, nose and mouth. This method is based on geometrical techniques used to find location of eyes, nose and mouth from the frontal face image. We used 115 face images for learning and testing. Each-individual persons images are divided into three difference images for training and two difference images for testing. The Two-Dimension Principle Component Analysis (2D-PCA) technique is used for feature extraction and the Support Vector Machine (SVM) method is used for face recognition. The results show that the recognition percentage is 97.83%.

Vermeulen, J, Luyten, K, van den Hoven, E & Coninx, K 2013, 'Crossing the Bridge over Norman's Gulf of Execution: Revealing Feedforward's True Identity', Proceedings of the SIGCHI Conference on Human Factors in Computing Systems 2013 (CHI'13), International Conference on Human Factors in Computing Systems, ACM, Paris, France, pp. 1931-1940.
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Feedback and affordances are two of the most well-known principles in interaction design. Unfortunately, the related and equally important notion of feedforward has not been given as much consideration. Nevertheless, feedforward is a powerful design principle for bridging Normans Gulf of Execution. We reframe feedforward by disambiguating it from related design principles such as feedback and perceived affordances, and identify new classes of feedforward. In addition, we present a reference framework that provides a means for designers to explore and recognize different opportunities for feedforward.

Vichitvanichphong, S, Kerr, D, Talaei-Khoei, A & Ghapanchi, AH 2013, 'Analysis of research in adoption of assistive technologies for aged care', Proceedings of the 24th Australasian Conference on Information Systems.
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© 2013. The main objective of this study is to provide detailed analysis on the research conducted in the area of adoption for assistive technologies in aged care. The article analyses the studies and concludes with avenues, guidelines and gaps for research in this area. This study has conducted a systematic search on eight popular academic databases and identified relevant papers published. The paper identifies potential technologies that have been utilised to address seniors’ daily life difficulties in three areas: independent living, social isolation, dementia and medication taking. The article presents the theoretical lenses used for studying the adoption of these technologies in aged care. In addition to that, the systematic review has come up with interesting demographics on research approaches, and fields of publication for the research in this area. The paper outlines that the Australian research in adoption of assistive technologies for aged care has been over focused on healthcare domain and has largely ignored information system outlets. The possible reasons and potential directions for this issue have been discussed.

Wan, L, Chen, L & Zhang, C 2013, 'Mining Dependent Frequent Serial Episodes from Uncertain Sequence Data', Proceedings of the13th IEEE International Conference on Data Mining, IEEE International Conference on Data Mining, IEEE Computer Society Press, Dallas, TX, USA, pp. 1211-1216.
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In this paper, we focus on the problem of mining Probabilistic Dependent Frequent Serial Episodes (P-DFSEs) from uncertain sequence data. By observing that the frequentness probability of an episode in an uncertain sequence is a Markov Chain imbeddable variable, we first propose an Embedded Markov Chain-based algorithm that efficiently computes the frequentness probability of an episode by projecting the probability space into a set of limited partitions. To further improve the computation efficiency, we devise an optimized approach that prunes candidate episodes early by estimating the upper bound of their frequentness probabilities.

Wan, L, Chen, L & Zhang, C 2013, 'Mining Frequent Serial Episodes over Uncertain Sequence Data', The 16th International Conference on Extending Database Technology (EDBT 2013), Extending Database Technology, ACM EDBT/ICDT 2013, Genoa, Italy, pp. 215-226.
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Data uncertainty has posed many unique challenges to nearly all types of data mining tasks, creating a need for uncertain data mining. In this paper, we focus on the particular task of mining probabilistic frequent serial episodes (P-FSEs) from uncertain sequence data, which applies to many real applications including sensor readings as well as customer purchase sequences. We first define the notion of P-FSEs, based on the frequentness probabilities of serial episodes under possible world semantics. To discover P-FSEs over an uncertain sequence, we propose: 1) an exact approach that computes the accurate frequentness probabilities of episodes; 2) an approximate approach that approximates the frequency of episodes using probability models; 3) an optimized approach that efficiently prunes a candidate episode by estimating an upper bound of its frequentness probability using approximation techniques. We conduct extensive experiments to evaluate the performance of the developed data mining algorithms. Our experimental results show that: 1) while existing research demonstrates that approximate approaches are orders of magnitudes faster than exact approaches, for P-FSE mining, the efficiency improvement of the approximate approach over the exact approach is marginal; 2) although it has been recognized that the normal distribution based approximation approach is fairly accurate when the data set is large enough, for P-FSE mining, the binomial distribution based approximation achieves higher accuracy when the the number of episode occurrences is limited; 3) the optimized approach clearly outperforms the other two approaches in terms of the runtime, and achieves very high accuracy.

Wang, W & Huang, M 2013, 'Parallel Coordinates Visualization of Large Data Investigation on HDDs', International Conference Computer Graphics, Imaging and Visualization, International Conference Computer Graphics, Imaging and Visualization, IEEE, Macau, China, pp. 93-99.
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Data Visualization and Visual Analytics (DVVA) techniques help human to extract essential information and knowledge from large and complex data sets, and then represent them clearly and comprehensively in the graphic format for better understanding. These techniques have been successfully applied in many areas, including the application in computer forensic science. This paper discusses the background, approaches to the visual analysis of typical computer forensic data. Primarily we will look at how visualization techniques can enhance the computer forensics task, and proposes a new model with a set of data attributes for visual analytics of computer forensics.

Wang, W, Johnston, B & Williams, MA 2013, 'Recognition and representation of robot skills in real time: A theoretical analysis', Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), International Conference on Social Robotics (ICSR), Springer, Bristol, UK, pp. 127-137.
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Sharing reusable knowledge among robots has the potential to sustainably develop robot skills. The bottlenecks to sharing robot skills across a network are how to recognise and represent reusable robot skills in real-time and how to define reusable robot skills in a way that facilitates the recognition and representation challenge. In this paper, we first analyse the considerations to categorise reusable robot skills that manipulate objects derived from R.C. Schank's script representation of human basic motion, and define three types of reusable robot skills on the basis of the analysis. Then, we propose a method with potential to identify robot skills in real-time. We present a theoretical process of skills recognition during task performance. Finally, we characterise reusable robot skill based on new definitions and explain how the new proposed representation of robot skill is potentially advantageous over current state-of-the-art work. © Springer International Publishing 2013.

Wang, X, Wang, Z & Xu, X 2013, 'An improved artificial bee colony approach to QoS-aware service selection', Proceedings - IEEE 20th International Conference on Web Services, ICWS 2013, pp. 395-402.
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As available services accumulate on the Internet, QoS-aware service selection (SSP) becomes an increasingly difficult task. Since Artificial Bee Colony algorithm (ABC) has been successful in solving many problems as a simpler implementation of swarm intelligence, its application to SSP is promising. However, ABC was initially designed for numerical optimization, and its effectiveness highly depends on what we call optimality continuity property of the solution space, i.e., similar variable values (or neighboring solutions) result in similar objective values (or evaluation results). We will show that SSP does not possess such property. We further propose an approximation approach based on greedy search strategies for ABC, to overcome this problem. In this approach, neighboring solutions are generated for a composition greedily based on the neighboring services of its component services. Two algorithms with different neighborhood measures are presented based on this approach. The resulting neighborhood structure of the proposed algorithms is analogical to that of continuous functions, so that the advantages of ABC can be fully leveraged in solving SSP. Also, they are pure online algorithms which are as simple as canonical ABC. The rationale of the proposed approach is discussed and the complexity of the algorithms is analyzed. Experiments conducted against canonical ABC indicate that the proposed algorithms can achieve better optimality within limited time. © 2013 IEEE.

Wang, X, Zhuo, X, Yang, B, Meng, FJ, Jin, P, Huang, W, Young, CC, Zhang, C, Xu, JM & Montinarelli, M 2013, 'A Novel Service Composition Approach for Application Migration to Cloud', SERVICE-ORIENTED COMPUTING, ICSOC 2013, 11th International Conference on Service Oriented Computing (ICSOC), SPRINGER-VERLAG BERLIN, Berlin, GERMANY, pp. 667-674.

Wang, YK, Jung, TP, Chen, SA, Huang, CS & Lin, CT 2013, 'Tracking Attention Based on EEG Spectrum', Search Home Contact Us Log in HCI: International Conference on Human-Computer Interaction HCI International 2013 - Posters’ Extended Abstracts, International Conference on Human-Computer Interaction, Springer, Las Vegas, NV, USA, pp. 450-454.
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Distraction while driving is a serious problem that can have many catastrophic consequences. Developing a countermeasure to detect the drivers’ distraction is imperative. This study measured Electroencephalography (EEG) signals from six healthy participants while they were asked to pay their full attention to a lane-keeping driving task or a math problem-solving task. The time courses of six distinct brain networks (Frontal, Central, Parietal, Occipital, Left Motor, and Right Motor) separated by Independent Component Analysis were used to build the distraction-detection model. EEG data were segmented into 400-ms epochs. Across subjects, 80% of the EEG epochs were used to train various classifiers that were tested against the remaining 20% of the data. The classification performance based on support vector machines (SVM) with a radial basis function (RBF) kernel achieved accuracy of 84.7±2.7% or 85.8±1.3% for detecting subjects’ focuses of attention to the math-solving or lane-deviation task, respectively. The high attention-detection accuracy demonstrated the feasibility of accurately detecting drivers’ attention based on the brain activities. This demonstration may lead to a practical real-time distraction-detection system for improving road safety.

Wang, Z, Luo, T, Xu, G & Wang, X 2013, 'A New Indexing Technique for Supporting By-attribute Membership Query of Multidimensional Data', Web-Age Information Management - WAIM 2013 International Workshops: HardBD, MDSP, BigEM, TMSN, LQPM, BDMS, Beidaihe, China, June 14-16, 2013. Proceedings, International Conference on Web-Age Information Management, Springer, China, pp. 266-277.
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Wen, S, Li, P, Wu, D, Xiang, Y & Zhou, W 2013, 'Detecting stepping stones by abnormal causality probability', Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pp. 308-322.
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Locating the real source of the Internet attacks has long been an important but difficult problem to be addressed. In the real world attackers can easily hide their identities and evade punishment by relaying their attacks through a series of compromised systems or devices, called stepping stones. Currently, researchers mainly use similar features from the network traffic, such as packet timestamps and frequencies, to detect stepping stones. However, these features can be easily destroyed by attackers using evasive techniques. In addition, it is also difficult to implement an appropriate threshold of similarity which can help justify the stepping stones. In order to counter these problems, in this paper, we introduce the consistent causality probability to detect the stepping stones. We formulate the ranges of abnormal causality probabilities according to the different network conditions, and on the basis of it, we further implement two self-adaptive methods to capture stepping stones. To evaluate our proposed detection methods, we adopt theoretic analysis and empirical studies, which have demonstrated accuracy of the abnormal causality probability. Moreover, we compare of our proposed methods with previous works. The result show that our methods in this paper significantly outperform previous works in the accuracy of detection malicious stepping stones, even when evasive techniques are adopted by attackers. © Springer International Publishing Switzerland 2013.

Wen, S, Xiang, Y & Zhou, W 2013, 'Modeling and analysis for thwarting worm propagation in email networks', Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pp. 763-769.
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Email worm has long been a critical but intractable threat to Internet users. In this paper, we propose an analytical model to present the propagation dynamics of email worms using difference equations. Based on this model, we further investigate the quarantine conditions for the number of infected users decreasing as soon as possible. In this field, previous works have found that a static threshold for worms fast dying out does not exist. In our work, we extend the modeling with dynamical quarantine processes to see if the previous viewpoint is still supported or not. By contrast, the results suggest that it is possible to have a sharp decline in the number of infected users within a short period of time. In the experiments, we implement both the empirical and theoretical methods to support our analysis. The work of this paper can provide practical values on protecting email networks. © 2013 Springer-Verlag.

Williams, MA, Abidi, S, Gärdenfors, P, Wang, X, Kuipers, B & Johnston, B 2013, 'Interpreting robot pointing behavior', Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), International Conference on Social Robotics (ICSR), Springer, Bristol, UK, pp. 148-159.
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The ability to draw other agents' attention to objects and events is an important skill on the critical path to effective human-robot collaboration. People use the act of pointing to draw other people's attention to objects and events for a wide range of purposes. While there is significant work that aims to understand people's pointing behavior, there is little work analyzing how people interpret robot pointing. Since robots have a wide range of physical bodies and cognitive architectures, interpreting pointing will be determined by a specific robot's morphology and behavior. Humanoids and robots whose heads, torso and arms resemble humans that point may be easier for people to interpret, however if such robots have different perceptual capabilities to people then misinterpretation may occur. In this paper we investigate how ordinary people interpret the pointing behavior of a leading state-of-the-art service robot that has been designed to work closely with people. We tested three hypotheses about how robot pointing is interpreted. The most surprising finding was that the direction and pitch of the robot's head was important in some conditions. © Springer International Publishing 2013.

Williams, SP, Hardy, CA & Holgate, JA 2013, 'Information security governance practices in critical infrastructure organizations: A socio-technical and institutional logic perspective', ELECTRONIC MARKETS, SPRINGER HEIDELBERG, pp. 341-354.
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Williams, SP, Hausmann, V, Hardy, CA & Schubert, P 2013, 'Enterprise 2.0 research: Meeting the challenges of practice', 26th Bled eConference - eInnovations: Challenges and Impacts for Individuals, Organizations and Society, Proceedings, pp. 251-263.
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Through an in-depth survey of scholarly research studies and practitioner reports this study examines the extent to which current scholarly research addresses the challenges and impacts of Enterprise 2.0 (E2.0) being faced by organisations. Our findings reveal that whilst there is a growing body of work about E2.0, the first stream of research has focused primarily on providing an overview of E2.0 and its adoption and use. Our analysis of the practitioner literature reveals a different set of imperatives clustered around information management and compliance issues, the identification and measurement of benefits and the integration of social software into organisational business processes and business software. To address this misalignment of research imperatives we propose a second stream of research that moves attention from the initiation and exploration of E2.0 to its institutionalisation and integration.

Wu, D, Zhang, G & Lu, J 2013, 'A Fuzzy Tree Similarity Based Recommendation Approach for Telecom Products', 2013 Joint IFSA World Congress NAFIPS Annual Meeting (IFSA/NAFIPS), Joint IFSA World Congress NAFIPS Annual Meeting, IEEE, Edmonton, Canada, pp. 813-818.
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Due to the huge product assortments and complex descriptions of telecom products, it is a great challenge for customers to select appropriate products. A fuzzy tree similarity based hybrid recommendation approach is proposed to solve this issue. In this study, fuzzy techniques are used to deal with the various uncertainties existing within the product and customer data. A fuzzy tree similarity measure is developed to evaluate the semantic similarity between tree structured products or user profiles. The similarity measures for items and users both integrate the collaborative filtering (CF) and semantic similarities. The final recommendation hybridizes item-based and user-based CF recommendation techniques. A telecom product recommendation case study is given to show the effectiveness of the proposed approach.

Wu, D, Zhang, G & Lu, J 2013, 'A Fuzzy Tree Similarity Measure and Its Application in Telecom Product Recommendation', 2013 IEEE International Conference on Systems, Man and Cybernetics (SMC), IEEE International Conference on Systems, Man and Cybernetics, IEEE, Manchester, UK, pp. 3483-3488.
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The recommender systems field has been well developed in the last few years to provide item recommendations to related users. Existing recommendation approaches, however, assume that an item is described by a single value or a vector. Unfortunately, some items in real world applications, such as telecom products, could have a tree structure. This paper aims to handle this issue by developing a comprehensive fuzzy tree similarity measure. The fuzzy tree similarity measure compares both the concepts and values in two trees of items. The focus of this study is primarily on the fuzzy value similarity between two trees. In the similarity measure, each attribute is associated with a set of linguistic terms to express the value granularly. The node values are first transformed to membership vectors related to the linguistic terms, and the values of the conceptual corresponding nodes are then compared. These local similarities are aggregated into the final fuzzy value similarity between the two trees. A telecom product recommendation case study shows the effectiveness of the proposed fuzzy tree similarity measure and its applicability for telecom product recommendations

Wu, L, Chin, A, Xu, G, Du, L, Wang, X, Meng, K, Guo, Y & Zhou, Y 2013, 'Who Will Follow Your Shop? Exploiting Multiple Information Sources in Finding Followers', Lecture Notes in Computer Science, Database Systems for Advanced Applications, Springer Berlin / Heidelberg, Wuhan, pp. 401-415.
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WuXianGouXiang is an O2O(offline to online and vice versa)-based mobile application that recommends the nearby coupons and deals for users, by which users can also follow the shops they are interested in. If the potential followers of a shop can be discovered, the merchants targeted advertising can be more effective and the recommendations for users will also be improved. In this paper, we propose to predict the link relations between users and shops based on the following behavior. In order to better model the characteristics of the shops, we first adopt Topic Modeling to analyze the semantics of their descriptions and then propose a novel approach, named INtent Induced Topic Search (INITS) to update the hidden topics of the shops with and without a description. In addition, we leverage the user logs and search engine results to get the similarity between users and shops. Then we adopt the latent factor model to calculate the similarity between users and shops, in which we use the multiple information sources to regularize the factorization. The experimental results demonstrate that the proposed approach is effective for detecting followers of the shops and the INITS model is useful for shop topic inference.

Wu, SL, Wu, CW, Pal, NR, Chen, CY, Chen, SA & Lin, CT 2013, 'Common spatial pattern and linear discriminant analysis for motor imagery classification', Proceedings of the 2013 IEEE Symposium on Computational Intelligence, Cognitive Algorithms, Mind, and Brain, CCMB 2013 - 2013 IEEE Symposium Series on Computational Intelligence, SSCI 2013, IEEE Symposium on Computational Intelligence, Cognitive Algorithms, Mind, and Brain (CCMB), IEEE, Singapore, pp. 146-151.
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A Brain-Computer Interface (BCI) system provides a convenient way of communication for healthy subjects and subjects who suffer from severe diseases such as amyotrophic lateral sclerosis (ALS). Motor imagery (MI) is one of the popular ways of designing BCI systems. The architecture of many BCI system is quite complex and they involve time consuming processing. The electroencephalography (EEG) signal is the most commonly used inputs for BCI applications but EEG is often contaminated with noise. To overcome such drawbacks, in this paper we use the common spatial pattern (CSP) for feature extraction from EEG and the linear discriminant analysis (LDA) for motor imagery classification. In this study, CSP and LDA have been used to reduce the artifact and classify MI-based EEG signal. We have used two-level cross validation scheme to determine the subject specific best time window and number of CSP features. We have compared the performance of our system with BCI competition results. We have also experimented with MI data generated in our lab. The proposed system is found to produce good results. In particular, using our EEG data for MI movements, we have obtained an average classification accuracy of 80% for two subjects using only 9 channels, without any feature selection. This proposed MI-based BCI system may be used in real life applications. © 2013 IEEE.

Wu, Z, Yin, W, Cao, J, Xu, G & Cuzzocrea, A 2013, 'Community Detection in Multi-relational Social Networks', Lecture Notes in Computer Science, International Conference on Web Information Systems Engineering, Springer Berlin / Heidelberg, Nanjing, pp. 43-56.
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Multi-relational networks are ubiquitous in many fields such as bibliography, twitter, and healthcare. There have been many studies in the literature targeting at discovering communities from social networks. However, most of them have focused on single-relational networks. A hint of methods detected communities from multi-relational networks by converting them to single-relational networks first. Nevertheless, they commonly assumed different relations were independent from each other, which is obviously unreal to real-life cases. In this paper, we attempt to address this challenge by introducing a novel co-ranking framework, named MutuRank. It makes full use of the mutual influence between relations and actors to transform the multi-relational network to the single-relational network. We then present GMM-NK (Gaussian Mixture Model with Neighbor Knowledge) based on local consistency principle to enhance the performance of spectral clustering process in discovering overlapping communities. Experimental results on both synthetic and real-world data demonstrate the effectiveness of the proposed method.

Xu, G 2013, 'Advances in Knowledge Discovery and Data Mining, 17th Pacific-Asia Conference, PAKDD 2013, Gold Coast, Australia, April 14-17, 2013, Proceedings, Part II', Springer.
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Yaish, HM & Goyal, ML 2013, 'A Multi-tenant Database Architecture Design for Software Applications', IEEE 16th International Conference on Computational Science and Engineering, IEEE International Conference on Big Data Science and Engineering, IEEE, Sydney, Australia, pp. 933-940.
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Multi-tenant database is a new cloud computing paradigm that has recently attracted attention to deliver database functionalities for multiple tenants to create, store, and access their databases over the internet. This multi-tenant database should be highly configurable and secure to meet tenants' expectations and their different business requirements. In this paper, we propose an architecture design to build an intermediate database layer to be used between software applications and Relational Database Management Systems (RDBMS) to store and access multiple tenants' data in the Elastic Extension Table (EET) multi-tenant database schema. This database layer combines multi-tenant relational tables and virtual relational tables and makes them work together to act as one database for each tenant. This architecture design is suitable for multi-tenant database environment that can run any business domain database by using a combination of a database schema, which contains shared physical structured tables and virtual structured tenant's tables. Further, this multi-tenant database architecture design can be used as a base to build software applications in general and Software as a Service (SaaS) applications in particular.

Yaish, HM & Goyal, ML 2013, 'Multi-tenant Database Access Control', IEEE 16th International Conference on Computational Science and Engineering, IEEE International Conference on Big Data Science and Engineering, IEEE, Sydney, Australia, pp. 870-877.
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Storing data in the cloud is a new multi-tenant database solution that has recently emerged to deliver database for multiple users, who can store and access their data over the internet. This multi-tenant database designed to be used by multiple tenants and each tenant may have multiple users. Therefore, this database type demands a special multi-tenant access control model, which provides an access control not only for multiple tenants, but also for multiple users per tenant. In this paper, we are proposing a multi-tenant access control model based on a multi-tenant database schema called Elastic Extension Tables (EET). In this model, we define access control data architecture, and the EET access grants which can be granted to tenants' users. Moreover, we propose an access control algorithm, which allows users to access the data granted to them based on a number of groups or roles assigned to these users.

Yaish, HM, Goyal, ML & Feuerlicht, G 2013, 'A Method of Optimizing Multi-tenant Database Query Access', Lecture Notes in Computer Science, International Conference on Web Information Systems Engineering, Springer-Verlag Berlin and Heidelberg GmbH & Co. K, Nanjing, China, pp. 194-212.
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The database of multi-tenant Software as a Service (SaaS) applications has challenges in designing and developing a relational database for multi-tenant applications. In addition, combining relational tables and virtual relational tables to make them work together and act as one database for each single tenant is a hard and complex problem to solve. Based on our multi-tenant Elastic Extension Tables (EET), we are proposing in this paper a multi-tenant database proxy service to combine multi-tenant relational tables and virtual relational tables, to make them act as one database for each single tenant. This combined database is suitable to run with multi-tenant SaaS single instance applications, which allow tenants designing their database and automatically configuring its behavior during application runtime execution. In addition, these applications allow retrieving tenants data by simply calling functions from this service which spare tenants from spending money and efforts on writing SQL queries and backend data management codes, and instead allowing them to focus on their business and to create their web, mobile, and desktop applications. The feasibility and effectiveness of the proposed service are verified by using experimental data on some of this service functions.

Yaish, HM, Goyal, ML & Feuerlicht, G 2013, 'Proxy Service for Multi-tenant Database Access', Availability, Reliability, and Security in Information Systems and HCI, The International Cross Domain Conference and Workshop, Springer, Regensburg, Germany, pp. 100-117.
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The database of multi-tenant Software as a Service (SaaS) applications has challenges in designing and developing a relational database for multi-tenant applications. In addition, combining relational tables and virtual relational tables to make them work together and act as one database for each single tenant is a hard and complex problem to solve. Based on our multi-tenant Elastic Extension Tables (EET), we are proposing in this paper a multi-tenant database proxy service to combine multi-tenant relational tables and virtual relational tables, to make them act as one database for each single tenant. This combined database is suitable to run with multi-tenant SaaS single instance applications, which allow tenants designing their database and automatically configuring its behavior during application runtime execution. In addition, these applications allow retrieving tenants data by simply calling functions from this service which spare tenants from spending money and efforts on writing SQL queries and backend data management codes, and instead allowing them to focus on their business and to create their web, mobile, and desktop applications. The feasibility and effectiveness of the proposed service are verified by using experimental data on some of this service functions.

Yang, P, Liu, W, Zhou, BB, Chawla, S & Zomaya, AY 2013, 'Ensemble-based wrapper methods for feature selection and class imbalance learning', Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pp. 544-555.
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The wrapper feature selection approach is useful in identifying informative feature subsets from high-dimensional datasets. Typically, an inductive algorithm "wrapped" in a search algorithm is used to evaluate the merit of the selected features. However, significant bias may be introduced when dealing with highly imbalanced dataset. That is, the selected features may favour one class while being less useful to the adverse class. In this paper, we propose an ensemble-based wrapper approach for feature selection from data with highly imbalanced class distribution. The key idea is to create multiple balanced datasets from the original imbalanced dataset via sampling, and subsequently evaluate feature subsets using an ensemble of base classifiers each trained on a balanced dataset. The proposed approach provides a unified framework that incorporates ensemble feature selection and multiple sampling in a mutually beneficial way. The experimental results indicate that, overall, features selected by the ensemble-based wrapper are significantly better than those selected by wrappers with a single inductive algorithm in imbalanced data classification. © Springer-Verlag 2013.

Yi, X, Paulet, R, Bertino, E & Xu, G 2014, 'Private data warehouse queries', Proceedings of the 18th ACM Symposium on Access Control Models and Technologies, Symposium on Access Control Models and Technologies, ACM (was RBAC), ACM, Amsterdam, pp. 25-36.
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Publicly accessible data warehouses are an indispensable resource for data analysis. But they also pose a significant risk to the privacy of the clients, since a data warehouse operator may follow the client's queries and infer what the client is interested in. Private Information Retrieval (PIR) techniques allow the client to retrieve a cell from a data warehouse without revealing to the operator which cell is retrieved. However, PIR cannot be used to hide OLAP operations performed by the client, which may disclose the client's interest. This paper presents a solution for private data warehouse queries on the basis of the Boneh-Goh-Nissim cryptosystem which allows one to evaluate any multi-variate polynomial of total degree 2 on ciphertexts. By our solution, the client can perform OLAP operations on the data warehouse and retrieve one (or more) cell without revealing any information about which cell is selected. Furthermore, our solution supports some types of statistical analysis on data warehouse, such as regression and variance analysis, without revealing the client's interest. Our solution ensures both the server's security and the client's security.

Yin, H, Sun, Y, Cui, B, Hu, Z & Chen, L 2013, 'LCARS: A Location-Content-Aware Recommender System', ACM SIGKDD Conference on Knowledge Discovery and Data Mining, ACM International Conference on Knowledge Discovery and Data Mining, ACM, Chicago, Illinois USA, pp. 221-229.
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Newly emerging location-based and event-based social network services provide us with a new platform to understand users preferences based on their activity history. A user can only visit a limited number of venues/events and most of them are within a limited distance range, so the user-item matrix is very sparse, which creates a big challenge for traditional collaborative filtering-based recommender systems. The problem becomes more challenging when people travel to a new city where they have no activity history. In this paper, we propose LCARS, a location-content-aware recommender system that offers a particular user a set of venues (e.g., restaurants) or events (e.g., concerts and exhibitions) by giving consideration to both personal interest and local preference. This recommender system can facilitate peoples travel not only near the area in which they live, but also in a city that is new to them. Specifically, LCARS consists of two components: offline modeling and online recommendation. The offline modeling part, called LCA- LDA, is designed to learn the interest of each individual user and the local preference of each individual city by capturing item co- occurrence patterns and exploiting item contents. The online recommendation part automatically combines the learnt interest of the querying user and the local preference of the querying city to produce the top-k recommendations. To speed up this online process, a scalable query processing technique is developed by extending the classic Threshold Algorithm (TA). We evaluate the performance of our recommender system on two large-scale real data sets, Douban- Event and Foursquare. The results show the superiority of LCARS in recommending spatial items for users, especially when traveling to new cities, in terms of both effectiveness and efficiency.

You, Y, Xu, G, Cao, J, Zhang, Y & Huang, G 2013, 'Leveraging visual features and hierarchical dependencies for conference information extraction', Lecture Notes in Computer Science, Joint International Conference on Asia-Pacific Web Conference (APWeb)/Web-Age Information Management (WAIM), Springer, Sydney, pp. 404-416.
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Traditional information extraction methods mainly rely on visual feature assisted techniques; but without considering the hierarchical dependencies within the paragraph structure, some important information is missing. This paper proposes an integrated a

Yu, S, Doss, R, Zhou, W & Guo, S 2013, 'A general cloud firewall framework with dynamic resource allocation', IEEE International Conference on Communications, pp. 1941-1945.
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Cloud is becoming a dominant computing platform. However, we see few work on how to protect cloud data centers. As a cloud usually hosts many different type of applications, the traditional packet level firewall mechanism is not suitable for cloud platforms in case of complex attacks. It is necessary to perform anomaly detection at the event level. Moreover, protecting objects are more diverse than the traditional firewall. Motivated by this, we propose a general framework of cloud firewall, which features event level detection chain with dynamic resource allocation. We establish a mathematical model for the proposed framework. Moreover, a linear resource investment function is proposed for economical dynamical resource allocation for cloud firewalls. A few conclusions have been extracted for the reference of cloud service providers and designers. © 2013 IEEE.

Yu, S, Zhou, W, Guo, S & Guo, M 2013, 'A dynamical deterministic packet marking scheme for DDoS traceback', GLOBECOM - IEEE Global Telecommunications Conference, pp. 729-734.
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DDoS attack source traceback is an open and challenging problem. Deterministic packet marking (DPM) is a simple and relatively effective traceback scheme among the available traceback methods. However, the existing DPM schemes inheret a critical drawback of scalability in tracing all possible attack sources, which roots at their static mark encoding and attempt to mark all Internet routers for their traceback purpose. We find that a DDoS attack session usually involves a limited number of attack sources, e.g. at the thousand level. In order to achieve the traceback goal, we only need to mark these attack related routers. We therefore propose a novel Marking on Demand (MOD) scheme based on the DPM mechanism to dynamical distribute marking IDs in both temporal and space dimensions. The proposed MOD scheme can traceback to all possible sources of DDoS attacks, which is not possible for the existing DPM schemes. We thoroughly compare the proposed MOD scheme with two dominant DPM schemes through theoretical analysis and experiments. The the results demonstrate that the MOD scheme outperforms the existing DPM schemes. © 2013 IEEE.

Zhang, C, Zhang, Y, Zhang, W & Lin, X 2013, 'Inverted linear quadtree: Efficient top k spatial keyword search', IEEE 29th International Conference on Data Engineering, IEEE International Conference on Data Engineering, IEEE, Brisbane, Australia, pp. 901-912.
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With advances in geo-positioning technologies and geo-location services, there are a rapidly growing amount of spatio-textual objects collected in many applications such as location based services and social networks, in which an object is described by its spatial location and a set of keywords (terms). Consequently, the study of spatial keyword search which explores both location and textual description of the objects has attracted great attention from the commercial organizations and research communities. In the paper, we study the problem of top k spatial keyword search (TOPK-SK), which is fundamental in the spatial keyword queries. Given a set of spatio-textual objects, a query location and a set of query keywords, the top k spatial keyword search retrieves the closest k objects each of which contains all keywords in the query. Based on the inverted index and the linear quadtree, we propose a novel index structure, called inverted linear quadtree (IL-Quadtree), which is carefully designed to exploit both spatial and keyword based pruning techniques to effectively reduce the search space. An efficient algorithm is then developed to tackle top k spatial keyword search. In addition, we show that the IL-Quadtree technique can also be applied to improve the performance of other spatial keyword queries such as the direction-aware top k spatial keyword search and the spatio-textual ranking query. Comprehensive experiments on real and synthetic data clearly demonstrate the efficiency of our methods.

Zhang, J & Huang, M 2013, '5Ws Model for Big Data Analysis and Visualization', Computational Science and Engineering (CSE), 2013 IEEE 16th International Conference on, International Conference on Computational Science and Engineering, IEEE CS Press, Sydney, Australia, pp. 1021-1028.
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Zhang, J & Huang, M 2013, 'Visual Analytics Model for Intrusion Detection in Flood Attack', 2013 12th IEEE International Conference on Trust, Security and Privacy in Computing and Communications, IEEE International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom), IEEE, Melbourne, Australia, pp. 277-284.
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Flood attacks are common forms of Distributed Denial-of-Service (DDoS) attack threats on internet in nature. This has necessitated the need for visual analysis within an intrusion detection system to identify these attacks. The challenges are how to increase the accuracy of detection and how to visualize and present flood attacks in networks for early detection. In this paper, we introduce three coefficients, which not only classify the behaviors of flood attacks, but also measure the system performance under those flood attacks: a) attack-density that patterns the characters of flood attack, b) system workload which represents the system capability in handling flood attack and c) the scalability to classify the impact level of the flood attack at victim site. A visual clustered method is used to display the DDoS flood attacks. The experimentation results are presented to demonstrate our new model significantly improves the accuracy of the detection of DDoS attacks and provides a better understanding of the nature of flood attacks on networks.

Zhang, J, Chen, C, Xiang, Y & Zhou, W 2013, 'Robust network traffic identification with unknown applications', ASIA CCS 2013 - Proceedings of the 8th ACM SIGSAC Symposium on Information, Computer and Communications Security, pp. 405-414.
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Traffic classification is a fundamental component in advanced network management and security. Recent research has achieved certain success in the application of machine learning techniques into flow statistical feature based approach. However, most of flow statistical feature based methods classify traffic based on the assumption that all traffic flows are generated by the known applications. Considering the pervasive unknown applications in the real world environment, this assumption does not hold. In this paper, we cast unknown applications as a specific classification problem with insufficient negative training data and address it by proposing a binary classifier based framework. An iterative method is proposed to extract unknown information from a set of unlabelled traffic flows, which combines asymmetric bagging and flow correlation to guarantee the purity of extracted negatives. A binary classifier is used as an application signature which can operate on a bag of correlated flows instead of individual flows to further improve its effectiveness. We carry out a series of experiments in a real-world network traffic dataset to evaluate the proposed methods. The results show that the proposed method significantly outperforms the-state-of-art traffic classification methods under the situation of unknown applications present. © 2013 ACM.

Zhang, J, Chen, X, Xiang, Y & Zhou, W 2013, 'Zero-day traffic identification', Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pp. 213-227.
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Recent research on Internet traffic classification has achieved certain success in the application of machine learning techniques into flow statistics based method. However, existing methods fail to deal with zero-day traffic which are generated by previously unknown applications in a traffic classification system. To tackle this critical problem, we propose a novel traffic classification scheme which has the capability of identifying zero-day traffic as well as accurately classifying the traffic generated by pre-defined application classes. In addition, the proposed scheme provides a new mechanism to achieve fine-grained classification of zero-day traffic through manually labeling very few traffic flows. The preliminary empirical study on a big traffic data show that the proposed scheme can address the problem of zero-day traffic effectively. When zero-day traffic present, the classification performance of the proposed scheme is significantly better than three state-of-the-art methods, random forest classifier, classification with flow correlation, and semi-supervised traffic classification. © Springer International Publishing Switzerland 2013.

Zhang, Q, Ye, P, Lin, X & Zhang, Y 2013, 'Skyline probability over uncertain preferences', Proceedings of the 16th International Conference on Extending Database Technology, Extending Database Technology, ACM, Genoa, Italy, pp. 395-405.
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Skyline analysis is a key in a wide spectrum of real applications involving multi-criteria optimal decision making. In recent years, a considerable amount of research has been contributed on efficient computation of skyline probabilities over uncertain environment. Most studies if not all, assume uncertainty lies only in attribute values. To the extent of our knowledge, only one study addresses the skyline probability computation problem in scenarios where uncertainty resides in attribute preferences, instead of values. However this study takes a problematic approach by assuming independent object dominance, which we find is not always true in uncertain preference scenarios. In fact this assumption has already been shown to be not necessarily true in uncertain value scenarios. Motivated by this, we revisit the skyline probability computation over uncertain preferences in this paper. We first show that the problem of skyline probability computation over uncertain preferences is #P-complete. Then we propose efficient exact and approximate algorithms to tackle this problem. While the exact algorithm remains exponential in the worst case, our experiments demonstrate its efficiency in practice. The approximate algorithm achieves e-approximation by the confidence (1 - d) with time complexity O(dn1/e2 ln 1/d), where n is the number of objects and d is the dimensionality. The efficiency and effectiveness of our methods are verified by extensive experimental results on real and synthetic data sets.

Zhang, W, Li, A, Cheema, MA, Zhang, Y & Chang, L 2013, 'Probabilistic n-of-N skyline computation over uncertain data streams', Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), International Conference on Web Information Systems Engineering, Springer, Nanjing, China, pp. 439-457.
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Skyline operator is a useful tool in multi-criteria decision making in various applications. Uncertainty is inherent in real applications due to various reasons. In this paper, we consider the problem of efficiently computing probabilistic skylines against the most recent N uncertain elements in a data stream seen so far. Specifically, we study the problem in the n-of-N model; that is, computing the probabilistic skyline for the most recent n (∀n ≤ N) elements, where an element is a probabilistic skyline element if its skyline probability is not below a given probability threshold q. Firstly, an effective pruning technique to minimize the number of uncertain elements to be kept is developed. It can be shown that on average storing only O(log d N) uncertain elements from the most recent N elements is sufficient to support the precise computation of all probabilistic n-of-N skyline queries in a d-dimension space if the data distribution on each dimension is independent. A novel encoding scheme is then proposed together with efficient update techniques so that computing a probabilistic n-of-N skyline query in a d-dimension space is reduced to O (d loglogN + s) if the data distribution is independent, where s is the number of skyline points. Extensive experiments demonstrate that the new techniques on uncertain data streams can support on-line probabilistic skyline query computation over rapid data streams. © 2013 Springer-Verlag.

Zhang, Z, Oberst, S & Lai, JCS 2013, 'Application of polynomial chaos expansions to analytical models of friction oscillators', Annual Conference of the Australian Acoustical Society 2013, Acoustics 2013: Science, Technology and Amenity, Annual Conference of the Australian Acoustical Society, Victor Harbor, Australia, pp. 408-414.
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Despite past substantial research efforts, the prediction of brake squeal propensity remains a largely unresolved problem. The standard practice to predict the brake squeal propensity is to analyse dynamic instabilities using the complex eigenvalue analysis. However, it is well known that not every predicted unstable vibration mode will lead to squeal and vice-versa. Owing to nonlinearity and problem complexity (e.g. operating conditions), treating brake squeal with uncertainty seems appealing. Another indicator of brake squeal propensity, not often used, is based on negative dissipated energy. In this study, uncertainty analysis induced by polynomial chaos expansions is examined for 1-dof and 4-dof friction models. Results are compared with dissipated energy calculations and standard complex eigenvalue analysis. The potential of this approach for the prediction of brake squeal propensity is discussed. © (2013) by the Australian Acoustical Society.

Zhang, Z, Zhang, G, Lu, J & Guo, C 2013, 'A fuzzy tri-level decision making algorithm and its application in supply chain', 8th Conference of the European Society for Fuzzy Logic and Technology, EUSFLAT 2013 - Advances in Intelligent Systems Research, World Congress of the International-Fuzzy-Systems-Association (IFSA) / Conference of the European-Society-for-Fuzzy-Logic-and-Technology (EUSFLAT), Atlantis Press, Milano, Italy, pp. 154-160.
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In this paper, we develop a fuzzy tri-level decision making (FTLDM) model to deal with decentralized decision making problems with three levels of decision makers. Based on the -cut of fuzzy set, we transform an FTLDM problem into a multiobjective tri-level decision making problem. Based on the linear tri-level Kth-best algorithm, the global optimal solution can be obtained. A case study for third-party logistics decision making in supply chain is utilized to illustrate the effectiveness of the proposed algorithm. © 2013. The authors-Published by Atlantis Press.

Zhou, T, Bian, W & Tao, D 2013, 'Divide-and-Conquer Anchoring for Near-Separable Nonnegative Matrix Factorization and Completion in High Dimensions', IEEE 13th International Conference on Data Mining, IEEE International Conference on Data Mining, IEEE, Dallas, TX, USA, pp. 917-926.
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Abstract Nonnegative matrix factorization (NMF) becomes tractable in polynomial time with unique solution under separability assumption , which postulates all the data points are contained in the conical hull of a few anchor data points. Recently developed linear programming and greedy pursuit methods can pick out the anchors from noisy data and results in a near-separable NMF. But their efficiency could be seriously weakened in high dimensions. In this paper, we show that the anchors can be precisely located from low- dimensional geometry of the data points even when their high dimensional features suffer from serious incompleteness. Our framework, entitled divide-and-conquer anchoring (DCA), divides the high-dimensional anchoring problem into a few cheaper sub-problems seeking anchors of data projections in low-dimensional random spaces, which can be solved in parallel by any near-separable NMF, and combines all the detected low-dimensional anchors via a fast hypothesis testing to identify the original anchors. We further develop two non- iterative anchoring algorithms in 1D and 2D spaces for data in convex hull and conical hull, respectively. These two rapid algorithms in the ultra low dimensions suffice to generate a robust and efficient near-separable NMF for high-dimensional or incomplete data via DCA. Compared to existing methods, two vital advantages of DCA are its scalability for big data, and capability of handling incomplete and high-dimensional noisy data. A rigorous analysis proves that DCA is able to find the correct anchors of a rank- k matrix by solving O ( k log k ) sub- problems. Finally, we show DCA outperforms state-of-the-art methods on various datasets and tasks.

Zhou, W & Josang, A 2013, 'TrustCom 2013: Message from the general chairs', Proceedings - 12th IEEE International Conference on Trust, Security and Privacy in Computing and Communications, TrustCom 2013.
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Zhou, W, Di Martino, B & Min, G 2013, 'IUCC 2013: Message from the general chairs', Proceedings - 12th IEEE International Conference on Trust, Security and Privacy in Computing and Communications, TrustCom 2013.
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Zhou, W, Goscinski, A & Morin, C 2013, 'ISPA 2013: Message from the general chairs', Proceedings - 12th IEEE International Conference on Trust, Security and Privacy in Computing and Communications, TrustCom 2013.
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Zhu, T, Li, G, Ren, Y, Zhou, W & Xiong, P 2013, 'Differential privacy for neighborhood-based Collaborative Filtering', Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2013, pp. 752-759.
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As a popular technique in recommender systems, Collaborative Filtering (CF) has received extensive attention in recent years. However, its privacy-related issues, especially for neighborhood-based CF methods, can not be overlooked. The aim of this study is to address the privacy issues in the context of neighborhood-based CF methods by proposing a Private Neighbor Collaborative Filtering (PNCF) algorithm. The algorithm includes two privacy-preserving operations: Private Neighbor Selection and Recommendation-Aware Sensitivity. Private Neighbor Selection is constructed on the basis of the notion of differential privacy to privately choose neighbors. Recommendation-Aware Sensitivity is introduced to enhance the performance of recommendations. Theoretical and experimental analysis are provided to show the proposed algorithm can preserve differential privacy while retaining the accuracy of recommendations. Copyright 2013 ACM.

Zhu, T, Li, G, Ren, Y, Zhou, W & Xiong, P 2013, 'Privacy preserving for tagging recommender systems', Proceedings - 2013 IEEE/WIC/ACM International Conference on Web Intelligence, WI 2013, pp. 81-88.
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Tagging recommender systems allow Internet users to annotate resources with personalized tags. The connection among users, resources and these annotations, often called a folksonomy, permits users the freedom to explore tags, and to obtain recommendations. Releasing these tagging datasets accelerates both commercial and research work on recommender systems. However, adversaries may re-identify a user and her/his sensitivity information from the tagging dataset using a little background information. Recently, several private techniques have been proposed to address the problem, but most of them lack a strict privacy notion, and can hardly resist the number of possible attacks. This paper proposes an private releasing algorithm to perturb users' profile in a strict privacy notion, differential privacy, with the goal of preserving a user's identity in a tagging dataset. The algorithm includes three privacy-preserving operations: Private Tag Clustering is used to shrink the randomized domain and Private Tag Selection is then applied to find the most suitable replacement tags for the original tags. To hide the numbers of tags, the third operation, Weight Perturbation, finally adds Laplace noise to the weight of tags We present extensive experimental results on two real world datasets, Delicious and Bibsonomy. While the personalization algorithm is successful in both cases. © 2013 IEEE.

Zhu, T, Xiong, P, Xiang, Y & Zhou, W 2013, 'An effective deferentially private data releasing algorithm for decision tree', Proceedings - 12th IEEE International Conference on Trust, Security and Privacy in Computing and Communications, TrustCom 2013, pp. 388-395.
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Differential privacy is a strong definition for protecting individual privacy in data releasing and mining. However, it is a rigid definition introducing a large amount of noise to the original dataset, which significantly decreases the quality of data mining results. Recently, how to design a suitable data releasing algorithm for data mining purpose is a hot research area. In this paper, we propose a differential private data releasing algorithm for decision tree construction. The proposed algorithm provides a non-interactive data releasing method through which miner can obtain the complete dataset for data mining purpose. With a given privacy budget, the proposed algorithm generalizes the original dataset, and then specializes it in a differential privacy constrain to construct decision trees. As the designed novel scheme selection operation can fully utilize the allocated privacy budget, the data set released by the proposed algorithm can yield better decision tree models than other method. Experimental results demonstrate that the proposed algorithm outperforms existing methods for private decision tree construction. © 2013 IEEE.

Instone, L, Mee, K, Palmer, JM, Williams, M & Vaughan, N National Climate Change Adaptation Research Facility 2013, Climate Change Adaptation and the Rental Sector, Gold Coast, Australia.
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The research employed an asset-based approach to understanding the capacities, assets and skills which tenants, landlords and housing managers bring to climate change adaptation. The project also took a pro-poor approach focusing on the adaptive capacity of low-income renters in the public and private sectors, addressing the equity dimensions of vulnerability and adaptation. In addition to analysing a range of secondary sources such as media articles, `green guides and policy documents, the research analysed primary data from interviews and focus groups, focusing on: The assets of the rental sector in adaptation Barriers which limit the capacity of individuals and organisations to exercise these assets The relationships between the stakeholders tenants, landlords and property managers which underlie both assets and barriers to adaptation. We found that the tenants we interviewed were motivated by concern about the impact of human activity on the environment, and exercised this concern through everyday sustainable household practices, as well as through engagement with community or political organisations. They believed however that their capacity to act in the home was inhibited by a lack of care from some landlords and property managers about the sustainability of rental housing. Public housing managers who were interviewed positioned the public housing sector as policy leaders in sustainability and adaptation, but as constrained by a lack of resources (human and financial) and the busy reactive nature of their work. Busyness and lack of resources was also seen as a constraint on private property managers capacity to advocate or arrange for sustainability modifications to the properties they managed. Property managers emerged as crucial `knowledge brokers mediating between landlords and tenants, but expressed a need for more information and training. Both tenants and property managers acknowledged that the current shortage of rental housing in ...

Johnston, AJ 2013, 'Pixel Mountain', Stalker Theatre, Gwacheon Festival, Hi Seoul, Korea.
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Ayyar, K & Gill, AQ 2013, 'An Integrated, Agile Approach to Enterprise Architecture for Managing Complex Enterprise Transformation'.

Gill, AQ 2013, 'Defining a Facility Architecture within the Agile Enterprise Architecture Context', Orbus Software.
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Facility architecture is important for architecting and supporting other domain architectures, and enterprises need to understand and design it as a part of their overall enterprise architecture. However, the existing mainstream enterprise architecture frameworks lack the support for developing facility architecture. The Gill Framework provides this support, as it can be used with available tools for developing facility architecture within the overall context of enterprise architecture. This white paper explains the key components of the facility architecture domain that could help the architects, analysts, and leaders in understanding its applicability and integration with other EA domain architectures. Firstly, it discusses the need for a new facility architecture domain. Secondly, it discusses The Gill Framework and defines the novel facility architecture. Finally, it discusses the facility architecture components, concluding with a short discussion about how the facility architecture can be used within the overall context of enterprise architecture.

Gill, AQ 2013, 'Defining a Social Architecture within the Enterprise Architecture Context', Orbus Software.
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Organizations have a significant interest in the adoption of social technologies (e.g. Twitter, Facebook, Yammer) for creating an effective social enterprise but before adopting any social technology, enterprises need to understand and design their social architecture. Social Architecture along with other well-established enterprise architecture domains is important for architecting and establishing an effective social enterprise. However, the existing mainstream enterprise architecture frameworks need to be extended for developing situation specific social architecture. This is where Asif Gill introduces The Gill Framework which provides the needed support for developing the social architecture and can be used with available tools within the overall context of enterprise architecture. The paper begins by discussing the need for a new social architecture domain and considers The Gill Framework. Asif then continues to discuss how the framework defines the novel social architecture and the components involved.

Gill, AQ 2013, 'The Gill Framework: Next Generation Information Management Agile Enterprise Strategy, Architecture and Solutions'.