Publications

Cao, L, Zhang, C, Luo, D & Dai, R 2007, 'Intelligence Metasynthesis in Building Business Intelligence Systems' in Carbonell, JG, Siekmann, J, Zhong, N, Liu, J, Yao, Y, Wu, J, Lu, S & Li, K (eds), Web Intelligence Meets Brain Informatics, Springer Berlin Heidelberg, Germany, pp. 454-470.
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In our previous work, we have analyzed the shortcomings of existing business intelligence (BI) theory and its actionable capability. One of the works we have presented is the ontology-based integration of business, data warehousing and data mining. This way may make existing BI systems as user and business-friendly as expected. However, it is challenging to tackle issues and construct actionable and business friendly systems by simply improving existing BI framework. Therefore, in this paper, we further propose a new framework for constructing next generation BI systems. That is intelligence metasynthesis, namely the next-generation BI systems should to some extent synthesize four types of intelligence, including data intelligence, domain intelligence, human intelligence and network/web intelligence. The theory for guiding the intelligence metasynthesis is metasynthetic engineering. To this end, an appropriate intelligence integration framework is substantially important. We first address the roles of each type of intelligence in developing nextgeneration BI systems. Further, implementation issues are addressed by discussing key components for synthesizing the intelligence. The proposed framework is based on our real-world experience and practice in designing and implementing BI systems. It also greatly benefits from multi-disciplinary knowledge dialog such as complex intelligent systems and cognitive sciences. The proposed theoretical framework has potential to deal with key challenges in existing BI framework and systems.

Sidhu, AS, Kennedy, PJ & Simoff, S 2007, 'Knowledge Discovery in Biomedical Data Facilitated by Domain Ontologies' in Zhu, X & Davidson, I (eds), Knowledge Discovery and Data Mining, IGI Global, Hershey, USA, pp. 189-201.
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In some real-world areas, it is important to enrich the data with external background knowledge so as to provide context and to facilitate pattern recognition. These areas may be described as data rich but knowledge poor. There are two challenges to incorporate this biological knowledge into the data mining cycle: (1) generating the ontologies; and (2) adapting the data mining algorithms to make use of the ontologies. This chapter presents the state-of-the-art in bringing the background ontology knowledge into the pattern recognition task for biomedical data.

AUNG, Z & LI, J 2007, 'MINING SUPER-SECONDARY STRUCTURE MOTIFS FROM 3D PROTEIN STRUCTURES: A SEQUENCE ORDER INDEPENDENT APPROACH', Genome Informatics 2007, vol. 19, pp. 15-+.
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Axelrad, DA, Bellinger, DC, Ryan, LM & Woodruff, TJ 2007, 'Dose-response relationship of prenatal mercury exposure and IQ: An integrative analysis of epidemiologic data', ENVIRONMENTAL HEALTH PERSPECTIVES, vol. 115, no. 4, pp. 609-615.
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Background: Prenatal exposure to mercury has been associated with adverse childhood neurologic outcomes in epidemiologic studies. Dose-response information for this relationship is useful for estimating benefits of reduced mercury exposure. Objectives: We estimated a dose-response relationship between maternal mercury body burden and subsequent childhood decrements in intelligence quotient (IQ), using a Bayesian hierarchical model to integrate data from three epidemiologic studies. Methods: Inputs to the model consist of dose-response coefficients from studies conducted in the Faroe Islands, New Zealand, and the Seychelles Islands. IQ coefficients were available from previous work for the latter two studies, and a coefficient for the Faroe Islands study was estimated from three IQ subtests. Other tests of cognition/achievement were included in the hierarchical model to obtain more accurate estimates of study-to-study and end point-to-end point variability. Results: We find a central estimate of -0.18 IQ points (95% confidence interval, -0.378 to -0.009) for each parts per million increase of maternal hair mercury, similar to the estimates for both the Faroe Islands and Seychelles studies, and lower in magnitude than the estimate for the New Zealand study. Sensitivity analyses produce similar results, with the IQ coefficient central estimate ranging from -0.13 to -0.25. Conclusions: IQ is a useful end point for estimating neurodevelopmental effects, but may not fully represent cognitive deficits associated with mercury exposure, and does not represent deficits related to attention and motor skills. Nevertheless, the integrated IQ coefficient provides a more robust description of the dose-response relationship for prenatal mercury exposure and cognitive functioning than results of any single study.

CAO, L & ZHANG, C 2007, 'THE EVOLUTION OF KDD: TOWARDS DOMAIN-DRIVEN DATA MINING', International Journal of Pattern Recognition and Artificial Intelligence, vol. 21, no. 04, pp. 677-692.
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Traditionally, data mining is an autonomous data-driven trial-and-error process. Its typical task is to let data tell a story disclosing hidden information, in which domain intelligence may not be necessary in targeting the demonstration of an algorithm. Often knowledge discovered is not generally interesting to business needs. Comparably, real-world applications rely on knowledge for taking effective actions. In retrospect of the evolution of KDD, this paper briefly introduces domain-driven data mining to complement traditional KDD. Domain intelligence is highlighted towards actionable knowledge discovery, which involves aspects such as domain knowledge, people, environment and evaluation. We illustrate it through mining activity patterns in social security data.

Cao, L, Luo, D & Zhang, C 2007, 'Knowledge actionability: satisfying technical and business interestingness', International Journal of Business Intelligence and Data Mining, vol. 2, no. 4, pp. 496-496.
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Traditionally, knowledge actionability has been investigated mainly by developing and improving technical interestingness. Recently, initial work on technical subjective interestingness and business-oriented profit mining presents general potential, while it is a long-term mission to bridge the gap between technical significance and business expectation. In this paper, we propose a two-way significance framework for measuring knowledge actionability, which highlights both technical interestingness and domain-specific expectations. We further develop a fuzzy interestingness aggregation mechanism to generate a ranked final pattern set balancing technical and business interests. Real-life data mining applications show the proposed knowledge actionability framework can complement technical interestingness while satisfy real user needs. © 2007, Inderscience Publishers.

Cao, L, Zhang, C, Yang, Q, Bell, D, Vlachos, M, Taneri, B, Keogh, E, Yu, PS, Zhong, N, Ashrafi, MZ, Taniar, D, Dubossarsky, E & Graco, W 2007, 'Domain-Driven, Actionable Knowledge Discovery', IEEE Intelligent Systems, vol. 22, no. 4, pp. 78-88, c3.
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Cao, L, Zhang, C, Zhao, Y, Yu, PS & Williams, G 2007, 'DDDM2007', ACM SIGKDD Explorations Newsletter, vol. 9, no. 2, pp. 84-86.
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Real-world data mining generally must consider and involve domain and business oriented factors such as human knowledge, constraints and business expectations. This encourages the development of a domain driven methodology to strengthen data-centered pattern mining. This report presents a review of the ACM SIGKDD Workshop on Domain Driven Data Mining (DDDM2007), held in conjunction with the Thirteenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD07), which was held in San Jose, USA on 12 August, 2007. The aims and objectives of this workshop were to provide a premier forum for sharing innovative findings, knowledge, insights, experiences and lessons in tackling challenges met in domain driven, actionable knowledge discovery in the real world.

Celedon, JC, Milton, DK, Ramsey, CD, Litonjua, AA, Ryan, L, Platts-Mills, TAE & Gold, DR 2007, 'Exposure to dust mite allergen and endotoxin in early life and asthma and atopy in childhood', JOURNAL OF ALLERGY AND CLINICAL IMMUNOLOGY, vol. 120, no. 1, pp. 144-149.
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Background: There has been no longitudinal study of the relation between concurrent exposure to dust mite allergen and endotoxin in early life and asthma and atopy at school age. Objectives: To examine the relation between exposure to dust mite allergen and endotoxin at age 2 to 3 months and asthma, wheeze, and atopy in high-risk children. Methods: Birth cohort study of 440 children with parental history of atopy in the Boston metropolitan area. Results: In multivariate analyses, early exposure to high levels of dust mite allergen (≥10 μg/g) was associated with increased risks of asthma at age 7 years (odds ratio [OR], 3.0; 95% CI, 1.1-7.9) and late-onset wheeze (OR, 5.0; 95% CI, 1.5-16.4). Exposure to endotoxin levels above the lowest quartile at age 2 to 3 months was associated with reduced odds of atopy at school age (OR, 0.5; 95% CI, 0.2-0.9). In contrast with its inverse association with atopy, endotoxin exposure in early life was associated with an increased risk of any wheeze between ages 1 and 7 years that did not change significantly with time (hazard ratio for each quartile increment in endotoxin levels, 1.23; 95% CI, 1.07-1.43). Conclusion: Among children at risk of atopy, early exposure to high levels of dust mite allergen is associated with increased risks of asthma and late-onset wheeze. In these children, endotoxin exposure is associated with a reduced risk of atopy but an increased risk of wheeze. Clinical implications: Early endotoxin exposure may be a protective factor against atopy but a risk factor for wheeze in high-risk children. © 2007 American Academy of Allergy, Asthma & Immunology.

Chen, Q, Chen, Y-PP & Zhang, C 2007, 'Detecting inconsistency in biological molecular databases using ontologies', Data Mining and Knowledge Discovery, vol. 15, no. 2, pp. 275-296.
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The rapid growth of life science databases demands the fusion of knowledge from heterogeneous databases to answer complex biological questions. The discrepancies in nomenclature, various schemas and incompatible formats of biological databases, however, result in a significant lack of interoperability among databases. Therefore, data preparation is a key prerequisite for biological database mining. Integrating diverse biological molecular databases is an essential action to cope with the heterogeneity of biological databases and guarantee efficient data mining. However, the inconsistency in biological databases is a key issue for data integration. This paper proposes a framework to detect the inconsistency in biological databases using ontologies. A numeric estimate is provided to measure the inconsistency and identify those biological databases that are appropriate for further mining applications. This aids in enhancing the quality of databases and guaranteeing accurate and efficient mining of biological databases.

Clark, DE, Ryan, LM & Lucas, FL 2007, 'A multi-state piecewise exponential model of hospital outcomes after injury', JOURNAL OF APPLIED STATISTICS, vol. 34, no. 10, pp. 1225-1239.
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To allow more accurate prediction of hospital length of stay (LOS) after serious injury or illness, a multi-state model is proposed, in which transitions from the hospitalized state to three possible outcome states (home, long-term care, or death) are assumed to follow constant rates for each of a limited number of time periods. This results in a piecewise exponential (PWE) model for each outcome. Transition rates may be affected by time-varying covariates, which can be estimated from a reference database using standard statistical software and Poisson regression. A PWE model combining the three outcomes allows prediction of LOS. Records of 259,941 injured patients from the US Nationwide Inpatient Sample were used to create such a multi-state PWE model with four time periods. Hospital mortality and LOS for patient subgroups were calculated from this model, and time-varying covariate effects were estimated. Early mortality was increased by anatomic injury severity or penetrating mechanism, but these effects diminished with time; age and male sex remained strong predictors of mortality in all time periods. Rates of discharge home decreased steadily with time, while rates of transfer to long-term care peaked at five days. Predicted and observed LOS and mortality were similar for multiple subgroups. Conceptual background and methods of calculation are discussed and demonstrated. Multi-state PWE models may be useful to describe hospital outcomes, especially when many patients are not discharged home.

Du, C 2007, 'Integrating affinity propagation clustering method with linear discriminant analysis for face recognition', Optical Engineering, vol. 46, no. 11, pp. 110501-110501.
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The Fisherface method suffers from the problem of using all training face images to recognize a test face image. To tackle this problem, we propose combining a novel clustering method, affinity propagation (AP), recently reported in the journal Science, with linear discriminant analysis (LDA) to form a new method, AP-LDA, for face recognition. By using AP, a representative face image for each subject can be obtained. Our AP-LDA method uses only these representative face images rather than all training images for recognition. Thus, it is more computationally efficient than Fisherface. Experimental results on several benchmark face databases also show that AP-LDA outperforms Fisherface in terms of recognition rate. © 2007 Society of Photo-Optical Instrumentation Engineers.

Earnest, A, Morgan, G, Mengersen, K, Ryan, L, Summerhayes, R & Beard, J 2007, 'Evaluating the effect of neighbourhood weight matrices on smoothing properties of Conditional Autoregressive (CAR) models', INTERNATIONAL JOURNAL OF HEALTH GEOGRAPHICS, vol. 6, no. 54.
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Eastwood, M & Gabrys, B 2007, 'The Dynamics of Negative Correlation Learning', The Journal of VLSI Signal Processing Systems for Signal, Image, and Video Technology, vol. 49, no. 2, pp. 251-263.
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Gil Lafuente, AM, Ortigosa, M & Merigó, JM 2007, 'The uncertainty theory assignment in the customer lifetime valuation (CLV) for contractual settings with security intervals', Revista de Metodos Cuantitativos para la Economia y la Empresa, vol. 4, pp. 75-97.
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The Customer Lifetime Value (CLV) concept has been highly purposed in many reseaxches in the marketing area since long time ago. Almost all of them tend to be based on determinist or stochastic assumptions when measuring magnitudes or events which have to do with CLV estimates. Often, the Customer Lifetime Valuation (CLV) involves magnitudes that link to the future by the running environment, its mutability and uncertainty, and this turn out the results to be too accurate. Kaufman and Gil Aluja (1986), who are the two most well known European investigators, have carried out researches into several operative management techniques, stood by the following statement 'Most of our traditional tools for formal modelling, reasoning, and computing are crisp, deterministic and precise in character'. Then traditional modelling with precise data can not necessarily mean to be accurate. In this study the authors will deal with some useful directions for uncertainty data, fuzzy data to stand out more accurate according to the reality. Two different Customer Lifetime Value (CLV) models with a least structured uncertainty theory tool will be introduced as well as security intervals that are connected to uncertain magnitudes in the CLV estimation.

Gunes, H & Piccardi, M 2007, 'Bi-modal emotion recognition from expressive face and body gestures', JOURNAL OF NETWORK AND COMPUTER APPLICATIONS, vol. 30, no. 4, pp. 1334-1345.
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Psychological research findings suggest that humans rely on the combined visual channels of face and body more than any other channel when they make judgments about human communicative behavior. However, most of the existing systems...

Hauser, R, Meeker, JD, Singh, NP, Silva, MJ, Ryan, L, Duty, S & Calafat, AM 2007, 'DNA damage in human sperm is related to urinary levels of phthalate monoester and oxidative metabolites', HUMAN REPRODUCTION, vol. 22, no. 3, pp. 688-695.
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BACKGROUND: The ubiquitous use of phthalate esters in plastics, personal care products and food packaging materials results in widespread general population exposure. In this report, we extend our preliminary study on the relationship between urinary concentrations of phthalate metabolites and sperm DNA damage among a larger sample of men and include measurements of mono-(2-ethyl-5-hydroxyhexyl) phthalate (MEHAIR) and mono-(2-ethyl-5-oxohexyl) phthalate (MEOHP), two oxidative metabolites of di-(2-ethylhexyl) phthalate (DEHP). METHODS: Among 379 men from an infertility clinic, urinary concentrations of phthalate metabolites were measured using isotope-dilution high-performance liquid chromatography-tandem mass spectrometry. Sperm DNA damage measurements, assessed with the neutral comet assay, included comet extent (CE), percentage of DNA in tail (Tail%) and tail distributed moment (TDM). RESULTS: Monoethyl phthalate (MEP), a metabolite of diethyl phthalate, was associated with increased DNA damage, confirming our previous findings. Mono-(2-ethylhexyl) phthalate (MERP), a metabolite of DEHP, was associated with DNA damage after adjustment for the oxidative DEHP metabolites. After adjustment for MEHHP, for an interquartile range increase in urinary MEHP, CE increased 17.3% [95% confidence interval (CI) = 8.7-25.7%], TDM increased 14.3% (95% CI = 6.8-21.7%) and Tail% increased 17.5% (95% CI = 3.5-31.5%). CONCLUSIONS: Sperm DNA damage was associated with MEP and with MEHP after adjusting for DEHP oxidative metabolites, which may serve as phenotypic markers of DEHP metabolism to 'less toxic' metabolites. The urinary levels of phthalate metabolites among these men were similar to those reported for the US general population, suggesting that exposure to some phthalates may affect the population distribution of sperm DNA damage.

He, S, Wang, H, Jia, W, Wu, Q, Hur, N, Kim, J & Hintz, TB 2007, 'Uniform Image Partitioning for Fractal Compression on Virtual Hexagonal Structure', International Journal of Information and Systems Science, vol. 3, no. 3, pp. 492-509.
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Hexagonal structure is different from the traditional square structure for image representation. The geometrical arrangement of pixels on hexag-onal structure can be described in terms of a hexagonal grid. Uniformly sepa-rating image into seven similar copies with a smaller scale has commonly been used for parallel and accurate image processing including image compression on hexagonal structure. However, all the existing hardware for capturing image and for displaying image are produced based on square architecture. It has become a serious problem affecting the advanced research based on hexagonal structure. Furthermore, the current techniques used for uniform separation of images on hexagonal structure do not coincide with the rectangular shape of images. This has been an obstacle in the use of hexagonal structure for image processing. In this paper, we briefly review a newly developed virtual hexagonal structure that is scalable. Based on this virtual structure, algorithms for uni-form image separation are presented. The virtual hexagonal structure retains image resolution during the process of image separation, and does not intro-duce distortion. Furthermore, images can be smoothly and easily transferred between the traditional square structure and the hexagonal structure while the image shape is kept in rectangle. As an application of image partitioning, we present a Fractal Image Compression (FIC) method on the virtual image struc- ture by adopting Fisher's basic FIC method on the traditional square image structure. The modifcation on the definition of range block and domain block is implemented in order to utilize the enhanced image structure. The results of the FIC approach applied to testing images are analyzed and show higher fidelity.

Houseman, EA, Marsit, C, Karagas, M & Ryan, LM 2007, 'Penalized item response theory models: Application to epigenetic alterations in bladder cancer', BIOMETRICS, vol. 63, no. 4, pp. 1269-1277.
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Increasingly used in health-related applications, latent variable models provide an appealing framework for handling high-dimensional exposure and response data. Item response theory (IRT) models, which have gained widespread popularity, were originally developed for use in the context of educational testing, where extremely large sample sizes permitted the estimation of a moderate-to-large number of parameters. In the context of public health applications, smaller sample sizes preclude large parameter spaces. Therefore, we propose a penalized likelihood approach to reduce mean square error and improve numerical stability. We present a continuous family of models, indexed by a tuning parameter, that range between the Rasch model and the IRT model. The tuning parameter is selected by cross validation or approximations such as Akaike Information Criterion. While our approach can be placed easily in a Bayesian context, we find that our frequentist approach is more computationally efficient. We demonstrate our methodology on a study of methylation silencing of gene expression in bladder tumors. We obtain similar results using both frequentist and Bayesian approaches, although the frequentist approach is less computationally demanding. In particular, we find high correlation of methylation silencing among 16 loci in bladder tumors, that methylation is associated with smoking and also with patient survival. © 2007, The International Biometric Society.

Izquierdo, E 2007, 'Editorial: Knowledge Engineering, Semantics, and Signal Processing in Audio–Visual Information Retrieval', IEEE Transactions on Circuits and Systems for Video Technology, vol. 17, no. 3, pp. 257-260.
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Jackson, D & Darbyshire, P 2007, 'Preface', Contemporary Nurse, vol. 23, no. 2, pp. v-vi.
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Kazienko, P & Musial, K 2007, 'On utilising social networks to discover representatives of human communities', International Journal of Intelligent Information and Database Systems, vol. 1, no. 3/4, pp. 293-293.
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: Virtual human communities that exist on the internet reflect social relationships between people. There is a great need to find important individuals, a set of people who would represent larger communities. These people would be able to perform specific tasks or could become a target group for marketing or advertising purposes. The new research on representative discovery for human communities is presented in this paper. Its main goal is to improve the process of target group selection by adding the social elements derived from the behaviours of people. The entire selection process considered in the paper is called human filtering. © 2007 Inderscience Enterprises Ltd.

Li, J & Yang, Q 2007, 'Strong Compound-Risk Factors: Efficient Discovery Through Emerging Patterns and Contrast Sets', IEEE Transactions on Information Technology in Biomedicine, vol. 11, no. 5, pp. 544-552.
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Odds ratio (OR), relative risk (RR) (risk ratio), and absolute risk reduction (ARR) (risk difference) are biostatistics measurements that are widely used for identifying significant risk factors in dichotomous groups of subjects. In the past, they have often been used to assess simple risk factors. In this paper, we introduce the concept of compound-risk factors to broaden the applicability of these statistical tests for assessing factor interplays. We observe that compound-risk factors with a high risk ratio or a big risk difference have an one-to-one correspondence to strong emerging patterns or strong contrast sets-two types of patterns that have been extensively studied in the data mining field. Such a relationship has been unknown to researchers in the past, and efficient algorithms for discovering strong compound-risk factors have been lacking. In this paper, we propose a theoretical framework and a new algorithm that unify the discovery of compound-risk factors that have a strong OR, risk ratio, or a risk difference. Our method guarantees that all patterns meeting a certain test threshold can be efficiently discovered. Our contribution thus represents the first of its kind in linking the risk ratios and ORs to pattern mining algorithms, making it possible to find compound-risk factors in large-scale data sets. In addition, we show that using compound-risk factors can improve classification accuracy in probabilistic learning algorithms on several disease data sets, because these compound-risk factors capture the interdependency between important data attributes. © 2007 IEEE.

Liu, X, Liu, W, Yang, L, Xia, B, Li, J, Zuo, J & Li, X 2007, 'Increased Connexin 43 Expression Improves the Migratory and Proliferative Ability of H9c2 Cells by Wnt-3a Overexpression', Acta Biochimica et Biophysica Sinica, vol. 39, no. 6, pp. 391-398.
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The change of connexin 43 (Cx43) expression and the biological behaviors of Cx43 in rat heart cell line H9c2, expressing Wnt-3a (wingless-type MMTV integration site family, member 3A), were evaluated in the present study. Plasmid pcDNA3.1/Wnt-3a was constructed and transferred into H9c2 cells. The cell model Wnt-3a(+)-H9c2 steadily expressing Wnt-3a was obtained. Compared with H9c2 and pcDNA3.1-H9c2 cells, the expression of Cx43 in Wnt-3a(+)-H9c2 cells was clearly increased, the proliferation of Wnt-3a(+)-H9c2 cells was significantly changed, and cell migration abilities were also improved(P<0.05). In comparison with H9c2 and pcDNA3.1-H9c2 cells, the G2 phase of the cell cycle increased by 11% in Wnt-3a(+)-H9c2 cells. Thus, Wnt-3a overexpression is associated with an increase in Cx43 expression and altered migratory and proliferative activity in H9c2 cells. Cx43 might be one of the downstream target genes regulated by Wnt-3a.

Lu, S, Zhang, J & Dagan Feng, D 2007, 'Detecting unattended packages through human activity recognition and object association', Pattern Recognition, vol. 40, no. 8, pp. 2173-2184.
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This paper provides a novel approach to detect unattended packages in public venues. Different from previous works on this topic which are mostly limited to detecting static objects where no human is nearby, we provide a solution which can detect an unat

Madden, C, Cheng, ED & Piccardi, M 2007, 'Tracking people across disjoint camera views by an illumination-tolerant appearance representation', Machine Vision and Applications, vol. 18, no. 3-4, pp. 233-247.
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Tracking single individuals as they move across disjoint camera views is a challenging task since their appearance may vary significantly between views. Major changes in appearance are due to different and varying illumination conditions and the deformable geometry of people. These effects are hard to estimate and take into account in real-life applications. Thus, in this paper we propose an illumination-tolerant appearance representation, which is capable of coping with the typical illumination changes occurring in surveillance scenarios. The appearance representation is based on an online k-means colour clustering algorithm, a data-adaptive intensity transformation and the incremental use of frames. A similarity measurement is also introduced to compare the appearance representations of any two arbitrary individuals. Post-matching integration of the matching decision along the individuals' tracks is performed in order to improve reliability and robustness of matching. Once matching is provided for any two views of a single individual, its tracking across disjoint cameras derives straightforwardly. Experimental results presented in this paper from a real surveillance camera network show the effectiveness of the proposed method. © Springer-Verlag 2007.

Marchionini, G, Abbasi, A, Agichtein, E, Ahmad, K, Al-Maskari, A, Amati, G, Yahia, SA, Argamon, S, Ashbrook, D, Atzeni, P, Bacchin, M, Back, G, Badia, A, Banczur, A, Berendt, B, Bertino, E, Bhagyavati, B, Bhavnani, S, Bhosale, D, Bodoff, D, Boldi, P, Bollen, J, Bonifati, A, Borlund, P, Bose, J, Bouguettaya, A, Brinkmeier, M, Brown, P, Brusilovsky, P, Bruza, P, Burges, C, Burke, R, Carterette, B, Cater, A, Chang, K, Chen, HH, Chen, Z, Cheney, J, Cheng, PJ, Chiang, R, Choi, B, Chua, TS, Clarke, C, Clough, P, Consens, M, Cormack, G, Craswell, N, Crestani, F, Crouch, C, Cucerzan, SP, Cui, H, Cunningham, SJ, Cutrell, E, De La Fuente, P, De Vries, A, Diekema, A, Dominich, S, Doraisamy, S, Dunlop, M, Dupret, G, Efron, M, Ellman, J, Enser, P, Erkan, G, Fochtmann, L, Fongen, A, Ford, N, Franz, M, Fu, X, Garza, P, Gauch, S, Geneves, P, Gladney, H, Gnasa, M, Goldberg, A, Goncalves, M, Goutte, C, Grossman, D, Groth, D, Gwizdka, J, Haas, S, Harabagiu, S, Harman, D, Henrich, A, Hiemstra, D, Hollaar, L, Hsu, CN, Huang, F, Huang, Z, Huhns, M, Hurtado, C, Innoue, K, Ipeirotis, P, Jansen, B, Jianqiang, W, Jin, R, Junkkari, M, Juola, P, Kakade, V & Kamps, J 2007, 'TOIS reviewers January 2006 through May 2007', ACM Transactions on Information Systems, vol. 25, no. 4, pp. 15-15.
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McCarty, KM, Chen, Y-C, Quamruzzaman, Q, Rahman, M, Mahiuddin, G, Hsueh, Y-M, Su, L, Smith, T, Ryan, L & Christiani, DC 2007, 'Arsenic methylation, GSTT1, GSTM1, GSTP1 polymorphisms, and skin lesions', ENVIRONMENTAL HEALTH PERSPECTIVES, vol. 115, no. 3, pp. 341-345.
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Objective: We investigated whether primary and secondary arsenic methylation ratios were associated with skin lesions and whether GSTT1, GSTP1, and GSTM1 polymorphisms modify these relationships. Methods: A case-control study of 600 cases and 600 controls that were frequency matched on age and sex was conducted in Pabna, Bangladesh, in 2001-2002. Individual well water, urine, and blood samples were collected. Water arsenic concentration was determined using inductively coupled plasma mass spectrometry (ICP-MS). Urinary arsenic speciation was determined using high performance liquid chromatography hydride with generator atomic absorption spectrometry and ICP-MS. Genotyping was conducted using multiplex polymerase chain reaction and TaqMan. Results: A 10-fold increase in primary methylation ratio [monomethylarsonic acid (MMA)/(arsenite + arsenate) was associated with a 1.50-fold increased risk of skin lesions (multivariate odds ratio = 1.50; 95% confidence interval, 1.00-2.26). We observed significant interaction on the multiplicative scale between GSTT1 wildtype and secondary methylation ratio [dimethylarsinic acid/MMA; likelihood ratio test (LRT), p = 0.01]. No significant interactions were observed for GSTM1 or GSTP1 or for primary mathylation ratios. Conclusion: Our findings suggest that increasing primary methylation ratios are associated with an increase in risk of arsenic-related skin lesions. The interaction between GSTT1 wildtype and secondary methylation ratio modifies risk of skin lesions among arsenic-exposed individuals.

McCarty, KM, Ryan, L, Houseman, EA, Williams, PL, Miller, DP, Quamruzzaman, Q, Rahman, M, Mahiuddin, G, Smith, T, Gonzalez, E, Su, L & Christiani, DC 2007, 'A case-control study of GST polymorphisms and arsenic related skin lesions', ENVIRONMENTAL HEALTH, vol. 6, no. 5, pp. 1-10.
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Background. Polymorphisms in GSTT1, GSTM1 and GSTP1 impact detoxification of carcinogens by GSTs and have been reported to increase susceptibility to environmentally related health outcomes. Individual factors in arsenic biotransformation may influence disease susceptibility. GST activity is involved in the metabolism of endogenous and exogenous compounds, including catalyzing the formation of arsenic-GSH conjugates. Methods. We investigated whether polymorphisms in GSTT1, GSTP1 and GSTM1 were associated with risk of skin lesions and whether these polymorphisms modify the relationship between drinking water arsenic exposure and skin lesions in a case control study of 1200 subjects frequency matched on age and gender in community clinics in Pabna, Bangladesh in 2001-2002. Results and discussion. GSTT1 homozygous wildtype status was associated with increased odds of skin lesions compared to the null status (OR1.56 95% CI 1.10-2.19). The GSTP1 GG polymorphism was associated with greater odds of skin lesions compared to GSTP1 AA, (OR 1.86 (95%CI 1.15-3.00). No evidence of effect modification by GSTT1, GSTM1 or GSTP1 polymorphisms on the association between arsenic exposure and skin lesions was detected. Conclusion. GSTT1 wildtype and GSTP1 GG are associated with increased risk of skin lesions. © 2007 McCarty et al; licensee BioMed Central Ltd.

McCarty, KM, Smith, TJ, Zhou, W, Gonzalez, E, Quamruzzaman, Q, Mahiuddin, G, Ryan, L, Su, L & Christiani, DC 2007, 'Polymorphisms in XPD (Asp312Asn and Lys751Gln) genes, sunburn and arsenic-related skin lesions', CARCINOGENESIS, vol. 28, no. 8, pp. 1697-1702.
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Background: Single-nucleotide polymorphisms in genes related to DNA repair capacity and ultraviolet exposure have not been well investigated in relation to skin lesions associated with arsenic exposure. This population based case-control study, of 600 ca

Merigó Lindahl, JM & Gil Lafuente., AM 2007, 'UNIFICATION POINT IN METHODS FOR THE SELECTION OF FINANCIAL PRODUCTS', FUZZY ECONOMIC REVIEW, vol. 12, no. 01, pp. 35-50.
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In this paper, we analyse in detail the selection of financial products. We apply the index of maximum and minimum level for the selection of financial products and we analyse what we have called the unification point between the Hamming distance and the adequacy coefficient. First, we study this situation for the case of maximum levels in the characteristics of the ideal financial product. Then, we generalize it for all the possible situations where it can be found. Finally, we study the unification point in the index of maximum and minimum level. The result found shows a transformation of this index into the Hamming distance.

Pang, BC, Kuralmani, V, Joshi, R, Hongli, Y, Lee, KK, Ang, BT, Li, J, Leong, TY & Ng, I 2007, 'Hybrid Outcome Prediction Model for Severe Traumatic Brain Injury', Journal of Neurotrauma, vol. 24, no. 1, pp. 136-146.
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Numerous studies addressing different methods of head injury prognostication have been published. Unfortunately, these studies often incorporate different head injury prognostication models and study populations, thus making direct comparison difficult, if not impossible. Furthermore, newer artificial intelligence tools such as machine learning methods have evolved in the field of data analysis, alongside more traditional methods of analysis. This study targets the development of a set of integrated prognostication model combining different classes of outcome and prognostic factors. Methodologies such as discriminant analysis, logistic regression, decision tree, Bayesian network, and neural network were employed in the study. Several prognostication models were developed using prospectively collected data from 513 severe closed head-injured patients admitted to the Neurocritical Unit at National Neuroscience Institute of Singapore, from April 1999 to February 2003. The correlation between prognostic factors at admission and outcome at 6 months following injury was studied. Overfitting error, which may falsely distinguish different outcomes, was compared graphically. Tenfold cross-validation technique, which reduces overfitting error, was used to validate outcome prediction accuracy. The overall prediction accuracy achieved ranged from 49.79% to 81.49%. Consistently high outcome prediction accuracy was seen with logistic regression and decision tree. Combining both logistic regression and decision tree models, a hybrid prediction model was then developed. This hybrid model would more accurately predict the 6-month post-severe head injury outcome using baseline admission parameters. © Mary Ann Liebert, Inc.

Qin, Y, Zhang, S, Zhu, X, Zhang, J & Zhang, C 2007, 'Semi-parametric optimization for missing data imputation', Applied Intelligence, vol. 27, no. 1, pp. 79-88.
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Missing data imputation is an important issue in machine learning and data mining. In this paper, we propose a new and efficient imputation method for a kind of missing data: semi-parametric data. Our imputation method aims at making an optimal evaluation about Root Mean Square Error (RMSE), distribution function and quantile after missing-data are imputed. We evaluate our approaches using both simulated data and real data experimentally, and demonstrate that our stochastic semi-parametric regression imputation is much better than existing deterministic semi-parametric regression imputation in efficiency and effectiveness. © Springer Science+Business Media, LLC 2007.

Ramsey, CD, Gold, DR, Litonjua, AA, Sredl, DL, Ryan, L & Celedon, JC 2007, 'Respiratory illnesses in early life and asthma and atopy in childhood', JOURNAL OF ALLERGY AND CLINICAL IMMUNOLOGY, vol. 119, no. 1, pp. 150-156.
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Background: The relation between respiratory illnesses in early life and the development of asthma and atopy in childhood is incompletely understood. Objective: We sought to examine the relationship between respiratory illnesses in early life and atopic diseases at school age. Methods: We performed a prospective birth cohort study of the relationship between respiratory illnesses in the first year of life and asthma, atopy (sensitization to ≥1 allergen), and allergic rhinitis at school age in 440 children with a parental history of atopy. Logistic regression was used to examine the relationship between respiratory illnesses and asthma, atopy, and allergic rhinitis. The relationship between respiratory illnesses in early life and repeated measures of wheezing between the ages of 1 and 7 years was investigated by using a proportional hazards models. Results: Physician-diagnosed croup (adjusted odds ratio [OR], 0.30; 95% CI, 0.12-0.72) and having 2 or more physician-diagnosed ear infections (adjusted OR, 0.58; 95% CI, 0.35-0.98) in the first year of life were inversely associated with atopy at school age. Physician-diagnosed bronchiolitis before age 1 year was significantly associated with asthma at age 7 years (adjusted OR, 2.77; 95% CI, 1.23-6.22). Recurrent nasal catarrh (≥3 episodes of a runny nose) in the first year of life was associated with allergic rhinitis at age 7 years (adjusted OR, 2.99; 95% CI, 1.03-8.67). Conclusion: The relationship between early-life respiratory illnesses and asthma and atopy is complex and likely dependent on the type of infection and immune response it initiates. Clinical implications: Certain respiratory illnesses in early life modify the risk of atopy and asthma at school age. © 2007 American Academy of Allergy, Asthma & Immunology.

Riedel, S & Gabrys, B 2007, 'Combination of Multi Level Forecasts', The Journal of VLSI Signal Processing Systems for Signal, Image, and Video Technology, vol. 49, no. 2, pp. 265-280.
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Scirica, CV, Gold, DR, Ryan, L, Abulkerim, H, Celedon, JC, Platts-Mills, TAE, Naccara, LM, Weiss, ST & Litonjua, AA 2007, 'Predictors of cord blood IgE levels in children at risk for asthma and a atopy', JOURNAL OF ALLERGY AND CLINICAL IMMUNOLOGY, vol. 119, no. 1, pp. 81-88.
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Background: Increased cord blood IgE levels, in conjunction with a family history of atopy, are associated with the development of allergic diseases in children. However, little is known about predictors of cord blood IgE levels. Objective: Our objective was to identify predictors of cord blood IgE levels among infants at increased risk of atopy. Methods: Cord blood IgE levels were measured in 874 infants who were screened for participation in a birth cohort. Questionnaires were administered after birth of the infant, and maternal and cord blood was obtained for measurement of IgE levels. Logistic and tobit regression models were used to study the association between perinatal factors and cord blood IgE levels. Results: In multivariable models infant male sex, increased maternal total IgE level, maternal allergen sensitization, Hispanic ethnicity, and residence in low-income areas were associated with detectable or increased cord blood IgE levels, whereas increasing maternal age was associated with undetectable or lower cord blood IgE levels. Although maternal smoking during pregnancy was positively associated with cord blood IgE levels in univariable models, the effect did not persist after adjusting for potential confounders. Conclusion: Maternal allergen sensitization, markers of socioeconomic disadvantage and race/ethnicity, maternal age, and infant sex might influence fetal production of IgE. We found no association of maternal parity, mode of delivery, gestational age, or season of birth with cord blood IgE levels. Clinical implications: The identification of these definable familial and environmental factors that predict cord blood IgE levels might help in the early detection of infants at risk for atopic disorders. © 2007 American Academy of Allergy, Asthma & Immunology.

Surkan, PJ, Ryan, LM, Vieira, LMC, Berkman, LF & Peterson, KE 2007, 'Maternal social and pyschological conditions and physical growth in low-income children in Piaui, Northeast Brazil', SOCIAL SCIENCE & MEDICINE, vol. 64, no. 2, pp. 375-388.
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Prevalence of child undernutrition remains high in many developing countries. In settings with scarce resources, modifiable maternal social conditions may influence feeding and parenting practices, in turn affecting child growth. This study aims to quantify the association between maternal social support and depression to children's physical growth outcomes in Teresina, Piauí, northeast Brazil. Interviews were conducted with a random sample of 595 mothers of children 6-24 months old in four low-income sections of Teresina, Piauí. We collected data on sociodemographic factors, mothers' social support, mothers' depressive symptomatology, and child's weight and recumbent length. Weight-for-height z-scores (WHZ), height-for-age z-scores (HAZ) and weight-for-age z-scores (WAZ) were calculated using the National Center for Chronic Disease Prevention and Health Promotion Center SAS program based on the 2000 Centers for Disease Control reference growth curves. Multivariable linear regression was used to model the association between maternal social support and depression to child growth, adjusting for biological and socio-demographic variables. Interviewer and neighborhood variation was accounted for through the inclusion of random effects. In adjusted models, material support, measured by number of friends or family members available to mothers when needing food or milk, was related to 0.3 higher average WHZ and 0.2 higher average WAZ in their children. Maternal positive social interaction, which reflects engagement in leisure-time activities with others, was associated with 0.3 higher average WHZ. Mothers' affectionate support was related to 0.2 higher average children's WHZ and WAZ, whereas social support for resolving a conflict was associated with 0.2 lower average HAZ. Maternal depression was not associated with child growth. It is concluded that inadequate growth in children may be sensitive to maternal social support. © 2006 Elsevier Ltd. All rights reserved.

Yan, X, Zhang, S & Zhang, C 2007, 'ON DATA STRUCTURES FOR ASSOCIATION RULE DISCOVERY', Applied Artificial Intelligence, vol. 21, no. 2, pp. 57-79.
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Systematically we study data structures used to implement the algorithms of association rule mining, including hash tree, itemset tree, and FP-tree (frequent pattern tree). Further, we present a generalized FP-tree in an applied context. This assists in better understanding existing association-rule-mining strategies. In addition, we discuss and analyze experimentally the generalized k-FP-tree, and demonstrate that the generalized FP-tree reduces the computation costs significantly. This study will be useful to many association analysis tasks where one must provide really interesting rules and develop efficient algorithms for identifying association rules.

Zhang, H, Jia, W, He, X & Wu, Q 2007, 'Learning-based license plate detection in vehicle image database', International Journal of Intelligent Information and Database Systems, vol. 1, no. 2, pp. 228-228.
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This paper proposes a learning-based algorithm to detect license plates of vehicles from vehicle image database. There are three main contributions in this paper. The first contribution is to define a novel vertical edge map, which makes the image processing more effectively. The second contribution is to propose a learning-based cascade classifier composing of two kinds of sub-classifiers, which makes the system very robust. The third contribution is to experimentally estimate the parameter of scaling factor and chose an optimal one for the algorithm to seek a good balance between detection rate and processing time. © 2007 Inderscience Enterprises Ltd.

Zhang, H, Zhao, Y, Cao, L & Zhang, C 2007, 'Class Association Rule Mining with Multiple Imbalanced Attributes', Lecture Notes in Computer Science, vol. 4830, pp. 827-831.
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In this paper, we propose a novel framework to deal with data imbalance in class association rule mining. In each class association rule, the right-hand is a target class while the left-hand may contain one or more attributes. This framework is focused on the multiple imbalanced attributes on the left-hand. In the proposed framework, the rules with and without imbalanced attributes are processed in parallel. The rules without imbalanced attributes are mined through standard algorithm while the rules with imbalanced attributes are mined based on new defined measurements. Through simple transformation, these measurements can be in a uniform space so that only a few parameters need to be specified by user. In the case study, the proposed algorithm is applied into social security field. Although some attributes are severely imbalanced, the rules with minority of the imbalanced attributes have been mined efficiently.

Zhang, S, Zhang, J & Zhang, C 2007, 'EDUA: An efficient algorithm for dynamic database mining', Information Sciences, vol. 177, no. 13, pp. 2756-2767.
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Maintaining frequent itemsets (patterns) is one of the most important issues faced by the data mining community. While many algorithms for pattern discovery have been developed, relatively little work has been reported on mining dynamic databases, a major area of application in this field. In this paper, a new algorithm, namely the Efficient Dynamic Database Updating Algorithm (EDUA), is designed for mining dynamic databases. It works well when data deletion is carried out in any subset of a database that is partitioned according to the arrival time of the data. A pruning technique is proposed for improving the efficiency of the EDUA algorithm. Extensive experiments are conducted to evaluate the proposed approach and it is demonstrated that the EDUA is efficient. © 2007 Elsevier Inc. All rights reserved.

Zhang, Z & Zhang, C 2007, 'Building agent-based hybrid intelligent systems: A case study', Web Intelligence and Agent Systems, vol. 5, no. 3, pp. 255-271.
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Many complex problems (e.g., financial investment planning, foreign exchange trading, data mining from large/multiple databases) require hybrid intelligent systems that integrate many intelligent techniques (e.g., fuzzy logic, neural networks, and genetic algorithms). However, hybrid intelligent systems are difficult to develop because they have a large number of parts or components that have many interactions. On the other hand, agents offer a new and often more appropriate route to the development of complex systems, especially in open and dynamic environments. Thus, this paper discusses the development of an agent-based hybrid intelligent system for financial investment planning, in which a great number of heterogeneous computing techniques/packages are easily integrated into a unifying agent framework. This shows that agent technology can indeed facilitate the development of hybrid intelligent systems.

Bouchachia, A, Gabrys, B & Sahel, Z 1970, 'Overview of Some Incremental Learning Algorithms', 2007 IEEE International Fuzzy Systems Conference, 2007 IEEE International Fuzzy Systems Conference, IEEE, London, ENGLAND, pp. 1811-+.
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Cao, L 1970, 'Multi-strategy Integration for Actionable Trading Agents', 2007 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology - Workshops, 2007 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology - Workshops, IEEE, San Jose, USA, pp. 487-490.
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Trading agents are very useful for developing and back-testing quality trading strategies to support smart trading actions in the market. However, the existing trading agent research mainly focuses on simple and simulated strategies. As a result, there exists a big gap between academia and business when the developed trading agents are deployed in the real life. Therefore, the actionable capability of developed trading agents is often very limited. In this paper, we introduce approaches for optimizing and integrating multiple classes of strategies for trading agents. Five categories of trading strategies, including 36 types of trading strategies are trained and tested. A strategy integration and optimization approach is proposed to identify golden trading strategy in each category, and finally recommend positions associated with these golden strategies to trading agents. Test in five international markets on ten years of data respectively has shown that the final strategies recommended to trading agents can lead to high benefits while low costs. Concurrent execution of positions recommended by all golden strategies can greatly enhance performance. © 2007 IEEE.

Cao, L 1970, 'Multi-strategy Integration for Actionable Trading Agents', 2007 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology - Workshops, 2007 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology - Workshops, IEEE.
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Cao, L & Zhang, C 1970, 'F-trade', Proceedings of the 6th international joint conference on Autonomous agents and multiagent systems, AAMAS07: International Conference on Autonomous Agents and Mulitagent Systems, ACM, Honolulu, Hawai'i, pp. 1363-1364.
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The interaction and integration of agent technology and data mining presents prominent benefits to solve some of challenging issues in individual areas. For instance, data mining can enhance agent learning, while agent can benefit data mining with distributed pattern discovery. In this paper, we summarize the main functionalities and features of an agent service and data mining symbiont -- F-Trade. The F-Trade is constructed in Java agent service following the theory of open complex agent systems. We demonstrate the roles of agents in building up the F-Trade, as well as how agents can support data mining. On the other hand, data mining is used to strengthen agents. F-Trade provides flexible and efficient services of trading evidence back-testing, optimization and discovery, as well as plug and play of algorithms, data and system modules for financial trading and surveillance with online connectivity to huge quantities of global market data. and mining symbiont.

Cao, L, Luo, C & Zhang, C 1970, 'Agent-Mining Interaction: An Emerging Area', Autonomous Intelligent Systems: Multi-Agents and Data Mining, International Workshop Autonomous Intelligent Systems: Agents and Data Mining, Springer Berlin Heidelberg, St. Petersburg, Russia, pp. 60-73.
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In the past twenty years, agents (we mean autonomous agent and multi-agent systems) and data mining (also knowledge discovery) have emerged separately as two of most prominent, dynamic and exciting research areas. In recent years, an increasingly remarkable trend in both areas is the agent-mining interaction and integration. This is driven by not only researcherâs interests, but intrinsic challenges and requirements from both sides, as well as benefits and complementarity to both communities through agent-mining interaction. In this paper, we draw a high-level overview of the agent-mining interaction from the perspective of an emerging area in the scientific family. To promote it as a newly emergent scientific field, we summarize key driving forces, originality, major research directions and respective topics, and the progression of research groups, publications and activities of agent-mining interaction. Both theoretical and application-oriented aspects are addressed. The above investigation shows that the agent-mining interaction is attracting everincreasing attention from both agent and data mining communities. Some complicated challenges in either community may be effectively and efficiently tackled through agent-mining interaction. However, as a new open area, there are many issues waiting for research and development from theoretical, technological and practical perspectives. This work is sponsored by Australian Research Council Discovery Grant (DP0773412, LP0775041, DP0667060, DP0449535), and UTS internal grants.

Cao, L, Luo, C & Zhang, C 1970, 'Developing Actionable Trading Strategies for Trading Agents', 2007 IEEE/WIC/ACM International Conference on Intelligent Agent Technology (IAT'07), 2007 IEEE/WIC/ACM International Conference on Intelligent Agent Technology (IAT'07), IEEE, Fremont, CA, pp. 72-+.
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Cao, L, Zhao, Y, Figueiredo, F, Ou, Y & Luo, D 1970, 'Mining High Impact Exceptional Behavior Patterns', Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Pacific-Asia Conference on Knowledge Discovery and Data Mining, Springer Berlin Heidelberg, Nanjing, China, pp. 56-63.
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In the real world, exceptional behavior can be seen in many situations such as security-oriented fields. Such behavior is rare and dispersed, while some of them may be associated with significant impact on the society. A typical example is the event September 11. The key feature of the above rare but significant behavior is its high potential to be linked with some significant impact. Identifying such particular behavior before generating impact on the world is very important. In this paper, we develop several types of high impact exceptional behavior patterns. The patterns include frequent behavior patterns which are associated with either positive or negative impact, and frequent behavior patterns that lead to both positive and negative impact. Our experiments in mining debt-associated customer behavior in social-security areas show the above approaches are useful in identifying exceptional behavior to deeply understand customer behavior and streamline business process. © Springer-Verlag Berlin Heidelberg 2007.

Chen, L, Bhowmick, S & Nejdl, W 1970, 'Mirror site maintenance based on evolution associations of web directories', Proceedings of the 16th international conference on World Wide Web, WWW'07: 16th International World Wide Web Conference, ACM.
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Chen, Q, Zhang, C & Chen, Y-PP 1970, 'Probabilistic Reasoning of Inconsistent Belief in Protocol Analysis', Proceedings on Intelligent Systems and Knowledge Engineering (ISKE2007), International Conference on Intelligent Systems and Knowledge Engineering 2007, Atlantis Press.
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Chen, Y, Wu, Q & He, X 1970, 'Study on human behaviour retrieval', Proceedings of the 2007 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2007, International Conference on Image Processing, Computer Vision and Pattern Recognition, CSREA Press, Las Vegas, pp. 448-454.
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Human behavior analysis is a hot topic in computer vision and is applied widely in many applications. Human behavior retrieval is another frontier technology in the area of multimedia information retrieval, which is related to human behavior analysis but holds several differences because of its special application purpose. Human behaviour retrieval to some extent is similar to human behaviour analysis, but the technology used for human behavior analysis cannot be used for human behavior directly. This paper will address such kind of differences and review several technologies including video retrieval, feature extraction, similarity measure and human behavior analysis. This paper will also address the importance of human behaviour retrieval. The ideas unveiled by this paper will benefit the research community and indicate a direction of human behavior retrieval research.

Chen, Y, Wu, Q, He, X, Jia, W & Hintz, T 1970, 'Pixel Structure Based on Hausdorff Distance for Human Detection in Outdoor Environments', 9th Biennial Conference of the Australian Pattern Recognition Society on Digital Image Computing Techniques and Applications (DICTA 2007), 9th Biennial Conference of the Australian Pattern Recognition Society on Digital Image Computing Techniques and Applications (DICTA 2007), IEEE, pp. 67-72.
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This paper proposes a novel method for human detection from static images based on pixel structure of input images. In training stage, all sample images consisting of human images and non-human images are used to construct a Hausdorff distance map based on statistically analyzing the difference between the different blocks on each original image. A projection matrix will be created with Linear Discriminant Method (LDM) based on the Hausdorff distance map. This projection matrix will be used to transform multi-dimensional feature vectors (distance maps of testing images) into a feature in a one-dimensional domain. The decision will be made on the simple one-dimensional feature domain according to a precalculated threshold to distinguish human figures from non-human figures. In comparison with the common method based on Mahalanobis distance maps, the proposed method based on Hausdorff distance maps performs much better. Encouraging experimental results have been obtained using 800 human images and 800 non-human images. © 2007 IEEE.

Christen, P, Gao, J, Kennedy, PJ, Li, J, Li, W, Kolyshkina, I, Ong, K & Williams, G 1970, 'Data Mining, Artificial Intelligence & Analytics 2007: Proceedings of the 6th Australasian Data Mining Conference (AusDM 2007) and the 2nd International Workshop on Integrating AI and Data Mining (AIDM 2007)', Data Mining, Artificial Intelligence & Analytics 2007: Proceedings of the 6th Australasian Data Mining Conference (AusDM 2007) and the 2nd International Workshop on Integrating AI and Data Mining (AIDM 2007), Australian Data Mining Conference, Australian Computer Society, Gold Coast, Australia.

Clark, DE, Lucas, FL & Ryan, LM 1970, 'Predicting hospital mortality, length of stay, and transfer to long-term care for injured patients', JOURNAL OF TRAUMA-INJURY INFECTION AND CRITICAL CARE, 19th Annual Meeting of the Eastern-Association-for-the-Surgery-of-Trauma, Lippincott Williams & Wilkins, Orlando, FL, pp. 592-600.
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Background: Using hospital length of stay (LOS) to measure trauma care efficiency is complicated by short LOS resulting from early mortality or transfer to long-term care (LTC). Methods: Records from the 1999 to 2003 National Trauma Data Bank were used t

Dong, H, Hussain, FK & Chang, E 1970, 'An Integrative view of the concept of Digital Ecosystem', International Conference on Networking and Services (ICNS '07), 2007 International Conference on Networking and Services, IEEE.
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In the literature we fid two broad definitions of the concept of Digital Ecosystem, hence leading to confusion and ambiguity with regards to its semantic interpretation. In this paper we make use of ontology, which is a well-known tool for knowledge sharing, in order to present an integrative view of the concept of Digital Ecosystem. We implement the ontology by using Protégé-owl. © 2007 IEEE.

Dong, H, Hussain, FK & Chang, E 1970, 'Application of Protege and SPARQL in the field of project knowledge management', 2007 Second International Conference on Systems and Networks Communications (ICSNC 2007), 2007 2nd International Conference on Systems and Networks Communications, IEEE, pp. 74-79.
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Protégé is a set of open-source ontology design software developed in Stanford Medical Informatics. SPARQL (Protocol and RDF Query Language) is recommended by W3C, to represent the RDF (Resource Description Framework) graph - a set of triples that consist of a subject, a predicate and an object as the basic expression of data stored in OWL-based knowledge base. In this paper, we propose an ontology-based project knowledge management methodology, by means of Protégé and SPARQL, to solve the issues in project management activities. By introducing a set of new ontology notations, we present the conceptual model of our ontology to realize the function of knowledge management in project organizations. Following that, we realize the prototype in Protégé and validate it by means of SPARQL. Finally we make comments on our project and plan our future work. © 2007 IEEE.

Dong, H, Hussain, FK & Chang, E 1970, 'Exploring the Conceptual Model of Digital Ecosystem', 2007 Second International Conference on Digital Telecommunications (ICDT'07), Second International Conference on Digital Telecommunications, ICDT 2007, IEEE, p. 18.
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Digital Ecosystem, as a neoteric terminology, has emerged along with the appearance of Business Ecosystem which is a form of naturally existing business network of small and medium enterprises. However, few researches have been found in the field of defining digital ecosystem. In this paper, by means of ontology technology as our research methodology, we propose to develop a conceptual model for digital ecosystem. By introducing an innovative ontological notation system, we create the hierarchical framework of digital ecosystem form up to down, based on the related theories form Digital Ecosystem and Business Intelligence Institute. © 2007 IEEE.

Du, C, Yang, J, Wu, Z, Yuan, Q & Wu, Q 1970, 'Improved neural network based manifold learning method for face recognition with less face images per individual', Proceedings of the 2007 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2007, pp. 444-447.
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In this paper, a novel neural network based manifold learning method(NNBML)[1] recently appeared in the Journal of Science is introduced. It can effectively convert high-dimensional data into low-dimensional codes, which are then used for classification. However, it performs not well while dealing with small size face database used for face recognition. We propose a solution generating more samples data based on the existing data. The proposed method is implemented on two well-known face databases, viz. ORL and Yale face databases. The experimental results show that NNBML is able to deal with the task of face recognition after more data samples generated using the proposed method, and also that NNBML outperforms LDA in terms of recognition rate.

Gao, J & Xu, RY 1970, 'Mixture of the Robust L1 Distributions and Its Applications', Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Springer Berlin Heidelberg, pp. 26-35.
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Recently a robust probabilistic L1-PCA model was introduced in [1] by replacing the conventional Gaussian noise model with the Laplacian L1 model. Due to the heavy tail characteristics of the L1 distribution, the proposed model is more robust against data outliers. In this paper, we generalized the L1-PCA into a mixture of L1-distributions so that the model can be used for possible multiclustering data. For the model learning we use the property that the L1 density can be expanded as a superposition of infinite number of Gaussian densities to include a tractable Bayesian learning and inference based on the variational EM-type algorithm. © Springer-Verlag Berlin Heidelberg 2007.

Geng, X, Wang, L, Li, M, Wu, Q & Smith-Miles, K 1970, 'Distance-driven Fusion of Gait and Face for Human Identification in Video', Proceedings of Image and Vision Computing New Zealand 2007, Image and Vision Computing Conference, Image and Vision Computing New Zealand, Hamilton, New Zealand, pp. 19-24.

He, S, Zhang, H, Jia, W, Wu, Q & Hintz, TB 1970, 'Combining Global and Local Features for Detection of License Plates in Video', Proceedings of Image and Vision Computing New Zealand 2007, Image and Vision Computing Conference, Image and Vision Computing New Zealand, Hamilton, New Zealand, pp. 288-293.

He, X, Hintz, T, Li, J, Zhang, H, Wu, Q & Jia, W 1970, 'Local binary pattern on hexagonal structure for face matching', Proceedings of the 2007 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2007, International Conference on Image Processing, Computer Vision and Pattern Recognition, CSREA Press, Las Vegas, USA, pp. 455-460.
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Principal Components Analysis (PCA), Independent Component Analysis (ICA) and Linear Discriminant Analysis (LDA), have been widely used for 2D face recognition. Local Binary Pattern (LBP), however, provides a simpler and more effective way to represent faces. With LBP, face image is divided into small regions from which LBP histograms are extracted and concatenated into a single and global feature histogram representing the face image. The recognition is performed using Chi square and other commonly used dissimilarity measures. In this paper, we construct LBP codes together with three dissimilarity measures on hexagonal structure. We show that LBPs defined on hexagonal structure will lead to a faster and more accurate scheme for face recognition.

He, X, Jia, W, Li, J, Wu, Q & Hintz, T 1970, 'An Approach to Edge Detection on a Virtual Hexagonal Structure', 9th Biennial Conference of the Australian Pattern Recognition Society on Digital Image Computing Techniques and Applications (DICTA 2007), 9th Biennial Conference of the Australian Pattern Recognition Society on Digital Image Computing Techniques and Applications (DICTA 2007), IEEE, Glenelg, Australia, pp. 340-345.
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Hexagonal structure is another image structure alternative to traditional square image structure for image processing and computer vision. The geometrical arrangement of pixels on a hexagonal structure can be described as a collection of hexagonal pixels. Because all the existing hardware for capturing image and for displaying image are produced based on square structure, it becomes important to find a proper software approach to mimic hexagonal structure so that images represented on the traditional square structure can be smoothly converted from or to the images on hexagonal structure. For accurate image processing, it is critical to best maintain the image resolution during the image conversion. In this paper, a bilinear interpolation algorithm that is used to convert an image from square structure to hexagonal structure is presented. Based on this, an edge detection method is proposed. Our experimental results show that the bilinear interpolation improves the edge detection accuracy. © 2007 IEEE.

He, X, Jia, W, Wu, Q & Hintz, T 1970, 'Advances in Grid and Pervasive Computing', Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), International Conference on Grid and Pervasive Computing, Springer Berlin Heidelberg, Paris, France, pp. 751-756.
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This paper presents an edge detection method based on bilateral filtering taking into account both spatial closeness and intensity similarity of pixels in order to preserve important visual cues provided by edges and reduce the sharpness of transitions in intensity values as well. In addition, the edge detection method proposed in this paper is achieved on sampled images represented on a newly developed virtual hexagonal structure. Due to the compact and circular nature of the hexagonal lattice, a better quality edge map is obtained. We also present a parallel implementation for edge detection on the virtual hexagonal structure that significantly increases the computation speed. © Springer-Verlag Berlin Heidelberg 2007.

He, X, Li, J, Chen, Y, Wu, Q & Jia, W 1970, 'Local Binary Patterns for Human Detection on Hexagonal Structure', Ninth IEEE International Symposium on Multimedia (ISM 2007), Ninth IEEE International Symposium on Multimedia (ISM 2007), IEEE, Taichung, Taiwan, pp. 65-71.
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Local Binary Pattern (LBP) was designed and has been widely used for efficient texture classification. LBP provides a simple and effective way to represent texture patterns. Uniform LBPs play an important role for LBP-based pattern/object recognition as they include majority of LBPs. On the other hand, Human detection based on Mahalanobis Distance Map (MDM) recognizes appearance of human based on geometrical structure. Each MDM shows a clear texture pattern that can be classified using LBPs. In this paper, we compute LBPs of MDMs on a hexagonal structure. The circular pixel arrangement in hexagonal structure results in higher accuracy for LBP representation than on square structure. Chi-square as a measure is used for human detection based on uniform LBPs obtained. We show that our method using LBPs built on MDMs has a higher human detection rate and a lower false positive rate compared to the method merely based on MDMs. We will also show using experimental results that LBPs on hexagonal structure lead to more robust human classification.

He, X, Li, J, Jia, W, Wu, Q & Hintz, T 1970, 'Local Binary Patterns on Hexagonal Image Structure', 7th IEEE International Conference on Computer and Information Technology (CIT 2007), 7th IEEE International Conference on Computer and Information Technology (CIT 2007), IEEE, Aizu-Wakamatsu City, Fukushima, Japan, pp. 639-644.
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Local binary pattern (LBP) was designed and widely used for efficient texture classification. It has been used for face recognition and has potential applications in many other research areas such as human detection. LBP provides a simple and effective way to represent patterns. Uniform LBPs play an important role for LBP-based pattern /object recognition as they include majority of LBPs. In this paper, we present LBP codes on hexagonal image structure. We show that LBPs defined on hexagonal structure have higher percentages of uniform LBPs that will lead to a more efficient and accurate recognition scheme for image classification.

He, X, Wu, Q, Zhang, H & Hintz, T 1970, 'A trend for face recognition', Fourth International Conference on Information Technology and Applications, ICITA 2007, International Conference on Information Technology and Applications, Macquarie Scientific Publishing, Harbin, China, pp. 254-257.
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Face recognition has many applications in law enforcement, crowd surveillance, security access control and human computer interaction. However, the applications have been, greatly constrained by the limitations of the currently available recognition tools because these tools are either too slow, sensitive to pose, illumination and facial expression, or too expensive, and hence are impractical. Face recognition is difficult and still has a long way to go before it really becomes practical. The aim of this paper is to present how a system for real-time, robust and inexpensive face recognition may be approached. The system contains the following components: Low cost CCTV video cameras or simple digital, cameras to quickly locate faces on 2D face images captured. A constructor of 3D face images using the captured 2D images. Algorithms that accurately match the constructed 3D face images to the 2D face images preciously existing in a gallery in real-time for pose and illumination invariant face recognition.

Hussain, FK, Chang, E & Hussain, OK 1970, 'State of the art review of the existing bayesian-network based approaches to trust and reputation computation', Second International Conference on Internet Monitoring and Protection (ICIMP 2007), Second International Conference on Internet Monitoring and Protection (ICIMP 2007), IEEE, pp. 26-30.
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In this paper we present a state of the art review of the bayesian-network based approaches for trust and reputation computation. We divide the bayesian network based approaches for trust and reputation computation into four different classes. Each of the four different classes is discussed in this paper. © 2007 IEEE.

Hussain, FK, Hussain, OK & Chang, E 1970, 'An overview of the interpretations of trust and reputation', 2007 IEEE Conference on Emerging Technologies & Factory Automation (EFTA 2007), 2007 IEEE Conference on Emerging Technologies & Factory Automation (EFTA 2007), IEEE, pp. 826-830.
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In this paper we present an overview of the definitions of the terms of trust and reputation from the literature. Trust and reputation have been defined in different ways by the various researchers. As a result of these various definitions of trust and reputation there is a lot of confusion regarding what these terms actually mean. Additionally in the literature there is no work towards collecting all the definitions of trust and reputation. In this paper we discuss and present an overview of the terms of trust and reputation from the literature. © 2007 IEEE.

Jia, W, He, S, Zhang, H & Wu, Q 1970, 'Combining Edge and Colour Information for Number Plate Detection', Proceedings of Image and Vision Computing New Zealand 2007, Image and Vision Computing Conference, Image and Vision Computing New Zealand, Hamilton, New Zealand, pp. 227-232.
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This paper presents a method for vehicle number plate detection which combines edge and colour features of number plates. We concentrate on two key issues of this application: speed and robustness. Our focus is put on detecting parts of a number plate, instead of the number plate itself as a whole. To achieve the target of real-time detection, two simple features based on a rede¯ned vertical edge map are constructed. To address the illumination-sensitive problem of using colour information, a Gaussian weighted histogram intersection (GWHI) method is proposed. The above new ideas compose the major part of the algorithm. Our experimental results demonstrate a promising preliminary result on detecting yellow number plates in terms of detection speed and robustness, which shows the feasibility of the proposed method.

Jia, W, Tien, D, He, X, Hope, BA & Wu, Q 1970, 'Advances in Visual Information Systems', Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), International Conference on Visual Information Systems, Springer Berlin Heidelberg, Shanghai, China, pp. 478-489.
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Developing a spatial searching tool to enhance the search car pabilities of large spatial repositories for Geographical Information System (GIS) update has attracted more and more attention. Typically, objects to be detected are represented by many local features or local parts. Testing images are processed by extracting local features which are then matched with the object's model image. Most existing work that uses local features assumes that each of the local features is independent to each other. However, in many cases, this is not true. In this paper, a method of applying the local cooccurring patterns to disclose the cooccurring relationships between local features for object detection is presented. Features including colour features and edge-based shape features of the interested object are collected. To reveal the cooccurring patterns among multiple local features, a colour cooccurrence histogram is constructed and used to search objects of interest from target images. The method is demonstrated in detecting swimming pools from aerial images. Our experimental results show the feasibility of using this method for effectively reducing the labour work in finding man-made objects of interest from aerial images. © Springer-Verlag Berlin Heidelberg 2007.

Jilian, Z, Shichao, Z, Xiaofeng, Z, Xindong, W & Chengqi, Z 1970, 'Measuring the uncertainty of differences for contrasting groups', Proceedings of the National Conference on Artificial Intelligence, National Conference of the American Association for Artificial Intelligence, AAAI Press, Vancouver, Canada, pp. 1920-1921.
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In this paper, we propose an empirical likelihood (EL) based strategy for building confidence intervals for differences between two contrasting groups. The proposed method can deal with the situations when we know little prior knowledge about the two groups, which are referred to as non-parametric situations. We experimentally evaluate our method on UCI datasets and observe that proposed EL based method outperforms other methods. Copyright © 2007, Association for the Advancement of Artificial Intelligence(www.aaai.org). All rights reserved.

Kazienko, P & Musiał, K 1970, 'Assessment of Personal Importance Based on Social Networks', MICAI 2007: ADVANCES IN ARTIFICIAL INTELLIGENCE, 6th Mexican International Conference on Artificial Intelligence (MICAI 2007), Springer Berlin Heidelberg, Aguascalientes, MEXICO, pp. 529-539.
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Kobayashi, M & Ito, T 1970, 'A Transactional Relationship Visualization System in Internet Auctions', 2007 IEEE/WIC/ACM International Conference on Intelligent Agent Technology (IAT'07), 2007 IEEE/WIC/ACM International Conference on Intelligent Agent Technology (IAT'07), IEEE, San Jose, pp. 72-75.
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Trading agents are very useful for developing and backtesting quality trading strategies for actions taking in the real world. However, the existing trading agent research mainly focuses on simulation using artificial data and market models. As a result, the actionable capability of developed trading strategies is often limited. In this paper, we analyze such constraints on developing actionable trading strategies for trading agents. These points are deployed into developing a series of trading strategies for trading agents through optimizing, and enhancing actionable trading strategies. We demonstrate working case studies in large-scale of market data. These approaches and their performance are evaluated from both technical and business perspectives.

Li, J & Hu, X 1970, 'Workshop BioDM'07 - An overview', Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 11th Pacific-Asia Conference on Knowledge Discovery and Data Mining, SPRINGER-VERLAG BERLIN, Nanjing, PEOPLES R CHINA, pp. 110-111.
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This edited volume contains the papers selected for presentation at the Second Workshop on Data Mining for Biomedical Applications (BioDM'07) held in Nanjing, China on 22nd of May 2007. The workshop was held in conjunction with the 11th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2007), a leading international conference in the areas of data mining and knowledge discovery. The aim of this workshop was to provide a forum for discussing research topics related to biomedical applications where data mining techniques were found to be necessary and/or useful. © Springer-Verlag Berlin Heidelberg 2007.

Macaš, M, Gabrys, B, Ruta, D & Lhotská, L 1970, 'Particle Swarm Optimisation of Multiple Classifier Systems', COMPUTATIONAL AND AMBIENT INTELLIGENCE, 9th International Work-Conference on Artificial Neural Networks, Springer Berlin Heidelberg, San Sebastian, SPAIN, pp. 333-340.
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Madden, C & Piccardi, M 1970, 'A framework for track matching across disjoint cameras using robust shape and appearance features', 2007 IEEE Conference on Advanced Video and Signal Based Surveillance, 2007 IEEE Conference on Advanced Video and Signal Based Surveillance, IEEE, London, UK, pp. 188-193.
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This paper presents a framework based on robust shape and appearance features for matching the various tracks generated by a single individual moving within a surveillance system. Each track is first automatically analysed in order to detect and remove the frames affected by large segmentation errors and drastic changes in illumination. The object's features computed over the remaining frames prove more robust and capable of supporting correct matching of tracks even in the case of significantly disjointed camera views. The shape and appearance features used include a height estimate as well as illumination-tolerant colour representation of the individual's global colours and the colours of the upper and lower portions of clothing. The results of a test from a real surveillance system show that the combination of these four features can provide a probability of matching as high as 91 percent with 5 percent probability of false alarms under views which have significantly differing illumination levels and suffer from significant segmentation errors in as many as 1 in 4 frames. © 2007 IEEE.

Madden, C & Piccardi, M 1970, 'Detecting Major Segmentation Errors for a Tracked Person Using Colour Feature Analysis', 14th International Conference on Image Analysis and Processing (ICIAP 2007), 14th International Conference on Image Analysis and Processing (ICIAP 2007), IEEE, Modena, ITALY, pp. 524-+.
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Madden, C, Piccardi, M & Zuffi, S 1970, 'Comparison of Techniques for Mitigating the Effects of Illumination Variations on the Appearance of Human Targets', Lecture Notes in Computer Science vol.4842,Advances in Visual Computing, International Symposium on Visual Computing, Springer Berlin Heidelberg, Lake Tahoe, USA, pp. 116-127.
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Several techniques have been proposed to date to build colour invariants between camera views with varying illumination conditions. In this paper, we propose to improve colour invariance by using data-dependent techniques. To this aim, we compare the effectiveness of histogram stretching, illumination filtration, full histogram equalisation and controlled histogram equalisation in a video surveillance domain. All such techniques have limited computational requirements and are therefore suitable for real time implementation. Controlled histogram equalisation is a modified histogram equalisation operating under the influence of a control parameter [1]. Our empirical comparison looks at the ability of these techniques to make the global colour appearance of single human targets more matchable under illumination changes, whilst still discriminating between different people. Tests are conducted on the appearance of individuals from two camera views with greatly differing illumination conditions and invariance is evaluated through a similarity measure based upon colour histograms. In general, our results indicate that these techniques improve colour invariance; amongst them, full and controlled equalisation consistently showed the best performance.

Madden, CS & Piccardi, M 1970, 'Detecting Major Segmentation Errors for a Tracked Person Using Colour Feature Analysis', Proceedings of 14th International Conference on Image Analysis and Processing 2007, International Conference on Image Analysis and Processing, IEEE Computer Society, Modena, Italy, pp. 524-529.
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This paper presents a method to identify frames with significant segmentation errors in an individuals track by analysing the changes in appearance and size features along the frame sequence. The features used and compared include global colour histograms, local histograms and the bounding box size. Experiments were carried out on 26 tracks from 4 different people across two cameras with differing illumination conditions. By fusing two local colour features with a global colour feature, probabilities of segmentation error detection as high as 83 percent of human expert-identified major segmentation errors are achieved with false alarm rates of only 3 percent. This indicates that the analysis of such features along a track can be useful in the automatic detection of significant segmentation errors. This can improve the final results of many applications that wish to use robust segmentation results from a tracked person.

McCracken, J, Schwartz, J, Mittleman, M, Ryan, L, Diaz Artiga, A & Smith, KR 1970, 'Biomass smoke exposure and acute lower respiratory infections among Guatemalan children', EPIDEMIOLOGY, 19th Annual Conference of the International-Society-for-Environmental-Epidemiology, LIPPINCOTT WILLIAMS & WILKINS, Mexico City, MEXICO, pp. S185-S185.

Merigó, JM & Gil-Lafuente, AM 1970, 'The induced generalized OWA operator', New Dimensions in Fuzzy Logic and Related Technologies - Proceedings of the 5th EUSFLAT 2005 Conference, 5th Conference of the European-Society-for-Fuzzy-Logic-and-Technology, UNIV OSTRAVA, Ostrava, CZECH REPUBLIC, pp. 463-470.
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We study different types of aggregation operators. We focus on the generalized OWA (GOWA) operator developed by Yager which represents a generalization to a wide range of aggregation operators. We distinguish between aggregations with a descending or with an ascending order. We introduce the induced generalized OWA (IGOWA) operator which represents an extension to the GOWA operator. It generalizes a wider range of aggregation operators as the GOWA operator is a particular case of this type of generalization. We study its main properties and some particular cases obtained with it. Finally, we develop a further generalization to the IGOWA operator by using quasi-arithmetic means.

Missmer, SA, Pearson, KR, Ryan, LM, Meeker, JD, Cramer, DW & Hauser, R 1970, 'Methodologic issues and statistical approaches to the analysis of multiple cycle data from couples undergoing in vitro fertilization (IVF).', FERTILITY AND STERILITY, 63rd Annual Meeting of the American-Society-for-Reproductive-Medicine, ELSEVIER SCIENCE INC, Washington, DC, pp. S123-S123.
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Morara, M, Ryan, L, Houseman, A & Strauss, W 1970, 'Optimal design for epidemiological studies subject to designed missingness', LIFETIME DATA ANALYSIS, Conference on Statistical Methods for Emerging Issues in Observational Studies and Epidemiology, Springer, Seattle, WA, pp. 583-605.
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In large epidemiological studies, budgetary or logistical constraints will typically preclude study investigators from measuring all exposures, covariates and outcomes of interest on all study subjects. We develop a flexible theoretical framework that in

Otoom, AF, Gunes, H & Piccardi, M 1970, 'Towards Automatic Abandoned Object Classification in Visual Surveillance Systems', Proceedings of Asia-Pacific Workshop 2007 on Visual Information Processing, Asia-Pacific Workshop on Visual Information Processing, National Cheng Kung University, Tainan, Taiwan, pp. 143-149.
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One of the core components of any visual surveillance system is object classification, where detected objects are classified into different categories of interest. Although in airports or train stations, abandoned objects are mainly luggage or trolleys, none of the existing works in the literature have attempted to classify or recognize trolleys. In this paper, we analyze and classify images of trolleys, bags, persons, and groups of people by using various shape features. We conducted a set of experiments with a number of uncluttered (images collected from the Internet with clear background) and cluttered images (images segmented out from the background in real videos) using various criteria. Our experimental results show that the features extracted enable 100% recognition accuracy for the trolley category. For our four-class object recognition problem, we achieved an overall recognition accuracy of 83.3% and an average false positive rate of 6%.

Ou, Y, Cao, L, Yu, T & Zhang, C 1970, 'Detecting Turning Points of Trading Price and Return Volatility for Market Surveillance Agents', 2007 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology - Workshops, 2007 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology - Workshops, IEEE, pp. 491-494.
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Trading agent concept is very useful for trading strategy design and market mechanism design. In this paper, we introduce the use of trading agent for market surveillance. Market surveillance agents can be developed for market surveillance officers and management teams to present them alerts and indicators of abnormal market movements. In particular, we investigate the strategies for market surveillance agents to detect the impact of company announcements on market movements. This paper examines the performance of segmentation on the time series of trading price and return volatility, respectively. The purpose of segmentation is to detect the turning points of market movements caused by announcements, which are useful to identify the indicators of insider trading. The experimental results indicate that the segmentation on the time series of return volatility outperforms that on the time series of trading price. It is easier to detect the turning points of return volatility than the turning points of trading price. The results will be used to code market surveillance agents for them to monitor abnormal market movements before the disclosure of market sensitive announcements. In this way, the market surveillance agents can assist market surveillance officers with indicators and alerts. © 2007 IEEE.

Ou, Y, Cao, L, Yu, T & Zhang, C 1970, 'Detecting Turning Points of Trading Price and Return Volatility for Market Surveillance Agents', 2007 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology - Workshops, 2007 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology - Workshops, IEEE, Fremont, CA, pp. 491-+.
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Trading agent concept is very useful for trading strategy design and market mechanism design. In this paper, we introduce the use of trading agent for market surveillance. Market surveillance agents can be developed for market surveillance officers and management teams to present them alerts and indicators of abnormal market movements. In particular, we investigate the strategies for market surveillance agents to detect the impact of company announcements on market movements. This paper examines the performance of segmentation on the time series of trading price and return volatility, respectively. The purpose of segmentation is to detect the turning points of market movements caused by announcements, which are useful to identify the indicators of insider trading. The experimental results indicate that the segmentation on the time series of return volatility outperforms that on the time series of trading price. It is easier to detect the turning points of return volatility than the turning points of trading price. The results will be used to code market surveillance agents for them to monitor abnormal market movements before the disclosure of market sensitive announcements. In this way, the market surveillance agents can assist market surveillance officers with indicators and alerts.

Paisitkriangkrai, S, Shen, C & Zhang, J 1970, 'An Experimental Evaluation of Local Features for Pedestrian Classification', 9th Biennial Conference of the Australian Pattern Recognition Society on Digital Image Computing Techniques and Applications (DICTA 2007), 9th Biennial Conference of the Australian Pattern Recognition Society on Digital Image Computing Techniques and Applications (DICTA 2007), IEEE, Glenelg, SA, pp. 53-60.
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The ability to detect pedestrians is a first important step in many computer vision applications such as video surveillance. This paper presents an experimental study on pedestrian detection using state-of-the-art local feature extraction and support vec

Pérez, Ó, Piccardi, M, García, J & Molina, JM 1970, 'Comparison of Classifiers for Human Activity Recognition', Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), International Work-Conference on the Interplay, Springer Berlin Heidelberg, La Manga del Mar Menor, Spain, pp. 192-201.
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The human activity recognition in video sequences is a field where many types of classifiers have been used as well as a wide range of input features that feed these classifiers. This work has a double goal. First of all, we extracted the most relevant features for the activity recognition by only utilizing motion features provided by a simple tracker based on the 2D centroid coordinates and the height and width of each person's blob. Second, we present a performance comparison among seven different classifiers (two Hidden Markov Models (HMM), a J.48 tree, two Bayesian classifiers, a classifier based on rules and a Neuro-Fuzzy system). The video sequences under study present four human activities (inactive, active, walking and running) that have been manual labeled previously. The results show that the classifiers reveal different performance according to the number of features employed and the set of classes to sort. Moreover, the basic motion features are not enough to have a complete description of the problem and obtain a good classification. © Springer-Verlag Berlin Heidelberg 2007.

Pérez, Ó, Piccardi, M, García, J, Patricio, MÁ & Molina, JM 1970, 'Comparison Between Genetic Algorithms and the Baum-Welch Algorithm in Learning HMMs for Human Activity Classification', Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Evo Workshops, Springer Berlin Heidelberg, Valencia, Spain, pp. 399-406.
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A Hidden Markov Model (HMM) is used as an efficient and robust technique for human activities classification. The HMM evaluates a set of video recordings to classify each scene as a function of the future, actual and previous scenes. The probabilities of transition between states of the HMM and the observation model should be adjusted in order to obtain a correct classification. In this work, these matrixes are estimated using the well known Baum-Welch algorithm that is based on the definition of the real observations as a mixture of two Gaussians for each state. The application of the GA follows the same principle but the optimization is carried out considering the classification. In this case, GA optimizes the Gaussian parameters considering as a fitness function the results of the classification application. Results show the improvement of GA techniques for human activities recognition. © Springer-Verlag Berlin Heidelberg 2007.

Piccardi, M & Perez, O 1970, 'Hidden Markov Models with Kernel Density Estimation of Emission Probabilities and their Use in Activity Recognition', 2007 IEEE Conference on Computer Vision and Pattern Recognition, 2007 IEEE Conference on Computer Vision and Pattern Recognition, IEEE, Minneapolis, pp. 1-8.
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In this paper, we present a modified hidden Markov model with emission probabilities modelled by kernel density estimation and its use for activity recognition in videos. In the proposed approach, kernel density estimation of the emission probabilities is operated simultaneously with that of all the other model parameters by an adapted Baum-Welch algorithm. This allows us to retain maximum-likelihood estimation while overcoming the known limitations of mixture of Gaussions in modelling certain probability distributions. Experiments on activity recognition have been performed on groundtruthed data from the CAVIAR video surveillance database and reported in the paper. The error on the training and validation sets with kernel density estimation remains around 14-16% while for the conventional Gaussian mixture approach varies between 15 and 24%, strongly depending on the initial values chosen for the parameters. Overall, kernel density estimation proves capable of providing more flexible modelling of the emission probabilities and, unlike Gaussian mixtures, does not suffer from being highly parametric and of difficult initialisation. © 2007 IEEE.

Piccardi, M & Perez, O 1970, 'Hidden Markov models with kernel density estimation of emission probabilities and their use in activity recognition', 2007 IEEE CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION, VOLS 1-8, IEEE Conference on Computer Vision and Pattern Recognition, IEEE, Minneapolis, MN, pp. 3774-+.

Riedel, S & Gabrys, B 1970, 'Dynamic Pooling for the Combination of Forecasts generated using Multi Level Learning', 2007 International Joint Conference on Neural Networks, 2007 International Joint Conference on Neural Networks, IEEE, Orlando, FL, pp. 454-+.
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Ruta, D & Gabrys, B 1970, 'Neural Network Ensembles for Time Series Prediction', 2007 International Joint Conference on Neural Networks, 2007 International Joint Conference on Neural Networks, IEEE, Orlando, FL, pp. 1204-1209.
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Ruta, D, Gabrys, B, Maroulis, G & Simos, TE 1970, 'Reducing Spatial Data Complexity for Classification Models', AIP Conference Proceedings, Computational Methods in Science and Engineering, AIP, Corfu, GREECE, pp. 603-613.
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Sahel, Z, Bouchachia, A, Gabrys, B & Rogers, P 1970, 'Adaptive Mechanisms for Classification Problems with Drifting Data', KNOWLEDGE-BASED INTELLIGENT INFORMATION AND ENGINEERING SYSTEMS: KES 2007 - WIRN 2007, PT II, PROCEEDINGS, 11th International Conference on Knowledge-Based Intelligent Informational and Engineering Systems/17th Italian Workshop on Neural Networks, Springer Berlin Heidelberg, Vietri sul Mare, ITALY, pp. 419-426.
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Sijun Lu, Jian Zhang & David Feng 1970, 'An efficient method for detecting ghost and left objects in surveillance video', 2007 IEEE Conference on Advanced Video and Signal Based Surveillance, 2007 IEEE Conference on Advanced Video and Signal Based Surveillance, AVSS 2007, IEEE, London, pp. 540-545.
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This paper proposes an efficient method for detecting ghost and left objects in surveillance video, which, if not identified, may lead to errors or wasted computation in background modeling and object tracking in surveillance systems. This method contain

Stoianoff, NP 1970, 'Economic Incentives for Ecological Gifts: A comparison of conservation covenant incentives in Australia and Canada', 19th Annual Australasian Tax Teachers Association Conference, TC Bernie School of Law, University of Queensland.

Stoianoff, NP 1970, 'Environmental Fiscal Instruments and the Development of the Environmental Management Services Industry in Australia', Eighth Annual Global Conference on Environmental Tax, Munich, Germany.

Vellaisamy, K & Li, J 1970, 'Multidimensional Decision Support Indicator (mDSI) for Time Series Stock Trend Prediction', ADVANCES IN KNOWLEDGE DISCOVERY AND DATA MINING, PROCEEDINGS, 11th Pacific-Asia Conference on Knowledge Discovery and Data Mining, Springer Berlin Heidelberg, Nanjing, PEOPLES R CHINA, pp. 841-848.
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Wang, JC-P, Abolhasan, M, Franklin, DR, Safaei, F & Lipman, J 1970, 'On Separating Route Control and Data Flows in Multi-radio Multi-hop Ad Hoc Network.', ICON, IEEE International Conference on Networks, IEEE, Adelaide, Australia, pp. 19-24.
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Ad hoc networks typically require a significant amount of routing and control information to be distributed in a timely and reliable manner throughout the network, particularly in dynamic environments. As traffic levels increase and the network becomes more heavily congested, there is an increased probability that these critical packets are lost, resulting in obsolete control information being used to make important decisions. This would further compound the problem of network congestion and lead to a very rapid loss of connectivity and throughput. Given this, we argue the solutions to these problems should not rely on putting extra bandwidth on a radio interface. Instead, we should exploit the use of multiple radios to ensure the route can be firmly established. In this paper, we propose a multi-radio solution which reserves one radio channel exclusively for routing. Our simulation results have demonstrated that using a separate radio for routing protocol would dramatically improve reliability in heavily loaded ad hoc wireless networks, thereby effectively alleviating the impact of network congestion. © 2007 IEEE.

Wang, JC-P, Abolhasan, M, Franklin, DR, Safaei, F, Lipman, J & IEEE 1970, 'On separating route control and data flows in multi-radio multi-hop ad hoc network', 2007 15TH IEEE INTERNATIONAL CONFERENCE ON NETWORKS, 15th IEEE International Conference on Networks, IEEE, Adelaide, AUSTRALIA, pp. 114-119.
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Wu, Q, Wang, L, Geng, X, Li, M & He, S 1970, 'Dynamic Biometrics Fusion at Feature Level for Video-Based Human Recognition', Proceedings of Image and Vision Computing New Zealand 2007, Image and Vision Computing Conference, Image and Vision Computing New Zealand, Hamilton, New Zealand, pp. 152-157.

Xiaofeng, Z, Shichao, Z, Jilian, Z & Chengqi, Z 1970, 'Cost-sensitive imputing missing values with ordering', Proceedings of the National Conference on Artificial Intelligence, National Conference of the American Association for Artificial Intelligence, AAAI Press, Vancouver, Canada, pp. 1922-1923.
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Various approaches for dealing with missing data have been developed so far. In this paper, two strategies are proposed for cost-sensitive iterative imputing missing values with optimal ordering. Experimental results demonstrate that proposed strategies outperform the existing methods in terms of imputation cost and accuracy. Copyright © 2007, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved.

Xu, J, Ye, G & Zhang, J 1970, 'Long-term Trajectory Extraction for Moving Vehicles', 2007 IEEE 9th Workshop on Multimedia Signal Processing, 2007 IEEE 9th Workshop on Multimedia Signal Processing, IEEE, Chania, GREECE, pp. 223-226.
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Xu, Z, Zhang, C, Zhang, S, Song, W & Yang, B 1970, 'Efficient Attribute Reduction Based on Discernibility Matrix', Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Rough Sets and Knowledge Technology, Springer Berlin Heidelberg, Canada, pp. 13-21.
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To reduce the time complexity of attribute reduction algorithm based on discernibility matrix, a simplified decision table is first introduced, and an algorithm with time complexity O(| C ∥ U |) is designed for calculating the simplified decision table. And then, a new measure of the significance of an attribute is defined for reducing the search space of simplified decision table. A recursive algorithm is proposed for computing the attribute significance that its time complexity is of 0(|U/C|). Finally, an efficient attribute reduction algorithm is developed based on the attribute significance. This algorithm is equal to existing algorithms in performance and its time complexity is O(| C ∥r U |) +O(| C |2| / C |). © Springer-Verlag Berlin Heidelberg 2007.

Yang, J & Zhang, J 1970, 'Offline Swimmer Cap Tracking Using Trajectory Interpolation', 9th Biennial Conference of the Australian Pattern Recognition Society on Digital Image Computing Techniques and Applications (DICTA 2007), 9th Biennial Conference of the Australian Pattern Recognition Society on Digital Image Computing Techniques and Applications (DICTA 2007), IEEE, pp. 579-585.
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In this paper, we present a preliminary attempt to solve the difficult problem of tracking swimmer cap in swimming videos to facilitate swimmer performance assessment. Due to the great challenges posed by moving camera and severe figure-background occlusions, an offline approach based on trajectory interpolation is adopted. Firstly, each frame is searched for hypothesized positions of the target cap using mean shift mode seeking. Secondly, most outliers due to ambiguities and noise are eliminated using lane constraints, and the hypothesis in the space-time volume are clustered into trajectory segments based on a spatial and temporal closeness criteria. Finally, cubic spline trajectory interpolation is used to infer the target cap position in occluded frames. Experiments show that satisfying tracking results are achieved by our approach. © 2007 IEEE.

Zhang, C, Zhu, X, Zhang, J, Qin, Y & Zhang, S 1970, 'GBKII: An Imputation Method for Missing Values', Advances in Knowledge Discovery and Data Mining, Pacific-Asia Conference on Knowledge Discovery and Data Mining, Springer Berlin Heidelberg, Nanjing, China, pp. 1080-1087.
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Missing data imputation is an actual and challenging issue in machine learning and data mining. This is because missing values in a dataset can generate bias that affects the quality of the learned patterns or the classification performances. To deal with this issue, this paper proposes a Grey-Based K-NN Iteration Imputation method, called GBKII, for imputing missing values. GBKII is an instance-based imputation method, which is referred to a non-parametric regression method in statistics. It is also efficient for handling with categorical attributes. We experimentally evaluate our approach and demonstrate that GBKII is much more efficient than the k-NN and mean-substitution methods.

Zhang, S, Zhu, X, Zhang, J & Zhang, C 1970, 'Cost-Time Sensitive Decision Tree with Missing Values', Knowledge Science, Engineering and Management, International Conference on Knowledge Science, Engineering and Management, Springer Berlin Heidelberg, Melboure, pp. 447-459.
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Cost-sensitive decision tree learning is very important and popular in machine learning and data mining community. There are many literatures focusing on misclassification cost and test cost at present. In real world application, however, the issue of time-sensitive should be considered in cost-sensitive learning. In this paper, we regard the cost of time-sensitive in cost-sensitive learning as waiting cost (referred to WC), a novelty splitting criterion is proposed for constructing cost-time sensitive (denoted as CTS) decision tree for maximal decrease the intangible cost. And then, a hybrid test strategy that combines the sequential test with the batch test strategies is adopted in CTS learning. Finally, extensive experiments show that our algorithm outperforms the other ones with respect to decrease in misclassification cost.

Zhang, Y & Xu, G 1970, 'On web communities mining and analysis', 3rd International Conference on Semantics, Knowledge, and Grid, SKG 2007, Third International Conference on Semantics, Knowledge and Grid (SKG 2007), IEEE, Shan Xi, China, pp. 20-25.
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Due to the lack of a uniform schema for web documents and the sheer amount and dynamics of web data, both the effectiveness and the efficiency of information management and retrieval of web data is often unsatisfactory when using conventional data management and searching techniques. To address this issue, we have adopted web mining and web community analysis approaches. Based on the analysis of web document contents, hyperlinks analysis, user access logs and semantic analysis, we have developed various approaches or algorithms to construct and analyze web communities, and to make recommendations. This paper will introduce and discuss various approaches on web community mining and recommendation. © 2007 IEEE.

Zhang, Z & Piccardi, M 1970, 'A review of tracking methods under occlusions', Proceedings of IAPR Conference on Machine Vision Applications, MVA 2007, Machine Vision Applications, Institute of Industrial Science, The University of Tokyo, Tokyo, Japan, pp. 146-149.
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Object tracking in computer vision refers to the task of tracking individual moving objects accurately from one frame to another in an image sequence. Several tracking methods have been proposed in the recent literature capable of coping with a certain degree of occlusions of the objects. However, no comparative analysis of such methods has been presented to date and both the expert and the newcomer to this area may be confused about the relative effectiveness of each method when compared under the same level of complexity of the dynamic scene. In order to fulfill this need, this paper proposes a set of analysis criteria and provides a comparative review of the main recent tracking methods, in particular with respect to their capability of tracking objects under occlusions.

Zhao, Y, Zhang, H, Figueiredo, F, Cao, L & Zhang, C 1970, 'Mining for combined association rules on multiple datasets', Proceedings of the 2007 international workshop on Domain driven data mining, KDD07: The 13th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, ACM, San Jose, USA, pp. 18-23.
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Many organisations have their digital information stored in a distributed systems structure scheme, be it in different locations, using vertically and horizontally distributed repositories, which brings about an high level of complexity to data mining. From a classical data mining view, where the algorithms expect a denormalised structure to be able to operate on, heterogeneous data sources, such as static demographic and dynamic transactional data are to be manipulated and integrated to the extent commercial association rules algorithms can be applied. Bearing in mind the usefulness and understandability of the application from a business perspective, combined rules of multiple patterns derived from different repositories, containing historical and point in time data, were used to produce new techniques in association mining applied to debt recovery. Initially debt repayment patterns were discovered using transactional data and class labels defined by domain expertise, then demographic patterns were attached to each of the class labels. After combining the patterns, two type of rules were discovered leading to different results: 1) same demographic pattern with different repayment patterns, and 2) same repayment pattern with different demographic patterns. The rules produced are interesting, valuable, complete and understandable, which shows the applicability and effectiveness of the new method.

Zheng, L, He, S, Wu, Q & Hintz, TB 1970, 'Number Plate Recognition without Segmentation', Proceedings of Image and Vision Computing New Zealand 2007, Image and Vision Computing Conference, Image and Vision Computing New Zealand, Hamilton, New Zealand, pp. 164-168.

Gorodetsky, V, Chengqi, Z, Skormin, V & Longbing, C 2007, 'Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics): Preface'.