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this research focuses on presenting an empirical method to gather necessary data and then developing several models to predict the chance of diabetic retinopathy (proliferative and non-proliferative) by observing HbA1c, duration of disease and albumin excretion rate of diabetic patients. We gathered required knowledge fromother studies that have investigated the relation of different risk factors and complications in diabetes. In order to create 1-1 models, curve fitting was performed by using two different software applications: Tiberius and SPSS which work based on ANN And least square regression, respectively. To start producing the model, seven different patterns ie linear, logarithmic, quadratic, cubic, power, s and exponential have been chosen as the best regression options. Using R-squared it can be clearly seen that the best selected regression models fit the data in all the dataset tables better than ANN< as well as the other six regression patterns.

Lattice Quantum Chromodynamics is used to investigate the behavior of quarks under the influence of the Strong Nuclear force. The computer implementation requires the solution of square sparse matrices with the number of rows up to the lOO's of millions, and this represents the major computational factor with regards to overall runtime. In this paper we present verification of an algorithm that grows only linearly with respect to matrix size in terms of the computing resources required. Once realistically sized calculations can be done on commonly available hardware, this opens the door to the investigation of quantum fields in other areas such as condensed matter physics and nanotechnology.

Electronic Commerce has been a very significant commercial phenomenon in recent years, and autonomous agents are widely adopted by business or individuals in electronic marketplaces to fulfill time consuming tasks in trading. Agent negotiation mechanisms are usually applied between conflicted agents in order to reach a mutually beneficial agreement. Prediction of trading agents' strategies and behaviours in negotiation is a very significant research topic in agent negotiation. By employing the prediction results on opponents' possible strategies and behaviours during a negotiation, trading agents can plan and perform corresponding strategies in order to maximize their own profits. Significant achievements have been made on this topic. However, most existing approaches are based on machine learning mechanisms, which may fail to capture opponents' behaviours in open and dynamic electronic marketplaces. In this paper, two agent behaviour expectation approaches are introduced to help trading agents to capture opponents' potential behaviours during a negotiation in complex e-marketplaces. (i) The regression analysis approach focuses on illustrating the main trends of opponents' trading behaviours; (ii) the vector analysis approach pays more attention to identifying opponents' detailed negotiation strategies. The experimental results show the efficiency and efficacy of the two proposed approaches in open and dynamic negotiation environments.

This paper explores the feasibility of incorporating personal digital assistants (PDAs) into problem-based learning (PBL) approach in medical education. Method: Database searched was conducted by using relevant keywords. From 1,317 relevant journal articles, 489 articles (37%) are related to the use of PDAs in medical settings, medical education and aspects regarding PDA use in both areas. The appropriate materials were input into NVivo 7 for analysis. Results: Five PDA functionalities (clinical-log, reference, personal information management, communication and special functions) and 8 factors (data security and information privacy, interoperability, scalability and network connectivity, education and training, technology comfort, electromagnetic interference, social acceptance, and maintenance and support) for the incorporation of PDAs into PBL-medical curriculum were identified. Conclusion: A little is known whether PDAs can be incorporate at the beginning of medical study in particular to a PBL-medical curriculum at the University of Wollongong (UOW). Therefore the further study is to determine whether PDAs, their functionalities and influence factors are feasible to deploy into medical education and how possible they can be incorporated to medical education at the UOW.

Diabetes as an unprecedented epidemic is spreading all around the world. While one in every seven health care dollars in USA is spent on diabetes, 60% of direct costs and almost 80-90% of indirect costs of that are related to diabetic complications. The ultimate aim of this study is to develop a rule-based model for advising the risk of chronic diabetic complications. An extensive literature review has been carried out to gather actual knowledge about diabetic complications and their related predisposing factors. NViv08 is used to organize and categorize the acquired knowledge. A rule-based decision support model is constructed from the obtained knowledge. CLIPS is used to represent and implement the rules and build a knowledge based decision support system.

The focus of this paper is twofold: firstly we make a case for the use of Computational Intelligence (CI) techniques in the modelling and/or prediction of global weather, CO2 emissions, climate change and similar endeavours. CI exploits processes found in Nature, albeit by way of software simulations on digital computers (i.e. in silico), and excel in particular at pattern recognition and/or classification. Moreover, they are characterized as being non-algorithmic, bottom-up, data-driven, and learn-by-example. The second focus of this paper is to propose the use of carbonrather than silicon-based computing, specifically in the form of DNA (or molecular) computing. Notwithstanding the unsolved difficulties with the latter (especially concerning Input/Output), its inherent massive parallelism has the potential to yield significant performance advantages. Finally, to come full circle, it could well eventuate that the inherent parallelism of DNA Computing could be brought to bear in the modelling/prediction endeavours mentioned previously.

The objective of this study is to understand the adoption of personal digital assistants (PDAs) in the problem-based learning (PBL) curriculum at the University of Wollongong (UOW). Therefore, the research question in this study is 'what are the appropriate strategies for the incorporation of PDAs into the UOW PBL-medical curriculum?' given the resource and financial implications, technology barriers, electromagnetic interference (EI), social acceptance and equity of learning medicine with and without PDA technology. In-depth interviews were designed and conducted with medical faculty members, educational technology specialists and honorary clinical academics. Six concerns and three strategies for the incorporation of PDAs into PBL- medical curriculum were identified. The strategy for the incorporation of PDAs into PBL-approach in medical education at the UOW could be considered as a guideline for the adoption of mobile technology in medical education elsewhere. 2010 Inderscience Enterprises Ltd.

We present a quantitative analysis on the effect of Rashba spinorbit interaction on the thermodynamic properties of two-dimensionalsemiconductors. Quantities such as the Helmholtz free energy, the electron internal energy, the electron entropy and the electron heatcapacity are calculated as a function of temperature and the spinorbit coupling strength. It is shown that the free energy decreases withthe spinorbit coupling while entropy increases with the spinorbit coupling. At the temperature of around 10% of Fermi temperature,the reduction of free energy due to Rashba coupling alone is round 15%.

This study focuses on pattern recognition in pathology data collected from patients tested for Chlamydia pneumoniae (Cp) infection, with co-infection by Mycoplasma pneumoniae (Myco) also considered. Both Cp and Myco are microbes that cause respiratory disease in some infected people. As well as the immunoassay results revealing whether the patient had been infected, or not, an extensive range of other routine pathology data was also available for each patient, allowing the analysis of associations between a positive immunoassay laboratory result for Cp or Myco, and a range of tests for biochemical and cellular markers (e.g. liver enzymes, electrolyte balance, haematological indices such as red/white cell counts). Decision trees and logistic regression were used to enhance laboratory diagnosis of these respiratory infections via the formulation of association rules derived from immunoassay results and associated pathology data.