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<p>Medical decision support systems are one of the main applications for data mining and machine learning techniques. Most of these systems involve solving a classification problem. Classification models can be generated by one of two types of learning classification algorithms: batch or incremental learning algorithms.</p> <p>A batch learning algorithm generates a classification model trained by using the complete available data. Examples of batch learning algorithms are: decision tree C4.5 and multilayer perceptron neural network algorithms. However, an incremental learning algorithm generates a classification model trained incrementally through batches of training data. Examples of this are Learn++ and DWMV Learn++. Incremental learning algorithms are effective in problems in the healthcare domain where the training data become available periodically over time or where the size of database is very large. In the health care system, we consider heart disease a major cause death, and thus, it is a domain requiring attention. Early screening of patients for heart disease before they actually have its symptoms could therefore be an effective solution for decreasing the risk of this disease. Classification techniques can be employed to recognize patients who are at high risk of developing heart disease in order to send them for further attention or treatment by specialists.</p> <p>This work proposes an incremental learning algorithm, called modified DWMV Learn++, for primary care decision support that classifies patients into high risk and low risk, based on certain risk factors. This system has been tested and proven to have good performance using real-world patient clinical records.</p> / Master of Science (MSc)

<p>While operating system concepts are taught to students in undergraduate programs in Computer Science, a student project involving the development of an operating system creates a difficult situation due to time and financial considerations. Using GPSS to simulate the behavior of a student-treated operating system can reduce these problems and serve as an effective learning device. Many features and concepts can be simulated that might otherwise be ignored in a student project. An implementation of a student-created operating system is discussed. Statistics collected from the GPSS simulated model are used to operating system.</p> / Master of Science (MS)

<p>This project documents the results of an investigation into binary search trees. Because of their favourable characteristics binary search trees have become popular for information storage and retrieval applications in a one level store. The trees may be of two types, weighted and unweighted. Various algorithms are presented, in a machine independent context, for both types and an empirical evaluation is performed. An important software aid used for graphically displaying a binary tree is also described.</p> / Master of Science (MS)

<p>A survey of printers and plotters is given, and in particular the operation and capabilities of electrostatic printer/Plotters is discussed. An implementation of a plotting system which plots on an electrostatic printer/plotter is presented. This plotting system is designed to be compatible with the Benson-Lehner plotting system. The standard "PLOT" routine is replaced by a two pass system, which generates plots on the printer/plotter. In addition to the plotting system, an implementation of a graph utility is presented. This utility provides a single one pass system that plots one or more functions (where the function has one value for each value of x.)</p> / Master of Science (MS)

<p>A critical survey of research done in automatic, indexing and classification and statistical linguistics, of importance to the study of bibliographic data bases, is given. A theory of measures of association in vector form is presented and applied using the FAMULUS system for storage and retrieval, and a data base in the social sciences constructed using that system. Certain conclusions are drawn regarding the usefulness of the various measures of association employed, and some argue of future research are given.</p> / Master of Science (MS)

<p>The purpose of this research was to develop a model which would aid in selecting the best systems development approach for supplying a decision maker with a computer based support system. The research proceeded in several stages. First a hierarchical model was developed. The "top" level of the model described situations in terms of four factors or meta-constructs; User Participation in the Decision Making Process, Problem Space Complexity, Resource Availability and Organizational Context. The set of factors was based on Churchman's systems theory and the organizational interaction represented by the Leavitt Diamond. In the "lower" level the factors were each described by a set of attributes. The list of attributes was based on a literature search, aided by a model developed by Ginzberg and Stohr. Next the model was validated in a three phase process. The first phase involved validation of the model structure and content. A normative group technique (Delphi method) was chosen to obtain expert consensus on both the factors and the attributes that defined them. The second phase of the validation aided in content validation of the lower level of the model and associated a factor value with each unique set of attribute levels. It consisted of two sets of case-based interviews. Two of the factors had been defined as managerial in nature and these interviews were conducted with senior administrative personnel. The other two factors had been defined as technical in nature and the subjects of these interviews had a systems background. The thrid phase of the research aided in content validation of the "top" level of the model and determined which approaches were preferred in which situations (unique set of factor values). It consisted of a set of case-based interviews with senior MIS personnel (including experienced academics) to assign the "best" or "preferred" approach to each of the situations (set of factor values). Based on the results of these studies we have shown that it is possible to define situations in terms of a hierarchically ordered set of attributes, for the purpose of determining how best to provide computer based support for the decision maker facing a particular situation.</p> / Doctor of Philosophy (PhD)

<p> The prosperity of the Internet has made it attractive to hackers and malicious attackers. Distributed attacks, such as: DDoS attacks and Internet worms have become major threats towards the network infrastructure. Collaborating existent single-point-deployed security applications over multi-domains for distributed defense is promising. Taking advantage of the small-world network model, a three-layered network modeling platform was developed for exploring behaviors of collaborative defense under the scope of a complex system. Using this platform, a comparison study between two major collaborative defense schemes was conducted. Their performance and eectiveness against signature-embedded worm attacks were evaluated accordingly. </p><p> Given the rapid evolution of attack methods and toolkits, software-based solutions to secure the network infrastructure have become overburdened. The performance gap between the execution speed of security software and the amount of data to be processed is ever widening. A common solution to close this performance gap is through hardware implementation of security functions. After a comprehensive survey on major recongurable hardware-based approaches application on network infrastructure security area, an optimized design of FPGA-based Power Spectral Density (PSD) data converter for online Shrew DDoS attack detection was proposed and prototyped. Combining an innovative component-reusable Auto-Correlation (AC) algorithm and the adapted 2N-point real-valued Discrete Fourier Transform (DFT) algorithm, a maximum reduction of 61.8% processing time from 27471.4 us to 10504.8 us was achieved. These ecient hardware realization enabled the implementation of this design to a Xilinx Virtex2 Pro FGPA. </p><p> The scalability issue against continuously expanding signature databases is another major impediment aecting hardware application for network intrusion detection. With the observation that signature patterns are constructed from combinations of a limited number of primary patterns, a two-stage decomposition approach was developed to solve this issue. The evaluation results show that a reduction in size of over 77% can be achieved on top of signature patterns extracted from the Snort rule database after decomposition.</p>