An essential task of university administration is to monitor the financial position of its auxiliary enterprises. This is an ill-defined and complex task which often requires more administrative time and information than is available. In order to perform this task in an adequate manner a large amount of expertise is required to: (1) determine what constitutes reasonable performance, (2) define unacceptable levels of performance, and (3) suggest courses of action which will alleviate an unacceptable situation. Thorough analysis requires a substantial amount of an expert’s time. The purpose of this research is to explore the opportunities for the enhancement of the financial analysis of auxiliary enterprises through the use of expert systems. The research has included: (1) a comprehensive review of analytical techniques that can be used in financial position analysis, (2) a determination of the the applicability of such techniques to auxiliary enterprises, and (3) an assessment of their amenability to expert system development. As a part of the above described research, an expert system prototype was developed which addresses several of the above issues for one auxiliary enterprise at Virginia Polytechnic Institute and State University. It integrates the knowledge of an expert with both accounting data from the VPI & SU accounting system and other types of data from the auxiliary enterprise operation. The system provides a comprehensive, systematic analysis of the financial position of the Tailor Shop at VPI & SU. This analysis is performed in much less time than would be required by an expert. As a result of the research conducted, it has been concluded that building such a system is possible and it can provide significant benefits to a user. However, financial position analysis requires a substantial amount of data and numerical calculations, both of which require large amounts of computer memory and computations. Therefore, designing an expert system to efficiently perform this task requires the use of a package or a language that efficiently utilizes computer memory and CPU. / Ph. D.

Thesis (M. Tech.) - Central University of Technology, Free State, 2009

This dissertation describes a research study conducted to determine the benefits and use of ontology technologies to support a simulation environment that evaluates countermeasures employed to protect military aircraft. Within the military, aircraft represent a significant investment and these valuable assets need to be protected against various threats, such as man-portable air-defence systems. To counter attacks from these threats, countermeasures are deployed, developed and evaluated by utilising modelling and simulation techniques. The system described in this research simulates real world scenarios of aircraft, missiles and countermeasures in order to assist in the evaluation of infra-red countermeasures against missiles in specified scenarios. Traditional ontology has its origin in philosophy, describing what exists and how objects relate to each other. The use of formal ontologies in Computer Science have brought new possibilities for modelling and representation of information and knowledge in several domains. These advantages also apply to military information systems where ontologies support the complex nature of military information. After considering ontologies and their advantages against the requirements for enhancements of the simulation system, an ontology was constructed by following a formal development methodology. Design research, combined with the adaptive methodology of development, was conducted in a unique way, therefore contributing to establish design research as a formal research methodology. The ontology was constructed to capture the knowledge of the simulation system environment and the use of it supports the functions of the simulation system in the domain. The research study contributes to better communication among people involved in the simulation studies, accomplished by a shared vocabulary and a knowledge base for the domain. These contributions affirmed that ontologies can be successfully use to support military simulation systems / Computing / M. Tech. (Information Technology)

This dissertation reports on an effort to design, construct, test, and adjust an expert system for making certain business decisions. A widely used approach to recurring judgmental decisions in business and other social organizations is the "rule-based decision system". This arrangement employs staff experts to propose decision choices and selections to a decisionmaker. Such decisions can be very important because of the large resources involved. Rules and values encountered in such systems are often vague and uncertain. Major questions explored by this experimental effort were: (1) could the output of such a decision system be mimicked easily by a mechanism incorporating the rules people say they use, and (2) could the imprecision endemic in such a system be represented by fuzzy set constructs. The task environment chosen for the effort was a computer-based game which required player teams to make a number of interrelated, recurring decisions in a realistic business situation. The primary purpose of this research is to determine the feasibility of using these methods in real decision systems. The expert system which resulted is a relatively complicated, feed-forward network of "simple" inferences, each with no more than one consequent and one or two antecedents. Rules elicited from an expert in the game or from published game instructions become the causal implications in these inferences. Fuzzy relations are used to represent imprecise rules and two distinctly different fuzzy set formats are employed to represent imprecise values. Once imprecision appears from the environment or rules the mechanism propagates it coherently through the inference network to the proposed decision values. The mechanism performs as well as the average human team, even though the strategy is relatively simple and the inferences crude linear approximations. Key aspects of this model, distinct from previous work, include: (1) the use of a mechanism to propose decisions in situations usually considered ill-structured; (2) the use of continuous rather than two-valued variables and functions; (3) the large scale employment of fuzzy set constructs to represent imprecision; and (4) use of feed forward network structure and simple inferences to propose human-like decisions.

The domain of molecular biology is complex and vast. Bio-ontologies and information visualisation have arisen in recent years as means to assist biologists in making sense of this information. Ontologies can enable the construction of conceptual queries, but existing systems to do this are too technical for most biologists. OntoDas, the software developed as part of this thesis work, demonstrates how the application of techniques from information visualisation and human computer interaction can result in software which enables biologists to construct conceptual queries. / Thesis (M.Comp.Sc.)-Universty of KwaZulu-Natal, Pietermaritzburg, 2007.

This work presents the implementation of the the IEEE 1609.2 WAVE Security Services Standard. This implementation provides the ability to generate a message signature, along with the capability to verify that signature for wave short messages transmitted over an unsecured medium. Only the original sender of the message can sign it, allowing for the authentication of a message to be checked. As hashing is used during the generation and verification of signatures, message integrity can be verified because a failed signature verification is a result of a compromised message. Also provided is the ability to encrypt and decrypt messages using AES-CCM to ensure that sensitive information remains safe and secure from unwanted recipients. Additionally this implementation provides a way for the 1609.2 specific data types to be encoded and decoded for ease of message transmittance. This implementation was built to support the Smart Drive initiative’s VANET testbed, supported by the National Science Foundation and is intended to run on the Vehicular Multi-technology Communication Device (VMCD) that is being developed. The VMCD runs on the embedded Linux operating system and this implementation will reside inside of the Linux kernel. / Includes bibliography. / Thesis (M.S.)--Florida Atlantic University, 2016. / FAU Electronic Theses and Dissertations Collection

Scene understanding attempts to produce a textual description of visible and latent concepts in an image to describe the real meaning of the scene. Concepts are either objects, events or relations depicted in an image. To recognize concepts, the decision of object detection algorithm must be further enhanced from visual similarity to semantical compatibility. Semantically relevant concepts convey the most consistent meaning of the scene. Object detectors analyze visual properties (e.g., pixel intensities, texture, color gradient) of sub-regions of an image to identify objects. The initially assigned objects names must be further examined to ensure they are compatible with each other and the scene. By enforcing inter-object dependencies (e.g., co-occurrence, spatial and semantical priors) and object to scene constraints as background information, a concept classifier predicts the most semantically consistent set of names for discovered objects. The additional background information that describes concepts is called context. In this dissertation, a framework for building context-based concept detection is presented that uses a combination of multiple contextual relationships to refine the result of underlying feature-based object detectors to produce most semantically compatible concepts. In addition to the lack of ability to capture semantical dependencies, object detectors suffer from high dimensionality of feature space that impairs them. Variances in the image (i.e., quality, pose, articulation, illumination, and occlusion) can also result in low-quality visual features that impact the accuracy of detected concepts. The object detectors used to build context-based framework experiments in this study are based on the state-of-the-art generative and discriminative graphical models. The relationships between model variables can be easily described using graphical models and the dependencies and precisely characterized using these representations. The generative context-based implementations are extensions of Latent Dirichlet Allocation, a leading topic modeling approach that is very effective in reduction of the dimensionality of the data. The discriminative contextbased approach extends Conditional Random Fields which allows efficient and precise construction of model by specifying and including only cases that are related and influence it. The dataset used for training and evaluation is MIT SUN397. The result of the experiments shows overall 15% increase in accuracy in annotation and 31% improvement in semantical saliency of the annotated concepts. / Includes bibliography. / Dissertation (Ph.D.)--Florida Atlantic University, 2016. / FAU Electronic Theses and Dissertations Collection

We present an implementation of the IEEE WAVE (Wireless Access in Vehicular Environments) 1609.4 standard, Multichannel Operation. This implementation provides concurrent access to a control channel and one or more service channels, enabling vehicles to communicate among each other on multiple service channels while still being able to receive urgent and control information on the control channel. Also included is functionality that provides over-the-air timing synchronization, allowing participation in alternating channel access in the absence of a reliable time source. Our implementation runs on embedded Linux and is built on top of IEEE 802.11p, as well as a customized device driver. This implementation will serve as a key compo- nent in our IEEE 1609-compliant Vehicular Multi-technology Communication Device (VMCD) that is being developed for a VANET testbed under the Smart Drive initiative, supported by the National Science Foundation. / Includes bibliography. / Thesis (M.S.)--Florida Atlantic University, 2014. / FAU Electronic Theses and Dissertations Collection

Wellness and healthy life are the most common concerns for an individual to lead a happy life. A web-based approach known as Wellness Scoring is being developed taking into people’s concerns for their health issues. In this approach, four different classifiers are being investigated to predict the wellness. In this thesis, we investigated four different classifiers (a probabilistic graphical model, simple probabilistic classifier, probabilistic statistical classification and an artificial neural network) to predict the wellness outcome. An approach to calculate wellness score is also addressed. All these classifiers are trained on real data, hence giving more accurate results. With this solution, there is a better way of keeping track of an individuals’ health. In this thesis, we present the design and development of such a system and evaluate the performance of the classifiers and design considerations to maximize the end user experience with the application. A user experience model capable of predicting the wellness score for a given set of risk factors is developed. / Includes bibliography. / Thesis (M.S.)--Florida Atlantic University, 2014. / FAU Electronic Theses and Dissertations Collection

by David Yeung Fong. / Thesis (M.B.A.)--Chinese University of Hong Kong, 1993. / Includes bibliographical references (leaves 118-119). / Executive Summary --- p.ii / Table of Contents --- p.iii / List of Illustrations --- p.vii / Acknowledgment --- p.viii / Chapter Chapter I - --- Introduction --- p.1 / Concepts of Expert Systems --- p.1 / Definition --- p.1 / Components of Expert Systems --- p.3 / Knowledge Acquisition --- p.4 / Knowledge Representation --- p.6 / Inference Engine --- p.8 / Benefits of Expert Systems --- p.9 / Recent Development --- p.10 / Expert Systems in Law --- p.11 / Applications --- p.11 / Problems of Expert Systems with Case Law --- p.12 / Translation of cases --- p.12 / Representation of cases --- p.12 / Interpretation --- p.13 / Policy considerations --- p.13 / Reasoning with precedent --- p.14 / Doctrine of precedent --- p.14 / Rule Model --- p.15 / Induction --- p.15 / Alternative approach to precedent --- p.16 / Product/Service Liability in Hong Kong --- p.17 / Definition --- p.17 / Law --- p.18 / Significance to Management --- p.19 / Chapter Chapter II - --- Research Definition --- p.21 / Research Goal --- p.21 / Research Objective --- p.21 / Scope of the Project --- p.21 / Chapter Chapter III - --- Research Methodology --- p.23 / Knowledge Acquisition --- p.23 / Brief Outline of the rules --- p.24 / Knowledge Representation --- p.24 / Expert System Development Tools for the project --- p.25 / XXXPERT --- p.25 / Imp shell --- p.26 / Turbo Prolog --- p.26 / Chapter Chapter IV - --- Research Limitation --- p.28 / Chapter Chapter V - --- System Configuration & Analysis --- p.29 / System Design --- p.29 / Main Module --- p.29 / Case Screening Module --- p.29 / Duty of Care Module --- p.30 / Breach of Duty Module --- p.30 / Causation Module --- p.30 / Remoteness of Damage Module --- p.31 / Defendant's Defense Module --- p.31 / Reference Cases Module --- p.31 / Help Module --- p.31 / Minimum System Requirements --- p.32 / System Testing --- p.32 / Chapter Chapter VI - --- Recommendations --- p.33 / Appendix A : Inference Tree --- p.34 / Appendix B: Cases Referenced in the Expert System --- p.48 / Appendix C: Program Listing --- p.64 / Tort.pro --- p.64 / Tdoms.pro --- p.67 / Status.pro --- p.68 / Tpreds.pro --- p.68 / Def.pro --- p.73 / Func.pro --- p.75 / Refcases.pro --- p.79 / Watstage.pro --- p.90 / Screen.pro --- p.92 / Duty.pro --- p.95 / "Breach, pro" --- p.100 / Causatio.pro --- p.106 / Remote.pro --- p.111 / Defense.pro --- p.111 / Appendix D: Bibliography --- p.118