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.

Rating agencies provide service by offering information about different kinds of securities and/or investment opportunities. This paper addresses questions often asked during the 2008 U.S. financial crisis: Why did no one see this coming? Why were all the explanations given afterward, not given before as precautions? Or if they were given before, why did nobody listen? Using Giddens’ idea of disembedded systems [Giddens A (1991a) The Consequences of Modernity (Polity Press, Cambridge, UK)], the paper describes and frames the phenomenon of U.S. financial crisis and the role of rating agencies in particular as a disembedded service system. Hereby it offers an explanation of the crises in contrast to the common incentive-oriented or moralizing perspectives. The paper shows that the U.S. financial crisis emerged from a disembedded service system, a simulacrum of ratings, which after a while was no more connected to the reality of securities. Information-providing service systems are in danger to become simulacra, and with it they can disembed. The paper offers a new insightful perspective on how to analyze and understand information-providing service systems and hence offers a perspective to avoid crises based on disembedded systems. This is the first paper to our knowledge to analyze information-providing service systems based on Giddens’ theory of abstract disembedded systems. It provides a new understanding of information-providing service systems that can help to avoid crises based on disembedded systems.

<p>Rad je posvećen problemu rane i brze detekcije i izolacije neželjenih stanja dinamičkih sistema, sa posebnim naglaskom na rano otkrivanje različitih nepravilnosti u radu i kvarova industrijskih procesa.</p> / <p>The thesys is dedicated to the problem of early and swift detection and isolation of unwanted working regimes of dynamical systems, with particular emphasis on the early detection of various irregularities and failures of industrial processes.</p>

A existência de novas condições econômicas e de trabalho tem conduzido as empresas a uma modernização de técnicas e metodologias para a resolução de problemas em Engenharia de Produção. Embora seja rápido o surgimento de novas ferramentas de informática e haja uma grande preocupação, no sentido de empregar a informática como suporte à tomada de decisões, o que se tem notado é que a utilização dos computadores nas empresas não tem sido feita na plenitude de suas possibilidades, ou seja, os usuários (especialmente os engenheiros) fazem uso de programas especialistas para chegarem a decisões isoladas e, posteriormente, transferem os resultados obtidos para outros aplicativos e/ou realização das análises. Este trabalho desenvolveu estudos multidisciplinares que envolvem as novas ferramentas oferecidas pelos avanços da Informática e pelos modernos conceitos de administração e otimização de processos, estudados em Engenharia de Produção. Tais estudos foram direcionados para a obtenção de resultados práticos que possam ser rapidamente aplicados nas empresas brasileiras, ou seja, dentro do contexto financeiro-tecnológico nacional. Estas pesquisam procuraram documentar qual é o formato do sistema, para que sejam capazes de facilitar e automatizar o planejamento da produção de uma indústria ou de uma empresa de serviços. Pretendeu-se, assim, registrar os conceitos e filosofias necessários para se construir uma ferramenta para otimização de processos produtivos que resolva, ou atenue, eventuais problemas causados por restrições nadisponibilidade de recursos (equipamento, mão-de-obra, material e tempo) ou de outra natureza. / The existence of new economic and work conditions has been driving the companies to a modernization of techniques and methodologies for resolution of problems in Production Engineering. Although be fast the appearance of new computer science tools and there be a great concern in the sense of using the computer science as support to the taking of decisions, which one has been noticing is that the use of the computers in the companies has not been made in the fullness of its possibilities, that is to say, the users (especially the engineers) make use of expert programs for they arrive to isolated decisions, and later, they transfer the results obtained for another applications and/or accomplishment of the analyses. This research developed multidisciplinaries studies involving the new tools offered by the progresses of the Computer Science and by the modern administration concepts, and optimization of processes studied by the Production Engineering. Such studies were addressed for the obtaining of practical results that they can be quickly applied in the Brazilian companies, that is to say, inside the national financial-technological context. Those researches tried to document which is the format of the system, so that they are capable to facilitate and to automate the planning of the production of an industry or company of services. It was intended like this to register the concepts and necessary philosophies to build a tool for optimization of productive processes that it solves, or attenuate, eventual problems caused by restrictions in the readiness of resources (equipment, work-hand, material and time) or by another nature.

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

Sistemas de suporte a decisão são utilizados em cenários com incertezas. Uma decisão normalmente é auxiliada por resultados obtidos com ações passadas em problemas semelhantes. Quando um sistema de suporte a decisão incorpora conhecimento específico de uma área, estes recebem o nome de sistemas especialistas. Tal conhecimento especifico é utilizado para inferência juntamente com as informações de entrada a respeito do problema. O objetivo deste trabalho é a avaliação e modelagem de sistemas de auxílio a decisão, foram analisadas duas abordagens para um mesmo problema alvo, sendo uma de gerenciamento do problema e outra de detecção do problema. A abordagem de gerenciamento utiliza redes Bayesianas para modelagem, tanto do conhecimento específico quanto para a inferência. As variáveis utilizadas, as relações de dependência e as probabilidades condicionais entre as variáveis foram extraídas da literatura. A abordagem de detecção do problema utilizou imagens para extração de características seguida de um algoritmo de agrupamento para comparação com a classificação de um especialista. Uma das áreas de aplicação de sistemas especialistas é na área clínica, podendo auxiliar tanto na detecção, diagnóstico e tratamento de doenças. A cárie dental é um problema generalizado que afeta a maioria das pessoas, tanto em países ricos, como em países pobres. Existem poucos sistemas para auxílio no processo de diagnóstico da cárie, sendo a maior parte dos sistemas existentes determinísticos, focando apenas na detecção da lesão. O sistema de gerenciamento da cárie desenvolvido foi apresentado a dois profissionais da odontologia, a opinião deles mostra que está abordagem é promissora e aplicável em campos como a educação e a atenção básica a saúde. Além da apresentação aos profissionais, foram utilizados casos bem estabelecidos da literatura para analisar as sugestões fornecidas pela Rede, e o resultado foi coerente com o cenário real de tomada de decisão. A metodologia de detecção da cárie resultou em um alto valor de acurácia, 96.88%, mostrando que tal metodologia é promissora em comparação com outros trabalhos da área. Além da contribuição para a área de informática odontológica, os resultados mostram que a extração da estrutura e das probabilidades condicionais da rede a partir da literatura é uma metodologia que pode ser utilizada em outras áreas com cenário similar ao do diagnóstico da cárie. Nos próximos passos do projeto alguns pontos referentes a modelagem de sistemas e redes Bayesianas serão analisados, como escalabilidade e testes de validação, tanto quantitativamente como qualitativamente, isto inclui o desenvolvimento de métodos computacionalmente efetivos para a geração de casos aleatórios utilizando o Método de Monte Carlo / Decision support systems are used in uncertainty scenarios; normally a decision is choose using similar problems actions results. Decision support systems could incorporate specific knowledge; such systems are called expert systems. The specific knowledge is used for inference about the problem scenario. This work objective is the evaluation and modeling of decision support systems, we analyzed two distinct approaches for the same problem, one for detection, another for management. The management approach uses Bayesian networks for modeling the specific knowledge and the inference engine. The variables choice, the dependences relationship and the conditional probabilities were extracted from the scientific literature. The detection approach used images and feature extraction to perform a clustering and compare the output labels with a specialist classification. One application of expert systems is clinical, supporting diseases detection, diagnosis and treatment. Dental caries is a generalized problem that affects major part of the population, few systems exists for support the caries diagnostic process, the major part is deterministic, focusing only the detection problem. The caries management system developed here was shown to two odontology professionals, and they opinion encourage such approach to be applied in fields like odontology education and basic health. Beyond this, we used well-established cases to analyze the network output suggestions, the result obtained was coherent with the real decision making scenario. The caries detection approach resulted in a high accuracy, 96.88%, showing that methodology is promising. Besides the contribution for dental informatics field, the results obtained here shows that the extraction of the network structure from the literature could be used in problems similar with caries diagnoses. The project next steps are to analyze some points of systems modeling and Bayesian networks, like scalability and validation tests, both quantitative and qualitative, and including the development of computational effectives methods for the use of Monte Carlo methodology