In this thesis, we are concerned with various aspects of fuzzy ideals of commutative rings. The central theorem is that of primary decomposition of a fuzzy ideal as an intersection of fuzzy primary ideals in a commutative Noetherian ring. We establish the existence and the two uniqueness theorems of primary decomposition of any fuzzy ideal with membership value 1 at the zero element. In proving this central result, we build up the necessary tools such as fuzzy primary ideals and the related concept of fuzzy maximal ideals, fuzzy prime ideals and fuzzy radicals. Another approach explores various characterizations of fuzzy ideals, namely, generation and level cuts of fuzzy ideals, relation between fuzzy ideals, congruences and quotient fuzzy rings. We also tie up several authors' seemingly different definitions of fuzzy prime, primary, semiprimary and fuzzy radicals available in the literature and show some of their equivalences and implications, providing counter-examples where certain implications fail.

The objective of this thesis is to develop certain aspects of the theory of (L,M)-fuzzy topological spaces, where L and M are complete lattices (with additional conditions when necessary). We obtain results which are to a large extent analogous to results given in a series of papers of Šostak (where L = M = [0,1]) but not necessarily with analogous proofs. Often, our generalizations require a variety of techniques from lattice theory e.g. from continuity or complete distributive lattices.

The objective of this thesis is a survey of crisp and fuzzy sober topological spaces. We begin by examining sobriety of crisp topological spaces. We then extend this to the L- topological case and obtain analogous results and characterizations to those of the crisp case. We then brie y examine semi-sobriety of (L;M)-topological spaces.

A multi-input multi-output system to implement on-line process monitoring and intelligent control of complex curvature friction stir welding was proposed. An extra rotation axis was added to the existing three translation axes to perform friction stir welding of complex curvature other than straight welding line. A clamping system was designed for locating and holding the workpieces to bear the large force involved in the process between the welding tool and workpieces. Process parameters (feed rate, spindle speed, tilt angle and plunge depth), and process conditions (parent material and curvature), were used as factors for the orthogonal array experiments to collect sensor data of force, torque and tool temperature using multiple sensors and telemetry system. Using statistic analysis of the experimental data, sensitive signal features were selected to train the feed-forward neural networks, which were used for mapping the relationships between process parameters, process conditions and sensor data. A fuzzy controller with initial input/output membership functions and fuzzy rules generated on-line from the trained neural network was applied to perceive process condition changes and make adjustment of process parameters to maintain tool/workpiece contact and energy input. Input/output scaling factors of the fuzzy controller were tuned on-line to improve output response to the amount and trend of control variable deviation from the reference value. Simulation results showed that the presented neuro-fuzzy control scheme has adaptability to process conditions such as parent material and curvature changes, and that the control variables were well regulated. The presented neuro-fuzzy control scheme can be also expected to be applied in other multi-input multi-output machining processes.

No description available.

La spectroscopie par résonance magnétique (SRM) est une technique d'analyse noninvasive des informations biochimiques des tissus du corps humain. L'un des éléments essentiels des examens SRM in vivo est la quantification des données SRM, qui consiste à retrouver les amplitudes ou surfaces des pics de chacun des métabolites en présence.Toutefois, cette tâche est encore difficile en raison du recouvrement important entre les différents pics, de la présence d'un bruit de fond qui chevauche tous les pics et du faible rapport signal sur bruit des spectres observés.Dans cette thèse, nous proposons deux nouvelles méthodes de quantification SRM dans le domaine fréquentiel. A partir d'un dictionnaire construit selon des connaissances a priori sur le modèle mathématique des pics des métabolites, nos deux méthodes estiment correctement les pics d'intérêt, en utilisant les représentations parcimonieuses des signaux.Les expériences de simulation menées montrent les excellents résultats de nos méthodes par rapport à l'état de l'art actuel. De plus, les quantifications de spectres SRM in vivo du cerveau pour le suivi au cours du temps de tumeurs sur des patients, ainsi que de spectres SRM in vivo de la prostate, démontrent la pertinence de nos méthodes.Dans cette thèse, nous avons également étudié la fusion des signaux SRM et des images IRM (imagerie par résonance magnétique). Les spectres SRM délivrent des informations biochimiques sur les tissus humains, tandis que les images IRM donnent des informations anatomiques. Quelques publications ont démontré récemment que la combinaison des deux informations SRM et IRM peuvent améliorer de façon critique la détection des cancers de la prostate. Dans ce contexte, nous avons proposé d'utiliser une technique de fusion d'informations floues de données SRM et IRM, afin d'automatiser la localisation de tissus cancéreux de la prostate. Dans cette étude préliminaire, nous avons montré les résultats encourageants obtenus par notre technique. / MRS (magnetic resonance spectroscopy) has proved to be an important non invasive technique for analyzing biochemical information about the tissues of the human body. One oft he essential elements of an in vivo MRS examination is the quantification of MRS data,which concerns the calculation of the amplitude or areas of the spectral peaks of individual metabolites. However, it is a challenging problem, because of the strongly overlapping metabolites peaks, the presence of a broad background (baseline) which overlaps the metabolites peaks, and the low signal to noise ratio.In this thesis, we have proposed two new MRS quantification methods in the frequency domain. The proposed methods achieved the accurate estimations of the spectral peaks of interest by finding their sparse representations with respect to a dictionary constructed based on their mathematical models and some a priori knowledge about these model parameters.Simulation experiments show the superiority of the proposed methods for MRS quantifications, compared with other methods. Moreover, the quantifications of in vivo brain MR spectra from tumor patients in different stages of progression, as well as in vivo prostate MR spectra, demonstrate the effectiveness of the proposed methods.Another research in this thesis is the fusion of information about MRS spectra and MRI(magnetic resonance imaging) images. MRS spectra provide biochemical information about human tissues while MRI images provide anatomical information. Some clinical researches inthe literature have shown that the combination of the information of MRS spectra and MRI images can ameliorate significantly the detection of prostate tumors. In this context, we proposed a technique using fuzzy information fusion of MRS data and MRI data for the automatic localization of the cancerous tissues of the prostate. As a preliminary research, we have shown the encouraging results obtained with the proposed technique.

Electronic Support (ES) operations concern themselves with the ability to search for, intercept, track and classify threat emitters. Modern radar systems in turn aim to operate undetected by intercept receivers. These radar systems maintain Low Probability of Intercept (LPI) by utilizing low power emissions, coded waveforms, wideband operation, narrow beamwidths and evasive scan patterns without compromising accuracy and resolution. The term LPI refers to the small chance or likelihood of intercept actually occurring. The complexity and degrees of freedom available to modern radar place a high demand on ES systems to provide detailed and accurate real-time information. Intercept alone is not sufficient and this study focusses on the detection, feature extraction (parameter estimation) and classification (using Fuzzy ARTMAP), of the Pilot Mk3 LPI radar. Fuzzy ARTMAP is a cognitive neural method combining fuzzy logic and Adaptive Resonance Theory (ART) to create categories of class prototypes to be classified. Fuzzy ARTMAP systems are formed by self-organizing neural architectures that are able to rapidly learn and classify both discreet and continuous input patterns. To evaluate the suitability of a given ES intercept receiver against a particular LPI radar, the LPI performance factor is defined by combining the radar range, intercept receiver range and sensitivity equations. The radar wants to force an opposing intercept receiver into its range envelope. On the contrary, the intercept receiver would ideally want to operate outside the specified radar detection range to avoid being detected by the radar. The Maximum Likelihood (ML) detector developed for this study is capable of detecting the Pilot Mk3 radar, as it allows sufficient integration gain for detection beyond the radar maximum range. The accuracy of parameter estimation in an intercept receiver is of great importance, as it has a direct impact on the accuracy of the classification stage. Among the various potentially useful radar parameters, antenna rotation rate, transmit frequency, frequency sweep and sweep repetition frequency were used to classify the Pilot Mk3 radar. Estimation of these parameters resulted in very clear clustering of parameter data that distinguish the Pilot Mk3 radar. The estimated radar signal parameters are well separated to the point that there is no overlap of features. If the detector is able to detect an intercepted signal it will be able to make accurate estimates of these parameters. The Fuzzy ARTMAP classifier is capable of classifying the radar modes of the Pilot Mk3 LPI radar. Correct Classification Decisions (CCD) of 100% are easily achieved for a variety of classifier configurations. Classifier training is quite efficient as good generalisation between input and output spaces is achieved from a training dataset comprising only 5% of the total dataset. If any radar is LPI, there must be a consideration for the radar as well as the opposing intercept receiver. Calculating the LPI performance factor is a useful tool for such an evaluation. The claim that a particular radar is LPI against any intercept receiver is too broad to be insightful. This also holds for an intercept receiver claiming to have 100% Probability of Intercept (POI) against any radar. AFRIKAANS : Elektroniese ondersteuningsoperasies het ten doel om uitsendings van bedreigings te soek, te onderskep, te volg en ook te klassifiseer. Moderne radarstelsels probeer op hulle beurt om hul eie werk te verrig sonder om onderskep te word. Hierdie tipe radarstelsels handhaaf ’n Lae Waarskynlikheid van Onderskepping (LWO) d.m.v. lae senderdrywing, geënkodeerde golfvorms, wyebandfrekwensiegebruik, noue antennabundels en vermydende antennasoekpatrone. Hierdie eienskappe veroorsaak dat ’n LWO radar nie akkuraatheid en resolusie prysgee nie. Die term LWO verwys na die skrale kans of waarskynlikheid van onderskepping deur ’n ontvanger wat die radar se gedrag probeer naspeur. Die komplekse seinomgewing en vele grade van vryheid beskikbaar vir ’n LWO-radar, stel baie hoë eise aan onderskeppingsontvangers om gedetaileerde en akkurate inligting in reële tyd te lewer. Die ondersoek van LWO-radaronderskepping op sy eie is nie voldoende nie. Hierdie studie beskou die deteksie, parameter-estimasie asook klassifikasie (m.b.v. Fuzzy ARTMAP) van die Pilot Mk3 LWO-radar as ’n probleem in die geheel. Fuzzy ARTMAP is ’n kognitiewe neurale metode wat fuzzy-logika en Aanspasbare Resonante Teorie (ART) kombineer om kategorieë of klassifikasieprototipes te vorm en hulle te klassifiseer. Fuzzy ARTMAP stelsels bestaan uit selfvormende neurale komponente wat diskrete asook kontinue insette vinnig kan leer en klassifiseer. Om die geskiktheid van enige onderskeppingsontvanger te bepaal word ’n LWO-werkverrigtingsyfer gedefinieer. Hierdie werkverrigtingsyfer kombineer beide radar- en onderskeppings ontvanger vergelykings vir operasionele reikafstand en sensitiwiteit. Die radar beoog om die onderskeppingsontvanger tot binne sy eie reikafstand in te forseer om die ontvangerplatform op te spoor. Die onderskeppingsontvanger wil daarenteen op ’n veilige afstand (verder as die radarbereik) bly, en nogsteeds die radar se uitsendings onderskep. ’n Maksimale Waarskynlikheid (MW) detektor is ontwikkel wat die Pilot Mk3- radargolfvorms kan opspoor, met voldoende integrasie-aanwins vir betroubare deteksie en wat veel verder strek as die radarreikafstand. Akkurate radarparameterestimasie is ’n baie belangrike funksie in ’n onderskeppingsontvanger aangesien dit ’n direkte implikasie het vir die akkuraatheid van die klassifikasiefunksie. Vanuit ’n wye verskeidenheid van relevante radar parameters word estimasies van antennadraaitempo, senderfrekwensie, frekwensieveegbandwydte en veegherhalingstempo gebruik om die Pilot Mk3-radar te klassifiseer. Die estimasie van hierdie parameters is duidelik gegroepeer met geen oorvleuling om moontlike verwarring te voorkom. Indien die detektor deteksies verklaar, volg die estimasiefunksie met baie akkurate waardes van radarparameters. Die Fuzzy ARTMAP-klassifiseerder wat ontwikkel is vir hierdie studie beskik oor die vermoë om die Pilot Mk3 LWO-radar te klassifiseer. Korrekte Klassifikasiebesluite (KKB) van 100% is moontlik vir ’n verskeidenheid klassifiseerderverstellings. Die klassifiseerder behaal ’n goeie veralgemening van in- en uitset ruimtes, en die leer- (of oefen-) roetines is baie effektief met so min as 5% van die volle datastel. Enige radarstelsel wat roem op LWO moet sowel die radar as ’n moontlike onderskeppingsontvanger in gelyke maat beskou. Die LWO- werkverrigtingsyfer verskaf ’n handige maatstaf vir sulke evaluasies. Om bloot te eis dat ’n radar LWO-eienskappe teenoor enige onderskeppingsontvanger het, is te algemeen en nie insiggewend nie. Dieselfde geld vir ’n onderskeppingsontvanger wat 100% (of totale) onderskepping kan verrig teenoor enige radar. Copyright / Dissertation (MEng)--University of Pretoria, 2012. / Electrical, Electronic and Computer Engineering / unrestricted

Orientador: Leonardo de Souza Mendes / Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Elétrica e de Computação / Made available in DSpace on 2018-08-22T07:53:28Z (GMT). No. of bitstreams: 1 AriasArias_Richard_M.pdf: 2020622 bytes, checksum: d259852aeda010c74fd5adffbf0cc63c (MD5) Previous issue date: 2012 / Resumo: Esta dissertação propõe um modelo de avaliação de aprendizado de alunos baseado em lógica difusa para ambientes de educação mediada por computador. O modelo proposto contempla as três dimensões relevantes citadas pelo método de Weon e Kim (2001): dificuldade, complexidade e importância das atividades. A avaliação multidimensional é feita por meio dos processos de fuzzificação, defuzzificação e de inferência difusa de Mandani (1974). O modelo tem como entrada os acertos e o tempo gasto pelos alunos nas atividades realizadas nos módulos educacionais. As regras difusas e os pesos da complexidade e importância são definidos pelo professor especialista na disciplina. A saída do modelo é um vetor de notas correspondente ao desempenho dos alunos que foram avaliados multidimensionalmente. O modelo foi aplicado em uma escola que utiliza o sistema Conexão do Saber, desenvolvido pelo Laboratório de Redes de Comunicações da Faculdade de Engenharia Elétrica e Computação da UNICAMP. Os resultados obtidos mostram que o modelo pode ser usado para avaliar o desempenho de alunos em várias dimensões e de uma forma mais precisa e interpretativa / Abstract: This dissertation proposes a model to evaluate a student's learning development based on fuzzy logic for educational environments mediated by computer. The proposed model considers the three main dimensions quoted by Weon and Kim method (2001): difficulty, complexity and importance of activities. Multidimensional evaluation is carried out through the fuzzification, fuzzy inference and defuzzification processes of Mandani (1974). The inputs for the model are the ac-curacy rates of student's answerscripts and the time spent by them on educational activities in the modules. The fuzzy rules and weight for complexity and importance are defined by the specialist in the discipline. The output is an array of scores corresponding to the performance of students who were assessed multidimensionally. The model was applied to a school that uses the Conexão do Saber system, developed by the Laboratory of Communication Networks at the School of Electrical and Computer Engineering of the University of Campinas. The results show that the model can be used to evaluate the performance of students in various dimensions and an easily interpreted way / Mestrado / Telecomunicações e Telemática / Mestre em Engenharia Elétrica

Orientador: Fernando Antonio Campos Gomide / Tese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia Eletrica / Made available in DSpace on 2018-07-18T14:06:55Z (GMT). No. of bitstreams: 1 Scarpelli_HeloisadeArrudaCamargo_D.pdf: 7789586 bytes, checksum: be24fbc2123951211626bb728be27c2a (MD5) Previous issue date: 1993 / Resumo: Neste trabalho são propostos dois modelos formais para a representação de regras de produção nebulosas, como base em teoria de redes. A proposta desses modelos tem o objetivo de oferecer um mecanismo de representação onde os problemas relativos ao projeto, execução e verificação de bases de conhecimento nebulosas possam ser tratados de maneira uniforme e integrada. O modelo de Redes de Petri Nebulosas representa detalhadamente a execução da regra de inferência principal do raciocínio aproximado, chamada de regra composicional. O modelo de Redes de Petri Nebulosas de Alto Nível permite representar as regras nebulosas de um nível de abstração mais alto, gerando representações mais compactas e tratáveis. Os componentes de cada um desses dois modelos guardam uma relação bastante próxima, possibilitando que as informações sejam acessadas a partir do nível mais conveniente a cada fase do desenvolvimento de sistemas. A modelagem de vários tipos de regras como regras com múltiplos antecedentes, regras quantificadas e qualificadas, regras paralelas, regras conflitantes e fontes parciais de informação é discutida. Dois algoritmos de raciocínio aproximado são apresentados, utilizando as estratégias de encadeamento para frente e encadeamento para trás. A questão de verificação de inconsistência entre regras de produção nebulosas é discutida. Procedimentos para verificação da existência de conflitos em potencial, tanto a nível local como a nível global, são apresentados / Abstract: This work presents two formal models for the representation of fuzzy production rules, based on net theory. The proposal of the models aims at offering a mechanism where problems concerning design, execution and verification of fuzzy knowledge bases can be faced in an uniform and integrated manner. The Fuzzy Petri Net model represents in details the numerical components underlying the main inference rule in approximate reasoning, called compositional rule. The High LeveI Fuzzy Petri Net model allows to represent fuzzy rules in a higher leveI of abstraction, yielding more compact and manageable representations. The components of both systems are dosely related, allowing the accessing of information from the most convenient leveI in each phase of systems development. The modeling of several rule types like rules with multiple antecedent, quantified and qualified rules, par alIeI rules, conflicting rules and partial sources of information has been discussed. Two different fuzzy reasoning algorithms have been presented, using forward chaining and backward chaining strategies. The issue of inconsistency checking among fuzzy production rules has also been approached. Procedures for verifying the existence of potencial conflicts, both at local and globallevels are included. / Doutorado / Doutor em Engenharia Elétrica

This diploma thesis deals with the design of models for rating of suppliers in public procurement tender. Describes used methods and procedures for the rating of suppliers using fuzzy logic and fuzzy sets. The goal is to design a functional and comprehensible model, possible to use repeatedly with small variations.