Cognitive radio is a intelligent technology that helps in resolving the issue of spectrum scarcity. In a spectrum sharing network, where secondary user can communicate simultaneously along with the primary user in the same frequency band, one of the challenges in cognitive radio is to obtain balance between two conflicting goals that are to minimize the interference to the primary users and to improve the performance of the secondary user. In our thesis we have considered a primary link and a secondary link (cognitive link) in a fading channel. To improve the performance of the secondary user by maintaining the Quality of Service (Qos) to the primary user, we considered varying the transmit power of the cognitive user. Efficient utilization of power in any system helps in improving the performance of that system. For this we proposed ANFIS based opportunistic power control strategy with primary user’s SNR and primary user’s channel gain interference as inputs. By using fuzzy inference system, Qos of primary user is adhered and there is no need of complex feedback channel from primary receiver. The simulation results of the proposed strategy shows better performance than the one without power control. Initially we have considered propagation environment without path loss and then extended our concept to the propagation environment with path loss where we have considered relative distance between the links as one of the input parameters.

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Orientador: José Arnaldo Frutuoso Roveda / Resumo: No Brasil e no mundo é latente a necessidade de fazer a proteção, a ampliação e a promoção do patrimônio geológico, com a finalidade de garantir as próximas gerações acesso a este tipo de patrimônio natural, de modo econômica e ecologicamente sustentável. Diante disso, a Organização das Nações Unidas para a Educação, a Ciência e a Cultura - UNESCO criou a GGN - Global Geoparks Network, ou em sua tradução Rede Global de Geoparques - RGG. A Rede Global de Geoparques tem por função fazer a inclusão de novos parques membros, bem como, fazer a manutenção dos parques membros já existentes. Para que um parque seja postulante a membro do RGG, este deve atender uma série de requisitos, dentre as quais a Geoeducação, além disso, os parques membros de tempos em tempos devem passar por validação destes requisitos. Os parques candidatos possuem a dificuldade de elencar quais são as ações prioritárias num esforço de se tornarem membros da RGG. Como estes parques podem se tornar membros da RGG com o menor esforço. O presente trabalho se tem como objetivo apresenta uma proposta de criação um Sistema de Inferência Fuzzy (SIF) para tomada de decisões em Geoeducação, por parte dos gestores de áreas passíveis de se tornarem membros da RGG. A metodologia utilizada foi a teoria de conjuntos Fuzzy, através da criação de um sistema de inferência para geração de índices de adequação em Geoeducação das áreas candidatas. Foram criados 155 cenários para testar e validar o comportamento do sistema, o mes... (Resumo completo, clicar acesso eletrônico abaixo) / Mestre

The coronavirus (COVID-19) pandemic has caused severe adverse effects on the human life and the global economy affecting all communities and individuals due to its rapid spreading, increase in the number of affected cases and creating severe health issues and death cases worldwide. Since no particular treatment has been acknowledged so far for this disease, prompt detection of COVID-19 is essential to control and halt its chain. In this paper, we introduce an intelligent fuzzy inference system for the primary diagnosis of COVID-19. The system infers the likelihood level of COVID-19 infection based on the symptoms that appear on the patient. This proposed inference system can assist physicians in identifying the disease and help individuals to perform self-diagnosis on their own cases.

Fine-scale resolution digital elevation models (DEMs) created from data collected using high precision instruments have become ubiquitous in fluvial geomorphology. They permit a diverse range of spatially explicit analyses including hydraulic modeling, habitat modeling and geomorphic change detection. Yet, the intercomparison of survey technologies across a diverse range of wadeable stream habitats has not yet been examined. Additionally, we lack an understanding regarding the precision of DEMs derived from ground-based surveys conducted by different, and inherently subjective, observers. This thesis addresses current knowledge gaps with the objectives i) to intercompare survey techniques for characterizing instream topography, and ii) to characterize observer variability in instream topographic surveys. To address objective i, we used total station (TS), real-time kinematic (rtk) GPS, terrestrial laser scanner (TLS), and infrared airborne laser scanning (ALS) topographic data from six sites of varying complexity in the Lemhi River Basin, Idaho. The accuracy of derived bare earth DEMs was evaluated relative to higher precision TS point data. Significant DEM discrepancies between pairwise techniques were calculated using propagated DEM errors thresholded at a 95% confidence interval. Mean discrepancies between TS and rtkGPS DEMs were relatively low (≤ 0.05 m), yet TS data collection time was up to 2.4 times longer than rtkGPS. ALS DEMs had lower accuracy than TS or rtkGPS DEMs, but ALS aerial coverage and floodplain topographic representation was superior to all other techniques. The TLS bare earth DEM accuracy and precision were lower than other techniques as a result of vegetation returns misinterpreted as ground returns. To address objective ii, we used a case study where seven field crews surveyed the same six sites to quantify the magnitude and effect of observer variability on DEMs interpolated from the survey data. We modeled two geomorphic change scenarios and calculated net erosion and deposition volumes at a 95% confidence interval. We observed several large magnitude elevation discrepancies across crews, however many of these i) tended to be highly localized, ii) were due to systematic errors, iii) did not significantly affect DEM-derived metric precision, and iv) can be corrected post-hoc.

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The fuzzy inference system has been tuned and revamped many times over and applied to numerous domains. New and improved techniques have been presented for fuzzification, implication, rule composition and defuzzification, leaving rule aggregation relatively underrepresented. Current FIS aggregation operators are relatively simple and have remained more-or-less unchanged over the years. For many problems, these simple aggregation operators produce intuitive, useful and meaningful results. However, there exists a wide class of problems for which quality aggregation requires nonditivity and exploitation of interactions between rules. Herein, the fuzzy integral, a parametric non-linear aggregation operator, is used to fill this gap. Specifically, recent advancements in extensions of the fuzzy integral to “unrestricted” fuzzy sets, i.e., subnormal and non-convex, makes this now possible. The roles of two extensions, gFI and the NDFI, are explored and demonstrate when and where to apply these aggregations, and present efficient algorithms to approximate their solutions.

During recent years, much focus have been put on replacing time consuming manual mappingand classification tasks with automatic methods, having minimal human interaction. Now it ispossible to quickly classify land cover and terrain features covering large areas to a digital formatand with a high accuracy. This can be achieved using nothing but remote sensing techniques,which provide a far more sustainable process and product. Still, some terrain features do not havean established methodology for high quality automatic mapping.The Scandinavian Mountains contain several terrain features with low passability, such asmires, shrub and stony ground. It would be of interest to anyone passing the land to avoid theseareas. However, they are not sufficiently mapped in current map products.The aim of this thesis was to find a methodology to classify and map these terrain featuresin the Scandinavian Mountains with high accuracy and minimal human interaction, using remotesensing techniques. The study area chosen for the analysis is a large valley and mountain sidesouth-east of the small town Abisko in northern Sweden, which contain clearly visible samplesof the targeted terrain features. The methodology was based on training a Fuzzy Logic classifierusing labeled training samples and descriptors derived from ortophotos, LiDAR data and currentmap products, chosen to separate the classes from each other by their characteristics. Firstly,a set of candidate descriptors were chosen, from which the final descriptors were obtained byimplementing a Fisher score filter. Secondly a Fuzzy Inference System was constructed usinglabeled training data from the descriptors, created by the user. Finally the entire study area wasclassified pixel-by-pixel by using the trained classifier and a majority filter was used to cluster theoutputs. The result was validated by visual inspection, comparison to the current map productsand by constructing Confusion Matrices, both for the training data and validation samples as wellas for the clustered- and non-clustered results.The results showed that / De senaste åren har mycket fokus lagts på att ersätta tidskrävande manuella karterings- och klassificeringsmetodermed automatiserade lösningar med minimal mänsklig inverkan. Det är numeramöjligt att digitalt klassificera marktäcket och terrängföremål över stora områden, snabbt och medhög noggrannhet. Detta med hjälp av enbart fjärranalys, vilket medför en betydligt mer hållbarprocess och slutprodukt. Trots det finns det fortfarande terrängföremål som inte har en etableradmetod för noggrann automatisk kartering.Den skandinaviska fjällkedjan består till stor del av svårpasserade terrängföremål som sankmarker,videsnår och stenig mark. Alla som tar sig fram i terrängen obanat skulle ha nytta av attkunna undvika dessa områden men de är i nuläget inte karterade med önskvärd noggrannhet.Målet med denna analys var att utforma en metod för att klassificera och kartera dessa terrängföremåli Skanderna, med hög noggrannhet och minimal mänsklig inverkan med hjälp avfjärranalys. Valet av testområde för analysen är en större dal och bergssida sydost om Abisko inorra Sverige som innehåller tydliga exemplar av alla berörda terrängföremål. Metoden baseradespå att träna en Fuzzy Logic classifier med manuellt utvald träningsdata och deskriptorer,valda för att bäst separera klasserna utifrån deras karaktärsdrag. Inledningsvis valdes en uppsättningav kandidatdeskriptorer som sedan filtrerades till den slutgiltiga uppsättningen med hjälp avett Fisher score filter. Ett Fuzzy Inference System byggdes och tränades med träningsdata fråndeskriptorerna vilket slutligen användes för att klassificera hela testområdet pixelvis. Det klassificeraderesultatet klustrades därefter med hjälp av ett majoritetsfilter. Resultatet validerades genomvisuell inspektion, jämförelse med befintliga kartprodukter och genom confusion matriser, vilkaberäknades både för träningsdata och valideringsdata samt för det klustrade och icke-klustraderesultatet.Resultatet visade att de svårpasserade terrängföremålen sankmark, videsnår och stenig markkan karteras med hög noggrannhet med hjälp denna metod och att resultaten generellt är tydligtbättre än nuvarande kartprodukter. Däremot kan metoden finjusteras på flera plan för att optimeras.Bland annat genom att implementera deskriptorer för markvattenrörelser och användandeav LiDAR med högre spatial upplösning, samt med ett mer fulltäckande och spritt val av klasser.

A eficiência e a racionalidade energética da iluminação pública têm relevante importância no sistema elétrico, porque contribui para diminuir a necessidade de investimentos na construção de novas fontes geradoras de energia elétrica e nos desperdícios energéticos. Apresenta-se como objetivo deste trabalho de pesquisa o desenvolvimento e aplicação do IDE (índice de desempenho energético), fundamentado no sistema de inferência nebulosa e indicadores de eficiência e racionalidade de uso da energia elétrica. A opção em utilizar a inferência nebulosa deve-se aos fatos de sua capacidade de reproduzir parte do raciocínio humano, e estabelecer relação entre a diversidade de indicadores envolvidos. Para a consecução do sistema de inferência nebulosa, foram definidas como variáveis de entrada: os indicadores de eficiência e racionalidade; o método de inferência foi baseado em regras produzidas por especialista em iluminação pública, e como saída um número real que caracteriza o IDE. Os indicadores de eficiência e racionalidade são divididos em duas classes: globais e específicos. Os indicadores globais são: FP (fator de potência), FC (fator de carga) e FD (fator de demanda). Os indicadores específicos são: FU (fator de utilização), ICA (consumo de energia por área iluminada), IE (intensidade energética) e IL (intensidade de iluminação natural). Para a aplicação deste trabalho, foi selecionada e caracterizada a iluminação pública da Cidade Universitária \"Armando de Salles Oliveira\" da Universidade de São Paulo. Sendo assim, o gestor do sistema de iluminação, a partir do índice desenvolvido neste trabalho, dispõe de condições para avaliar o uso da energia elétrica e, desta forma, elaborar e simular estratégias com o objetivo de economizá-la. / The energy efficiency and rationality of public lighting have great importance in the electrical system, because it contributes to reduce the need for investment in building new sources of power and energy waste. It presented as objective of this work research development and application of IDE (Energy Performance Index), based on the fuzzy inference system and indicators of efficiency and rationality of use of electricity. The option to use the fuzzy inference is due to the facts of his ability to play part of human reasoning, and establish the relationship between indicators of diversity involved. To achieve the fuzzy inference system, it was defined as input variables: the efficiency and rationality indicators; the inference rules-based method was produced by expert in public lighting and as output a real number that characterizes the IDE. Efficiency and rationality indicators are divided into two classes: global and specific. The global indicators are: PF (power factor), FC (load factor) and FD (demand factor). Specific indicators are: FU (utilization factor), ICA (energy consumption per lit area), IE (energy intensity) and IL (daylight intensity). For the application of this work was selected and characterized the public lighting of the University City \"Armando de Salles Oliveira\" the University of São Paulo. Thus, the lighting system manager from the index developed in this work, have conditions to evaluate the use of electricity and thus prepare and simulate strategies in order to save it.

A eficiência e a racionalidade energética da iluminação pública têm relevante importância no sistema elétrico, porque contribui para diminuir a necessidade de investimentos na construção de novas fontes geradoras de energia elétrica e nos desperdícios energéticos. Apresenta-se como objetivo deste trabalho de pesquisa o desenvolvimento e aplicação do IDE (índice de desempenho energético), fundamentado no sistema de inferência nebulosa e indicadores de eficiência e racionalidade de uso da energia elétrica. A opção em utilizar a inferência nebulosa deve-se aos fatos de sua capacidade de reproduzir parte do raciocínio humano, e estabelecer relação entre a diversidade de indicadores envolvidos. Para a consecução do sistema de inferência nebulosa, foram definidas como variáveis de entrada: os indicadores de eficiência e racionalidade; o método de inferência foi baseado em regras produzidas por especialista em iluminação pública, e como saída um número real que caracteriza o IDE. Os indicadores de eficiência e racionalidade são divididos em duas classes: globais e específicos. Os indicadores globais são: FP (fator de potência), FC (fator de carga) e FD (fator de demanda). Os indicadores específicos são: FU (fator de utilização), ICA (consumo de energia por área iluminada), IE (intensidade energética) e IL (intensidade de iluminação natural). Para a aplicação deste trabalho, foi selecionada e caracterizada a iluminação pública da Cidade Universitária \"Armando de Salles Oliveira\" da Universidade de São Paulo. Sendo assim, o gestor do sistema de iluminação, a partir do índice desenvolvido neste trabalho, dispõe de condições para avaliar o uso da energia elétrica e, desta forma, elaborar e simular estratégias com o objetivo de economizá-la. / The energy efficiency and rationality of public lighting have great importance in the electrical system, because it contributes to reduce the need for investment in building new sources of power and energy waste. It presented as objective of this work research development and application of IDE (Energy Performance Index), based on the fuzzy inference system and indicators of efficiency and rationality of use of electricity. The option to use the fuzzy inference is due to the facts of his ability to play part of human reasoning, and establish the relationship between indicators of diversity involved. To achieve the fuzzy inference system, it was defined as input variables: the efficiency and rationality indicators; the inference rules-based method was produced by expert in public lighting and as output a real number that characterizes the IDE. Efficiency and rationality indicators are divided into two classes: global and specific. The global indicators are: PF (power factor), FC (load factor) and FD (demand factor). Specific indicators are: FU (utilization factor), ICA (energy consumption per lit area), IE (energy intensity) and IL (daylight intensity). For the application of this work was selected and characterized the public lighting of the University City \"Armando de Salles Oliveira\" the University of São Paulo. Thus, the lighting system manager from the index developed in this work, have conditions to evaluate the use of electricity and thus prepare and simulate strategies in order to save it.