986 resultados para Sistemas fuzzy Takagi-Sugeno
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Digital image segmentation is the process of assigning distinct labels to different objects in a digital image, and the fuzzy segmentation algorithm has been used successfully in the segmentation of images from several modalities. However, the traditional fuzzy segmentation algorithm fails to segment objects that are characterized by textures whose patterns cannot be successfully described by simple statistics computed over a very restricted area. In this paper we present an extension of the fuzzy segmentation algorithm that achieves the segmentation of textures by employing adaptive affinity functions as long as we extend the algorithm to tridimensional images. The adaptive affinity functions change the size of the area where they compute the texture descriptors, according to the characteristics of the texture being processed, while three dimensional images can be described as a finite set of two-dimensional images. The algorithm then segments the volume image with an appropriate calculation area for each texture, making it possible to produce good estimates of actual volumes of the target structures of the segmentation process. We will perform experiments with synthetic and real data in applications such as segmentation of medical imaging obtained from magnetic rosonance
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There are authentication models which use passwords, keys, personal identifiers (cards, tags etc) to authenticate a particular user in the authentication/identification process. However, there are other systems that can use biometric data, such as signature, fingerprint, voice, etc., to authenticate an individual in a system. In another hand, the storage of biometric can bring some risks such as consistency and protection problems for these data. According to this problem, it is necessary to protect these biometric databases to ensure the integrity and reliability of the system. In this case, there are models for security/authentication biometric identification, for example, models and Fuzzy Vault and Fuzzy Commitment systems. Currently, these models are mostly used in the cases for protection of biometric data, but they have fragile elements in the protection process. Therefore, increasing the level of security of these methods through changes in the structure, or even by inserting new layers of protection is one of the goals of this thesis. In other words, this work proposes the simultaneous use of encryption (Encryption Algorithm Papilio) with protection models templates (Fuzzy Vault and Fuzzy Commitment) in identification systems based on biometric. The objective of this work is to improve two aspects in Biometric systems: safety and accuracy. Furthermore, it is necessary to maintain a reasonable level of efficiency of this data through the use of more elaborate classification structures, known as committees. Therefore, we intend to propose a model of a safer biometric identification systems for identification.
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The Amyotrophic Lateral Sclerosis (ALS) is a neurodegenerative disease characterized by progressive muscle weakness that leads the patient to death, usually due to respiratory complications. Thus, as the disease progresses the patient will require noninvasive ventilation (NIV) and constant monitoring. This paper presents a distributed architecture for homecare monitoring of nocturnal NIV in patients with ALS. The implementation of this architecture used single board computers and mobile devices placed in patient’s homes, to display alert messages for caregivers and a web server for remote monitoring by the healthcare staff. The architecture used a software based on fuzzy logic and computer vision to capture data from a mechanical ventilator screen and generate alert messages with instructions for caregivers. The monitoring was performed on 29 patients for 7 con-tinuous hours daily during 5 days generating a total of 126000 samples for each variable monitored at a sampling rate of one sample per second. The system was evaluated regarding the rate of hits for character recognition and its correction through an algorithm for the detection and correction of errors. Furthermore, a healthcare team evaluated regarding the time intervals at which the alert messages were generated and the correctness of such messages. Thus, the system showed an average hit rate of 98.72%, and in the worst case 98.39%. As for the message to be generated, the system also agreed 100% to the overall assessment, and there was disagreement in only 2 cases with one of the physician evaluators.
Resumo:
The Amyotrophic Lateral Sclerosis (ALS) is a neurodegenerative disease characterized by progressive muscle weakness that leads the patient to death, usually due to respiratory complications. Thus, as the disease progresses the patient will require noninvasive ventilation (NIV) and constant monitoring. This paper presents a distributed architecture for homecare monitoring of nocturnal NIV in patients with ALS. The implementation of this architecture used single board computers and mobile devices placed in patient’s homes, to display alert messages for caregivers and a web server for remote monitoring by the healthcare staff. The architecture used a software based on fuzzy logic and computer vision to capture data from a mechanical ventilator screen and generate alert messages with instructions for caregivers. The monitoring was performed on 29 patients for 7 con-tinuous hours daily during 5 days generating a total of 126000 samples for each variable monitored at a sampling rate of one sample per second. The system was evaluated regarding the rate of hits for character recognition and its correction through an algorithm for the detection and correction of errors. Furthermore, a healthcare team evaluated regarding the time intervals at which the alert messages were generated and the correctness of such messages. Thus, the system showed an average hit rate of 98.72%, and in the worst case 98.39%. As for the message to be generated, the system also agreed 100% to the overall assessment, and there was disagreement in only 2 cases with one of the physician evaluators.
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The main aim of this investigation is to propose the notion of uniform and strong primeness in fuzzy environment. First, it is proposed and investigated the concept of fuzzy strongly prime and fuzzy uniformly strongly prime ideal. As an additional tool, the concept of t/m systems for fuzzy environment gives an alternative way to deal with primeness in fuzzy. Second, a fuzzy version of correspondence theorem and the radical of a fuzzy ideal are proposed. Finally, it is proposed a new concept of prime ideal for Quantales which enable us to deal with primeness in a noncommutative setting.
Resumo:
The main aim of this investigation is to propose the notion of uniform and strong primeness in fuzzy environment. First, it is proposed and investigated the concept of fuzzy strongly prime and fuzzy uniformly strongly prime ideal. As an additional tool, the concept of t/m systems for fuzzy environment gives an alternative way to deal with primeness in fuzzy. Second, a fuzzy version of correspondence theorem and the radical of a fuzzy ideal are proposed. Finally, it is proposed a new concept of prime ideal for Quantales which enable us to deal with primeness in a noncommutative setting.
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The electric power systems are getting more complex and covering larger areas day by day. This fact has been contribuiting to the development of monitoring techniques that aim to help the analysis, control and planning of power systems. Supervisory Control and Data Acquisition (SCADA) systems, Wide Area Measurement Systems and disturbance record systems. Unlike SCADA and WAMS, disturbance record systems are mainly used for offilne analysis in occurrences where a fault resulted in tripping of and apparatus such as a transimission line, transformer, generator and so on. The device responsible for record the disturbances is called Digital Fault Recorder (DFR) and records, basically, electrical quantities as voltage and currents and also, records digital information from protection system devices. Generally, in power plants, all the DFRs data are centralized in the utility data centre and it results in an excess of data that difficults the task of analysis by the specialist engineers. This dissertation shows a new methodology for automated analysis of disturbances in power plants. A fuzzy reasoning system is proposed to deal with the data from the DFRs. The objective of the system is to help the engineer resposnible for the analysis of the DFRs’s information by means of a pre-classification of data. For that, the fuzzy system is responsible for generating unit operational state diagnosis and fault classification.
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From their early days, Electrical Submergible Pumping (ESP) units have excelled in lifting much greater liquid rates than most of the other types of artificial lift and developed by good performance in wells with high BSW, in onshore and offshore environments. For all artificial lift system, the lifetime and frequency of interventions are of paramount importance, given the high costs of rigs and equipment, plus the losses coming from a halt in production. In search of a better life of the system comes the need to work with the same efficiency and security within the limits of their equipment, this implies the need for periodic adjustments, monitoring and control. How is increasing the prospect of minimizing direct human actions, these adjustments should be made increasingly via automation. The automated system not only provides a longer life, but also greater control over the production of the well. The controller is the brain of most automation systems, it is inserted the logic and strategies in the work process in order to get you to work efficiently. So great is the importance of controlling for any automation system is expected that, with better understanding of ESP system and the development of research, many controllers will be proposed for this method of artificial lift. Once a controller is proposed, it must be tested and validated before they take it as efficient and functional. The use of a producing well or a test well could favor the completion of testing, but with the serious risk that flaws in the design of the controller were to cause damage to oil well equipment, many of them expensive. Given this reality, the main objective of the present work is to present an environment for evaluation of fuzzy controllers for wells equipped with ESP system, using a computer simulator representing a virtual oil well, a software design fuzzy controllers and a PLC. The use of the proposed environment will enable a reduction in time required for testing and adjustments to the controller and evaluated a rapid diagnosis of their efficiency and effectiveness. The control algorithms are implemented in both high-level language, through the controller design software, such as specific language for programming PLCs, Ladder Diagram language.
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This study focus on the reconfiguration of educational management in Argentina, Brazil, Chile and Mexico, which was promoted by the new logic of social regulation and the new role attributed to the State, considering each country's own historicity. So, the cultural factors that interfere on the dynamics of the 90' school reform are analyzed. Aspects that show the homogeneity or heterogeneity of these reforms in the region, as well as local specificities that block out the concretization of the reform are underlined. It is shown that the historicity that characterizes the educational reform has taken, in each country, a form that can be called, in Mexico, conservative rupture; in Chile, conservative continuity; in Brazil, conservative renovation; and, in Argentina, interrupted rupture. Some conclusions about the impact of educational reform in the selected countries are recuperated through the analysis of 186 academic texts on the subject.
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By the year 2005 the world biochemical market will reach an estimated $ 100 billion and separation processes are a vital link between lab discoveries and the fulfillment of this commercialization potential. The practical application of aqueous two-phase systems (ATPS) to extraction processes has been exploited for several years for the recovery of biological products. Unfortunately, this has not resulted in an extensive presence of the technique in commercial processes. In this paper a critical overview of the fundamental thermodynamic properties related to formation of aqueous two-phase systems and their application to extraction and purification of bioparticules is presented.
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One of the main referring subjects to the solar energy is how to compare it economically with other sources of energy, as much alternatives as with conventionals (like the electric grid). The purpose of this work was to develop a software which congregates the technical and economic main data to identify, through methods of microeconomic analysis, the commercial viability in the sizing of photovoltaic systems, besides considering the benefits proceeding from the proper energy generation. Considering the period of useful life of the components of the generation system of photovoltaic electricity, the costs of the energy proceeding from the conventional grid had been identified. For the comparison of the conventional sources, electric grid and diesel generation, three scenes of costs of photovoltaic panels and two for the factor of availability of diesel generation had been used. The results have shown that if the cost of the panels is low and the place of installation is more distant of the electric grid, the photovoltaic system becomes the best option.
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A trial was carried out to evaluate the chemical composition in the aerial part of lettuce, cv. 'Elisa', irrigated with wastewater treated with constructed wetland and source deposit water, grown on a Rhodic Hapludox Soil, using the irrigation systems sprinkle, subsurface drip and surface drip irrigation. The experiment was carried out from August 17th to October 3rd of 2001 and the chemical analyses of the lettuce were accomplished to 47 days after transplanting of the seedling. The aerial part of the lettuce was analyzed as for the levels of total nitrogen, nitrate, phosphorus, potassium, calcium, magnesium, sulfur, iron, manganese, copper, zinc, sodium, boron, cobalt and molybdenum. The sodium and the sulfur presented higher levels than the maximum suitable in the aerial part of the lettuce and the smallest level of magnesium, while other chemical elements analyzed were normal and appropriate considering the standard for well-nourished plants, not being influenced by the water type. The sodium was the chemical element that presented the highest levels in the aerial part of the lettuce in the treatments irrigated with wastewater, presenting significant difference in relationship to the treatments irrigated with source deposit water in the three irrigation systems. The use of the different irrigation systems by the application of wastewater treated with constructed wetland did not interfere in the levels of nutrients in the aerial part of the lettuce.
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Among the important changes in the production processes, it is necessary to guarantee the sustainability of the human enterprises, what makes us to foresee changes in the managerial administration to adapt to a new model, with the insert of the concepts of Clean Production, Cleaner, Lean and Total Productive Maintenance (TPM). The main focus of this work was to elaborate a methodology that made it possible to guarantee the reliability in the waterworks of the sugarcane harvester, identifying and analyzing the manners of flaws, in order to result in the improvement of the environmental and socioeconomic quality in the atmosphere of an industry of sugarcane through the significant decrease of hydraulic oil spill. Through the existent report in ERP (Enterprise Resource Planning), used in a Sugarcane Industry Plant, it was possible to accompany of the operational acting of the sugarcane harvester used during 03 crops, regarding the manners of flaws in the waterworks of the same ones, and, in one of the crops it was elaborated the total control of the waterworks of 5 harvesters. Based on the obtained data and the developed methodology it was possible to develop a software that specifies the electric outlet of decisions.
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Universidade Estadual de Campinas . Faculdade de Educação Física
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Os sistemas biológicos são surpreendentemente flexíveis pra processar informação proveniente do mundo real. Alguns organismos biológicos possuem uma unidade central de processamento denominada de cérebro. O cérebro humano consiste de 10(11) neurônios e realiza processamento inteligente de forma exata e subjetiva. A Inteligência Artificial (IA) tenta trazer para o mundo da computação digital a heurística dos sistemas biológicos de várias maneiras, mas, ainda resta muito para que isso seja concretizado. No entanto, algumas técnicas como Redes neurais artificiais e lógica fuzzy tem mostrado efetivas para resolver problemas complexos usando a heurística dos sistemas biológicos. Recentemente o numero de aplicação dos métodos da IA em sistemas zootécnicos tem aumentado significativamente. O objetivo deste artigo é explicar os princípios básicos da resolução de problemas usando heurística e demonstrar como a IA pode ser aplicada para construir um sistema especialista para resolver problemas na área de zootecnia.