Errors in diagnosing the disease is a critical risk that must be faced by any person giving treatment to the hospital. Medical treatment can not always be done with perfect accuracy. Lung cancer is one of the most dea...
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Errors in diagnosing the disease is a critical risk that must be faced by any person giving treatment to the hospital. Medical treatment can not always be done with perfect accuracy. Lung cancer is one of the most deadly disease that prone to misdiagnose. In general, some practitioners tend to “read” cancer in x-ray rontgen image as tumor this could be fatal. To generate a diagnose, a general practitioner use three kind of examination i.e : patient History, Radio logic examination, phisical examination. In this paper, Gray color for image indexing and retrieval are investigated. The features are derived based on the statistical distribution of Harralick feature from image sample. By utilizing the proposed invariant features, the similarity measure between query and database images provides reliable retrieval results.
A well know problem in the Wireless Sensor Network (WSN) research area is the usage of appropriate strategies to setup the sensor nodes such that they may accomplish sensing missions. This problem refers to the select...
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An important problem in Wireless Sensor Networks (WSN) is the occurrence of failures that lead to the disconnection of parts of the network, compromising the final results achieved by the WSN operation. A way to overc...
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Particle Swarm Optimization (PSO) algorithms have been proposed to solve engineering problems that require to find an optimal point of operation. There are several embedded applications which requires to solve online ...
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Photonic crystal cavities with tunable surface area via multiple-hole defects were investigated for increased resonance wavelength shifts upon exposure to variable-index analytes. Sensitivity was improved by 10% compa...
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Photonic crystal cavities with tunable surface area via multiple-hole defects were investigated for increased resonance wavelength shins upon exposure to variable-index analytes. Sensitivity was improved by 10% compar...
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Pure ZnO, pure MgO and 5 wt%MgO/ZnO nanocomposites were produced by flame spray pyrolysis (FSP) in a single step using zinc naphthenate and magnesium acetate tetrahydrate as Zn and Mg precursors. The particle properti...
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Artificial Immune Systems (AISs) are composed of techniques inspired by immunology. The clonal selection principle ensures the organism adaptation to fight invading antigens by an immune response activated by the bind...
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Artificial Immune Systems (AISs) are composed of techniques inspired by immunology. The clonal selection principle ensures the organism adaptation to fight invading antigens by an immune response activated by the binding of antigens and antibodies. As an immune response can be elicited even when the binding between an antigen and an antibody is not perfect, an approximate binding might suffice, and a Fuzzy Logic mechanism might be the most appropriate mechanism to control such process. This paper presents a novel hybrid model based on concepts of Immune and Fuzzy Systems with applications to pattern recognition problems. The preliminary results obtained here suggest the proposed model is a promising pattern recognition tool.
Crystal growth of Rb2CdI4 was performed by Czochralski method. Transparent colourless crystals with monoclinic structure were obtained. Temperature dependence of the dielectric constant along the b-axis was measured w...
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Cluster analysis is used in several research areas to classify data sets in groups by their similar characteristics. Metaheuristic-based techniques, such as Genetic Algorithms (GAs) and Ant Colony Optimization (ACO), ...
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Cluster analysis is used in several research areas to classify data sets in groups by their similar characteristics. Metaheuristic-based techniques, such as Genetic Algorithms (GAs) and Ant Colony Optimization (ACO), have been applied in order to increase the clustering algorithm performance. GA and ACO-based clustering algorithms are capable of efficiently and automatically forming natural groups from a pre-defined number of clusters. This paper presents a GA and an ACO algorithm to the clustering problem. Both algorithms were refined using local search in order to improve the clustering accuracy. The results are compared on numeric UCI databases.
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