846 resultados para COMPUTER-AIDED MOLECULAR DESIGN


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INTRODUCTION AND GOALS: Genus Bursaphelenchus includes several pests of the world importance for the rural economy, the most dangerous are the Bursaphelenchus xylophilus (the pinewood nematode caused decline of the pine trees in south Asia and in one spot area in Europe, Portugal, Peninsula de Setubal) and the Bursaphelenchus cocophilus, causing the decline of coco-palm plantations in Carribean and Latin American regions. The peculiarity of the host-parasite association of the genus that the nematode life cycle includes three trophic components: plant (mostly a tree), insect vector and a fungus. Goals of the presentation is to list all species of the world fauna and all efficient diagnostic characters, then create the identification tool and analyze the similarity of species and possible ways and causes of the host-parasite evolution of the group. RESULTS: Complete list of species with synonymy and a catalogue of all efficient diagnostic characters with their states, selected from papers of the most experienced taxonomists of the genus, are given for the genus Bursaphelenchus. List of known records of Bursaphelenchus species with names of natural vectors and plants and their families is given (for world pests the most important groups of trees and insects are listed). The tabular, traditional and computer-aided keys are presented. Dendrograms of species relationships (UPGMA, standard distance: mean character difference) based on all efficient taxonomic characters and separately on the spicule characters only, are given. Discussion whether the species groups are natural or purely diagnostic ones is based on the relationships dendrograms and the vector and associated plant ranges of Bursaphelenchus species; the xylophilus species group (B. xylophilus, B. abruptus, B. baujardi, B. conicaudatus, B. eroshenkii, B. fraudulentus, B. kolymensis, B. luxuriosae; B. mucronatus), the hunti group (B. hunti, B. seani, B. kevini and B. fungivorus) are probably the natural ones. CONCLUSIONS: The parasitic nematode association includes three trophic components: plant, insect vector and fungus. The initial insect-plant complex Scolytidae-Pinaceae is changeable and only in rare occasions the change of the preferred vector to Cerambycidae (the xylophilus group), Hymenoptera (the hunti group) led to formation of the natural species-groups. From the analysis it is clear that although the vector range is changeable it is comparatively more important for the evolution of the genus Bursaphelenchus than associations with plants at the family level. Data on the fungi species (3rd component in natural Bursaphelenchus associations) are insufficient for the detailed comparative analysis.

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Os estudos de maquinabilidade de biomateriais e outros materiais aplicados na área médica são extensos. Todavia, muitos destes estudos recorrem a modelos de geometria regular e operações elementares de maquinagem. Relativamente a estas, os estudos académicos atualmente disponíveis mostram que a tecnologia preferencial é o torneamento, opção que se fundamenta na simplicidade de análise (corte ortogonal). Saliente-se ainda que, neste contexto, a liga de titânio Ti-6Al-4V constitui o biomaterial mais utilizado. Numa perspetiva complementar, refira-se que as publicações científicas evidenciam que a informação disponível sobre a fresagem Ti-6Al-4V não é muito extensa e a do Co-28Cr-6Mo é quase inexistente. A presente dissertação enquadra-se neste domínio e representa mais uma contribuição para o estudo da maquinabilidade das ligas de Titânio e de crómio-cobalto. A aplicação de operações de maquinagem complexas, através do recurso a programas informáticos de fabrico assistido por computador (CAM), em geometrias complexas, como é o caso das próteses femorais anatómicas, e o estudo comparativo da maquinabilidade das ligas Co-28Cr-6Mo e Ti-6Al-4V, constituem os objetivos fundamentais deste trabalho de doutoramento. Neste trabalho aborda-se a problemática da maquinabilidade das ligas metálicas usadas nos implantes ortopédicos, nomeadamente as ligas de titânio, de crómiocobalto e os aços Inoxidáveis. Efetua-se ainda um estudo da maquinagem de uma prótese femoral com uma forma geométrica complexa, onde as operações de corte foram geradas recorrendo às tecnologias de fabrico assistido por computador (CAD/CAM). Posteriormente, procedeu-se ao estudo da maquinabilidade das duas ligas usadas neste trabalho, dando uma atenção particular à determinação das forças de corte para diferentes velocidades de corte. Para além da monitorização da evolução da força de corte, o desgaste das ferramentas, a dureza e a rugosidade foram avaliadas, em função da velocidade de corte imposta. Por fim, com base nas estratégias de maquinagem adotadas, analisa-se a maquinabilidade e selecionam-se os parâmetros de corte mais favoráveis para as ligas de Titânio e Crómio-cobalto. Os resultados obtidos mostram que a liga de crómio-cobalto induz maior valor de força de corte do que a liga de titânio. Observa-se um aumento progressivo das forças de corte quando a velocidade de corte aumenta, até atingir o valor máximo para a velocidade de corte de 80m/min, após a qual, a força de corte tende a diminuir. Apesar do fabricante das ferramentas recomendar a velocidade de corte de 50 m/min para ambos os materiais, conclui-se que a velocidade de corte de 65 m/min induz o mesmo desgaste na ferramenta de corte no caso da liga de titânio, e menor desgaste no caso da liga de crómio-cobalto.

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Trabalho Final de Mestrado para obtenção do grau de mestre em Engenharia Química e Biológica

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Trabalho Final de Mestrado para obtenção do Grau de Mestre em Engenharia Química e Biológica

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Electricity markets are complex environments, involving a large number of different entities, playing in a dynamic scene to obtain the best advantages and profits. MASCEM (Multi-Agent System for Competitive Electricity Markets) is a multi-agent electricity market simulator that models market players and simulates their operation in the market. Market players are entities with specific characteristics and objectives, making their decisions and interacting with other players. This paper presents a methodology to provide decision support to electricity market negotiating players. This model allows integrating different strategic approaches for electricity market negotiations, and choosing the most appropriate one at each time, for each different negotiation context. This methodology is integrated in ALBidS (Adaptive Learning strategic Bidding System) – a multiagent system that provides decision support to MASCEM's negotiating agents so that they can properly achieve their goals. ALBidS uses artificial intelligence methodologies and data analysis algorithms to provide effective adaptive learning capabilities to such negotiating entities. The main contribution is provided by a methodology that combines several distinct strategies to build actions proposals, so that the best can be chosen at each time, depending on the context and simulation circumstances. The choosing process includes reinforcement learning algorithms, a mechanism for negotiating contexts analysis, a mechanism for the management of the efficiency/effectiveness balance of the system, and a mechanism for competitor players' profiles definition.

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Electricity markets are complex environments, involving a large number of different entities, with specific characteristics and objectives, making their decisions and interacting in a dynamic scene. Game-theory has been widely used to support decisions in competitive environments; therefore its application in electricity markets can prove to be a high potential tool. This paper proposes a new scenario analysis algorithm, which includes the application of game-theory, to evaluate and preview different scenarios and provide players with the ability to strategically react in order to exhibit the behavior that better fits their objectives. This model includes forecasts of competitor players’ actions, to build models of their behavior, in order to define the most probable expected scenarios. Once the scenarios are defined, game theory is applied to support the choice of the action to be performed. Our use of game theory is intended for supporting one specific agent and not for achieving the equilibrium in the market. MASCEM (Multi-Agent System for Competitive Electricity Markets) is a multi-agent electricity market simulator that models market players and simulates their operation in the market. The scenario analysis algorithm has been tested within MASCEM and our experimental findings with a case study based on real data from the Iberian Electricity Market are presented and discussed.

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Smart Grids (SGs) have emerged as the new paradigm for power system operation and management, being designed to include large amounts of distributed energy resources. This new paradigm requires new Energy Resource Management (ERM) methodologies considering different operation strategies and the existence of new management players such as several types of aggregators. This paper proposes a methodology to facilitate the coalition between distributed generation units originating Virtual Power Players (VPP) considering a game theory approach. The proposed approach consists in the analysis of the classifications that were attributed by each VPP to the distributed generation units, as well as in the analysis of the previous established contracts by each player. The proposed classification model is based in fourteen parameters including technical, economical and behavioural ones. Depending of the VPP strategies, size and goals, each parameter has different importance. VPP can also manage other type of energy resources, like storage units, electric vehicles, demand response programs or even parts of the MV and LV distribution network. A case study with twelve VPPs with different characteristics and one hundred and fifty real distributed generation units is included in the paper.

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Dissertation to obtain the degree of Master in Electrical and Computer Engineering

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Adolescent idiopathic scoliosis (AIS) is a deformity of the spine manifested by asymmetry and deformities of the external surface of the trunk. Classification of scoliosis deformities according to curve type is used to plan management of scoliosis patients. Currently, scoliosis curve type is determined based on X-ray exam. However, cumulative exposure to X-rays radiation significantly increases the risk for certain cancer. In this paper, we propose a robust system that can classify the scoliosis curve type from non invasive acquisition of 3D trunk surface of the patients. The 3D image of the trunk is divided into patches and local geometric descriptors characterizing the surface of the back are computed from each patch and forming the features. We perform the reduction of the dimensionality by using Principal Component Analysis and 53 components were retained. In this work a multi-class classifier is built with Least-squares support vector machine (LS-SVM) which is a kernel classifier. For this study, a new kernel was designed in order to achieve a robust classifier in comparison with polynomial and Gaussian kernel. The proposed system was validated using data of 103 patients with different scoliosis curve types diagnosed and classified by an orthopedic surgeon from the X-ray images. The average rate of successful classification was 93.3% with a better rate of prediction for the major thoracic and lumbar/thoracolumbar types.

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A method for computer- aided diagnosis of micro calcification clusters in mammograms images presented . Micro calcification clus.eni which are an early sign of bread cancer appear as isolated bright spots in mammograms. Therefore they correspond to local maxima of the image. The local maxima of the image is lint detected and they are ranked according to it higher-order statistical test performed over the sub band domain data

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After skin cancer, breast cancer accounts for the second greatest number of cancer diagnoses in women. Currently the etiologies of breast cancer are unknown, and there is no generally accepted therapy for preventing it. Therefore, the best way to improve the prognosis for breast cancer is early detection and treatment. Computer aided detection systems (CAD) for detecting masses or micro-calcifications in mammograms have already been used and proven to be a potentially powerful tool , so the radiologists are attracted by the effectiveness of clinical application of CAD systems. Fractal geometry is well suited for describing the complex physiological structures that defy the traditional Euclidean geometry, which is based on smooth shapes. The major contribution of this research include the development of • A new fractal feature to accurately classify mammograms into normal and normal (i)With masses (benign or malignant) (ii) with microcalcifications (benign or malignant) • A novel fast fractal modeling method to identify the presence of microcalcifications by fractal modeling of mammograms and then subtracting the modeled image from the original mammogram. The performances of these methods were evaluated using different standard statistical analysis methods. The results obtained indicate that the developed methods are highly beneficial for assisting radiologists in making diagnostic decisions. The mammograms for the study were obtained from the two online databases namely, MIAS (Mammographic Image Analysis Society) and DDSM (Digital Database for Screening Mammography.

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Image processing has been a challenging and multidisciplinary research area since decades with continuing improvements in its various branches especially Medical Imaging. The healthcare industry was very much benefited with the advances in Image Processing techniques for the efficient management of large volumes of clinical data. The popularity and growth of Image Processing field attracts researchers from many disciplines including Computer Science and Medical Science due to its applicability to the real world. In the meantime, Computer Science is becoming an important driving force for the further development of Medical Sciences. The objective of this study is to make use of the basic concepts in Medical Image Processing and develop methods and tools for clinicians’ assistance. This work is motivated from clinical applications of digital mammograms and placental sonograms, and uses real medical images for proposing a method intended to assist radiologists in the diagnostic process. The study consists of two domains of Pattern recognition, Classification and Content Based Retrieval. Mammogram images of breast cancer patients and placental images are used for this study. Cancer is a disaster to human race. The accuracy in characterizing images using simplified user friendly Computer Aided Diagnosis techniques helps radiologists in detecting cancers at an early stage. Breast cancer which accounts for the major cause of cancer death in women can be fully cured if detected at an early stage. Studies relating to placental characteristics and abnormalities are important in foetal monitoring. The diagnostic variability in sonographic examination of placenta can be overlooked by detailed placental texture analysis by focusing on placental grading. The work aims on early breast cancer detection and placental maturity analysis. This dissertation is a stepping stone in combing various application domains of healthcare and technology.

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Speckle noise formed as a result of the coherent nature of ultrasound imaging affects the lesion detectability. We have proposed a new weighted linear filtering approach using Local Binary Patterns (LBP) for reducing the speckle noise in ultrasound images. The new filter achieves good results in reducing the noise without affecting the image content. The performance of the proposed filter has been compared with some of the commonly used denoising filters. The proposed filter outperforms the existing filters in terms of quantitative analysis and in edge preservation. The experimental analysis is done using various ultrasound images

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A compact coplanar waveguide-fed (CPW) monopole antenna for ultra-wideband wireless communication is presented. The proposed antenna comprises of a CPW-fed beveled rectangular patch with a modified slotted ground. The overall size of the antenna is 30 mm 27 mm 1.6 mm. The lower edge of the band is attained by properly decoupling the resonant frequencies due to the extended ground plane and the beveled rectangular patch of the antenna. The upper edge of the radiating band is enhanced by beveling the ground plane corners near the feed point. Experimental results show that the designed antenna operates in the 2.7–12 GHz band, for S11 10 dB with a gain of 2.7–5 dBi. Both the frequency domain and time domain characteristics of the antenna are investigated using antenna transfer function. It is observed that the antenna exhibits identical radiation patterns and reasonable transient characteristics over the entire operating band

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A compact coplanar waveguide (CPW)-fed uniplanar antenna with harmonic suppression characteristics is presented. The above characteristics are achieved by properly modifying the ground plane and adjusting the signal strip of an open-ended CPW-fed transmission line. The simulated and experimental characteristics of the antenna are presented, compared, and discussed.