61 resultados para Insetos - Identificação


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Unlike adult cancer, where cells usually originate from epithelial tissue and is linked to environmental factors, malignant tumors in childhood are mostly of embryonic origin and have a phase of rapid proliferation. When not started chemotherapy at this stage, the tumor increases in size, reducing their growth rate, thus reducing the response to chemotherapy. Childhood cancer is in Brazil, the second cause of mortality among children and adolescents from one to nineteen. His impact on the ranking of diseases becomes significantly important to public health since the first issue is related to accidents and violence. Many children are still sent to the centers of high complexity for cancer treatment with advanced stage disease. The delay in referral to diagnosis can be family, or the difficulty of access to the health sector, or the characteristics of the disease and lack of health staff regarding theme of childhood cancer. Before this problem, we aimed to assess the performance of health teams in the identification of child and adolescent symptoms of cancer in primary care, through the action research methodology, which includes the teaching-learning, seminars, describing the actions of the group and discussing the activities after the training. This study involved thirty-seven health professionals who provide care for children and adolescents in the USF Felipe Shrimp II, the Support Center for Children with Cancer and the pediatric hospital UFRN during the period from March to December 2010. The data were analyzed simultaneously to evaluate actions, following the direction of the analysis of ideas Freires, having as theoretical reference the primary health care. The diagnosis of current reality, as knowledge of the health team targeted for early identification of signs and symptoms raised through questioning, presented as generative themes: resistance to change, awareness of the need for apprehension of knowledge; prior knowledge through the media, fragmentation of the healthcare network, interfering with the operation of the reference and counter, the stigma of death, among others. The selected themes enabled the choice of content for the preparation of four seminars, such as implementation of collective action for discussion problematical. The teaching-learning process has allowed the study participants awareness of the problem and work through the knowledge acquired by interfering in decreasing the time interval between the identification of signs and symptoms of cancer and early specialist treatment. Their difficulties we are faced with a diagnosis of terminal cancer and associated with delayed access to laboratory tests and imaging necessary for the diagnosis of neoplasms. Thus, we find that when the team is consciously involved in the education process from identification of the problem situation, there may be significant changes in daily activities through awareness of being. However, we also realize that acquisition of knowledge and interest of the team are not enough, since to be efficiency of our service, we need an organization of cancer care network operating in the state of Rio Grande do Norte

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Infrastructure works are included in strategic areas for the social development. For that matter that all of the investments are very important for the social development. When the population has enough water and an acceptable quality, and it includes a wastewater gathering and its treatment, the whole society became less susceptible to the water diseases. Even the Water Supply and the Sewage depend for its perfect operation of reservoirs, or of the accumulation of water to provide the popular necessity, either due to retention or for the treatment wastewarer. These structures present very specific environmental conditions, because the microclimate created around them, like high environmental humidity and for the existence of many harmful substances for the concrete, such as chloride ions presents in water. The reservoir that compose the System of Water Supply of Natal were built between 1970s and 1980s, a period whom the technical and scientific community did not have in-depth studies about the reinforced concrete mechanism of deterioration. Therefore, these reservoirs have been suffered accelerated deterioration progress, and they have been shown many pathological manifestations strikingly visible. In front of all these problems this academic work aims to identify the generally conditions of conservation of all the reservoirs components of the Water Supply System of Natal. This academic work objectives to develop a recuperation plan for use in these reservoirs, in this academic work it was achieved all the survey of pathological manifestation existing in each reservoir. It was made with local visits, photographic recorders of all manifestations viii and realization of in loco tests. The other step consisted in a application of GDE/UnB metodolgy reformulated by Fonseca (2007). In the step of local visits in each reservoir it was evaluated carbonation depth, by spreading a phenolphthalein solution with 1% of concentration; evaluation of contamination of chlorides, by spreading silver nitrate solution with 1% of concentration, and evaluation of width cracks. After the conclusion of all the testings, it was established that all reservoir, studied in this academic work, have showed an advanced deteriorating condition. It´s presents prevalent pathological manifestations as unacceptable cracks, spots, efflorescence and reinforcement corrosion, and in some cases, chlorides contamination. After the conclusion of the testings and its concatenation it was able to implementing, using GDE/UnB methodology, the order of the restoration its service life and initial safety conditions

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This paper presents a new multi-model technique of dentification in ANFIS for nonlinear systems. In this technique, the structure used is of the fuzzy Takagi-Sugeno of which the consequences are local linear models that represent the system of different points of operation and the precursors are membership functions whose adjustments are realized by the learning phase of the neuro-fuzzy ANFIS technique. The models that represent the system at different points of the operation can be found with linearization techniques like, for example, the Least Squares method that is robust against sounds and of simple application. The fuzzy system is responsible for informing the proportion of each model that should be utilized, using the membership functions. The membership functions can be adjusted by ANFIS with the use of neural network algorithms, like the back propagation error type, in such a way that the models found for each area are correctly interpolated and define an action of each model for possible entries into the system. In multi-models, the definition of action of models is known as metrics and, since this paper is based on ANFIS, it shall be denominated in ANFIS metrics. This way, ANFIS metrics is utilized to interpolate various models, composing a system to be identified. Differing from the traditional ANFIS, the created technique necessarily represents the system in various well defined regions by unaltered models whose pondered activation as per the membership functions. The selection of regions for the application of the Least Squares method is realized manually from the graphic analysis of the system behavior or from the physical characteristics of the plant. This selection serves as a base to initiate the linear model defining technique and generating the initial configuration of the membership functions. The experiments are conducted in a teaching tank, with multiple sections, designed and created to show the characteristics of the technique. The results from this tank illustrate the performance reached by the technique in task of identifying, utilizing configurations of ANFIS, comparing the developed technique with various models of simple metrics and comparing with the NNARX technique, also adapted to identification

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In this work a modification on ANFIS (Adaptive Network Based Fuzzy Inference System) structure is proposed to find a systematic method for nonlinear plants, with large operational range, identification and control, using linear local systems: models and controllers. This method is based on multiple model approach. This way, linear local models are obtained and then those models are combined by the proposed neurofuzzy structure. A metric that allows a satisfactory combination of those models is obtained after the structure training. It results on plant s global identification. A controller is projected for each local model. The global control is obtained by mixing local controllers signals. This is done by the modified ANFIS. The modification on ANFIS architecture allows the two neurofuzzy structures knowledge sharing. So the same metric obtained to combine models can be used to combine controllers. Two cases study are used to validate the new ANFIS structure. The knowledge sharing is evaluated in the second case study. It shows that just one modified ANFIS structure is necessary to combine linear models to identify, a nonlinear plant, and combine linear controllers to control this plant. The proposed method allows the usage of any identification and control techniques for local models and local controllers obtaining. It also reduces the complexity of ANFIS usage for identification and control. This work has prioritized simpler techniques for the identification and control systems to simplify the use of the method

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In last decades, neural networks have been established as a major tool for the identification of nonlinear systems. Among the various types of networks used in identification, one that can be highlighted is the wavelet neural network (WNN). This network combines the characteristics of wavelet multiresolution theory with learning ability and generalization of neural networks usually, providing more accurate models than those ones obtained by traditional networks. An extension of WNN networks is to combine the neuro-fuzzy ANFIS (Adaptive Network Based Fuzzy Inference System) structure with wavelets, leading to generate the Fuzzy Wavelet Neural Network - FWNN structure. This network is very similar to ANFIS networks, with the difference that traditional polynomials present in consequent of this network are replaced by WNN networks. This paper proposes the identification of nonlinear dynamical systems from a network FWNN modified. In the proposed structure, functions only wavelets are used in the consequent. Thus, it is possible to obtain a simplification of the structure, reducing the number of adjustable parameters of the network. To evaluate the performance of network FWNN with this modification, an analysis of network performance is made, verifying advantages, disadvantages and cost effectiveness when compared to other existing FWNN structures in literature. The evaluations are carried out via the identification of two simulated systems traditionally found in the literature and a real nonlinear system, consisting of a nonlinear multi section tank. Finally, the network is used to infer values of temperature and humidity inside of a neonatal incubator. The execution of such analyzes is based on various criteria, like: mean squared error, number of training epochs, number of adjustable parameters, the variation of the mean square error, among others. The results found show the generalization ability of the modified structure, despite the simplification performed

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A new method to perform TCP/IP fingerprinting is proposed. TCP/IP fingerprinting is the process of identify a remote machine through a TCP/IP based computer network. This method has many applications related to network security. Both intrusion and defence procedures may use this process to achieve their objectives. There are many known methods that perform this process in favorable conditions. However, nowadays there are many adversities that reduce the identification performance. This work aims the creation of a new OS fingerprinting tool that bypass these actual problems. The proposed method is based on the use of attractors reconstruction and neural networks to characterize and classify pseudo-random numbers generators

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The present work describes the use of a mathematical tool to solve problems arising from control theory, including the identification, analysis of the phase portrait and stability, as well as the temporal evolution of the plant s current induction motor. The system identification is an area of mathematical modeling that has as its objective the study of techniques which can determine a dynamic model in representing a real system. The tool used in the identification and analysis of nonlinear dynamical system is the Radial Basis Function (RBF). The process or plant that is used has a mathematical model unknown, but belongs to a particular class that contains an internal dynamics that can be modeled.Will be presented as contributions to the analysis of asymptotic stability of the RBF. The identification using radial basis function is demonstrated through computer simulations from a real data set obtained from the plant

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Several mobile robots show non-linear behavior, mainly due friction phenomena between the mechanical parts of the robot or between the robot and the ground. Linear models are efficient in some cases, but it is necessary take the robot non-linearity in consideration when precise displacement and positioning are desired. In this work a parametric model identification procedure for a mobile robot with differential drive that considers the dead-zone in the robot actuators is proposed. The method consists in dividing the system into Hammerstein systems and then uses the key-term separation principle to present the input-output relations which shows the parameters from both linear and non-linear blocks. The parameters are then simultaneously estimated through a recursive least squares algorithm. The results shows that is possible to identify the dead-zone thresholds together with the linear parameters

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This work presents a modelling and identification method for a wheeled mobile robot, including the actuator dynamics. Instead of the classic modelling approach, where the robot position coordinates (x,y) are utilized as state variables (resulting in a non linear model), the proposed discrete model is based on the travelled distance increment Delta_l. Thus, the resulting model is linear and time invariant and it can be identified through classical methods such as Recursive Least Mean Squares. This approach has a problem: Delta_l can not be directly measured. In this paper, this problem is solved using an estimate of Delta_l based on a second order polynomial approximation. Experimental data were colected and the proposed method was used to identify the model of a real robot

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This work uses computer vision algorithms related to features in the identification of medicine boxes for the visually impaired. The system is for people who have a disease that compromises his vision, hindering the identification of the correct medicine to be ingested. We use the camera, available in several popular devices such as computers, televisions and phones, to identify the box of the correct medicine and audio through the image, showing the poor information about the medication, such: as the dosage, indication and contraindications of the medication. We utilize a model of object detection using algorithms to identify the features in the boxes of drugs and playing the audio at the time of detection of feauteres in those boxes. Experiments carried out with 15 people show that where 93 % think that the system is useful and very helpful in identifying drugs for boxes. So, it is necessary to make use of this technology to help several people with visual impairments to take the right medicine, at the time indicated in advance by the physician

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The traditional perimeter-based approach for computer network security (the castle and the moat model) hinders the progress of enterprise systems and promotes, both in administrators and users, the delusion that systems are protected. To deal with the new range of threats, a new data-safety oriented paradigm, called de-perimeterisation , began to be studied in the last decade. One of the requirements for the implementation of the de-perimeterised model of security is the definition of a safe and effective mechanism for federated identity. This work seeks to fill this gap by presenting the specification, modelling and implementation of a mechanism for federated identity, based on the combination of SAML and X.509 digital certificates stored in smart-cards, following the A3 standard of ICP-Brasil (Brazilian official certificate authority and PKI)

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A modelagem de processos industriais tem auxiliado na produção e minimização de custos, permitindo a previsão dos comportamentos futuros do sistema, supervisão de processos e projeto de controladores. Ao observar os benefícios proporcionados pela modelagem, objetiva-se primeiramente, nesta dissertação, apresentar uma metodologia de identificação de modelos não-lineares com estrutura NARX, a partir da implementação de algoritmos combinados de detecção de estrutura e estimação de parâmetros. Inicialmente, será ressaltada a importância da identificação de sistemas na otimização de processos industriais, especificamente a escolha do modelo para representar adequadamente as dinâmicas do sistema. Em seguida, será apresentada uma breve revisão das etapas que compõem a identificação de sistemas. Na sequência, serão apresentados os métodos fundamentais para detecção de estrutura (Modificado Gram- Schmidt) e estimação de parâmetros (Método dos Mínimos Quadrados e Método dos Mínimos Quadrados Estendido) de modelos. No trabalho será também realizada, através dos algoritmos implementados, a identificação de dois processos industriais distintos representados por uma planta de nível didática, que possibilita o controle de nível e vazão, e uma planta de processamento primário de petróleo simulada, que tem como objetivo representar um tratamento primário do petróleo que ocorre em plataformas petrolíferas. A dissertação é finalizada com uma avaliação dos desempenhos dos modelos obtidos, quando comparados com o sistema. A partir desta avaliação, será possível observar se os modelos identificados são capazes de representar as características estáticas e dinâmicas dos sistemas apresentados nesta dissertação

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Extended storage of refrigerated milk can lead to reduced quality of raw and processed milk, which is a consequence of the growth and metabolic activities of psychrotrophic bacteria, able to grow under 7oC or lower temperatures. Although most of these microorganisms are destroyed by heat treatment, some have the potential to produce termoresistant proteolytic and lipolytic enzymes that can survive even UHT processing and reduce the processed products quality. Recently, the IN 51 determineds that milk should be refrigerated and stored at the farm what increased the importance of this group of microorganisms. In this work, psychrotrophic bacteria were isolated from 20 communitarian bulk tanks and 23 individual bulk tanks from dairy farms located at Zona da Mata region of Minas Gerais State and from southeastern Rio de Janeiro. Selected milk dilutions were plated on standard agar and after incubation for 10 days at 7oC, five colonies were isolated, firstly using nutrient agar and after using McConkey agar for 24 hours at 21oC. The isolates were identified by morphology, Gram stain method, catalase production, fermentative/oxidative metabolism and by API 20E, API 20NE, API Staph, API Coryne or API 50 CH (BioMerieux). In order to ensure reproductibility, API was repeated for 50% of the isolates. Species identification was considered when APILAB indexes reached 75% or higher. 309 strains were isolated, 250 Gram negative and 59 Gram positive. 250 Gram negative isolates were identified as: Acinetobacter spp. (39), Aeromonas spp. (07), A. Hydrophila (16), A. sobria (1), A. caviae (1), Alcaligenes feacalis (1), Burkholderia cepacia (12), Chryseomonas luteola (3), Enterobacter sp. (1), Ewingella americana(6), Hafnia alvei (7), Klebsiella sp. (1), Klebsiella oxytoca (10), Yersinia spp. (2), Methylobacterium mesophilicum (1), Moraxella spp. (4), Pantoea spp. (16), Pasteurella sp. (1), Pseudomonas spp. (10), P. fluorescens (94), P. putida (3), Serratia spp. (3), Sphigomonas paucomobilis (1). Five isolates kept unidentified. Pseudomonas was the predominant bacteria found (43%) and P. fluorescens the predominant species (37.6%), in accordance with previous reports. Qualitative analysis of proteolytic and lipolytic activity was based on halo formation using caseinate agar and tributirina agar during 72 hours at 21oC and during 10 days at 4°C, 10oC and 7°C. Among 250 Gram negative bacteria found, 104 were identified as Pseudomonas spp. and 60,57% of this group showed proteolytic and lipolytic acitivities over all four studied temperatures. 20% of Acinetobacter, Aeromonas, Alcaligenes, Burkholderia, Chryseomonas, Methylobacterium, Moraxella presented only lipolytic activity. Some isolates presented enzymatic activity in one or more studied temperatures. Among Gram positive bacteria, 30.51% were proteolytic and lipolytic at 10oC, 8.47% were proteolytic at 7oC, 10oC, and 21oC, 8.47% were proteolytic at all studied temperatures (4oC, 7oC, 10oC and 21oC) and 3.38% were proteolytic only at 21oC. At 4oC, only one isolate showed proteolytic activity and six isolates were lipolytic. In relation to Gram negative microorganisms, 4% were proteolytic and lipolytic at 7oC, 10oC and 21oC, 10% were proteolytic at 10oC and 4.4% were lipolytic at 4oC, 7oC, 10oC and 21oC, while 6.4% of all isolates were proteolytic and lipolytic at 10oC and 21oC as well as lipolytic at 4oC and 7oC. These findings are in accordance with previous researches that pointed out Pseudomonas as the predominant psycrotrophic flora in stored refrigerated raw milk

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O estudo da variabilidade da precipitação é importante para o planejamento das atividades econômicas, possibilitando o uso mais eficiente e racional dos recursos hídricos. Dessa forma, o objetivo desta pesquisa é caracterizar o estado do Rio Grande do Norte com relação à variabilidade temporal da precipitação, agrupá-lo em regiões homogêneas e comparar diferentes técnicas de agrupamento. Para o estudo da variabilidade pluvial foram utilizados os índices: Grau de Concentração de Precipitação (PCD), que representa o grau em que a precipitação é distribuída ao longo do ano; e o Período de Concentração de Precipitação (PCP), que reflete o período no qual a precipitação está mais concentrada. Para a realização dos agrupamentos foram escolhidas as variáveis: PCD, PCP, médias da precipitações anuais e médias das precipitações mensais. Posteriormente, foi aplicada a análise de agrupamento para obter grupos com características similares. Os resultados mostraram que as precipitações são melhor distribuídas na região leste do estado, neste caso, os meses mais chuvosos são de maio a agosto. Os municípios localizados nessa área possuem dois picos de chuvas, devido à atuação de dois sistemas: Perturbações Ondulatórias dos Alísios (POA s) e Zona de Convergência Intertropical (ZCIT). Nas regiões localizadas a oeste os meses que possuem maior concentração de chuvas são março e abril, neste caso temos apenas um pico de precipitação, devido a atuação da ZCIT. A identificação de áreas homogêneas favorece o planejamento adequado de acordo com as características de cada grupo formado e o RN pode foi dividido em 4 (quatro) regiões homogêneas. As técnicas de agrupamento utilizadas apresentaram resultados semelhantes, porém, sugere-se o uso de mais de uma técnica para que se possa analisar qual delas reflete melhor a realidade local. O estudo da variabilidade de precipitação, através dos índices estudados e do agrupamento realizado, são ferramentas adequadas ao planejamento ambiental e econômico