40 resultados para Plantas alucinógenas - Identificação


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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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The present work has as objective to present a method of project and implementation of controllers PID, based on industrial instrumentation. An automatic system of auto-tunning of controllers PID will be presented, for systems of first and second order. The software presented in this work is applied in controlled plants by PID controllers implemented in a CLP. Software is applied to make the auto-tunning of the parameters of controller PID of plants that need this tunning. Software presents two stages, the first one is the stage of identification of the system using the least square recursive algorithm and the second is the stage of project of the parameters of controller PID using the root locus algorithm. An important fact of this work is the use of industrial instrumentation for the accomplishment of the experiments. The experiments had been carried through in controlled real plants for controllers PID implemented in the CLP. Thus has not only one resulted obtained with theoreticians experiments made with computational programs, and yes resulted obtained of real systems. The experiments had shown good results gotten with developed software

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This work shows a study about the Generalized Predictive Controllers with Restrictions and their implementation in physical plants. Three types of restrictions will be discussed: restrictions in the variation rate of the signal control, restrictions in the amplitude of the signal control and restrictions in the amplitude of the Out signal (plant response). At the predictive control, the control law is obtained by the minimization of an objective function. To consider the restrictions, this minimization of the objective function is done by the use of a method to solve optimizing problems with restrictions. The chosen method was the Rosen Algorithm (based on the Gradient-projection). The physical plants in this study are two didactical systems of water level control. The first order one (a simple tank) and another of second order, which is formed by two tanks connected in cascade. The codes are implemented in C++ language and the communication with the system to be done through using a data acquisition panel offered by the system producer

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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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It proposes a established computational solution in the development of a software to construct species-specific primers, used to improve the diagnosis of virus of plant for PCR. Primers are indispensable to PCR reaction, besides providing the specificity of the diagnosis. Primer is a synthetic, short, single stranded piece of DNA, used as a starter in PCR technique. It flanks the sequence desired to amplify. Species-specific primers indicate the well known region of beginning and ending where the polymerase enzyme is going to amplify on a certain species, i.e. it is specific for only a species. Thus, the main objective of this work is to automatize the process of choice of primers, optimizing the specificity of chosen primers by the traditional method

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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