919 resultados para Criptografia de dados (Computação)


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The great diversity in the architecture of biomedical devices, coupled with their different communication protocols, has hindered the implementation of systems that need to make access to these devices. Given these differences, the need arises to provide access to such a transparent manner. In this sense, this paper proposes an embedded architecture, service-oriented, for access to biomedical devices, as a way to abstract the mechanism for writing and reading data on these devices, thereby contributing to the increase in quality and productivity of biomedical systems so as to enable that, the focus of the development team of biomedical software, is almost exclusively directed to its functional requirements

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This work develops a methodology for defining the maximum active power being injected into predefined nodes in the studied distribution networks, considering the possibility of multiple accesses of generating units. The definition of these maximum values is obtained from an optimization study, in which further losses should not exceed those of the base case, i.e., without the presence of distributed generation. The restrictions on the loading of the branches and voltages of the system are respected. To face the problem it is proposed an algorithm, which is based on the numerical method called particle swarm optimization, applied to the study of AC conventional load flow and optimal load flow for maximizing the penetration of distributed generation. Alternatively, the Newton-Raphson method was incorporated to resolution of the load flow. The computer program is performed with the SCILAB software. The proposed algorithm is tested with the data from the IEEE network with 14 nodes and from another network, this one from the Rio Grande do Norte State, at a high voltage (69 kV), with 25 nodes. The algorithm defines allowed values of nominal active power of distributed generation, in percentage terms relative to the demand of the network, from reference values

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It s notorious the advance of computer networks in recent decades, whether in relation to transmission rates, the number of interconnected devices or the existing applications. In parallel, it s also visible this progress in various sectors of the automation, such as: industrial, commercial and residential. In one of its branches, we find the hospital networks, which can make the use of a range of services, ranging from the simple registration of patients to a surgery by a robot under the supervision of a physician. In the context of both worlds, appear the applications in Telemedicine and Telehealth, which work with the transfer in real time of high resolution images, sound, video and patient data. Then comes a problem, since the computer networks, originally developed for the transfer of less complex data, is now being used by a service that involves high transfer rates and needs requirements for quality of service (QoS) offered by the network . Thus, this work aims to do the analysis and comparison of performance of a network when subjected to this type of application, for two different situations: the first without the use of QoS policies, and the second with the application of such policies, using as scenario for testing, the Metropolitan Health Network of the Federal University of Rio Grande do Norte (UFRN)

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Even living in the XXI century are still some difficulties in access to broadband Internet in several Brazilian cities, due to the purchasing power of people and lack of government investment. But even with these difficulties, we seek to encourage the use of wireless technology, which is based on the IEEE 802.11b protocol - also known as Wi-Fi (Wireless Fidelity) Wireless Fidelity Communications, having wide range of commercial applications in the world market, nationally and internationally. In Brazil, this technology is in full operation in major cities and has proved attractive in relation to the access point to multipoint and point-to-point. This paper is a comparative analysis of prediction field, using models based on the prediction of propagation loss. To validate the techniques used here, the Okumura-Hata models, modified Okumura-Hata, Walfisch-Ikegami model, were applied to a wireless computer network, located in the neighborhood of Cajupiranga in the city of Melbourn, in Rio Grande do Norte . They are used for networking wireless 802.11b, using the Mobile Radio to measure signal levels, beyond the heights of the antennas and distances from the transmitter. The performance data versus distance are added to the graphs generated and compared with results obtained through calculations of propagation models

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The evolution of automation in recent years made possible the continuous monitoring of the processes of industrial plants. With this advance, the amount of information that automation systems are subjected to increased significantly. The alarms generated by the monitoring equipment are a major contributor to this increase, and the equipments are usually deployed in industrial plants without a formal methodology, which entails an increase in the number of alarms generated, thus overloading the alarm system and therefore the operators of such plants. In this context, the works of alarm management comes up with the objective of defining a formal methodology for installation of new equipment and detect problems in existing settings. This thesis aims to propose a set of metrics for the evaluation of alarm systems already deployed, so that you can identify the health of this system by analyzing the proposed indices and comparing them with parameters defined in the technical norms of alarm management. In addition, the metrics will track the work of alarm management, verifying if it is improving the quality of the alarm system. To validate the proposed metrics, data from actual process plants of the petrochemical industry were used

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This work presents the design and construction of an X-Y table of two degrees of freedom, as well as the development of a fuzzy system for its position and trajectory control. The table is composed of two bases that move perpendicularly to each other in the horizontal plane, and are driven by two DC motors. Base position is detected by position sensors attached to the motor axes. A data acquisition board performs the interface between a laptop and the plant. The fuzzy system algorithm was implemented in LabVIEW® programming environment that processes the sensors signals and determines the control variables values that drive the motors. Experimental results using position reference signals (step type signal) and straight and circular paths reference signals are presented to demonstrate the dynamic behavior of fuzzy system

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Due to the large amount of television content, which emerged from the Digital TV, viewers are facing a new challenge, how to find interesting content intuitively and efficiently. The Personalized Electronic Programming Guides (pEPG) arise as an answer to this complex challenge. We propose TrendTV a layered architecture that allows the formation of social networks among viewers of Interactive Digital TV based on online microblogging. Associated with a pEPG, this social network allows the viewer to perform content filtering on a particular subject from the indications made by other viewers of his network. Allowing the viewer to create his own indications for a particular content when it is displayed, or to analyze the importance of a particular program online, based on these indications. This allows any user to perform filtering on content and generate or exchange information with other users in a flexible and transparent way, using several different devices (TVs, Smartphones, Tablets or PCs). Moreover, this architecture defines a mechanism to perform the automatic exchange of channels based on the best program that is showing at the moment, suggesting new components to be added to the middleware of the Brazilian Digital TV System (Ginga). The result is a constructed and dynamic database containing the classification of several TV programs as well as an application to automatically switch to the best channel of the moment

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Recently, an amazing development has been observed in telecommunication systems. Two good examples of this development are observed in mobile communication and aerospace systems. This impressive development is related to the increasing need for receiving and transmitting communication signals. Particularly, this development has required the study of new antennas and filters. This work presents a fullwave analysis of reflectarrays. The considered structures are composed by arrays of rectangular conducting patches printed on multilayer dieletric substrates, that are mounted on a ground plane. The analysis is developed in the spectral domain, using an equivalent transmission line method in combination with Galerkin method. Results for the reflection coefficient of these structures are presented and compared to those available in the literature. A good agreement was observed. Particularly, the developed analysis uses the transmission lines theory in combination with the incident potentials and the field continuity equations, at the structures interfaces, for obtaining the scattered field components expressions as function of the patch surface currents and of the incident field. Galerkin method is used to determine the unknown coefficients in the boundary value problem. Curves for the reflection coefficient of several reflectarray geometries are presented as function of frequency and of the structural parameters

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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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The introduction of new digital services in the cellular networks, in transmission rates each time more raised, has stimulated recent research that comes studying ways to increase the data communication capacity and to reduce the delays in forward and reverse links of third generation WCDMA systems. These studies have resulted in new standards, known as 3.5G, published by 3GPP group, for the evolution of the third generation of the cellular systems. In this Masters Thesis the performance of a 3G WCDMA system, with diverse base stations and thousand of users is developed with assists of the planning tool NPSW. Moreover the performance of the 3.5G techniques hybrid automatic retransmission and multi-user detection with interference cancellation, candidates for enhance the WCDMA uplink capacity, is verified by means of computational simulations in Matlab of the increase of the data communication capacity and the reduction of the delays in the retransmission of packages of information

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This work shows a theoretical analysis together with numerical and experimental results of transmission characteristics from the microstrip bandpass filters with different geometries. These filters are built over isotropic dielectric substrates. The numerical analysis is made by specifical commercial softwares, like Ansoft Designer and Agilent Advanced Design System (ADS). In addition to these tools, a Matlab Script was built to analyze the filters through the Finite-Difference Time-Domain (FDTD) method. The filters project focused the development of the first stage of filtering in the ITASAT s Transponder receptor, and its integration with the others systems. Some microstrip filters architectures have been studied, aiming the viability of implementation and suitable practical application for the purposes of the ITASAT Project due to its lowspace occupation in the lower UHF frequencies. The ITASAT project is a Universityexperimental project which will build a satellite to integrate the Brazilian Data Collect System s satellite constellation, with efforts of many Brazilian institutes, like for example AEB (Brazilian Spatial Agency), ITA (Technological Institute of Aeronautics), INPE/CRN (National Institute of Spatial Researches/Northeastern Regional Center) and UFRN (Federal University of Rio Grande do Norte). Comparisons were made between numerical and experimental results of all filters, where good agreements could be noticed, reaching the most of the objectives. Also, post-work improvements were suggested.

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This paper aims to design and develop a control and monitoring system of vending machines, based on a Central Processing Unit with peripheral Internet communication. Coupled with the condom vending machines, a data acquisition module will be connected to the original circuits in order to collect and send, via internet, the information to the healthy government agencies, in the form of charts and reports. In the face of this, such agencies may analyze these data and compare them with the rates of reduction, in medium or long term, of the STD/AIDS in their respective regions, after the implementation of these vending machines, together with the conventional preventing programs. Reading the methodology, this paper is about an explaining and bibliography research, with the aspect of a qualitative-quantitative methodology, presenting a deductive method of approach and an indirect documentation technique research. About the results of the tests and simulations, we concluded that the implementation of this system will have the same success in any other type of dispenser machine

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One of the most important goals of bioinformatics is the ability to identify genes in uncharacterized DNA sequences on world wide database. Gene expression on prokaryotes initiates when the RNA-polymerase enzyme interacts with DNA regions called promoters. In these regions are located the main regulatory elements of the transcription process. Despite the improvement of in vitro techniques for molecular biology analysis, characterizing and identifying a great number of promoters on a genome is a complex task. Nevertheless, the main drawback is the absence of a large set of promoters to identify conserved patterns among the species. Hence, a in silico method to predict them on any species is a challenge. Improved promoter prediction methods can be one step towards developing more reliable ab initio gene prediction methods. In this work, we present an empirical comparison of Machine Learning (ML) techniques such as Na¨ýve Bayes, Decision Trees, Support Vector Machines and Neural Networks, Voted Perceptron, PART, k-NN and and ensemble approaches (Bagging and Boosting) to the task of predicting Bacillus subtilis. In order to do so, we first built two data set of promoter and nonpromoter sequences for B. subtilis and a hybrid one. In order to evaluate of ML methods a cross-validation procedure is applied. Good results were obtained with methods of ML like SVM and Naïve Bayes using B. subtilis. However, we have not reached good results on hybrid database

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Nowadays, classifying proteins in structural classes, which concerns the inference of patterns in their 3D conformation, is one of the most important open problems in Molecular Biology. The main reason for this is that the function of a protein is intrinsically related to its spatial conformation. However, such conformations are very difficult to be obtained experimentally in laboratory. Thus, this problem has drawn the attention of many researchers in Bioinformatics. Considering the great difference between the number of protein sequences already known and the number of three-dimensional structures determined experimentally, the demand of automated techniques for structural classification of proteins is very high. In this context, computational tools, especially Machine Learning (ML) techniques, have become essential to deal with this problem. In this work, ML techniques are used in the recognition of protein structural classes: Decision Trees, k-Nearest Neighbor, Naive Bayes, Support Vector Machine and Neural Networks. These methods have been chosen because they represent different paradigms of learning and have been widely used in the Bioinfornmatics literature. Aiming to obtain an improvment in the performance of these techniques (individual classifiers), homogeneous (Bagging and Boosting) and heterogeneous (Voting, Stacking and StackingC) multiclassification systems are used. Moreover, since the protein database used in this work presents the problem of imbalanced classes, artificial techniques for class balance (Undersampling Random, Tomek Links, CNN, NCL and OSS) are used to minimize such a problem. In order to evaluate the ML methods, a cross-validation procedure is applied, where the accuracy of the classifiers is measured using the mean of classification error rate, on independent test sets. These means are compared, two by two, by the hypothesis test aiming to evaluate if there is, statistically, a significant difference between them. With respect to the results obtained with the individual classifiers, Support Vector Machine presented the best accuracy. In terms of the multi-classification systems (homogeneous and heterogeneous), they showed, in general, a superior or similar performance when compared to the one achieved by the individual classifiers used - especially Boosting with Decision Tree and the StackingC with Linear Regression as meta classifier. The Voting method, despite of its simplicity, has shown to be adequate for solving the problem presented in this work. The techniques for class balance, on the other hand, have not produced a significant improvement in the global classification error. Nevertheless, the use of such techniques did improve the classification error for the minority class. In this context, the NCL technique has shown to be more appropriated

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One of the most important decisions to turn a substation automatic and no attended it relates to the communication media between this substation and Operation Center. Generally energy companies uses radio or optic fiber, depending of distances and infrastructure of each situation. This rule applies to common substations. Mobile substations are a particular case, therefore they are conceived for use at provisional situations, emergencies, preventive or corrective maintenance. Thus the telecommunication solution used at common substations are not applied so easily to mobile substations, due absence of infrastructure (media) or difficulty to insert the mobile substation data in existing automation network not long. The ideal media must supply covering in a great geographic area to satisfy presented requirements. The implantation costs of this big infrastructure are expensive, however a existing operator may be used. Two services that fulfill that requirements are satellite and cellular telephony. This work presents a solution for automation of mobile substations through satellite. It was successfully implanted at a brazilian electric energy concessionaire named COSERN. The operation became transparent to operators. Other gotten benefits had been operational security, quality in the supply of electric energy and costs reduction. The project presented is a new solution, designed to substations and general applications where few data should be transmitted, but there is difficulties in relation to the media. Despite the satellite having been used, the same resulted can be gotten using celullar telephony, through Short Messages or packet networks as GPRS or EDGE.