975 resultados para Interconexão em rede (Telecomunicações)
Resumo:
The occurrence of transients in electrocardiogram (ECG) signals indicates an electrical phenomenon outside the heart. Thus, the identification of transients has been the most-used methodology in medical analysis since the invention of the electrocardiograph (device responsible for benchmarking of electrocardiogram signals). There are few papers related to this subject, which compels the creation of an architecture to do the pre-processing of this signal in order to identify transients. This paper proposes a method based on the signal energy of the Hilbert transform of electrocardiogram, being an alternative to methods based on morphology of the signal. This information will determine the creation of frames of the MP-HA protocol responsible for transmitting the ECG signals through an IEEE 802.3 network to a computing device. That, in turn, may perform a process to automatically sort the signal, or to present it to a doctor so that he can do the sorting manually
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An alternative nonlinear technique for decoupling and control is presented. This technique is based on a RBF (Radial Basis Functions) neural network and it is applied to the synchronous generator model. The synchronous generator is a coupled system, in other words, a change at one input variable of the system, changes more than one output. The RBF network will perform the decoupling, separating the control of the following outputs variables: the load angle and flux linkage in the field winding. This technique does not require knowledge of the system parameters and, due the nature of radial basis functions, it shows itself stable to parametric uncertainties, disturbances and simpler when it is applied in control. The RBF decoupler is designed in this work for decouple a nonlinear MIMO system with two inputs and two outputs. The weights between hidden and output layer are modified online, using an adaptive law in real time. The adaptive law is developed by Lyapunov s Method. A decoupling adaptive controller uses the errors between system outputs and model outputs, and filtered outputs of the system to produce control signals. The RBF network forces each outputs of generator to behave like reference model. When the RBF approaches adequately control signals, the system decoupling is achieved. A mathematical proof and analysis are showed. Simulations are presented to show the performance and robustness of the RBF network
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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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This work presents a description of models development at DigSILENT PowerFactoryTM program for the transient stability study in power systems with wind turbine. The main goal is to make available means to use a dynamic simulation program in power systems, widely published, and utilize it as a tool that helps in programs results evaluations used for this intent. The process of simulations and analyses results starts after the models setting description phase. The results obtained by the DigSILENT PowerFactoryTM and ATP, program chosen to the validation also international recognized, are compared during this phase. The main tools and guide lines of PowerFactoryTM program use are presented here, directing these elements to the solution of the approached problem. For the simulation it is used a real system which it will be connected a wind farm. Two different technologies of wind turbines were implemented: doubly-fed induction generator with frequency converter, connecting the rotor to the stator and to the grid, and synchronous wind generator with frequency converter, interconnecting the generator to the grid. Besides presenting the basic conceptions of dynamic simulation, it is described the implemented control strategies and models of turbine and converters. The stability of the wind turbine interconnected to grid is analyzed in many operational conditions, resultant of diverse kinds of disturbances
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Industrial automation networks is in focus and is gradually replacing older architectures of systems used in automation world. Among existing automation networks, most prominent standard is the Foundation Fieldbus (FF). This particular standard was chosen for the development of this work thanks to its complete application layer specification and its user interface, organized as function blocks and that allows interoperability among different vendors' devices. Nowadays, one of most seeked solutions on industrial automation are the indirect measurements, that consist in infering a value from measures of other sensors. This can be made through implementation of the so-called software sensors. One of the most used tools in this project and in sensor implementation are artificial neural networks. The absence of a standard solution to implement neural networks in FF environment makes impossible the development of a field-indirect-measurement project, besides other projects involving neural networks, unless a closed proprietary solution is used, which dos not guarantee interoperability among network devices, specially if those are from different vendors. In order to keep the interoperability, this work's goal is develop a solution that implements artificial neural networks in Foundation Fieldbus industrial network environment, based on standard function blocks. Along the work, some results of the solution's implementation are also presented
Resumo:
The main objective of work is to show procedures to implement intelligent control strategies. This strategies are based on fuzzy scheduling of PID controllers, by using only standard function blocks of this technology. Then, the standardization of Foundation Fieldbus is kept. It was developed an environment to do the necessary tests, it validates the propose. This environment is hybrid, it has a real module (the fieldbus) and a simulated module (the process), although the control signals and measurement are real. Then, it is possible to develop controllers projects. In this work, a fuzzy supervisor was developed to schedule a network of PID controller for a non-linear plant. Analyzing its performance results to the control and regulation problem
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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.
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Attacks to devices connected to networks are one of the main problems related to the confidentiality of sensitive data and the correct functioning of computer systems. In spite of the availability of tools and procedures that harden or prevent the occurrence of security incidents, network devices are successfully attacked using strategies applied in previous events. The lack of knowledge about scenarios in which these attacks occurred effectively contributes to the success of new attacks. The development of a tool that makes this kind of information available is, therefore, of great relevance. This work presents a support system to the management of corporate security for the storage, retrieval and help in constructing attack scenarios and related information. If an incident occurs in a corporation, an expert must access the system to store the specific attack scenario. This scenario, made available through controlled access, must be analyzed so that effective decisions or actions can be taken for similar cases. Besides the strategy used by the attacker, attack scenarios also exacerbate vulnerabilities in devices. The access to this kind of information contributes to an increased security level of a corporation's network devices and a decreased response time to occurring incidents
Resumo:
This work presents a theoretical and experimental analysis about the properties of microstrip antennas with integrated frequency selective surfaces (Frequency Selective Surface - FSS). The integration occurs through the insertion of the FSS on ground plane of microstrip patch antenna. This integration aims to improve some characteristics of the antennas. The FSS using patch-type elements in square unit cells. Specifically, the simulated results are obtained using the commercial computer program CST Studio Suite® version 2011. From a standard antenna, designed to operate in wireless communication systems of IEEE 802.11 a / b / g / n the dimensions of the FSS are varied to obtain an optimization of some antenna parameters such as impedance matching and selectivity in the operating bands. After optimization of the investigated parameters are built two prototypes of microstrip patch antennas with and without the FSS ground plane. Comparisons are made of the results with the experimental results by 14 ZVB network analyzer from Rohde & Schwarz ®. The comparison aims to validate the simulations performed and show the improvements obtained with the FSS in integrated ground plane antenna. In the construction of prototypes, we used dielectric substrates of the type of Rogers Corporation RT-3060 with relative permittivity equal to 10.2 and low loss tangent. Suggestions for continued work are presented
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This paper presents an evaluative study about the effects of using a machine learning technique on the main features of a self-organizing and multiobjective genetic algorithm (GA). A typical GA can be seen as a search technique which is usually applied in problems involving no polynomial complexity. Originally, these algorithms were designed to create methods that seek acceptable solutions to problems where the global optimum is inaccessible or difficult to obtain. At first, the GAs considered only one evaluation function and a single objective optimization. Today, however, implementations that consider several optimization objectives simultaneously (multiobjective algorithms) are common, besides allowing the change of many components of the algorithm dynamically (self-organizing algorithms). At the same time, they are also common combinations of GAs with machine learning techniques to improve some of its characteristics of performance and use. In this work, a GA with a machine learning technique was analyzed and applied in a antenna design. We used a variant of bicubic interpolation technique, called 2D Spline, as machine learning technique to estimate the behavior of a dynamic fitness function, based on the knowledge obtained from a set of laboratory experiments. This fitness function is also called evaluation function and, it is responsible for determining the fitness degree of a candidate solution (individual), in relation to others in the same population. The algorithm can be applied in many areas, including in the field of telecommunications, as projects of antennas and frequency selective surfaces. In this particular work, the presented algorithm was developed to optimize the design of a microstrip antenna, usually used in wireless communication systems for application in Ultra-Wideband (UWB). The algorithm allowed the optimization of two variables of geometry antenna - the length (Ls) and width (Ws) a slit in the ground plane with respect to three objectives: radiated signal bandwidth, return loss and central frequency deviation. These two dimensions (Ws and Ls) are used as variables in three different interpolation functions, one Spline for each optimization objective, to compose a multiobjective and aggregate fitness function. The final result proposed by the algorithm was compared with the simulation program result and the measured result of a physical prototype of the antenna built in the laboratory. In the present study, the algorithm was analyzed with respect to their success degree in relation to four important characteristics of a self-organizing multiobjective GA: performance, flexibility, scalability and accuracy. At the end of the study, it was observed a time increase in algorithm execution in comparison to a common GA, due to the time required for the machine learning process. On the plus side, we notice a sensitive gain with respect to flexibility and accuracy of results, and a prosperous path that indicates directions to the algorithm to allow the optimization problems with "η" variables
Resumo:
Apresentamos um sistema implementado em Linux® com o intuito de proteger redes contendo estações de trabalho Windows® contra agentes maliciosos. O sistema, denominado LIV - Linux® Integrated Viruswall, agrega características existentes em outras soluções e acrescenta novas funcionalidades. Uma das funcionalidades implementadas é a capacidade de detecção de estações de trabalho contaminadas tendo como base a análise do tráfego de rede. Outra é o uso de uma técnica denominada compartilhamento armadilha para identificar agentes maliciosos em propagação na rede local. Uma vez detectado um foco de contaminação, o LIV é capaz de isolá-lo da rede, contendo a difusão do agente malicioso. Resultados obtidos pelo LIV na proteção de uma rede corporativa demonstram a eficácia da análise do tráfego de rede como instrumento de detecção de agentes maliciosos, especialmente quando comparada a mecanismos tradicionais de detecção, baseados exclusivamente em assinaturas digitais de códigos maliciosos
Resumo:
The use of wireless sensor and actuator networks in industry has been increasing past few years, bringing multiple benefits compared to wired systems, like network flexibility and manageability. Such networks consists of a possibly large number of small and autonomous sensor and actuator devices with wireless communication capabilities. The data collected by sensors are sent directly or through intermediary nodes along the network to a base station called sink node. The data routing in this environment is an essential matter since it is strictly bounded to the energy efficiency, thus the network lifetime. This work investigates the application of a routing technique based on Reinforcement Learning s Q-Learning algorithm to a wireless sensor network by using an NS-2 simulated environment. Several metrics like energy consumption, data packet delivery rates and delays are used to validate de proposal comparing it with another solutions existing in the literature
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New versions of SCTP protocol allow the implementation of handover procedures in the transport layer, as well as the supply of a partially reliable communication service. A communication architecture is proposed herein, integrating SCTP with the session initiation protocol, SIP, besides additional protocols. This architecture is intended to handle voice applications over IP networks with mobility requirements. User localization procedures are specified in the application layer as well, using SIP, as an alternative mean to the mechanisms used by traditional protocols, that support mobility in the network layer. The SDL formal specification language is used to specify the operation of a control module, which coordinates the operation of the system component protocols. This formal specification is intended to prevent ambiguities and inconsistencies in the definition of this module, assisting in the correct implementation of the elements of this architecture
Resumo:
The stability of synchronous generators connected to power grid has been the object of study and research for years. The interest in this matter is justified by the fact that much of the electricity produced worldwide is obtained with the use of synchronous generators. In this respect, studies have been proposed using conventional and unconventional control techniques such as fuzzy logic, neural networks, and adaptive controllers to increase the stabilitymargin of the systemduring sudden failures and transient disturbances. Thismaster thesis presents a robust unconventional control strategy for maintaining the stability of power systems and regulation of output voltage of synchronous generators connected to the grid. The proposed control strategy comprises the integration of a sliding surface with a linear controller. This control structure is designed to prevent the power system losing synchronism after a sudden failure and regulation of the terminal voltage of the generator after the fault. The feasibility of the proposed control strategy was experimentally tested in a salient pole synchronous generator of 5 kVA in a laboratory structure
Resumo:
Self-organizing maps (SOM) are artificial neural networks widely used in the data mining field, mainly because they constitute a dimensionality reduction technique given the fixed grid of neurons associated with the network. In order to properly the partition and visualize the SOM network, the various methods available in the literature must be applied in a post-processing stage, that consists of inferring, through its neurons, relevant characteristics of the data set. In general, such processing applied to the network neurons, instead of the entire database, reduces the computational costs due to vector quantization. This work proposes a post-processing of the SOM neurons in the input and output spaces, combining visualization techniques with algorithms based on gravitational forces and the search for the shortest path with the greatest reward. Such methods take into account the connection strength between neighbouring neurons and characteristics of pattern density and distances among neurons, both associated with the position that the neurons occupy in the data space after training the network. Thus, the goal consists of defining more clearly the arrangement of the clusters present in the data. Experiments were carried out so as to evaluate the proposed methods using various artificially generated data sets, as well as real world data sets. The results obtained were compared with those from a number of well-known methods existent in the literature