881 resultados para computer systems


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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Internal and external computer network attacks or security threats occur according to standards and follow a set of subsequent steps, allowing to establish profiles or patterns. This well-known behavior is the basis of signature analysis intrusion detection systems. This work presents a new attack signature model to be applied on network-based intrusion detection systems engines. The AISF (ACME! Intrusion Signature Format) model is built upon XML technology and works on intrusion signatures handling and analysis, from storage to manipulation. Using this new model, the process of storing and analyzing information about intrusion signatures for further use by an IDS become a less difficult and standardized process.

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This paper presents a new methodology for the adjustment of fuzzy inference systems. A novel approach, which uses unconstrained optimization techniques, is developed in order to adjust the free parameters of the fuzzy inference system, such as its intrinsic parameters of the membership function and the weights of the inference rules. This methodology is interesting, not only for the results presented and obtained through computer simulations, but also for its generality concerning to the kind of fuzzy inference system used. Therefore, this methodology is expandable either to the Mandani architecture or also to that suggested by Takagi-Sugeno. The validation of the presented methodology is accomplished through an estimation of time series. More specifically, the Mackey-Glass chaotic time series estimation is used for the validation of the proposed methodology.

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Purpose: The aim of this study was to evaluate the surface roughness of four packable composite resins, SureFil™ (Dentsply, Petrópolis, Rio de Janeiro, Brazil), Prodigy Condensable™ (Kerr Co., Orange, CA, USA), Filtek P60™ (3M do Brasil, São Paulo, Brazil), and ALERT® (Jeneric/Pentron, Inc., Wallingford, CT, USA) and one microhybrid composite resin (Filtek Z250™, 3M do Brasil) after polishing with four finishing systems. Materials and Methods: Twenty specimens were made of each material (5 mm in diameter and 4 mm high) and were analyzed with a profilometer (Perthometer® S8P, Perthen, Mahr, Germany) to measure the mean surface roughness (Ra). The specimens were then divided into four groups according to the polishing system: group 1 - Sof-Lex™ (3M do Brasil), group 2 - Enhance™ (Dentsply), group 3 - Composite Finishing Kit (KG Sorensen, Barueri, São Paulo, Brazil), and group 4 - Jiffy Polisher Cups® (Ultradent Products, Inc., South Jordan, UT, USA). The specimens were polished and then evaluated for Ra, and the data were subjected to analysis of variance, analysis of covariance, and Tukey's test (p = .05). Results: The mean Ra of SureFil polished with Sof-Lex was significantly lower than that of KG points. Prodigy Condensable polished with Enhance showed a significantly less rough surface than when polished with Sof-Lex. Filtek P60 did not exhibit a significant difference with the various polishing systems. For ALERT the lowest mean Ra was obtained with Sof-Lex and the highest mean Ra with KG points. Regarding Filtek Z250, polishing with KG and Jiffy points resulted in a significantly lower mean Ra than when polished with Enhance. Conclusions: Packable composite resins display variable roughness depending on the polishing system used; the Sof-Lex disks and Jiffy points resulted in the best Ra values for the majority of the materials tested.

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Postbloom fruit drop (PFD) of citrus, caused by Colletotrichum acutatum, infects petals of citrus flowers and produces orange-brown lesions that induce the abscission of young fruitlets and the retention of calyces. Proper timing of fungicide applications is essential for good disease control. Different systems for timing of fungicide applications for control of PFD in a major citrus-growing region in southern São Paulo state in Brazil were evaluated from 1999 to 2002. The following programs were compared to an unsprayed control using counts of diseased flowers, persistent calyces, or fruit: (i) a phenology-based program currently recommended in Brazil with one application at early and another at peak bloom; (ii) the Florida PFD model; (iii) the postbloom fruit drop-fungicide application decision system (PFD-FAD), a new computer-assisted decision method; and (iv) grower's choice. In 1999, no disease developed, sprays applied with the phenology-based program had no effect, and the Florida PFD model saved two sprays compared with the phenology-based program. In 2000, PFD was moderate and the phenology-based and growers' choice treatments had a significantly lower number of persistent calyces and higher fruit numbers than the control, but no differences were found between those treatments and the PFD model. In 2001, PFD was severe with considerable yield loss. The PFD model, the phenology-based program, and the grower's choice reduced flower blight and the number of persistent calyces, and improved fruit yields with two to three applications, but the PFD-FAD achieved comparable yields with only one spray. In 2002, the disease was mild, with no yield loss, and the Florida PFD model and the PFD-FAD saved one spray compared with the other systems. The PFD model and the PFD-FAD were equally effective for timing fungicide applications to control PFD in Brazil. Scouting of trees is simpler with PFD-FAD; therefore, this system is recommended and should eliminate unnecessary sprays and reduce costs for growers.

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We have recently proposed an extension to Petri nets in order to be able to directly deal with all aspects of embedded digital systems. This extension is meant to be used as an internal model of our co-design environment. After analyzing relevant related work, and presenting a short introduction to our extension as a background material, we describe the details of the timing model we use in our approach, which is mainly based in Merlin's time model. We conclude the paper by discussing an example of its usage. © 2004 IEEE.

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In this work, the linear and nonlinear feedback control techniques for chaotic systems were been considered. The optimal nonlinear control design problem has been resolved by using Dynamic Programming that reduced this problem to a solution of the Hamilton-Jacobi-Bellman equation. In present work the linear feedback control problem has been reformulated under optimal control theory viewpoint. The formulated Theorem expresses explicitly the form of minimized functional and gives the sufficient conditions that allow using the linear feedback control for nonlinear system. The numerical simulations for the Rössler system and the Duffing oscillator are provided to show the effectiveness of this method. Copyright © 2005 by ASME.

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The main objective involved with this paper consists of presenting the results obtained from the application of artificial neural networks and statistical tools in the automatic identification and classification process of faults in electric power distribution systems. The developed techniques to treat the proposed problem have used, in an integrated way, several approaches that can contribute to the successful detection process of faults, aiming that it is carried out in a reliable and safe way. The compilations of the results obtained from practical experiments accomplished in a pilot radial distribution feeder have demonstrated that the developed techniques provide accurate results, identifying and classifying efficiently the several occurrences of faults observed in the feeder.

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This paper explains why the reliability assessment of energy limited systems requires more detailed models for primary generating resources availability, internal and external generating dispatch and customer demand than the ones commonly used for large power systems and presents a methodology based on the full sequential Montecarlo simulation technique with AC power flow for their long term reliability assessment which can properly include these detailed models. By means of a real example, it is shown how the simplified modeling traditionally used for large power systems leads to pessimistic predictions if it is applied to an energy limited system and also that it cannot predict all the load point adequacy problems. © 2006 IEEE.

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The aim of this paper is to study the cropping system as complex one, applying methods from theory of dynamic systems and from the control theory to the mathematical modeling of the biological pest control. The complex system can be described by different mathematical models. Based on three models of the pest control, the various scenarios have been simulated in order to obtain the pest control strategy only through natural enemies' introduction. © 2008 World Scientific Publishing Company.

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This project aims to apply image processing techniques in computer vision featuring an omnidirectional vision system to agricultural mobile robots (AMR) used for trajectory navigation problems, as well as localization matters. To carry through this task, computational methods based on the JSEG algorithm were used to provide the classification and the characterization of such problems, together with Artificial Neural Networks (ANN) for pattern recognition. Therefore, it was possible to run simulations and carry out analyses of the performance of JSEG image segmentation technique through Matlab/Octave platforms, along with the application of customized Back-propagation algorithm and statistical methods in a Simulink environment. Having the aforementioned procedures been done, it was practicable to classify and also characterize the HSV space color segments, not to mention allow the recognition of patterns in which reasonably accurate results were obtained.

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Using robots for teaching is one approach that has gathered good results on Middle-School, High-School and Universities. Robotics gives chance to experiment concepts of a broad range of disciplines, principally those from Engineering courses and Computer Science. However, there are not many kits that enables the use of robotics in classroom. This article describes the methodologies to implement tools which serves as test beds for the use of robotics to teach Computer Science and Engineering. Therefore, it proposes the development of a flexible, low cost hardware to integrate sensors and control actuators commonly found on mobile robots, the development of a mobile robot device whose sensors and actuators allows the experimentation of different concepts, and an environment for the implementation of control algorithms through a computer network. This paper describes each one of these tools and discusses the implementation issues and future works. © 2010 IEEE.

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This paper presents an approach for probabilistic analysis of unbalanced three-phase weakly meshed distribution systems considering uncertainty in load demand. In order to achieve high computational efficiency this approach uses both an efficient method for probabilistic analysis and a radial power flow. The probabilistic approach used is the well-known Two-Point Estimate Method. Meanwhile, the compensation-based radial power flow is used in order to extract benefits from the topological characteristics of the distribution systems. The generation model proposed allows modeling either PQ or PV bus on the connection point between the network and the distributed generator. In addition allows control of the generator operating conditions, such as the field current and the power delivery at terminals. Results on test with IEEE 37 bus system is given to illustrate the operation and effectiveness of the proposed approach. A Monte Carlo Simulations method is used to validate the results. © 2011 IEEE.

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Distributed Generation, microgrid technologies, two-way communication systems, and demand response programs are issues that are being studied in recent years within the concept of smart grids. At some level of enough penetration, the Distributed Generators (DGs) can provide benefits for sub-transmission and transmission systems through the so-called ancillary services. This work is focused on the ancillary service of reactive power support provided by DGs, specifically Wind Turbine Generators (WTGs), with high level of impact on transmission systems. The main objective of this work is to propose an optimization methodology to price this service by determining the costs in which a DG incurs when it loses sales opportunity of active power, i.e, by determining the Loss of Opportunity Costs (LOC). LOC occur when more reactive power is required than available, and the active power generation has to be reduced in order to increase the reactive power capacity. In the optimization process, three objectives are considered: active power generation costs of DGs, voltage stability margin of the system, and losses in the lines of the network. Uncertainties of WTGs are reduced solving multi-objective optimal power flows in multiple probabilistic scenarios constructed by Monte Carlo simulations, and modeling the time series associated with the active power generation of each WTG via Fuzzy Logic and Markov Chains. The proposed methodology was tested using the IEEE 14 bus test system with two WTGs installed. © 2011 IEEE.