54 resultados para Multi-agent simulation and artificial snow optimization


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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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Today, the trend within the electronics industry is for the use of rapid and advanced simulation methodologies in association with synthesis toolsets. This paper presents an approach developed to support mixed-signal circuit design and analysis. The methodology proposed shows a novel approach to the problem of developing behvioural model descriptions of mixed-signal circuit topologies, by construction of a set of subsystems, that supports the automated mapping of MATLAB (R)/SINIULINK (R) models to structural VHDL-AMS descriptions. The tool developed, named (MSSV)-S-2, reads a SIMULINK (R) model file and translates it to a structural VHDL-AMS code. It also creates the file structure required to simulate the translated model in the SystemVision (TM). To validate the methodology and the developed program, the DAC08, AD7524 and AD5450 data converters were studied and initially modelled in MATLAB (R)/SIMULINK (R). The VHDL-AMS code generated automatically by (MSSV)-S-2, (MATLAB (R)/SIMULINK (R) to SystemVision (TM)), was then simulated in the SystemVision (TM). The simulation results show that the proposed approach, which is based on VHDL-AMS descriptions of the original model library elements, allows for the behavioural level simulation of complex mixed-signal circuits.

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Objective The purpose of this study was to identify the clinical factors associated with time to hCG remission among women with low-risk postmolar GTN. Methods This study included a non-concurrent cohort of 328 patients diagnosed with low-risk postmolar GTN according to FIGO 2002 criteria. Associations of time to hCG remission with history of prior mole, molar histology, time to persistence, use of D&C at persistence, presence of metastatic disease, FIGO score, hCG values at persistence, type of first line therapy and use of multiagent chemotherapy were investigated with both univariate and multivariate analyses. Results Overall median time to remission was 46 days. Ten percent of the patients required multi-agent chemotherapy to achieve hCG remission. Multivariate analysis incorporating the variables significant on univariate analysis confirmed that complete molar histology (HR 1.45), metastatic disease (HR 1.66), use of multi-agent therapy (HR 2.00) and FIGO score (HR 1.82) were associated with longer time to remission. There was a linear relationship between FIGO score and time to hCG remission. Each 1-point increment in FIGO score was associated with an average 17-day increase in hCG remission time (95% CI: 12.5-21.6). Conclusions Complete mole histology prior to GTN, presence of metastatic disease, use of multi-agent therapy and higher FIGO score were independent factors associated with longer time to hCG remission in low-risk GTN. Identifying the prognostic factors associated with time to remission and effective counseling may help improve treatment planning and reduce anxiety in patients and their families. © 2013 Elsevier Inc. All rights reserved.

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This paper presents a multi-agent system for real-time operation of simulated microgrid using the Smart-Grid Test Bed at Washington State University. The multi-agent system (MAS) was developed in JADE (Java Agent DEvelopment Framework) which is a Foundation for Intelligent Physical Agents (FIPA) compliant open source multi-agent platform. The proposed operational strategy is mainly focused on using an appropriate energy management and control strategies to improve the operation of an islanded microgrid, formed by photovoltaic (PV) solar energy, batteries and resistive and rotating machines loads. The focus is on resource management and to avoid impact on loads from abrupt variations or interruption that changes the operating conditions. The management and control of the PV system is performed in JADE, while the microgrid model is simulated in RSCAD/RTDS (Real-Time Digital Simulator). Finally, the outcome of simulation studies demonstrated the feasibility of the proposed multi-agent approach for real-time operation of a microgrid.

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In recent years, many researchers in the field of biomedical sciences have made successful use of mathematical models to study, in a quantitative way, a multitude of phenomena such as those found in disease dynamics, control of physiological systems, optimization of drug therapy, economics of the preventive medicine and many other applications. The availability of good dynamic models have been providing means for simulation and design of novel control strategies in the context of biological events. This work concerns a particular model related to HIV infection dynamics which is used to allow a comparative evaluation of schemes for treatment of AIDS patients. The mathematical model adopted in this work was proposed by Nowak & Bangham, 1996 and describes the dynamics of viral concentration in terms of interaction with CD4 cells and the cytotoxic T lymphocytes, which are responsible for the defense of the organism. Two conceptually distinct techniques for drug therapy are analyzed: Open Loop Treatment, where a priori fixed dosage is prescribed and Closed Loop Treatment, where the doses are adjusted according to results obtained by laboratory analysis. Simulation results show that the Closed Loop Scheme can achieve improved quality of the treatment in terms of reduction in the viral load and quantity of administered drugs, but with the inconvenience related to the necessity of frequent and periodic laboratory analysis.

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The ability of neural networks to realize some complex nonlinear function makes them attractive for system identification. This paper describes a novel barrier method using artificial neural networks to solve robust parameter estimation problems for nonlinear model with unknown-but-bounded errors and uncertainties. This problem can be represented by a typical constrained optimization problem. More specifically, a modified Hopfield network is developed and its internal parameters are computed using the valid-subspace technique. These parameters guarantee the network convergence to the equilibrium points. A solution for the robust estimation problem with unknown-but-bounded error corresponds to an equilibrium point of the network. Simulation results are presented as an illustration of the proposed approach.

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In this work it is proposed to validate an evolutionary tuning algorithm in plants composed by a grid connected inverter. The optimization aims the tuning of the slopes of P-Ω and Q-V curves so that the system is stable, damped and minimum settling time. Simulation and experimental results are presented to prove the feasibility of the proposed approach. However, experimental results demonstrate a compromising effect of grid frequency oscillations in the active power transferring. In addition, it was proposed an additional loop to compensate this effect ensuring a constant active power flow. © 2011 IEEE.

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In this paper, the use of differential evolution ( DE), a global search technique inspired by evolutionary theory, to find the parameters that are required to achieve optimum dynamic response of parallel operation of inverters with no interconnection among the controllers is proposed. Basically, in order to reach such a goal, the system is modeled in a certain way that the slopes of P-omega and Q-V curves are the parameters to be tuned. Such parameters, when properly tuned, result in system's eigenvalues located in positions that assure the system's stability and oscillation-free dynamic response with minimum settling time. This paper describes the modeling approach and provides an overview of the motivation for the optimization and a description of the DE technique. Simulation and experimental results are also presented, and they show the viability of the proposed method.

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Este artigo é uma tentativa de delinear as principais características da pesquisa numa nova área de estudos a chamada Inteligência Artificial (AI). Os itens 1 e 2 constituem um rápido histórico da AI e seus pressupostos básicos. O item 3 trata da teoria de resolução de problemas, desenvolvida por A. Newell e H. Simon. O item 4 procura mostrar a relevância da AI para a Filosofia, em especial para a filosofia da Mente e para a Teoria do Conhecimento.

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In Experiments 1, 2, and 3, we evaluated the effects of temporary weaning (TW), equine chorionic gonadotropin (eCG), and follicle-stimulating hormone (FSH) treatments on results of it fixed-time artificial insemination (TAI) protocol in postpartum Bos indicus cows. In Experiment 1, treatment with 400 IU eCG or with TW for 48 h consistently improved pregnancy rates (PRs) at TAI, but, in Experiment 2, FSH treatment was less effective than eCG or TW. In Experiment 3, the inclusion of eCG treatment in cows subjected to TW did not improve PRs. We concluded that TW or 400 IU eCG should be included in the TAI protocol in postpartum Bos indicus cows to enhance fertility. In Experiment 4, we used records front heifers and cows treated with the proposed protocol during the 2006-2007 (n = 27,195) and 2007-2008 (n = 36,838) breeding seasons from multiple locations in Brazil to evaluate factors potentially affecting PRs. Overall PR at TAI was 49.6% (31,786 of 64,033). Pregnancy rate differed (P < 0.01) among farm within location (results ranging between 26.8% and 68.0%; P < 0.01), cow group within farm, by breed (Bos indicus, 48.3% [26,123 of 54,145]; Bos taurus, 61.7% [3652 of 5922]; and crossbred Bos indicus x Bos taurus, 50.7% [2011 of 3966]), category (nulliparous, 39.6% [2095 of 52901] suckled primiparous, 45.2% [3924 of 8677]; suckled multiparous, 51.8% [24,245 of 46,767]; and nonsuckled multiparous, 46.1% [1522 of 3299]), body condition score at TAI (<= 2.5 43.0% [3409 of 7923]; 3.0, 49.6% [18,958 of 38,229]; and >3.5, 52.7% [9419 of 17,881]). Days postpartum at beginning, of protocol did not affect PR (30 to 60 d, 47.6% [4228 of 8881]; 61 to 90 d, 51.7% 116,325 to 31,5721; and 91 to 150 d, 50.8% [7616 to 14,991]; P > 0.1). Pregnancy rate was also consistently affected (P < 0.01) by sire (results ranging from 7.2% to 77.3%) and artificial insemination technician (results ranging from 15.1% to 81.8%). (C) 2009 Elsevier B.V. All rights reserved.

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This paper presents an approach to integrate an artificial intelligence (AI) technique, concretely rule-based processing, into mobile agents. In particular, it focuses on the aspects of designing and implementing an appropriate inference engine of small size to reduce migration costs. The main goal is combine two lines of agent research, First, the engineering oriented approach on mobile agent architectures, and, second, the AI related approach on inference engines driven by rules expressed in a restricted subset of first-order predicate logic (FOPL). In addition to size reduction, the main functions of this type of engine were isolated, generalized and implemented as dynamic components, making possible not only their migration with the agent, but also their dynamic migration and loading on demand. A set of classes for representing and exchanging knowledge between rule-based systems was also proposed.

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In this work, thermodynamic and economic analyses are applied to a Brazilian thermal power plant operating with natural gas. The analyses are performed in two cases: the current configuration and the future configuration. The current configuration is constituted by four gas turbines which operate in open cycle. The future configuration is obtained by a plant repowering by addition of four recovery boilers, two steam turbines and others equipment and accessories necessary to operate in combined cycle. In order to obtain the performance parameters, energetic and exergetic analyses for each case considered are carried out. on the other hand, thermoeconomic analysis provides means to evaluate the influences of the capital and fuel costs in the composition of the electricity costs. Techniques of investment analysis are also applied to the new configuration and from the results obtained it is possible to verify the advantages of the modifications.

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Differences in culture duration, metamorphosis rate and the productivity in hatchery culture of M. rosenbergii using a closed system with natural and artificial brackish water were evaluated. Reuse of brackish water in more than one hatchery cycle was also evaluated. Natural and artificial brackish water constituted the two tested treatments, which were distributed in four independent recirculating systems (tank and respective biofilter). Four batches of cultures were conducted and the 2nd and 4th reused the water from the 1st and 3rd, respectively. Mean duration of the hatchery period was 28 d in natural brackish water and 31 d in artificial brackish water. The metamorphosis rate and the average productivity for the natural brackish water treatment were 74% and 60 postlarvae/ L. respectively, and values obtained with artificial brackish water were 55% and 44 postlarvae/L. The successful hatchery culture of M. rosenbergii in this specific artificial brackish water suggests its potential use in enterprises located far from the coast. Brackish water can be used in two consecutive cultures without a negative effect on productivity.

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Supervising and controlling the many processes involved in petroleum production is both dangerous and complex. Herein, we propose a multiagent supervisory and control system for handle continuous processes like those in chemical and petroleum industries In its architeture, there are agents responsible for managing data production and analysis, and also the production equipments. Fuzzy controllers were used as control agents. The application of a fuzzy control system to managing an off-shore installation for petroleum production onto a submarine separation process is described. © 2008 IEEE.

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The use of sensorless technologies is an increasing tendency on industrial drivers for electrical machines. The estimation of electrical and mechanical parameters involved with the electrical machine control is used very frequently in order to avoid measurement of all variables related to this process. The cost reduction may also be considered in industrial drivers, besides the increasing robustness of the system, as an advantage of the use of sensorless technologies. This work proposes the use of a recurrent artificial neural network to estimate the speed of induction motor for sensorless control schemes using one single current sensor. Simulation and experimental results are presented to validate the proposed approach. ©2008 IEEE.