Uma arquitetura multiagente para sistemas de supervisão e controle de processos

Pós-graduação em Ciência da Computação - IBILCE

Simulação e controle de um quadcopter utilizando lógica fuzzy

The present work develops a model to simulate the dynamics of a quadcopter being controlled by a PD fuzzy controller. Initially is presented a brief history of quadcopters an introduction to fuzzy logic and fuzzy control systems. Afterwards is presented an overview of the quadcopter dynamics and the mathematical modelling development applying Newton-Euler method. Then the modelling are implemented in a Simulink model in addition to a PD fuzzy controller. A prototype proposition is made, by describing each necessary component to build up a quadcopter. In the end the results from the simulators are discussed and compared due to the discrepancy between the model using ideal sensor and the model using non-ideal sensors

Avaliação de Desempenho de Aplicações Paralelas Utilizando MPI e PETSc

This work presents a study about the use of standards and directions on parallel programming in distributed systems, using the MPI standard and PETSc toolkit, performing an analysis of their performances over certain mathematic operations involving matrices. The concepts are used to develop applications to solve problems involving Principal Components Analysis (PCA), which are executed in a Beowulf cluster. The results are compared to the ones of an analogous application with sequencial execution, and then it is analized if there was any performance boost on the parallel application

Teaching real-time with a scheduler simulator

In this paper we describe a scheduler simulator for real-time tasks, RTsim, that can be used as a tool to teach real-time scheduling algorithms. It simulates a variety of preprogrammed scheduling policies for single and multi-processor systems and simple algorithm variants introduced by its user. Using RTsim students can conduct experiments that will allow them to understand the effects of each policy given different load conditions and learn which policy is better for different workloads. We show how to use RTsim as a learning tool and the results achieved with its application on the Real-Time Systems course taught at the B.Sc. on Computer Science at Paulista State University - Unesp - at Rio Preto.

Considering Urban Dynamics in spatial electric load forecasting

When dealing with spatio-temporal simulations of load growth inside a service zone, one of the most important problems faced by a Distribution Utility is how to represent the different relationships among different areas. A new load in a certain part of the city could modify the load growth in other parts of the city, even outside of its radius of influence. These interactions are called Urban Dynamics. This work aims to discuss how to implement Urban Dynamics considerations into the spatial electric load forecasting simulations using multi-agent simulations. To explain the approach, three examples are introduced, including the effect of an attraction load, the effect of a repulsive load, and the effect of several attraction/repulsive loads at the same time when considering the natural load growth. © 2012 IEEE.

Prognostic factors associated with time to hCG remission in patients with low-risk postmolar gestational trophoblastic neoplasia

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.

Comportamento do pedestre e ambiente térmico urbano

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Serviço de referência digital: uma análise apoiada em agentes de interface

Pós-graduação em Ciência da Informação - FFC

Influência do local de seguimento da mola hidatiforme no prognóstico e tratamento da neoplasia trofoblástica gestacional pós-molar

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Efficient linear programming algorithm for the transmission network expansion planning problem

The transmission network planning problem is a non-linear integer mixed programming problem (NLIMP). Most of the algorithms used to solve this problem use a linear programming subroutine (LP) to solve LP problems resulting from planning algorithms. Sometimes the resolution of these LPs represents a major computational effort. The particularity of these LPs in the optimal solution is that only some inequality constraints are binding. This task transforms the LP into an equivalent problem with only one equality constraint (the power flow equation) and many inequality constraints, and uses a dual simplex algorithm and a relaxation strategy to solve the LPs. The optimisation process is started with only one equality constraint and, in each step, the most unfeasible constraint is added. The logic used is similar to a proposal for electric systems operation planning. The results show a higher performance of the algorithm when compared to primal simplex methods.

A multi-objective programming approach for the optimal operation of distributed generation considering uncertainty

Due to the renewed interest in distributed generation (DG), the number of DG units incorporated in distribution systems has been rapidly increasing in the past few years. This situation requires new analysis tools for understanding system performance, and taking advantage of the potential benefits of DG. This paper presents an evolutionary multi-objective programming approach to determine the optimal operation of DG in distribution systems. The objectives are the minimization of the system power losses and operation cost of the DG units. The proposed approach also considers the inherent stochasticity of DG technologies powered by renewable resources. Some tests were carried out on the IEEE 34 bus distribution test system showing the robustness and applicability of the proposed methodology. © 2011 IEEE.

Bilevel approach for optimal location and contract pricing of distributed generation in radial distribution systems using mixed-integer linear programming

In this study, a novel approach for the optimal location and contract pricing of distributed generation (DG) is presented. Such an approach is designed for a market environment in which the distribution company (DisCo) can buy energy either from the wholesale energy market or from the DG units within its network. The location and contract pricing of DG is determined by the interaction between the DisCo and the owner of the distributed generators. The DisCo intends to minimise the payments incurred in meeting the expected demand, whereas the owner of the DG intends to maximise the profits obtained from the energy sold to the DisCo. This two-agent relationship is modelled in a bilevel scheme. The upper-level optimisation is for determining the allocation and contract prices of the DG units, whereas the lower-level optimisation is for modelling the reaction of the DisCo. The bilevel programming problem is turned into an equivalent single-level mixed-integer linear optimisation problem using duality properties, which is then solved using commercially available software. Results show the robustness and efficiency of the proposed model compared with other existing models. As regards to contract pricing, the proposed approach allowed to find better solutions than those reported in previous works. © The Institution of Engineering and Technology 2013.

Design and management optimization of trickle irrigation systems using non-linear programming

A non-linear model is presented which optimizes the lay-out, as well as the design and management of trickle irrigation systems, to achieve maximum net benefit. The model consists of an objective function that maximizes profit at the farm level, subject to appropriate geometric and hydraulic constraints. It can be applied to rectangular shaped fields, with uniform or zero slope. The software used is the Gams-Minos package. The basic inputs are the crop-water-production function, the cost function and cost of system components, and design variables. The main outputs are the annual net benefit and pipe diameters and lengths. To illustrate the capability of the model, a sensitivity analysis of the annual net benefit for a citrus field is evaluated with respect to irrigated area, ground slope, micro-sprinkler discharge and shape of the field. The sensitivity analysis suggests that the greatest benefit is obtained with the smallest microsprinkler discharge, the greatest area, a square field and zero ground slope. The costs of the investment and energy are the components of the objective function that had the greatest effect in the 120 situations evaluated. (C) 1996 Academic Press Limited

Applying fuzzy logic systems in the estimation of crossflow filtration processes

The crossflow filtration process differs of the conventional filtration by presenting the circulation flow tangentially to the filtration surface. The conventional mathematical models used to represent the process have some limitations in relation to the identification and generalization of the system behavior. In this paper, a system based on fuzzy logic systems is developed to overcome the problems usually found in the conventional mathematical models. Imprecisions and uncertainties associated with the measurements made on the system are automatically incorporated in the fuzzy approach. Simulation results are presented to justify the validity of the proposed approach.

A new proposal of Arithmetic Logic Unit (ALU) to work with paraconsistent annotated logic

It can be observed that the number and the complexity of the application's domains, where the Paraconsistent Annotated Logic has been used, have grown a lot in the last decade. This increase in the complexity of the application's domain is an extra challenge for the designers of such systems, once there are not suitable computer hardware to run paraconsistent systems. This work proposes a new hardware architecture for the building Paraconsistent system.