A Framework supporting collaboration on the distributed design of integrated systems

The work described in this thesis aims to support the distributed design of integrated systems and considers specifically the need for collaborative interaction among designers. Particular emphasis was given to issues which were only marginally considered in previous approaches, such as the abstraction of the distribution of design automation resources over the network, the possibility of both synchronous and asynchronous interaction among designers and the support for extensible design data models. Such issues demand a rather complex software infrastructure, as possible solutions must encompass a wide range of software modules: from user interfaces to middleware to databases. To build such structure, several engineering techniques were employed and some original solutions were devised. The core of the proposed solution is based in the joint application of two homonymic technologies: CAD Frameworks and object-oriented frameworks. The former concept was coined in the late 80's within the electronic design automation community and comprehends a layered software environment which aims to support CAD tool developers, CAD administrators/integrators and designers. The latter, developed during the last decade by the software engineering community, is a software architecture model to build extensible and reusable object-oriented software subsystems. In this work, we proposed to create an object-oriented framework which includes extensible sets of design data primitives and design tool building blocks. Such object-oriented framework is included within a CAD Framework, where it plays important roles on typical CAD Framework services such as design data representation and management, versioning, user interfaces, design management and tool integration. The implemented CAD Framework - named Cave2 - followed the classical layered architecture presented by Barnes, Harrison, Newton and Spickelmier, but the possibilities granted by the use of the object-oriented framework foundations allowed a series of improvements which were not available in previous approaches: - object-oriented frameworks are extensible by design, thus this should be also true regarding the implemented sets of design data primitives and design tool building blocks. This means that both the design representation model and the software modules dealing with it can be upgraded or adapted to a particular design methodology, and that such extensions and adaptations will still inherit the architectural and functional aspects implemented in the object-oriented framework foundation; - the design semantics and the design visualization are both part of the object-oriented framework, but in clearly separated models. This allows for different visualization strategies for a given design data set, which gives collaborating parties the flexibility to choose individual visualization settings; - the control of the consistency between semantics and visualization - a particularly important issue in a design environment with multiple views of a single design - is also included in the foundations of the object-oriented framework. Such mechanism is generic enough to be also used by further extensions of the design data model, as it is based on the inversion of control between view and semantics. The view receives the user input and propagates such event to the semantic model, which evaluates if a state change is possible. If positive, it triggers the change of state of both semantics and view. Our approach took advantage of such inversion of control and included an layer between semantics and view to take into account the possibility of multi-view consistency; - to optimize the consistency control mechanism between views and semantics, we propose an event-based approach that captures each discrete interaction of a designer with his/her respective design views. The information about each interaction is encapsulated inside an event object, which may be propagated to the design semantics - and thus to other possible views - according to the consistency policy which is being used. Furthermore, the use of event pools allows for a late synchronization between view and semantics in case of unavailability of a network connection between them; - the use of proxy objects raised significantly the abstraction of the integration of design automation resources, as either remote or local tools and services are accessed through method calls in a local object. The connection to remote tools and services using a look-up protocol also abstracted completely the network location of such resources, allowing for resource addition and removal during runtime; - the implemented CAD Framework is completely based on Java technology, so it relies on the Java Virtual Machine as the layer which grants the independence between the CAD Framework and the operating system. All such improvements contributed to a higher abstraction on the distribution of design automation resources and also introduced a new paradigm for the remote interaction between designers. The resulting CAD Framework is able to support fine-grained collaboration based on events, so every single design update performed by a designer can be propagated to the rest of the design team regardless of their location in the distributed environment. This can increase the group awareness and allow a richer transfer of experiences among them, improving significantly the collaboration potential when compared to previously proposed file-based or record-based approaches. Three different case studies were conducted to validate the proposed approach, each one focusing one a subset of the contributions of this thesis. The first one uses the proxy-based resource distribution architecture to implement a prototyping platform using reconfigurable hardware modules. The second one extends the foundations of the implemented object-oriented framework to support interface-based design. Such extensions - design representation primitives and tool blocks - are used to implement a design entry tool named IBlaDe, which allows the collaborative creation of functional and structural models of integrated systems. The third case study regards the possibility of integration of multimedia metadata to the design data model. Such possibility is explored in the frame of an online educational and training platform.

Sustainable silvopastoral systems: theory and a practical case

Muitas transformações são esperadas por causa das mudanças do clima, especialmente das atividades agrícolas realizadas nos trópicos. Esta tese centra-se em dois aspectos. O primeiro deles é o de reunir o conhecimento de sistemas silvipastoris; este ponto de vista estabelece a importância de solos tropicais e sua gestão adequada de acordo com as normas ambientais e sustentáveis. A segunda parte da tese é a aplicação desses princípios em um caso específico: a fazenda "El Paraíso". O objetivo central ou problema a resolver da segunda parte é propor um projeto para melhorar as atividades de produção de carne e, ao mesmo tempo, ajudar a preservar e melhorar o meio ambiente e especialmente os ecossistemas tropicais. A metodologia utilizada na tese foi buscar e analisar informações sobre o assunto. Depois disso, a investigação experimental e de campo foi realizada para levantar o projeto que combinaria as duas partes da obra. No final, com a informação recolhida uma proposta de projeto foi feita. O objetivo era propor a transformação dos processos de produção na fazenda selecionada. Logo de desenvolver e apresentar o projeto, foram analisadas as possibilidades de implementação do projeto. A conclusão do estudo foi o de apresentar e discutir três cenários possíveis após a implementação. Finalmente, a conclusão geral apresenta as realizações, as oportunidades e possíveis expansões futuras do projeto.

Too difficult to manage, too big to ignore: party choice in multiparty presidential systems

In consensual (proportional) highly fragmented multiparty settings, political parties have two historical choices to make or pathways to follow: i) playing a majoritarian role by offering credible candidates to the head of the executive; or ii) playing the median legislator game. Each of those choices will have important consequences not only for the party system but also for the government. The purpose of this paper is to investigate the role played by median legislator parties on coalition management strategies of presidents in a comparative perspective. We analyze in depth the Brazilian case where the Partido do Movimento Democrático Brasileiro (PMDB) has basically functioned as the median legislator party in Congress by avoiding the approval of extreme policies, both on the left and on the right. Based on an expert survey in Latin America, we built an index of Pmdbismo and identified that there is a positive correlation between partisan fragmentation and median legislator parties. In addition, we investigate the effect of having a median legislator party in the governing coalition. We found that it is cheaper and less difficult for the government to manage the coalition having the median legislative party on board.

Nonautonomous difference equations with applications

This work is divided in two parts. In the first part we develop the theory of discrete nonautonomous dynamical systems. In particular, we investigate skew-product dynamical system, periodicity, stability, center manifold, and bifurcation. In the second part we present some concrete models that are used in ecology/biology and economics. In addition to developing the mathematical theory of these models, we use simulations to construct graphs that illustrate and describe the dynamics of the models. One of the main contributions of this dissertation is the study of the stability of some concrete nonlinear maps using the center manifold theory. Moreover, the second contribution is the study of bifurcation, and in particular the construction of bifurcation diagrams in the parameter space of the autonomous Ricker competition model. Since the dynamics of the Ricker competition model is similar to the logistic competition model, we believe that there exists a certain class of two-dimensional maps with which we can generalize our results. Finally, using the Brouwer’s fixed point theorem and the construction of a compact invariant and convex subset of the space, we present a proof of the existence of a positive periodic solution of the nonautonomous Ricker competition model.

Availability of soil water under tillage systems, mulch management and citrus rootstocks

The increased availability of soil water is important for the management of non-irrigated orange orchards. The objective of this study was to evaluate the availability of soil water in a Haplorthox (Rhodic Ferralsol) under different tillage systems used for orchard plantation, mulch management and rootstocks in a "Pera" orange orchard in northwest Parana, Brazil. An experiment in a split-split-plot design was established in 2002, in an area cultivated with Brachiaria brizantha grass in which three tillage systems (no tillage, conventional tillage and strip-tillage) were used for orchard plantation. This grass was mowed twice a year between the rows, representing two mulch managements in the split plots (no mulching and mulching in the plant rows). The split-split-plots were represented by two rootstocks ("Rangpur" lime and "Cleopatra" mandarin). The soil water content in the plant rows was evaluated in the 0-20 cm layer in 2007 and at 0-20 and 20-40 cm in 2008-2009. The effect of soil tillage systems prior to implantation of orange orchards on soil water availability was less pronounced than mulching and the rootstocks. The soil water availability was lower when "Pera" orange trees were grafted on "Cleopatra" mandarin than on "Rangpur" lime rootstocks. Mulching had a positive influence on soil water availability in the sandy surface layer (020 cm) and sandy clay loam subsurface (20-40 cm) of the soil in the spring. The production of B. brizantha between the rows and residue disposal in the plant rows as mulch increased water availability to the "Pera" orange trees.

Fluxo de potência ótimo reativo via método da função lagrangiana barreira modificada

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

A neural network approach for robust nonlinear parameter estimation in presence of unknown-but-bounded errors

Systems based on artificial neural networks have high computational rates due to the use of a massive number of simple processing elements and the high degree of connectivity between these elements. This paper presents a novel approach to solve robust parameter estimation problem for nonlinear model with unknown-but-bounded errors and uncertainties. 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. Copyright (C) 2000 IFAC.

Design and analysis of an efficient neural network model for solving nonlinear optimization problems

This paper presents an efficient approach based on a recurrent neural network for solving constrained nonlinear optimization. More specifically, a modified Hopfield network is developed, and its internal parameters are computed using the valid-subspace technique. These parameters guarantee the convergence of the network to the equilibrium points that represent an optimal feasible solution. The main advantage of the developed network is that it handles optimization and constraint terms in different stages with no interference from each other. Moreover, the proposed approach does not require specification for penalty and weighting parameters for its initialization. A study of the modified Hopfield model is also developed to analyse its stability and convergence. Simulation results are provided to demonstrate the performance of the proposed neural network.

An efficient neural approach to economic load dispatch in power systems

A neural approach to solve the problem defined by the economic load dispatch in power systems is presented in this paper, Systems based on artificial neural networks have high computational rates due to the use of a massive number of simple processing elements and the high degree of connectivity between these elements the ability of neural networks to realize some complex nonlinear function makes them attractive for system optimization the neural networks applyed in economic load dispatch reported in literature sometimes fail to converge towards feasible equilibrium points the internal parameters of the modified Hopfield network developed here are computed using the valid-subspace technique These parameters guarantee the network convergence to feasible quilibrium points, A solution for the economic load dispatch problem corresponds to an equilibrium point of the network. Simulation results and comparative analysis in relation to other neural approaches are presented to illustrate efficiency of the proposed approach.

Interior point method for long-term generation scheduling of large-scale hydrothermal systems

This paper presents an interior point method for the long-term generation scheduling of large-scale hydrothermal systems. The problem is formulated as a nonlinear programming one due to the nonlinear representation of hydropower production and thermal fuel cost functions. Sparsity exploitation techniques and an heuristic procedure for computing the interior point method search directions have been developed. Numerical tests in case studies with systems of different dimensions and inflow scenarios have been carried out in order to evaluate the proposed method. Three systems were tested, with the largest being the Brazilian hydropower system with 74 hydro plants distributed in several cascades. Results show that the proposed method is an efficient and robust tool for solving the long-term generation scheduling problem.

Artificial neural networks and clustering techniques applied in the reconfiguration of distribution systems

One objective of the feeder reconfiguration problem in distribution systems is to minimize the power losses for a specific load. For this problem, mathematical modeling is a nonlinear mixed integer problem that is generally hard to solve. This paper proposes an algorithm based on artificial neural network theory. In this context, clustering techniques to determine the best training set for a single neural network with generalization ability are also presented. The proposed methodology was employed for solving two electrical systems and presented good results. Moreover, the methodology can be employed for large-scale systems in real-time environment.

Allocation of protective devices in distribution circuits using nonlinear programming models and genetic algorithms

The optimized allocation of protective devices in strategic points of the circuit improves the quality of the energy supply and the system reliability index. This paper presents a nonlinear integer programming (NLIP) model with binary variables, to deal with the problem of protective device allocation in the main feeder and all branches of an overhead distribution circuit, to improve the reliability index and to provide customers with service of high quality and reliability. The constraints considered in the problem take into account technical and economical limitations, such as coordination problems of serial protective devices, available equipment, the importance of the feeder and the circuit topology. The use of genetic algorithms (GAs) is proposed to solve this problem, using a binary representation that does (1) or does not (0) show allocation of protective devices (reclosers, sectionalizers and fuses) in predefined points of the circuit. Results are presented for a real circuit (134 busses), with the possibility of protective device allocation in 29 points. Also the ability of the algorithm in finding good solutions while improving significantly the indicators of reliability is shown. (C) 2003 Elsevier B.V. All rights reserved.

A method for plotting the complementary root locus using the root-locus (positive gain) rules

The root-locus method is a well-known and commonly used tool in control system analysis and design. It is an important topic in introductory undergraduate engineering control disciplines. Although complementary root locus (plant with negative gain) is not as common as root locus (plant with positive gain) and in many introductory textbooks for control systems is not presented, it has been shown a valuable tool in control system design. This paper shows that complementary root locus can be plotted using only the well-known construction rules to plot root locus. It can offer for the students a better comprehension on this subject. These results present a procedure to avoid problems that appear in root-locus plots for plants with the same number of poles and zeros.

Sensitivity analysis by neural networks applied to power systems transient stability

This work presents a procedure for transient stability analysis and preventive control of electric power systems, which is formulated by a multilayer feedforward neural network. The neural network training is realized by using the back-propagation algorithm with fuzzy controller and adaptation of the inclination and translation parameters of the nonlinear function. These procedures provide a faster convergence and more precise results, if compared to the traditional back-propagation algorithm. The adaptation of the training rate is effectuated by using the information of the global error and global error variation. After finishing the training, the neural network is capable of estimating the security margin and the sensitivity analysis. Considering this information, it is possible to develop a method for the realization of the security correction (preventive control) for levels considered appropriate to the system, based on generation reallocation and load shedding. An application for a multimachine power system is presented to illustrate the proposed methodology. (c) 2006 Elsevier B.V. All rights reserved.

Multistage and coordinated planning of the expansion of transmission systems

In this paper, an efficient genetic algorithm (GA) is presented to solve the problem of multistage and coordinated transmission expansion planning. This is a mixed integer nonlinear programming problem, difficult for systems of medium and large size and high complexity. The GA presented has a set of specialized genetic operators and an efficient form of generation of the initial population that finds high quality suboptimal topologies for large size and high complexity systems. In these systems, multistage and coordinated planning present a lower investment than static planning. Tests results are shown in one medium complexity system and one large size high complexity system.