Toward a Run-Time Verification Framework for Real-Time Safety-Critical Systems

Presented at SEMINAR "ACTION TEMPS RÉEL:INFRASTRUCTURES ET SERVICES SYSTÉMES". 10, Apr, 2015. Brussels, Belgium.

Culture, politics and identity: critical readings on gender in southeast Asia

Indian Journal of Gender Studies October 2012 vol. 19 no. 3 437-467

Particle swarm optimization based approaches to vehicle-to-grid scheduling

This paper addresses the problem of energy resources management using modern metaheuristics approaches, namely Particle Swarm Optimization (PSO), New Particle Swarm Optimization (NPSO) and Evolutionary Particle Swarm Optimization (EPSO). The addressed problem in this research paper is intended for aggregators’ use operating in a smart grid context, dealing with Distributed Generation (DG), and gridable vehicles intelligently managed on a multi-period basis according to its users’ profiles and requirements. The aggregator can also purchase additional energy from external suppliers. The paper includes a case study considering a 30 kV distribution network with one substation, 180 buses and 90 load points. The distribution network in the case study considers intense penetration of DG, including 116 units from several technologies, and one external supplier. A scenario of 6000 EVs for the given network is simulated during 24 periods, corresponding to one day. The results of the application of the PSO approaches to this case study are discussed deep in the paper.

Self-optimization for dynamic scheduling in manufacturing systems

Scheduling is a critical function that is present throughout many industries and applications. A great need exists for developing scheduling approaches that can be applied to a number of different scheduling problems with significant impact on performance of business organizations. A challenge is emerging in the design of scheduling support systems for manufacturing environments where dynamic adaptation and optimization become increasingly important. In this paper, we describe a Self-Optimizing Mechanism for Scheduling System through Nature Inspired Optimization Techniques (NIT).

Ancillary services dispatch using linear programming and genetic algorithm approaches

Electricity market players operating in a liberalized environment requires access to an adequate decision support tool, allowing them to consider all the business opportunities and take strategic decisions. Ancillary services represent a good negotiation opportunity that must be considered by market players. For this, decision support tools must include ancillary market simulation. This paper proposes two different methods (Linear Programming and Genetic Algorithm approaches) for ancillary services dispatch. The methodologies are implemented in MASCEM, a multi-agent based electricity market simulator. A test case concerning the dispatch of Regulation Down, Regulation Up, Spinning Reserve and Non-Spinning Reserve services is included in this paper.

Self-optimization aspects for dynamic scheduling

Scheduling is a critical function that is present throughout many industries and applications. A great need exists for developing scheduling approaches that can be applied to a number of different scheduling problems with significant impact on performance of business organizations. A challenge is emerging in the design of scheduling support systems for manufacturing environments where dynamic adaptation and optimization become increasingly important. At this scenario, self-optimizing arise as the ability of the agent to monitor its state and performance and proactively tune itself to respond to environmental stimuli.

Context-aware emotion-based model for group decision making

Involving groups in important management processes such as decision making has several advantages. By discussing and combining ideas, counter ideas, critical opinions, identified constraints, and alternatives, a group of individuals can test potentially better solutions, sometimes in the form of new products, services, and plans. In the past few decades, operations research, AI, and computer science have had tremendous success creating software systems that can achieve optimal solutions, even for complex problems. The only drawback is that people don’t always agree with these solutions. Sometimes this dissatisfaction is due to an incorrect parameterization of the problem. Nevertheless, the reasons people don’t like a solution might not be quantifiable, because those reasons are often based on aspects such as emotion, mood, and personality. At the same time, monolithic individual decisionsupport systems centered on optimizing solutions are being replaced by collaborative systems and group decision-support systems (GDSSs) that focus more on establishing connections between people in organizations. These systems follow a kind of social paradigm. Combining both optimization- and socialcentered approaches is a topic of current research. However, even if such a hybrid approach can be developed, it will still miss an essential point: the emotional nature of group participants in decision-making tasks. We’ve developed a context-aware emotion based model to design intelligent agents for group decision-making processes. To evaluate this model, we’ve incorporated it in an agent-based simulator called ABS4GD (Agent-Based Simulation for Group Decision), which we developed. This multiagent simulator considers emotion- and argument based factors while supporting group decision-making processes. Experiments show that agents endowed with emotional awareness achieve agreements more quickly than those without such awareness. Hence, participant agents that integrate emotional factors in their judgments can be more successful because, in exchanging arguments with other agents, they consider the emotional nature of group decision making.

Inexact restoration approaches to solve mathematical program with complementarity constraints

Mathematical Program with Complementarity Constraints (MPCC) finds applica- tion in many fields. As the complementarity constraints fail the standard Linear In- dependence Constraint Qualification (LICQ) or the Mangasarian-Fromovitz constraint qualification (MFCQ), at any feasible point, the nonlinear programming theory may not be directly applied to MPCC. However, the MPCC can be reformulated as NLP problem and solved by nonlinear programming techniques. One of them, the Inexact Restoration (IR) approach, performs two independent phases in each iteration - the feasibility and the optimality phases. This work presents two versions of an IR algorithm to solve MPCC. In the feasibility phase two strategies were implemented, depending on the constraints features. One gives more importance to the complementarity constraints, while the other considers the priority of equality and inequality constraints neglecting the complementarity ones. The optimality phase uses the same approach for both algorithm versions. The algorithms were implemented in MATLAB and the test problems are from MACMPEC collection.

Sistema de visão para percepção e navegação de um UAV Quadrotor

Mestrado em Engenharia Electrotécnica e de Computadores

Adaptive learning in agents behaviour: a framework for electricity markets simulation

Electricity markets are complex environments with very particular characteristics. A critical issue regarding these specific characteristics concerns the constant changes they are subject to. This is a result of the electricity markets’ restructuring, which was performed so that the competitiveness could be increased, but it also had exponential implications in the increase of the complexity and unpredictability in those markets scope. The constant growth in markets unpredictability resulted in an amplified need for market intervenient entities in foreseeing market behaviour. The need for understanding the market mechanisms and how the involved players’ interaction affects the outcomes of the markets, contributed to the growth of usage of simulation tools. Multi-agent based software is particularly well fitted to analyze dynamic and adaptive systems with complex interactions among its constituents, such as electricity markets. This dissertation presents ALBidS – Adaptive Learning strategic Bidding System, a multiagent system created to provide decision support to market negotiating players. This system is integrated with the MASCEM electricity market simulator, so that its advantage in supporting a market player can be tested using cases based on real markets’ data. ALBidS considers several different methodologies based on very distinct approaches, to provide alternative suggestions of which are the best actions for the supported player to perform. The approach chosen as the players’ actual action is selected by the employment of reinforcement learning algorithms, which for each different situation, simulation circumstances and context, decides which proposed action is the one with higher possibility of achieving the most success. Some of the considered approaches are supported by a mechanism that creates profiles of competitor players. These profiles are built accordingly to their observed past actions and reactions when faced with specific situations, such as success and failure. The system’s context awareness and simulation circumstances analysis, both in terms of results performance and execution time adaptation, are complementary mechanisms, which endow ALBidS with further adaptation and learning capabilities.

Heading east this time: critical readings on gender in southeast Asia

This essay intends to discuss some critical readings of fictional and theoretical texts on gender condition in Southeast Asian countries. Nowadays, many texts about women in Southeast Asia apply concepts of power in unusual areas. Traditional forms of gender hegemony have been replaced by other powerful, if somewhat more covert, forms. We will discuss some universal values concerning conventional female roles as well as the strategies used to recognize women in political fields traditionally characterized by male dominance. Female empowerment will mean different things at different times in history, as a result of culture, local geography and individual circumstances. Empowerment needs to be perceived as an individual attitude, but it also has to be facilitated at the macrolevel by society and the State. Gender is very much at the heart of all these dynamics, strongly related to specificities of historical, cultural, ethnic and class situatedness, requiring an interdisciplinary transnational approach.

Para uma leitura não biográfica da obra de Mário de Sá Carneiro (e uma apreciação de o modernismo em Mário de Sá-Carneiro de Fernando Cabral Martins)

Este artigo pretende sublinhar a importância de entender a obra de Mário de Sá- Carneiro através de uma leitura atenta da sua produção literária que não procura provas da “veracidade” dessa leitura na biografia do poeta do Orpheu. Partindo de uma análise do trabalho crítico de Fernando Cabral Martins, levanta-se a problemática de deturpar uma análise de crítica literária com abordagens influenciadas por normas de história da literatura que inserem a obra no seu contexto histórico, o que tem sido o caso na recepção da obra de Sá-Carneiro, onde o mito do autor tende a ofuscar o seu legado literário. Assim, este artigo questiona se em O Modernismo em Mário de Sá-Carneiro, Fernando Cabral Martins consegue libertar a obra sá-carneiriana da sombra do poeta biográfico, e oferece uma avaliação panorâmica da tradição crítica dedicada ao autor, apontando para casos de interpretações que se prenderam com questões que ficam para fora do texto, como tem sido o caso com a natureza homossexual da obra e do homem.

Nephrotoxicity effects of the wood preservative chromium copper arsenate on mice: histopathological and quantitative approaches

Chromium copper arsenate(CCA)was used for the protection of wood building material suntil the restriction by EPA in2002. During a short period of time 14–24h,a comparative nephrotoxicity study was performed regarding the effects of CCA and its compounds per se. Histopathological and histochemical features were correlated with the concentration of the total arsenic and chromium in mice kidney. Animals were subcutaneously injected with CCA(7.2mg/kg arsenic and 10.2mg/kg chromium per body weight), CrO3 (10.2 mg/kg),As2O5 (7.2 mg/kg)andNaCl(0.9%) per se. The histopathological examination of the renal sections evidenced acute tubular necrosis in the groups of animals exposed to CCA(in both periods of time). Although the same contents of pentavalent arsenic and hexavalent chromium were injected in treated animals with CCA and with the prepared solutions of As2O5 and CrO3, the arsenic concentration on kidneys of CCA-exposed animals was much higher than those in animals exposed to As2O5 (32- and28-fold higher at 14 and 24h,respectively). However,the elimination of chromium seems to occur similarly in the kidneys of animals treated with CCA and CrO3 per se. Interactions among the components of CCA result in a marked decrease of the ability of kidney to eliminate simultaneously both analytes.The nephrotoxicity of CCA was higher than its components per se, evidencing a possible synergetic effect.

A perspective on LCA application in site remediation services: critical review of challenges

The remediation of contaminated sites supports the goal of sustainable development but may also have environmental impacts at a local, regional and global scale. Life cycle assessment (LCA) has increasingly been used in order to support site remediation decision-making. This review article discusses existing LCA methods and proposed models focusing on critical decisions and assumptions of the LCA application to site remediation activities. It is concluded that LCA has limitations as an adequate holistic decisionmaking tool since spatial and temporal differentiation of non-global impacts assessment is a major hurdle in site remediation LCA. Moreover, a consequential LCA perspective should be adopted when the different remediation services to be compared generate different site’s physical states, displacing alternative post-remediation scenarios. The environmental effects of the post-remediation stage of the site is generally disregarded in the past site remediation LCA studies and such exclusion may produce misleading conclusions and misdirected decision-making. In addition, clear guidance accepted by all stakeholders on remediation capital equipment exclusion and on dealing with multifunctional processes should be developed for site remediation LCA applications.

Comparison of allocation approaches in soybean biodiesel life cycle assessment

This work shows the influence of using different allocation approaches when modelling the inventory analysis in a soybean biodiesel life cycle assessment (LCA). Results obtained using mass, energy and economic based allocations are compared, focusing on the following aspects: normalised potential environmental impact (PEI) categories, total PEI and relative contributions to the total PEI from each life cycle stage and environmental impact category. Similar results are obtained either using economic and energy based allocations. However, different results are obtained when mass based allocation is used when compared with the other two. This study also illustrates that using different allocation approaches in biodiesel LCA may influence the final conclusions, especially in comparative assertions, emphasising the need to perform a sensitivity analysis in the LCA interpretation step.