A lightweight distributed super peer election algorithm for unstructured dynamic P2P systems

Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para obtenção do grau de Mestre em Engenharia Electrotécnica e de Computadores

Information professionals in business context: new professionals, old skills

This communication aims to present some reflections regarding the importance of information in organizational context, especially in business context. The ability to produce and to share expertise and knowledge among its employees is now a key factor in the success of any organization. However, it’s also true that workers are increasingly feeling that too much information can hurt their performance. The existence of skilled professionals able to organize, evaluate, select and disseminate information in organizations appears to be a prerequisite for success. The skills necessary for the formation of a professional devoted to the management of information and knowledge in the context of business organizations will be analysed. Then data collected in two focus group discussion with students from a graduate course in Business Information, from Polytechnic Institute of Porto, Portugal, a will be examined.

Pré-processamento e Tag automático de imagens em ambiente móvel e web, aplicado a um sistema de informação geográfica

No panorama socioeconómico atual, a contenção de despesas e o corte no financiamento de serviços secundários consumidores de recursos conduzem à reformulação de processos e métodos das instituições públicas, que procuram manter a qualidade de vida dos seus cidadãos através de programas que se mostrem mais eficientes e económicos. O crescimento sustentado das tecnologias móveis, em conjunção com o aparecimento de novos paradigmas de interação pessoa-máquina com recurso a sensores e sistemas conscientes do contexto, criaram oportunidades de negócio na área do desenvolvimento de aplicações com vertente cívica para indivíduos e empresas, sensibilizando-os para a disponibilização de serviços orientados ao cidadão. Estas oportunidades de negócio incitaram a equipa do projeto a desenvolver uma plataforma de notificação de problemas urbanos baseada no seu sistema de informação geográfico para entidades municipais. O objetivo principal desta investigação foca a idealização, conceção e implementação de uma solução completa de notificação de problemas urbanos de caráter não urgente, distinta da concorrência pela facilidade com que os cidadãos são capazes de reportar situações que condicionam o seu dia-a-dia. Para alcançar esta distinção da restante oferta, foram realizados diversos estudos para determinar características inovadoras a implementar, assim como todas as funcionalidades base expectáveis neste tipo de sistemas. Esses estudos determinaram a implementação de técnicas de demarcação manual das zonas problemáticas e reconhecimento automático do tipo de problema reportado nas imagens, ambas desenvolvidas no âmbito deste projeto. Para a correta implementação dos módulos de demarcação e reconhecimento de imagem, foram feitos levantamentos do estado da arte destas áreas, fundamentando a escolha de métodos e tecnologias a integrar no projeto. Neste contexto, serão apresentadas em detalhe as várias fases que constituíram o processo de desenvolvimento da plataforma, desde a fase de estudo e comparação de ferramentas, metodologias, e técnicas para cada um dos conceitos abordados, passando pela proposta de um modelo de resolução, até à descrição pormenorizada dos algoritmos implementados. Por último, é realizada uma avaliação de desempenho ao par algoritmo/classificador desenvolvido, através da definição de métricas que estimam o sucesso ou insucesso do classificador de objetos. A avaliação é feita com base num conjunto de imagens de teste, recolhidas manualmente em plataformas públicas de notificação de problemas, confrontando os resultados obtidos pelo algoritmo com os resultados esperados.

Using Baseline Methods to Identify Non-technical Losses in the Context of Smart Grids

Demand response has gained increasing importance in the context of competitive electricity markets and smart grid environments. In addition to the importance that has been given to the development of business models for integrating demand response, several methods have been developed to evaluate the consumers’ performance after the participation in a demand response event. The present paper uses those performance evaluation methods, namely customer baseline load calculation methods, to determine the expected consumption in each period of the consumer historic data. In the cases in which there is a certain difference between the actual consumption and the estimated consumption, the consumer is identified as a potential cause of non-technical losses. A case study demonstrates the application of the proposed method to real consumption data.

Reinforcement Learning Based on the Bayesian Theorem for Electricity Markets Decision Support

This paper presents the applicability of a reinforcement learning algorithm based on the application of the Bayesian theorem of probability. The proposed reinforcement learning algorithm is an advantageous and indispensable tool for ALBidS (Adaptive Learning strategic Bidding System), a multi-agent system that has the purpose of providing decision support to electricity market negotiating players. ALBidS uses a set of different strategies for providing decision support to market players. These strategies are used accordingly to their probability of success for each different context. The approach proposed in this paper uses a Bayesian network for deciding the most probably successful action at each time, depending on past events. The performance of the proposed methodology is tested using electricity market simulations in MASCEM (Multi-Agent Simulator of Competitive Electricity Markets). MASCEM provides the means for simulating a real electricity market environment, based on real data from real electricity market operators.

Application-Specific Modified Particle Swarm Optimization for energy resource scheduling considering vehicle-to-grid

This paper presents a modified Particle Swarm Optimization (PSO) methodology to solve the problem of energy resources management with high penetration of distributed generation and Electric Vehicles (EVs) with gridable capability (V2G). The objective of the day-ahead scheduling problem in this work is to minimize operation costs, namely energy costs, regarding the management of these resources in the smart grid context. The modifications applied to the PSO aimed to improve its adequacy to solve the mentioned problem. The proposed Application Specific Modified Particle Swarm Optimization (ASMPSO) includes an intelligent mechanism to adjust velocity limits during the search process, as well as self-parameterization of PSO parameters making it more user-independent. It presents better robustness and convergence characteristics compared with the tested PSO variants as well as better constraint handling. This enables its use for addressing real world large-scale problems in much shorter times than the deterministic methods, providing system operators with adequate decision support and achieving efficient resource scheduling, even when a significant number of alternative scenarios should be considered. The paper includes two realistic case studies with different penetration of gridable vehicles (1000 and 2000). The proposed methodology is about 2600 times faster than Mixed-Integer Non-Linear Programming (MINLP) reference technique, reducing the time required from 25 h to 36 s for the scenario with 2000 vehicles, with about one percent of difference in the objective function cost value.

Distributed Energy Resources Management using Plug-in Hybrid Electric Vehicles as a Fuel-Shifting Demand Response Resource

In the smart grids context, distributed energy resources management plays an important role in the power systems’ operation. Battery electric vehicles and plug-in hybrid electric vehicles should be important resources in the future distribution networks operation. Therefore, it is important to develop adequate methodologies to schedule the electric vehicles’ charge and discharge processes, avoiding network congestions and providing ancillary services. This paper proposes the participation of plug-in hybrid electric vehicles in fuel shifting demand response programs. Two services are proposed, namely the fuel shifting and the fuel discharging. The fuel shifting program consists in replacing the electric energy by fossil fuels in plug-in hybrid electric vehicles daily trips, and the fuel discharge program consists in use of their internal combustion engine to generate electricity injecting into the network. These programs are included in an energy resources management algorithm which integrates the management of other resources. The paper presents a case study considering a 37-bus distribution network with 25 distributed generators, 1908 consumers, and 2430 plug-in vehicles. Two scenarios are tested, namely a scenario with high photovoltaic generation, and a scenario without photovoltaic generation. A sensitivity analyses is performed in order to evaluate when each energy resource is required.

A study on parallel versus sequential relational fuzzy clustering methods

Dissertação para obtenção do Grau de Mestre em Engenharia Informática

Vision based context categorization for all-terrain robot

Dissertation presented at the Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa to obtain the Master degree in Electrical and Computer Engineering.

Study of Load Curves Concerning the Influence of Socioeconomic and Cultural Issues

The increase of electricity demand in Brazil, the lack of the next major hydroelectric reservoirs implementation, and the growth of environmental concerns lead utilities to seek an improved system planning to meet these energy needs. The great diversity of economic, social, climatic, and cultural conditions in the country have been causing a more difficult planning of the power system. The work presented in this paper concerns the development of an algorithm that aims studying the influence of the issues mentioned in load curves. Focus is given to residential consumers. The consumption device with highest influence in the load curve is also identified. The methodology developed gains increasing importance in the system planning and operation, namely in the smart grids context.

Artificial Intelligence in geospatial analysis: applications of self-organizing maps in the context of geographic information science.

A thesis submitted in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Information Systems.

Satisfaction towards human resources practices and repatriates’ retention: an empirical examination in the portuguese companies context

This paper examines the relationship between the level of satisfaction towards Human Resources Management practices among repatriates and the decision to remain on the home company after expatriation. Data was collected through semi-structured interviews of 28 Portuguese repatriates who remain and 16 organisational representatives from eight companies located in Portugal. The results show that (1) compensation system during the international assignment; (2) permanent support during the international assignment and; (3) recognition upon the return of the work and effort of expatriates during the international assignment are the most important HRM practices for promoting satisfaction among repatriates. Moreover, it is at repatriation phase that repatriates show higher dissatisfaction with HRM support. These findings will be discussed in detail and implications and suggestions for future research will be proposed as well.

Constructing and validating a scale of employee satisfaction with HRM practices in the healthcare context

The concept of HRM perceptions is a growing interest in the literature, as one of the antecedents of HRM outcomes. Regardless, not only the cognitive aspect of perception is interesting in this field (what you think) but also the affective perspective is of interest (how you feel about it). In this study we propose a scale for assessing satisfaction with the perceptions of the HRM practices. A 24 item Likert-type scale was developed considering literature review, to assess subjects’ satisfaction with Human Resources Practices in a healthcare setting. Talked reflections were held and a survey encompassing all workers from a Hospital was conducted later, with a sample of 922 subjects. Exploratory and Confirmatory Factor Analysis were performed; reliability was tested using Cronbach’s alpha. The scale presents good psychometric properties with alpha values that range from .71 to .91. Exploratory and Confirmatory Factor Analysis demonstrated that the scale presents a very good fit with CFI= 0.94, AGFI= 0.88, and RMSEA= 0.07. The present study represents a first approach in the usage of this scale and despite having a large sample, respondents originate from a single institution. This study presents a pertinent scale towards measuring a seldom explored construct of the worker-organization relationship. The scale is parsimonious and results are promising. There seems to be very little research on how subjects feel about the HRM practices. This construct, very much in line with more recent studies concerning worker perceptions can be especially interesting in the context of the worker-organization relationship.

Constraint-based modeling of minimum set covering: application to species differentation

Work presented in the context of the European Master in Computational Logics, as partial requisit for the graduation as Master in Computational Logics