Scheduling a cutting and treatment stainless steel sheet line with self-management capabilities

With advancement in computer science and information technology, computing systems are becoming increasingly more complex with an increasing number of heterogeneous components. They are thus becoming more difficult to monitor, manage, and maintain. This process has been well known as labor intensive and error prone. In addition, traditional approaches for system management are difficult to keep up with the rapidly changing environments. There is a need for automatic and efficient approaches to monitor and manage complex computing systems. In this paper, we propose an innovative framework for scheduling system management by combining Autonomic Computing (AC) paradigm, Multi-Agent Systems (MAS) and Nature Inspired Optimization Techniques (NIT). Additionally, we consider the resolution of realistic problems. The scheduling of a Cutting and Treatment Stainless Steel Sheet Line will be evaluated. Results show that proposed approach has advantages when compared with other scheduling systems

Information technology service management: an experimental approach towards IT service prediction

Dissertation presented to obtain a Masters degree in Computer Science

Extensible metadata repository for information systems

Thesis submitted to Faculdade de Ciências e Tecnologia of the Universidade Nova de Lisboa, in partial fulfillment of the requirements for the degree of Master in Computer Science

A tool to aid institutions recognize their employees competences acquired by informal learning

People do not learn only in formal educational institutions, but also throughout their lives, from their experiences, conversations, observations of others, exploration of the Internet, meetings and conferences, and chance encounters etc. However this informal and non-formal learning can easily remain largely invisible, making it hard for peers and employers to recognize or act upon it. The TRAILER project aims to make this learning visible so that it can benefit both the individual and the organization. The proposed demonstration will show a software solution that (i) helps the learners to capture, organize and classify a wide range of ’informal’ learning taking place in their lives, and (ii) assists the organization in recognizing this learning and use it to help managing human resources (benefiting both parts). This software tool has recently been used in two phases of pilot studies, which have run in four different European countries.

On-line defragmentation for run-time partially reconfigurable FPGAs

Dynamically reconfigurable systems have benefited from a new class of FPGAs recently introduced into the market, which allow partial and dynamic reconfiguration at run-time, enabling multiple independent functions from different applications to share the same device, swapping resources as needed. When the sequence of tasks to be performed is not predictable, resource allocation decisions have to be made on-line, fragmenting the FPGA logic space. A rearrangement may be necessary to get enough contiguous space to efficiently implement incoming functions, to avoid spreading their components and, as a result, degrading their performance. This paper presents a novel active replication mechanism for configurable logic blocks (CLBs), able to implement on-line rearrangements, defragmenting the available FPGA resources without disturbing those functions that are currently running.

Personalized public transportation information

Thesis to obtain the Master of Science Degree in Computer Science and Engineering

Solving Conflicting Beliefs with a Distributed Belief Revision Approach

The ability to solve conflicting beliefs is crucial for multi- agent systems where the information is dynamic, incomplete and dis- tributed over a group of autonomous agents. The proposed distributed belief revision approach consists of a distributed truth maintenance sy- stem and a set of autonomous belief revision methodologies. The agents have partial views and, frequently, hold disparate beliefs which are au- tomatically detected by system’s reason maintenance mechanism. The nature of these conflicts is dynamic and requires adequate methodolo- gies for conflict resolution. The two types of conflicting beliefs addressed in this paper are Context Dependent and Context Independent Conflicts which result, in the first case, from the assignment, by different agents, of opposite belief statuses to the same belief, and, in the latter case, from holding contradictory distinct beliefs. The belief revision methodology for solving Context Independent Con- flicts is, basically, a selection process based on the assessment of the cre- dibility of the opposing belief statuses. The belief revision methodology for solving Context Dependent Conflicts is, essentially, a search process for a consensual alternative based on a “next best” relaxation strategy.

Intelligent Distributed Environmental Decision Support System

This article discusses the development of an Intelligent Distributed Environmental Decision Support System, built upon the association of a Multi-agent Belief Revision System with a Geographical Information System (GIS). The inherent multidisciplinary features of the involved expertises in the field of environmental management, the need to define clear policies that allow the synthesis of divergent perspectives, its systematic application, and the reduction of the costs and time that result from this integration, are the main reasons that motivate the proposal of this project. This paper is organised in two parts: in the first part we present and discuss the developed Distributed Belief Revision Test-bed — DiBeRT; in the second part we analyse its application to the environmental decision support domain, with special emphasis on the interface with a GIS.

Automated illustration of multimedia stories

Submitted in part fulfillment of the requirements for the degree of Master in Computer Science

Integrated Management of IaaS Resources

This paper proposes and reports the development of an open source solution for the integrated management of Infrastructure as a Service (IaaS) cloud computing resources, through the use of a common API taxonomy, to incorporate open source and proprietary platforms. This research included two surveys on open source IaaS platforms (OpenNebula, OpenStack and CloudStack) and a proprietary platform (Parallels Automation for Cloud Infrastructure - PACI) as well as on IaaS abstraction solutions (jClouds, Libcloud and Deltacloud), followed by a thorough comparison to determine the best approach. The adopted implementation reuses the Apache Deltacloud open source abstraction framework, which relies on the development of software driver modules to interface with different IaaS platforms, and involved the development of a new Deltacloud driver for PACI. The resulting interoperable solution successfully incorporates OpenNebula, OpenStack (reuses pre-existing drivers) and PACI (includes the developed Deltacloud PACI driver) nodes and provides a Web dashboard and a Representational State Transfer (REST) interface library. The results of the exchanged data payload and time response tests performed are presented and discussed. The conclusions show that open source abstraction tools like Deltacloud allow the modular and integrated management of IaaS platforms (open source and proprietary), introduce relevant time and negligible data overheads and, as a result, can be adopted by Small and Medium-sized Enterprise (SME) cloud providers to circumvent the vendor lock-in problem whenever service response time is not critical.

A survey of e-learning content aggregation standards

As e-learning gradually evolved many specialized and disparate systems appeared to fulfil the needs of teachers and students, such as repositories of learning objects, authoring tools, intelligent tutors and automatic evaluators. This heterogeneity raises interoperability issues giving the standardization of content an important role in e-learning. This article presents a survey on current e-learning content aggregation standards focusing on their internal organization and packaging. This study is part of an effort to choose the most suitable specifications and standards for an e-learning framework called Ensemble defined as a conceptual tool to organize a network of e-learning systems and services for domains with complex evaluation.

Multiple Roots of Systems of Equations by Repulsion Merit Functions

In this paper we address the problem of computing multiple roots of a system of nonlinear equations through the global optimization of an appropriate merit function. The search procedure for a global minimizer of the merit function is carried out by a metaheuristic, known as harmony search, which does not require any derivative information. The multiple roots of the system are sequentially determined along several iterations of a single run, where the merit function is accordingly modified by penalty terms that aim to create repulsion areas around previously computed minimizers. A repulsion algorithm based on a multiplicative kind penalty function is proposed. Preliminary numerical experiments with a benchmark set of problems show the effectiveness of the proposed method.

Criador automático de aplicações nativas Android e iOS

Nos últimos anos tem-se verificado um acentuado aumento na utilização de dispositivos moveis a nível internacional, pelo que as aplicações desenvolvidas para este tipo específico de dispositivos, conhecidas por apps, tem vindo a ganhar uma enorme popularidade. São cada vez mais as empresas que procuram estar presentes nos mais diversos sistemas operativos móveis, com o objectivo de suportar e desenvolver o seu negócio, alargando o seu leque de possíveis consumidores. Neste sentido surgiram diversas ferramentas com a função de facilitar o desenvolvimento de aplicações móveis, denominadas frameworks multi-plataforma. Estas frameworks conduziram ao aparecimento de plataformas web, que permitem criar aplicações multi-plataforma sem ser obrigatório ter conhecimentos em programação. Assim, e a partir da análise de vários criadores online de aplicações móveis identificados e das diferentes estratégias de desenvolvimento de aplicações móveis existentes, foi proposta a implementação de uma plataforma web capaz de criar aplicações nativas Android e iOS, dois dos sistemas operativos mais utilizados na actualidade. Apos desenvolvida a plataforma web, designada MobileAppBuilder, foi avaliada a sua Qualidade e as aplicações criadas pela mesma, através do preenchimento de um questionário por parte de 10 indivíduos com formação em Engenharia Informática, resultando numa classificação geral de ”excelente”. De modo a analisar o desempenho das aplicações produzidas pela plataforma desenvolvida, foram realizados testes comparativos entre uma aplicação da MobileAppBuilder e duas homologas de dois dos criadores online estudados, nomeadamente Andromo e Como. Os resultados destes testes revelaram que a MobileAppBuilder gera aplicações menos pesadas, mais rápidas e mais eficientes em alguns aspetos, nomeadamente no arranque.

Demonstration of the Multi-Agent Simulator of Competitive Electricity Markets

Electricity markets are complex environments with very particular characteristics. A critical issue concerns the constant changes they are subject to. This is a result of the electricity markets’ restructuring, performed so that the competitiveness could be increased, but with 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 behavior. 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 paper presents the Multi-Agent System for Competitive Electricity Markets (MASCEM) – a simulator based on multi-agent technology that provides a realistic platform to simulate electricity markets, the numerous negotiation opportunities and the participating entities.

Automatic Electricity Markets Data Extraction for Realistic Multi-agent Simulations

Electricity markets worldwide suffered profound transformations. The privatization of previously nationally owned systems; the deregulation of privately owned systems that were regulated; and the strong interconnection of national systems, are some examples of such transformations [1, 2]. In general, competitive environments, as is the case of electricity markets, require good decision-support tools to assist players in their decisions. Relevant research is being undertaken in this field, namely concerning player modeling and simulation, strategic bidding and decision-support.