ESTG - CIICESI - Livro ou parte de livro, ou capítulo de livro
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- Ambient Intelligent Systems: The Role of Non-Intrusive and Sensitive ApproachesPublication . Gonçalves, Filipe; Pêgo, José Miguel; Carneiro, Davide; Novais, Paulo
- An Application to Enrich the Study of Auditory Emotion RecognitionPublication . Rodrigues, Renato; Mendes, Augusto J.; Carneiro, Davide; Amorim, Maria; Pinheiro, Ana P.; Novais, Paulo
- An Environment for Studying Visual Emotion PerceptionPublication . Carneiro, Davide; Rocha, Hélder; Novais, Paulo
- Analysis of Mental Fatigue and Mood States in WorkplacesPublication . Pimenta, André; Carneiro, Davide; Neves, José; Novais, Paulo
- Behavioral biometrics and ambient intelligence: New opportunities for context-aware applicationsPublication . Carneiro, Davide; Novais, Paulo
- A Case Study on Scheduling of Repairs in an Automobile ShopPublication . Pilar, M. Fátima; Costa e Silva, Eliana; Borges, AnaThe classical combinatorial problem of scheduling is extensively studied and arises in several economic domains. However, there are few studies in the automobile sector, particularly in scheduling vehicle repair tasks and using real instances. This paper intends to contribute to fill this gap, focusing on the scheduling of the repairs of the mechanical section of a Portuguese firm in the automobile sector. A mathematical model is presented that will assist the shop manager on the scheduling of the repairs, taking into account: the mechanics and other resources that are available, the mechanical interventions to be performed on each vehicle and its expected processing time. The aim is to reduce the time of inactivity of the vehicles between interventions, as well as, the downtime of mechanics, and therefore improve productivity. The results, from real instances extracted from the data provided by the firm, show that the interventions are scheduled in a suitable form, and there is a reduction of the downtimes.
- Classification of some penalty methodsPublication . Correia, Aldina; Matias, João; Mestre, Pedro; Serôdio, CarlosOptimization problems arise in science, engineering, economy, etc. and we need to find the best solutions for each reality. The methods used to solve these problems depend on several factors, including the amount and type of accessible information, the available algorithms for solving them, and, obviously, the intrinsic characteristics of the problem. There are many kinds of optimization problems and, consequently, many kinds of methods to solve them. When the involved functions are nonlinear and their derivatives are not known or are very difficult to calculate, these methods are more rare. These kinds of functions are frequently called black box functions. To solve such problems without constraints (unconstrained optimization), we can use direct search methods. These methods do not require any derivatives or approximations of them. But when the problem has constraints (nonlinear programming problems) and, additionally, the constraint functions are black box functions, it is much more difficult to find the most appropriate method. Penalty methods can then be used. They transform the original problem into a sequence of other problems, derived from the initial, all without constraints. Then this sequence of problems (without constraints) can be solved using the methods available for unconstrained optimization. In this chapter, we present a classification of some of the existing penalty methods and describe some of their assumptions and limitations. These methods allow the solving of optimization problems with continuous, discrete, and mixing constraints, without requiring continuity, differentiability, or convexity. Thus, penalty methods can be used as the first step in the resolution of constrained problems, by means of methods that typically are used by unconstrained problems. We also discuss a new class of penalty methods for nonlinear optimization, which adjust the penalty parameter dynamically.
- Detection of Behavioral Patterns for Increasing Attentiveness LevelPublication . Durães, Dalila; Gonçalves, Sérgio; Carneiro, Davide; Bajo, Javier; Novais, Paulo
- EUStress: A Human Behaviour Analysis System for Monitoring and Assessing Stress During ExamsPublication . Gonçalves, Filipe; Carneiro, Davide; Novais, Paulo; Pêgo, José
- Guia do Investidor do Tâmega e SousaPublication . Pereira, Carla Sofia; Braga, VítorPorquê o Tâmega e Sousa?; Localização; Pessoas; Caracterização Empresarial • Fileira da Moda (Têxtil e Vestuário) • Fileira da Moda (Calçado) • Mobiliário • Metalomecânica Infraestruturas: • Áreas Empresariais • Incubadoras de Empresas • Investigação e Desenvolvimento • Educação Qualidade de Vida; Cultura; Turismo; O Território do Tâmega e Sousa: • Amarante • Baião • Castelo de Paiva • Celorico de Basto • Cinfães • Felgueiras • Lousada • Marco de Canaveses • Paços de Ferreira • Penafiel • Resende Investir no Tâmega E Sousa; Apoio ao Investimento; Definir a Estrutura de uma Empresa; Criar uma Empresa; Contratar Pessoas; Custos da Sua Empresa; Viver no Tâmega e Sousa; Incentivos Municipais; Outros Incentivos. Programas de Apoio Nacionais Informações Úteis Contactos Úteis
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