Percorrer por autor "Sousa, Nelson"
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- Atipia das células glandulares: qual o diagnóstico?Publication . Pisco, Filipa; Sousa, Nelson; Fonseca, PaulaNo âmbito das patologias ginecológicas, o cancro do ovário apresenta a taxa de mortalidade mais elevada, uma vez que só é diagnosticado numa fase tardia quando surgem os primeiros sintomas. O caso em estudo corresponde a uma citologia de follow-up, após histerectomia total por carcinoma do ovário indiferenciado. A avaliação citológica sugeriu um Adenocarcinoma enquanto o diagnóstico histológico da lesão nodular revelou uma recidiva de Carcinoma Papilar Seroso do Ovário. A realização do exame histológico, neste e noutros casos, constitui uma peça fundamental para a confirmação do diagnóstico citológico, assim como para o diagnóstico diferencial.
- Autonomic computing for scheduling in manufacturing systemsPublication . Madureira, Ana Maria; Pereira, Ivo; Sousa, Nelson; Ávila, Paulo; Bastos, JoãoWe describe a novel approach to scheduling resolution by combining Autonomic Computing (AC), Multi-Agent Systems (MAS) and Nature Inspired Optimization Techniques (NIT). Autonomic Computing has emerged as paradigm aiming at embedding applications with a management structure similar to a central nervous system. A natural Autonomic Computing evolution in relation to Current Computing is to provide systems with Self-Managing ability with a minimum human interference. In this paper we envisage the use of Multi-Agent Systems paradigm for supporting dynamic and distributed scheduling in Manufacturing Systems with Autonomic properties, in order to reduce the complexity of managing systems and human interference. 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.
- Collective intelligence on dynamic manufacturing scheduling optimizationPublication . Madureira, Ana Maria; Pereira, Ivo; Sousa, NelsonSwarm Intelligence (SI) is a growing research field of Artificial Intelligence (AI). SI is the general term for several computational techniques which use ideas and get inspiration from the social behaviours of insects and of other animals. This paper presents hybridization and combination of different AI approaches, like Bio-Inspired Techniques (BIT), Multi-Agent systems (MAS) and Machine Learning Techniques (ML T). The resulting system is applied to the problem of jobs scheduling to machines on dynamic manufacturing environments.
- Comparative analysis between scheduling tools for cutting sheet metal industryPublication . Sousa, Nelson; Ávila, Paulo; Bastos, JoãoIn order to be competitive, companies need to embrace sustainable policies and practices. Company leaders are taking a new stand on sustainability, recognizing that there is opportunity inherent in the need to provide solutions to the world's environmental and social challenges. This paper addresses a very common objective in Industry: how to radically improve efficiency for core processes and activities, in order to reduce waste and resources consumption, through the use of operational planning tools. The present paper summarizes the research work conducted in a metal cutting sheet manufacturing company. The study involved the analysis of the company production process and the investigation of the working methods in order to evaluate material consumptions, response time and overall plans efficiency.
- Mecanismo de negociação para sistema de escalonamento dinâmicoPublication . Madureira, Ana Maria; Sousa, Nelson; Pereira, IvoEste artigo propõe um Mecanismo de Negociação para Escalonamento Dinâmico com recurso a Swarm Intelligence (SI). No Mecanismo de Negociação, os agentes devem competir para obter um plano de escalamento global. SI é o termo geral para várias técnicas computacionais que retiram ideias e inspiração nos comportamentos sociais de insectos e outros animais. Este artigo propõe uma abordagem híbrida de diferentes conceitos da Inteligência Artificial (IA), como SI, Negociação em Sistemas Multi-Agente (SMA) e Técnicas de Aprendizagem Automática (AA). Este trabalho concentra a sua atenção na negociação, processo através do qual múltiplos agentes auto-interessados podem chegar a acordo através da troca competitiva de recursos.
- Negotiation mechanism for self-organized scheduling systemPublication . Madureira, Ana Maria; Sousa, Nelson; Pereira, IvoThis paper presents a negotiation mechanism for Dynamic Scheduling based on Swarm Intelligence (SI). Under the new negotiation mechanism, agents must compete to obtain a global schedule. SI is the general term for several computational techniques which use ideas and get inspiration from the social behaviors of insects and other animals. This work is concerned with negotiation, the process through which multiple selfinterested agents can reach agreement over the exchange of operations on competitive resources.
- Scheduling a cutting and treatment stainless steel sheet line with self-management capabilitiesPublication . Madureira, Ana Maria; Pereira, Ivo; Sousa, Nelson; Ávila, Paulo; Bastos, JoãoWith 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
- Self-organization for scheduling in agile manufacturingPublication . Madureira, Ana Maria; Pereira, Ivo; Sousa, NelsonAgility refers to the manufacturing system ability to rapidly adapt to market and environmental changes in efficient and cost-effective ways. This paper addresses the development of self-organization methods to enhance the operations of a scheduling system, by integrating scheduling system, configuration and optimization into a single autonomic process requiring minimal manual intervention to increase productivity and effectiveness while minimizing complexity for users. We intend to conceptualize real manufacturing systems as interacting autonomous entities in order to build future Decision Support Systems (DSS) for Scheduling in agile manufacturing environments.
- Swarm intelligence for scheduling: a reviewPublication . Madureira, Ana Maria; Sousa, Nelson; Pereira, IvoSwarm Intelligence generally refers to a problem-solving ability that emerges from the interaction of simple information-processing units. The concept of Swarm suggests multiplicity, distribution, stochasticity, randomness, and messiness. The concept of Intelligence suggests that problem-solving approach is successful considering learning, creativity, cognition capabilities. This paper introduces some of the theoretical foundations, the biological motivation and fundamental aspects of swarm intelligence based optimization techniques such Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO) and Artificial Bees Colony (ABC) algorithms for scheduling optimization.