15 resultados para Berthing allocation
em Repositório Científico do Instituto Politécnico de Lisboa - Portugal
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This paper presents a distributed predictive control methodology for indoor thermal comfort that optimizes the consumption of a limited shared energy resource using an integrated demand-side management approach that involves a power price auction and an appliance loads allocation scheme. The control objective for each subsystem (house or building) aims to minimize the energy cost while maintaining the indoor temperature inside comfort limits. In a distributed coordinated multi-agent ecosystem, each house or building control agent achieves its objectives while sharing, among them, the available energy through the introduction of particular coupling constraints in their underlying optimization problem. Coordination is maintained by a daily green energy auction bring in a demand-side management approach. Also the implemented distributed MPC algorithm is described and validated with simulation studies.
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Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia Civil Especialização em Hidráulica
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Mestrado em Contabilidade e Gestão das Instituições Financeiras
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Mestrado em Contabilidade e Gestão das Instituições Financeiras
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Mestrado em Fiscalidade
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Mestrado em Fiscalidade
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Introdução – O bullying pode ser definido como atitudes agressivas, intencionais e repetidas durante um período de tempo. Diversos estudos verificaram a prevalência de bullying entre estudantes de vários países e demonstraram que este é um problema internacional e que pelo menos um em cada dez estudantes está envolvido numa situação de bullying. Objetivos – Caracterizar as situações de bullying no ambiente escolar, o papel do estudante, os sentimentos associados a essas ações e identificar as características do agressor. Métodos – A amostra foi constituída por 519 alunos matriculados em duas escolas da região sul de Portugal que preencheram um questionário anónimo sobre uma situação de bullying que vivenciaram, descrevendo o papel do aluno e o que sentiram nesta situação. Resultados – Os resultados revelaram que em 61,7% dos casos se tratou de agressão física e 29,7% de agressão verbal. Desempenharam o papel de agressores 12,7% dos alunos, 21,8% foram vítimas e 63,6% foram testemunhas desta situação. 10,6% dos alunos relataram sentir bem, 11% mostraram indiferença e 78,4% dos alunos sentiram‑se mal com a situação de bullying. Verificou‑se que, com o avanço da idade, o estudante aumentava em 1,5 vezes a probabilidade de desempenhar o papel de agressor e os rapazes apresentavam 5,2 vezes mais probabilidades de vir a ser agressor numa situação de bullying. Conclusão – O presente estudo verificou que a maioria dos alunos participou de uma situação de bullying escolar como testemunha, sendo os casos mais comuns de agressão física. A maioria dos alunos sentiu‑se mal com essa situação. Os rapazes e os alunos com mais idade tiveram mais probabilidade de vir a desempenhar o papel de agressor numa situação de bullying.
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Mestrado em Intervenção Sócio-Organizaional na Saúde - Ramo de especialização: Intervenção Comunitária
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Mestrado em Controlo e Gestão dos Negócios
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Dissertação apresentada à Escola Superior de Comunicação Social como parte dos requisitos para obtenção de grau de mestre em Gestão Estratégica das Relações Públicas.
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Cloud SLAs compensate customers with credits when average availability drops below certain levels. This is too inflexible because consumers lose non-measurable amounts of performance being only compensated later, in next charging cycles. We propose to schedule virtual machines (VMs), driven by range-based non-linear reductions of utility, different for classes of users and across different ranges of resource allocations: partial utility. This customer-defined metric, allows providers transferring resources between VMs in meaningful and economically efficient ways. We define a comprehensive cost model incorporating partial utility given by clients to a certain level of degradation, when VMs are allocated in overcommitted environments (Public, Private, Community Clouds). CloudSim was extended to support our scheduling model. Several simulation scenarios with synthetic and real workloads are presented, using datacenters with different dimensions regarding the number of servers and computational capacity. We show the partial utility-driven driven scheduling allows more VMs to be allocated. It brings benefits to providers, regarding revenue and resource utilization, allowing for more revenue per resource allocated and scaling well with the size of datacenters when comparing with an utility-oblivious redistribution of resources. Regarding clients, their workloads’ execution time is also improved, by incorporating an SLA-based redistribution of their VM’s computational power.
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Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia de Eletrónica e Telecomunicações
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Dissertação para obtenção do grau de Mestre em Engenharia Civil na Área de especialização em Hidráulica
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Risk Based Inspection (RBI) is a risk methodology used as the basis for prioritizing and managing the efforts for an inspection program allowing the allocation of resources to provide a higher level of coverage on physical assets with higher risk. The main goal of RBI is to increase equipment availability while improving or maintaining the accepted level of risk. This paper presents the concept of risk, risk analysis and RBI methodology and shows an approach to determine the optimal inspection frequency for physical assets based on the potential risk and mainly on the quantification of the probability of failure. It makes use of some assumptions in a structured decision making process. The proposed methodology allows an optimization of inspection intervals deciding when the first inspection must be performed as well as the subsequent intervals of inspection. A demonstrative example is also presented to illustrate the application of the proposed methodology.
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This paper proposes an implementation, based on a multi-agent system, of a management system for automated negotiation of electricity allocation for charging electric vehicles (EVs) and simulates its performance. The widespread existence of charging infrastructures capable of autonomous operation is recognised as a major driver towards the mass adoption of EVs by mobility consumers. Eventually, conflicting requirements from both power grid and EV owners require automated middleman aggregator agents to intermediate all operations, for example, bidding and negotiation, between these parts. Multi-agent systems are designed to provide distributed, modular, coordinated and collaborative management systems; therefore, they seem suitable to address the management of such complex charging infrastructures. Our solution consists in the implementation of virtual agents to be integrated into the management software of a charging infrastructure. We start by modelling the multi-agent architecture using a federated, hierarchical layers setup and as well as the agents' behaviours and interactions. Each of these layers comprises several components, for example, data bases, decision-making and auction mechanisms. The implementation of multi-agent platform and auctions rules, and of models for battery dynamics, is also addressed. Four scenarios were predefined to assess the management system performance under real usage conditions, considering different types of profiles for EVs owners', different infrastructure configurations and usage and different loads on the utility grid (where real data from the concession holder of the Portuguese electricity transmission grid is used). Simulations carried with the four scenarios validate the performance of the modelled system while complying with all the requirements. Although all of these have been performed for one charging station alone, a multi-agent design may in the future be used for the higher level problem of distributing energy among charging stations. Copyright (c) 2014 John Wiley & Sons, Ltd.