Personalized sightseeing tours support using mobile devices

In this paper, we present PSiS (Personalized Sightseeing Tours Recommendation System) Mobile. PSiS Mobile is our proposal to a mobile recommendation and planning support system, which is designed to provide effective support during the tourist visit with context-aware information and recommendations about places of interest (POI), exploiting tourist preferences and context.

MASDSheGATS – Scheduling System for Dynamic Manufacturing Environments

This chapter addresses the resolution of scheduling in manufacturing systems subject to perturbations. The planning of Manufacturing Systems involves frequently the resolution of a huge amount and variety of combinatorial optimisation problems with an important impact on the performance of manufacturing organisations. Examples of those problems are the sequencing and scheduling problems in manufacturing management, routing and transportation, layout design and timetabling problems.

Electricity Markets Simulation: MASCEM Contributions to the Challenging Reality

Electricity Markets are not only a new reality but an evolving one as the involved players and rules change at a relatively high rate. Multi-agent simulation combined with Artificial Intelligence techniques may result in sophisticated tools very helpful under this context. Some simulation tools have already been developed, some of them very interesting. However, at the present state it is important to go a step forward in Electricity Markets simulators as this is crucial for facing changes in Power Systems. This paper explains the context and needs of electricity market simulation, describing the most important characteristics of available simulators. We present our work concerning MASCEM simulator, presenting its features as well as the improvements being made to accomplish the change and challenging reality of Electricity Markets.

Metalearning in ALBidS: A Strategic Bidding System for electricity markets

Metalearning is a subfield of machine learning with special pro-pensity for dynamic and complex environments, from which it is difficult to extract predictable knowledge. The field of study of this work is the electricity market, which due to the restructuring that recently took place, became an especially complex and unpredictable environment, involving a large number of different entities, playing in a dynamic scene to obtain the best advantages and profits. This paper presents the development of a metalearner, applied to the decision support of electricity markets’ negotia-tion entities. The proposed metalearner takes advantage on several learning algorithms implemented in ALBidS, an adaptive learning system that pro-vides decision support to electricity markets’ participating players. Using the outputs of each different strategy as inputs, the metalearner creates its own output, considering each strategy with a different weight, depending on its individual quality of performance. The results of the proposed meth-od are studied and analyzed using MASCEM - a multi-agent electricity market simulator that models market players and simulates their operation in the market. This simulator provides the chance to test the metalearner in scenarios based on real electricity market´s data.

Adaptive learning in multiagent systems: a forecasting methodology based on error analysis

Electricity markets are complex environments, involving a large number of different entities, playing in a dynamic scene to obtain the best advantages and profits. MASCEM is a multi-agent electricity market simu-lator to model market players and simulate their operation in the market. Market players are entities with specific characteristics and objectives, making their decisions and interacting with other players. MASCEM pro-vides several dynamic strategies for agents’ behaviour. This paper presents a method that aims to provide market players strategic bidding capabilities, allowing them to obtain the higher possible gains out of the market. This method uses an auxiliary forecasting tool, e.g. an Artificial Neural Net-work, to predict the electricity market prices, and analyses its forecasting error patterns. Through the recognition of such patterns occurrence, the method predicts the expected error for the next forecast, and uses it to adapt the actual forecast. The goal is to approximate the forecast to the real value, reducing the forecasting error.

Adaptation model for PCMAT – Mathematics collaborative learning platform

The aim of this paper is to present an adaptation model for an Adaptive Educational Hypermedia System, PCMAT. The adaptation of the application is based on progressive self-assessment (exercises, tasks, and so on) and applies the constructivist learning theory and the learning styles theory. Our objective is the creation of a better, more adequate adaptation model that takes into account the complexities of different users.

An architecture for ambient intelligent environments

This paper presents the proposal of an architecture for developing systems that interact with Ambient Intelligence (AmI) environments. This architecture has been proposed as a consequence of a methodology for the inclusion of Artificial Intelligence in AmI environments (ISyRAmI - Intelligent Systems Research for Ambient Intelligence). The ISyRAmI architecture considers several modules. The first is related with the acquisition of data, information and even knowledge. This data/information knowledge deals with our AmI environment and can be acquired in different ways (from raw sensors, from the web, from experts). The second module is related with the storage, conversion, and handling of the data/information knowledge. It is understood that incorrectness, incompleteness, and uncertainty are present in the data/information/knowledge. The third module is related with the intelligent operation on the data/information/knowledge of our AmI environment. Here we include knowledge discovery systems, expert systems, planning, multi-agent systems, simulation, optimization, etc. The last module is related with the actuation in the AmI environment, by means of automation, robots, intelligent agents and users.

A perfusão isolada dos membros no melanoma maligno (a experiência do IPO-Porto)

Parte I - O contexto Neste capítulo faz-se a contextualização essencial do tema, dividindo-a em duas secções. A primeira secção apresenta conceitos relativos à patologia principal, o melanoma, apesar desta técnica não se aplicar só em doentes com esta patologia, mas considerando o peso da mesma na casuística da instituição, idêntico ao de outras instituições internacionais. A segunda secção apresenta o enquadramento da técnica e da terapêutica da Perfusão Isolada dos Membros, destacando as principais alterações ocorridas nos protocolos dos centros que a praticam, ao longo das últimas décadas. Parte II - A técnica e a terapêutica no IPOFG-Porto Neste capítulo é explicado passo a passo o procedimento da Perfusão Isolada dos Membros, segundo o protocolo do IPOFG-Porto, ilustrando cada passo com imagens de um caso real. Este procedimento apoia-se na técnica da circulação extracorporal, para aplicar uma terapêutica, a perfusão em dose elevada de uma dose pré-determinada de um ou mais citostáticos. São depois enumeradas as características essenciais de cada um dos citostáticos que foram e são usados na PIM ou associados a ela, terminando com a exposição da casuística da instituição, trabalhada apenas em contexto descritivo. Parte III - O seguimento dos doentes Neste capítulo elencam-se e explicam-se as variáveis em estudo no follow-up destes doentes, quer no pós-operatório imediato, quer no seguimento em ambulatório. O follow-up destes doentes pode ser muito longo, quase sempre dependendo do estadiamento prévio da doença antes da realização da PIM. O tipo de resposta clínica deve obter-se entre os 3 e os 6 meses pós PIM, mas pode obter-se antes ou depois. Todas as variáveis estão perfeitamente definidas internacionalmente e dão um contributo específico para o conhecimento da história natural da doença, mas para os doentes a que assume maior impacto é a necessidade, ou o evitar, da amputação do membro. São apresentados os dados destas variáveis relativos ao IPOFG-Porto. Parte IV - As reflexões Neste capítulo são feitas algumas reflexões sobre o custo, a sobrevivência e a qualidade de vida, e as perspetivas futuras da Perfusão Isolada dos Membros. Apesar da sua inegável eficácia terapêutica, a PIM é um procedimento de custo elevado e restrita a centros especializados, o que provoca assimetrias significativas. Os dados internacionais são claros, até agora não parece ter contribuído para um aumento da esperança média de vida destes doentes, mas o seu contributo para a qualidade de vida e manutenção da funcionalidade dos doentes é enorme. A Infusão Isolada dos Membros aparece como uma técnica standard promissora na quimioterapia regional.

Modelação do transporte e dispersão atmosférica de poluentes produzidos por uma refinaria: estudo de caso

Mestrado em Engenharia Química.Ramo Tecnologias de Protecção Ambiental

Smart-HOP: a reliable handoff mechanism for mobile wireless sensor networks

Handoff processes, the events where mobile nodes select the best access point available to transfer data, have been well studied in cellular and WiFi networks. However, wireless sensor networks (WSN) pose a new set of challenges due to their simple low-power radio transceivers and constrained resources. This paper proposes smart-HOP, a handoff mechanism tailored for mobile WSN applications. This work provides two important contributions. First, it demonstrates the intrinsic relationship between handoffs and the transitional region. The evaluation shows that handoffs perform the best when operating in the transitional region, as opposed to operating in the more reliable connected region. Second, the results reveal that a proper fine tuning of the parameters, in the transitional region, can reduce handoff delays by two orders of magnitude, from seconds to tens of milliseconds.

Building a microscope for the data center

Managing the physical and compute infrastructure of a large data center is an embodiment of a Cyber-Physical System (CPS). The physical parameters of the data center (such as power, temperature, pressure, humidity) are tightly coupled with computations, even more so in upcoming data centers, where the location of workloads can vary substantially due, for example, to workloads being moved in a cloud infrastructure hosted in the data center. In this paper, we describe a data collection and distribution architecture that enables gathering physical parameters of a large data center at a very high temporal and spatial resolutionof the sensor measurements. We think this is an important characteristic to enable more accurate heat-flow models of the data center andwith them, _and opportunities to optimize energy consumption. Havinga high resolution picture of the data center conditions, also enables minimizing local hotspots, perform more accurate predictive maintenance (pending failures in cooling and other infrastructure equipment can be more promptly detected) and more accurate billing. We detail this architecture and define the structure of the underlying messaging system that is used to collect and distribute the data. Finally, we show the results of a preliminary study of a typical data center radio environment.

Relatório de estágio em Educação Pré-Escolar

Mestrado em Educação Pré-Escolar

Uniprocessor EDF scheduling with mode change

Consider the problem of scheduling sporadically-arriving tasks with implicit deadlines using Earliest-Deadline-First (EDF) on a single processor. The system may undergo changes in its operational modes and therefore the characteristics of the task set may change at run-time. We consider a well-established previously published mode-change protocol and we show that if every mode utilizes at most 50% of the processing capacity then all deadlines are met. We also show that there exists a task set that misses a deadline although the utilization exceeds 50% by just an arbitrarily small amount. Finally, we present, for a relevant special case, an exact schedulability test for EDF with mode change.

Global static-priority preemptive multiprocessor scheduling with utilization bound 38%

Consider the problem of scheduling real-time tasks on a multiprocessor with the goal of meeting deadlines. Tasks arrive sporadically and have implicit deadlines, that is, the deadline of a task is equal to its minimum inter-arrival time. Consider this problem to be solved with global static-priority scheduling. We present a priority-assignment scheme with the property that if at most 38% of the processing capacity is requested then all deadlines are met.

Fractional control of legged robots

Fractional calculus (FC) is being used in several distinct areas of science and engineering, being recognized its ability to yield a superior modelling and control in many dynamical systems. This article illustrates the application of FC in the area of robot control. A Fractional Order PDμ controller is proposed for the control of an hexapod robot with 3 dof legs. It is demonstrated the superior performance of the system by using the FC concepts.