A 12*(1+|R|/(4m))-speed algorithm for scheduling constrained-deadline sporadic real-time tasks on a multiprocessor comprising m processors where a task may request one of |R| sequentially-reusable shared resources

We present a 12*(1+|R|/(4m))-speed algorithm for scheduling constrained-deadline sporadic real-time tasks on a multiprocessor comprising m processors where a task may request one of |R| sequentially-reusable shared resources.

Handling shared resources and precedence constraints in open systems

There is an increasing demand for highly dynamic realtime systems where several independently developed applications with different timing requirements can coexist. This paper proposes a protocol to integrate shared resources and precedence constraints among tasks in such systems assuming no precise information on critical sections and computation times is available. The concept of bandwidth inheritance is combined with a capacity sharing and stealing mechanism to efficiently exchange bandwidth among needed tasks, minimising the cost of blocking.

Shared resources and precedence constraints with capacity sharing and stealing

This paper proposes a new strategy to integrate shared resources and precedence constraints among real-time tasks, assuming no precise information on critical sections and computation times is available. The concept of bandwidth inheritance is combined with a greedy capacity sharing and stealing policy to efficiently exchange bandwidth among tasks, minimising the degree of deviation from the ideal system's behaviour caused by inter-application blocking. The proposed capacity exchange protocol (CXP) focus on exchanging extra capacities as early, and not necessarily as fairly, as possible. This loss of optimality is worth the reduced complexity as the protocol's behaviour nevertheless tends to be fair in the long run and outperforms other solutions in highly dynamic scenarios, as demonstrated by extensive simulations.

Task-based occupational exposure assessment and particle number concentration: two important data resources to perform risk assessment for occupational exposure to particles

Environment monitoring has an important role in occupational exposure assessment. However, due to several factors is done with insufficient frequency and normally don´t give the necessary information to choose the most adequate safety measures to avoid or control exposure. Identifying all the tasks developed in each workplace and conducting a task-based exposure assessment help to refine the exposure characterization and reduce assessment errors. A task-based assessment can provide also a better evaluation of exposure variability, instead of assessing personal exposures using continuous 8-hour time weighted average measurements. Health effects related with exposure to particles have mainly been investigated with mass-measuring instruments or gravimetric analysis. However, more recently, there are some studies that support that size distribution and particle number concentration may have advantages over particle mass concentration for assessing the health effects of airborne particles. Several exposure assessments were performed in different occupational settings (bakery, grill house, cork industry and horse stable) and were applied these two resources: task-based exposure assessment and particle number concentration by size. The results showed interesting results: task-based approach applied permitted to identify the tasks with higher exposure to the smaller particles (0.3 μm) in the different occupational settings. The data obtained allow more concrete and effective risk assessment and the identification of priorities for safety investments.

Occupational stress and coping resources in physiotherapists: a survey of physiotherapists in three general hospitals

Objectives - To identify occupational stressors and coping resources in a group of physiotherapists, and to analyse interactions between subjective levels of stress, efficacy in stress resolution and coping resources used by these professionals. Design - A sample of 55 physiotherapists working in three general hospitals in Portugal completed the Coping Resources Inventory for Stress, the Occupational Stressors Inventory and two subjective scales for stress and stress resolution. Main results - Most physiotherapists perceived that they were moderately stressed (19/55, 35%) or stressed (20/55, 36%) due to work, and reported that their efficacy in stress resolution was moderate (25/54, 46%) or efficient (23/54, 42%). Issues related to lack of professional autonomy, lack of organisation in the hierarchical command chain, lack of professional and social recognition, disorganisation in task distribution and interpersonal conflicts with superiors were identified as the main sources of stress. The most frequently used coping resources were social support, stress monitoring, physical health and structuring. Perceived efficacy in stress resolution was inversely related to perceived level of occupational stress (r = −0.61, P < 0.01). Significant correlations were found between several coping resources and the perceived level of stress and efficacy in stress resolution. Associations between problem solving, cognitive restructuring and stress monitoring and both low levels of perceived stress and high levels of perceived efficacy were particularly strong. Implications for practice - The importance of identifying stressors and coping resources related to physiotherapists’ occupational stress, and the need for the development of specific training programmes to cope with stress are supported.

Analysis of the domain of applicability of an algorithm for a resources system selection problem for Distributed/Agile/Virtual Enterprises integration

The process of resources systems selection takes an important part in Distributed/Agile/Virtual Enterprises (D/A/V Es) integration. However, the resources systems selection is still a difficult matter to solve in a D/A/VE, as it is pointed out in this paper. Globally, we can say that the selection problem has been equated from different aspects, originating different kinds of models/algorithms to solve it. In order to assist the development of a web prototype tool (broker tool), intelligent and flexible, that integrates all the selection model activities and tools, and with the capacity to adequate to each D/A/V E project or instance (this is the major goal of our final project), we intend in this paper to show: a formulation of a kind of resources selection problem and the limitations of the algorithms proposed to solve it. We formulate a particular case of the problem as an integer programming, which is solved using simplex and branch and bound algorithms, and identify their performance limitations (in terms of processing time) based on simulation results. These limitations depend on the number of processing tasks and on the number of pre-selected resources per processing tasks, defining the domain of applicability of the algorithms for the problem studied. The limitations detected open the necessity of the application of other kind of algorithms (approximate solution algorithms) outside the domain of applicability founded for the algorithms simulated. However, for a broker tool it is very important the knowledge of algorithms limitations, in order to, based on problem features, develop and select the most suitable algorithm that guarantees a good performance.

A genetic algorithm for project scheduling with multi-modes and renewable resources

This paper presents a genetic algorithm-based approach for project scheduling with multi-modes and renewable resources. In this problem activities of the project may be executed in more than one operating mode and renewable resource constraints are imposed. The objective function is the minimization of the project completion time. The idea of this approach is integrating a genetic algorithm with a schedule generation scheme. This study also proposes applying a local search procedure trying to yield a better solution when the genetic algorithm and the schedule generation scheme obtain a solution. The experimental results show that this algorithm is an effective method for solving this problem.

Project scheduling under multiple resources constraints using a genetic algorithm

The resource constrained project scheduling problem (RCPSP) is a difficult problem in combinatorial optimization for which extensive investigation has been devoted to the development of efficient algorithms. During the last couple of years many heuristic procedures have been developed for this problem, but still these procedures often fail in finding near-optimal solutions. This paper proposes a genetic algorithm for the resource constrained project scheduling problem. The chromosome representation of the problem is based on random keys. The schedule is constructed using a heuristic priority rule in which the priorities and delay times of the activities are defined by the genetic algorithm. The approach was tested on a set of standard problems taken from the literature and compared with other approaches. The computational results validate the effectiveness of the proposed algorithm.

Market of resources for virtual enterprise integration

Most definitions of virtual enterprise (VE) incorporate the idea of extended and collaborative outsourcing to suppliers and subcontractors in order to achieve a competitive response to market demands (Webster, Sugden, & Tayles, 2004). As suggested by several authors (Browne & Zhang, 1999; Byrne, 1993; Camarinha-Matos & Afsarmanesh, 1999; Cunha, Putnik, & Ávila, 2000; Davidow & Malone, 1992; Preiss, Goldman, & Nagel, 1996), a VE consists of a network of independent enterprises (resources providers) with reconfiguration capability in useful time, permanently aligned with the market requirements, created to take profit from a specific market opportunity, and where each participant contributes with its best practices and core competencies to the success and competitiveness of the structure as a whole. Even during the operation phase of the VE, the configuration can change, to assure business alignment with the market demands, traduced by the identification of reconfiguration opportunities and continuous readjustment or reconfiguration of the VE network, to meet unexpected situations or to keep permanent competitiveness and maximum performance (Cunha & Putnik, 2002, 2005a, 2005b).

Implementation contexts of a Tuberculosis Control Program in Brazilian prisons

OBJECTIVE To analyze the influence from context characteristics in the control of tuberculosis in prisons, and the influence from the program implementation degrees in observed effects.METHODS A multiple case study, with a qualitative approach, conducted in the prison systems of two Brazilian states in 2011 and 2012. Two prisons were analyzed in each state, and a prison hospital was analyzed in one of them. The data were submitted to a content analysis, which was based on external, political-organizational, implementation, and effect dimensions. Contextual factors and the ones in the program organization were correlated. The independent variable was the program implementation degree and the dependent one, the effects from the Tuberculosis Control Program in prisons.RESULTS The context with the highest sociodemographic vulnerability, the highest incidence rate of tuberculosis, and the smallest amount of available resources were associated with the low implementation degree of the program. The results from tuberculosis treatment in the prison system were better where the program had already been partially implemented than in the case with low implementation degree in both cases.CONCLUSIONS The implementation degree and its contexts – external and political-organizational dimensions – simultaneously contribute to the effects that are observed in the control of tuberculosis in analyzed prisons.

Enhancing the selection of a model-based clustering with external categorical variables

In cluster analysis, it can be useful to interpret the partition built from the data in the light of external categorical variables which are not directly involved to cluster the data. An approach is proposed in the model-based clustering context to select a number of clusters which both fits the data well and takes advantage of the potential illustrative ability of the external variables. This approach makes use of the integrated joint likelihood of the data and the partitions at hand, namely the model-based partition and the partitions associated to the external variables. It is noteworthy that each mixture model is fitted by the maximum likelihood methodology to the data, excluding the external variables which are used to select a relevant mixture model only. Numerical experiments illustrate the promising behaviour of the derived criterion. © 2014 Springer-Verlag Berlin Heidelberg.

Modified particle swarm optimization for day-ahead distributed energy resources scheduling including vehicle-to-grid

Mestrado em Engenharia Electrotécnica – Sistemas Eléctricos de Energia

Sistema de Torre de Refrigeração

Mestrado em Engenharia Química - Ramo Optimização Energética na Indústria Química

Análise do efeito de implementação de armazenamento térmico em banco de gelo e armazenamento elétrico em baterias Sódio-Enxofre (NaS) sobre o custo de exploração de edifícios de serviços

Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia Mecânica

Estratégia de internacionalização da Grande Porto: seleção, modos de entrada e marketing-mix na abordagem dos mercados internacionais

Dissertação apresentada ao Instituto Politécnico do Porto para obtenção do Grau de Mestre em Gestão das Organizações, Ramo de Gestão de Empresas Orientada pelo Professor Doutor José Freitas Santos