As operações militares e os media : O Teatro de Operações do Afeganistão

O presente Trabalho de Investigação Aplicada, intitulado de “As Operações Militares e os Media – O Teatro de Operações do Afeganistão”, tem como objetivo geral identificar e descrever as implicações relacionadas com a presença dos jornalistas portugueses no Teatro de Operações do Afeganistão na perspetiva dos militares de infantaria portugueses e dos próprios jornalistas. Fruto de compromissos de Estado ao nível internacional, o Exército Português tem empenhado forças militares no cumprimento de missões em vários Teatros de Operações. Para que os cidadãos e cidadãs tomem conhecimento da missão das Forças Armadas em Portugal e no mundo, os media assumem um papel crucial. É através das instâncias mediáticas que a população adquire noções sobre o trabalho que as suas Forças Armadas desenvolvem nos diversos pontos do globo. Neste sentido, é importante saber como se processa a interação entre militares e jornalistas num Teatro de Operações, sendo esta a problemática em que assenta a presente investigação. A metodologia implementada adotou uma perspetiva descritiva, procedendo-se a um estudo de caso, focado na participação portuguesa no Afeganistão entre 2002 e 2014, com o intuito de analisar a interação que resultou entre os militares e os jornalistas, com particular ênfase para as implicações. No que tange aos métodos e técnicas de recolha de dados, utilizámos a análise documental e consultámos fontes documentais para sustentar e enriquecer a investigação. As entrevistas constituem porém a técnica de recolha de informação fundamental, sendo a partir da sua análise que se discutirão as hipóteses levantadas. Visto que se pretendeu abranger a perspetiva de militares e de jornalistas realizaram-se entrevistas a quatro militares que foram comandantes de forças militares no Afeganistão e a cinco jornalistas que estiveram presentes nesse cenário de guerra durante o período em análise.Os resultados apurados permitem verificar que a incorporação de jornalistas no seio das forças militares e o consequente acompanhamento das operações, resultou na adaptação e aplicação de algumas medidas, algo fundamentável pela presença de elementos que não pertenciam à força e que não eram militares. Conclui-se que a interação entre os militares e os jornalistas no Afeganistão resultou em implicações para ambos. Nomeadamente na segurança, como foi o caso do fornecimento de equipamento de proteção aos jornalistas quando estes não dispunham, a segurança física que os militares garantiram aos jornalistas e a explicação das operações por parte dos militares (briefings). Relativamente ao acesso à informação por parte dos jornalistas, existiu um acordo verbal atinente às condições de acesso e divulgação da informação e existiram também restrições em matérias de importância militar e de natureza sensível, as quais mereceram consenso entre os entrevistados. Na componente logística, existiram implicações como foram o caso da alimentação, o alojamento, os equipamentos de proteção fornecidos e os cuidados médicos prestados aos jornalistas, contudo foi algo que não comprometeu o cumprimento das diversas missões e tarefas militares. Nos aspetos relacionais, assinalaram-se casos pontuais de alguma tensão, justificada pelos próprios como resultantes das circunstâncias e da especificidade das missões e objetivos de uns e outros. Porém, é de realçar que a convivência de jornalistas e militares no TO é reveladora de respeito e compreensão pelo trabalho mútuo. Deste modo, pode-se concluir que no plano relacional as implicações da presença de jornalistas contribuem para uma maior conhecimento e sensibilização a respeito do trabalho e das condicionantes a que estão sujeitos militares e jornalistas.

Entre o mar e estrela, um lugar para se bem viver : a problemática da expansão urbana da Cidade de Baía Formosa/RN

The urban expansion problem of Baía Formosa, a southern edge city of de Rio Grande do Norte eastern coast, which has been presented in other coast Brazilian towns, specially on those with tourist activities increase. Therefore, this situation brings huge concerns to their inhabitants, to their technical /scientific community and to the governments, because of the conflicts of interest and of the growth of urban problems that this has been created. At Baía Formosa, the situation is aggravated because the city is confined, once around it, there are large private proprieties, environmental preservation area and the sea, at the eastern edge. The objectives of this study are the analyses of this city expansion process in order to obtain adequate alternatives and defining methodology to apply in other urban nucleus that are subjected to similar situations. Of course, presents social relations, environmental conditions and promoting local population insertion should be considered in order that enjoin this process and contributing to a better social balance. This case study has used bibliography research, field data, maps and soil occupation recorders and photographs of the area, besides the primary data gathering by surveys carried out with many social actors. The present analysis shows that the urban expansion observed today is featured by a recent unsustainable model, which attacks the environment and brings either farm conflicts. On the other hand, the ecological tourism can represent an alternative in order to achieve an adequate expansion form, without forgetting the several structural parameters necessary to support the sustainable activities

Aider sans nuire: intervention de groupe destinée aux proches de victimes d'actes criminels

Rapport de stage présenté en vue de l’obtention du grade Maître ès sciences (M.Sc.) en criminologie option stage en intervention clinique.

Aider sans nuire: intervention de groupe destinée aux proches de victimes d'actes criminels

Rapport de stage présenté en vue de l’obtention du grade Maître ès sciences (M.Sc.) en criminologie option stage en intervention clinique.

Using multivariate sequential patterns to improve survival prediction in intensive care burn unit

Resuscitation and stabilization are key issues in Intensive Care Burn Units and early survival predictions help to decide the best clinical action during these phases. Current survival scores of burns focus on clinical variables such as age or the body surface area. However, the evolution of other parameters (e.g. diuresis or fluid balance) during the first days is also valuable knowledge. In this work we suggest a methodology and we propose a Temporal Data Mining algorithm to estimate the survival condition from the patient’s evolution. Experiments conducted on 480 patients show the improvement of survival prediction.

Energy-efficient virtual machine placement in data centers by genetic algorithm

Server consolidation using virtualization technology has become an important technology to improve the energy efficiency of data centers. Virtual machine placement is the key in the server consolidation. In the past few years, many approaches to the virtual machine placement have been proposed. However, existing virtual machine placement approaches to the virtual machine placement problem consider the energy consumption by physical machines in a data center only, but do not consider the energy consumption in communication network in the data center. However, the energy consumption in the communication network in a data center is not trivial, and therefore should be considered in the virtual machine placement in order to make the data center more energy-efficient. In this paper, we propose a genetic algorithm for a new virtual machine placement problem that considers the energy consumption in both the servers and the communication network in the data center. Experimental results show that the genetic algorithm performs well when tackling test problems of different kinds, and scales up well when the problem size increases.

An innovative information gathering and data analysis platform for railway level crossing safety data

This paper describes an innovative platform that facilitates the collection of objective safety data around occurrences at railway level crossings using data sources including forward-facing video, telemetry from trains and geo-referenced asset and survey data. This platform is being developed with support by the Australian rail industry and the Cooperative Research Centre for Rail Innovation. The paper provides a description of the underlying accident causation model, the development methodology and refinement process as well as a description of the data collection platform. The paper concludes with a brief discussion of benefits this project is expected to provide the Australian rail industry.

A hybrid genetic algorithm for the energy-efficient virtual machine placement problem in data centers

Server consolidation using virtualization technology has become an important technology to improve the energy efficiency of data centers. Virtual machine placement is the key in the server consolidation technology. In the past few years, many approaches to the virtual machine placement have been proposed. However, existing virtual machine placement approaches consider the energy consumption by physical machines only, but do not consider the energy consumption in communication network, in a data center. However, the energy consumption in the communication network in a data center is not trivial, and therefore should be considered in the virtual machine placement. In our preliminary research, we have proposed a genetic algorithm for a new virtual machine placement problem that considers the energy consumption in both physical machines and the communication network in a data center. Aiming at improving the performance and efficiency of the genetic algorithm, this paper presents a hybrid genetic algorithm for the energy-efficient virtual machine placement problem. Experimental results show that the hybrid genetic algorithm significantly outperforms the original genetic algorithm, and that the hybrid genetic algorithm is scalable.

Hunting and gathering : new imperatives in mapping and collecting student learning data to assure quality outcomes

Assurance of learning (AOL) is a quality enhancement and quality assurance process used in higher education. It involves a process of determining programme learning outcomes and standards, and systematically gathering evidence to measure students' performance on these. The systematic assessment of whole-of-programme outcomes provides a basis for curriculum development and management, continuous improvement, and accreditation. To better understand how AOL processes operate, a national study of university practices across one discipline area, business and management, was undertaken. To solicit data on AOL practice, interviews were undertaken with a sample of business school representatives (n = 25). Two key processes emerged: (1) mapping of graduate attributes and (2) collection of assurance data. External drivers such as professional accreditation and government legislation were the primary reasons for undertaking AOL outcomes but intrinsic motivators in relation to continuous improvement were also evident. The facilitation of academic commitment was achieved through an embedded approach to AOL by the majority of universities in the study. A sustainable and inclusive process of AOL was seen to support wider stakeholder engagement in the development of higher education learning outcomes.

A random key genetic algorithm for live migration of multiple virtual machines in data centers

Live migration of multiple Virtual Machines (VMs) has become an integral management activity in data centers for power saving, load balancing and system maintenance. While state-of-the-art live migration techniques focus on the improvement of migration performance of an independent single VM, only a little has been investigated to the case of live migration of multiple interacting VMs. Live migration is mostly influenced by the network bandwidth and arbitrarily migrating a VM which has data inter-dependencies with other VMs may increase the bandwidth consumption and adversely affect the performances of subsequent migrations. In this paper, we propose a Random Key Genetic Algorithm (RKGA) that efficiently schedules the migration of a given set of VMs accounting both inter-VM dependency and data center communication network. The experimental results show that the RKGA can schedule the migration of multiple VMs with significantly shorter total migration time and total downtime compared to a heuristic algorithm.

A modified Density-Based Scanning Algorithm with Noise for spatial travel pattern analysis from Smart Card AFC data

Smart Card Automated Fare Collection (AFC) data has been extensively exploited to understand passenger behavior, passenger segment, trip purpose and improve transit planning through spatial travel pattern analysis. The literature has been evolving from simple to more sophisticated methods such as from aggregated to individual travel pattern analysis, and from stop-to-stop to flexible stop aggregation. However, the issue of high computing complexity has limited these methods in practical applications. This paper proposes a new algorithm named Weighted Stop Density Based Scanning Algorithm with Noise (WS-DBSCAN) based on the classical Density Based Scanning Algorithm with Noise (DBSCAN) algorithm to detect and update the daily changes in travel pattern. WS-DBSCAN converts the classical quadratic computation complexity DBSCAN to a problem of sub-quadratic complexity. The numerical experiment using the real AFC data in South East Queensland, Australia shows that the algorithm costs only 0.45% in computation time compared to the classical DBSCAN, but provides the same clustering results.

Using genetic algorithm in profile-based assignment of applications to virtual machines for greener data centers

The increase in data center dependent services has made energy optimization of data centers one of the most exigent challenges in today's Information Age. The necessity of green and energy-efficient measures is very high for reducing carbon footprint and exorbitant energy costs. However, inefficient application management of data centers results in high energy consumption and low resource utilization efficiency. Unfortunately, in most cases, deploying an energy-efficient application management solution inevitably degrades the resource utilization efficiency of the data centers. To address this problem, a Penalty-based Genetic Algorithm (GA) is presented in this paper to solve a defined profile-based application assignment problem whilst maintaining a trade-off between the power consumption performance and resource utilization performance. Case studies show that the penalty-based GA is highly scalable and provides 16% to 32% better solutions than a greedy algorithm.

A penalty-based genetic algorithm for the migration cost-aware virtual machine placement problem in cloud data centers

In the past few years, the virtual machine (VM) placement problem has been studied intensively and many algorithms for the VM placement problem have been proposed. However, those proposed VM placement algorithms have not been widely used in today's cloud data centers as they do not consider the migration cost from current VM placement to the new optimal VM placement. As a result, the gain from optimizing VM placement may be less than the loss of the migration cost from current VM placement to the new VM placement. To address this issue, this paper presents a penalty-based genetic algorithm (GA) for the VM placement problem that considers the migration cost in addition to the energy-consumption of the new VM placement and the total inter-VM traffic flow in the new VM placement. The GA has been implemented and evaluated by experiments, and the experimental results show that the GA outperforms two well known algorithms for the VM placement problem.