Security issues during Lula's administration: from the reactive to the assertive approach

Brazil's security agenda during Lula's administration was not homogeneous through the two mandates: the first tenure (2002-2006) revealed a reactive approach towards security topics, while the second one (2006-2010) was more assertive. More specifically, the shift occurred in terms of both its geographical scope - once it incorporated global issues in a more systematic way -, and instruments through which the security agenda was exercised, given the multilateral initiative of Unasur's CDS

Information technology service management: an experimental approach towards IT service prediction

Dissertation presented to obtain a Masters degree in Computer Science

Reactive and proactive approaches for introspective CBR

This work investigates applying introspective reasoning to improve the performance of Case-Based Reasoning (CBR) systems, in both reactive and proactive fashion, by guiding learning to improve how a CBR system applies its cases and by identifying possible future system deficiencies. First we present our reactive approach, a new introspective reasoning model which enables CBR systems to autonomously learn to improve multiple facets of their reasoning processes in response to poor quality solutions. We illustrate our model’s benefits with experimental results from tests in an industrial design application. Then as for our proactive approach, we introduce a novel method for identifying regions in a case-base where the system gives low confidence solutions to possible future problems. Experimentation is provided for Zoology and Robo-Soccer domains and we argue how encountered regions of dubiosity help us to analyze the case-bases of a given CBR system.

A Transportation Safety Planning Tool for the City of Ames, August 2011

The historically-reactive approach to identifying safety problems and mitigating them involves selecting black spots or hot spots by ranking locations based on crash frequency and severity. The approach focuses mainly on the corridor level without taking the exposure rate (vehicle miles traveled) and socio-demographics information of the study area, which are very important in the transportation planning process, into consideration. A larger study analysis unit at the Transportation Analysis Zone (TAZ) level or the network planning level should be used to address the needs of development of the community in the future and incorporate safety into the long-range transportation planning process. In this study, existing planning tools (such as the PLANSAFE models presented in NCHRP Report 546) were evaluated for forecasting safety in small and medium-sized communities, particularly as related to changes in socio-demographics characteristics, traffic demand, road network, and countermeasures. The research also evaluated the applicability of the Empirical Bayes (EB) method to network-level analysis. In addition, application of the United States Road Assessment Program (usRAP) protocols at the local urban road network level was investigated. This research evaluated the applicability of these three methods for the City of Ames, Iowa. The outcome of this research is a systematic process and framework for considering road safety issues explicitly in the small and medium-sized community transportation planning process and for quantifying the safety impacts of new developments and policy programs. More specifically, quantitative safety may be incorporated into the planning process, through effective visualization and increased awareness of safety issues (usRAP), the identification of high-risk locations with potential for improvement, (usRAP maps and EB), countermeasures for high-risk locations (EB before and after study and PLANSAFE), and socio-economic and demographic induced changes at the planning-level (PLANSAFE).

Analyse par spectrométrie de masse d’hormones stéroïdiennes dans les eaux usées et abattement par oxydation chimique

Thèse réalisée en cotutelle avec Michèle Prévost (Ph.D), Professeure titulaire au département des génies civil, géologique et des mines de l'École Polytechnique de Montréal.

Robust Hybrid Mechanisms for Scheduling of Grid Tasks

This paper proposes three new hybrid mechanisms for the scheduling of grid tasks, which integrate reactive and proactive approaches. They differ by the scheduler used to define the initial schedule of an application and by the scheduler used to reschedule the application. The mechanisms are compared to reactive and proactive mechanisms. Results show that hybrid approach produces performance close to that of the reactive mechanisms, but demanding less migrations.

Volunteering in sport clubs

Volunteers are the most important resource for non-profit sport clubs seeking to bolster their viability (e.g. sporting programs). Although many people do voluntary work in sport clubs, stable voluntary engagement can no longer be granted. This difficulty is confirmed by existing research across various European countries. From a club management point of view, a detailed understanding of how to attract volunteers and retain them in the long term is becoming a high priority. The purpose of this study is (1) to analyse the influence of individual characteristics and corresponding organisational conditions on volunteering in sports clubs as well as (2) to examine the decision-making processes in relation to implement effective strategies for recruiting volunteers. For the first perspective a multi-level framework for the investigation of the factors of voluntary engagement in sports clubs is developed. The individual and context factors are estimated in different multi-level models based on a sample of n = 1,434 sport club members from 36 sport clubs in Switzerland. Results indicate that volunteering is not just an outcome of individual characteristics such as lower workloads, higher income, children belonging to the sport club, longer club memberships, or a strong commitment to the club. It is also influenced by club-specific structural conditions; volunteering is more probable in rural sports clubs whereas growth-oriented goals in clubs have a destabilising effect. Concerning decision-making processes an in-depth analysis of recruitment practices for volunteers was conducted in nine selected sport clubs (case study design) based on the garbage can model. Results show that the decision-making processes are generally characterised by a reactive approach in which dominant actors try to handle personnel problems of recruitment in the administration and sport domains through routine formal committee work and informal networks. In addition, it proved possible to develop a typology that deliver an overview of different decision-making practices in terms of the specific interplay of the relevant components of process control (top-down vs. bottom-up) and problem processing (situational vs. systematic). Based on the findings some recommendations for volunteer management in sport clubs are worked out.

How do sport clubs recruit volunteers? Analyzing and developing a typology of decision-making processes on recruiting volunteers in sport clubs.

Effective strategies for recruiting volunteers who are prepared to make a long-term commitment to formal positions are essential for the survival of voluntary sport clubs. This article examines the decision-making processes in relation to these efforts. Under the assumption of bounded rationality, the garbage can model is used to grasp these decision-making processes theoretically and access them empirically. Based on case study framework an in-depth analysis of recruitment practices was conducted in nine selected sport clubs. Results showed that the decision-making processes are generally characterized by a reactive approach in which dominant actors try to handle personnel problems of recruitment in the administration and sport domains through routine formal committee work and informal networks. In addition, it proved possible to develop a typology that deliver an overview of different decision-making practices in terms of the specific interplay of the relevant components of process control (top-down vs. bottom-up) and problem processing (situational vs. systematic).

Strategic divide management in pharmaceutical alliances: A partner’s strategic evolution as a reason for strategic divide

Strategic alliances are widely used in the pharmaceutical industry and, ideally, they are long-lasting structures that bring many benefits and value to the alliance partners. However, organizations continuously encounter pressures to enhance performance, while the environment in which they operate evolves. Therefore, an alliance partner might be forced to change its strategy, which can lead to the partners’ misaligned priorities and strategic divide. The academic literature acknowledges the impact a partner’s strategic change can have on the value of the alliance, but the phenomenon is not studied further, which is why the purpose of this study is to understand the role that a partner’s strategic evolution plays in strategic alliances within the pharmaceutical industry. The main purpose is further divided into three sub-objectives: 1) Describe reasons behind the strategic direction change of a partner firm, 2) Understand the consequences of partners’ misaligned priorities, and 3) Describe proactive and reactive ways to manage strategic divide between alliance partners. Since the phenomenon is not studied much, the empirical part of the study was conducted as a qualitative analysis using expert interviews to better understand, how the partner’s strategic evolution affects the alliance. The empirical data was organized into themes, according to the researcher’s interpretations on the interviews. The research findings demonstrated, how the partners change their strategies if the external or organizational environments change. The strategic changes, again, cause strategic divides between the alliance partners that are likely to have an impact on the alliance value. The findings revealed that the interviewees consider anticipation of the partner’s strategic change to be really difficult, but, at the same time, it was noted that a proactive strategic divide management could help to prevent and detect some divides. Additionally, the results showed that, after the detection, a reactive approach in a controlled manner was seen to be the most beneficial for the alliance’s future performance. This study proved that a partner’s strategic evolution affects the partners’ priority alignment and alliance value, which is why the strategic divide management is important in organizations that are involved with strategic alliances. In order to understand the role of a partner’s strategic evolution and provide managers with a tool to manage alliances and strategic divides, the study combined the alliance lifecycle as well as the proactive and reactive approaches to strategic divide, and presented a framework for strategic divide management.

Design and management of a supply chain: a joint location-inventory problem under uncertainty (Part B)

In recent years, global supply chains have increasingly suffered from reliability issues due to various external and difficult to-manage events. The following paper aims to build an integrated approach for the design of a Supply Chain under the risk of disruption and demand fluctuation. The study is divided in two parts: a mathematical optimization model, to identify the optimal design and assignments customer-facility, and a discrete-events simulation of the resulting network. The first one describes a model in which plant location decisions are influenced by variables such as distance to customers, investments needed to open plants and centralization phenomena that help contain the risk of demand variability (Risk Pooling). The entire model has been built with a proactive approach to manage the risk of disruptions assigning to each customer two types of open facilities: one that will serve it under normal conditions and a back-up facility, which comes into operation when the main facility has failed. The study is conducted on a relatively small number of instances due to the computational complexity, a matheuristic approach can be found in part A of the paper to evaluate the problem with a larger set of players. Once the network is built, a discrete events Supply Chain simulation (SCS) has been implemented to analyze the stock flow within the facilities warehouses, the actual impact of disruptions and the role of the back-up facilities which suffer a great stress on their inventory due to a large increase in demand caused by the disruptions. Therefore, simulation follows a reactive approach, in which customers are redistributed among facilities according to the interruptions that may occur in the system and to the assignments deriving from the design model. Lastly, the most important results of the study will be reported, analyzing the role of lead time in a reactive approach for the occurrence of disruptions and comparing the two models in terms of costs.

Efficient learning of reactive robot behaviors with a Neural-Q_learning approach

The purpose of this paper is to propose a Neural-Q_learning approach designed for online learning of simple and reactive robot behaviors. In this approach, the Q_function is generalized by a multi-layer neural network allowing the use of continuous states and actions. The algorithm uses a database of the most recent learning samples to accelerate and guarantee the convergence. Each Neural-Q_learning function represents an independent, reactive and adaptive behavior which maps sensorial states to robot control actions. A group of these behaviors constitutes a reactive control scheme designed to fulfill simple missions. The paper centers on the description of the Neural-Q_learning based behaviors showing their performance with an underwater robot in a target following task. Real experiments demonstrate the convergence and stability of the learning system, pointing out its suitability for online robot learning. Advantages and limitations are discussed

Efficient learning of reactive robot behaviors with a Neural-Q_learning approach

The purpose of this paper is to propose a Neural-Q_learning approach designed for online learning of simple and reactive robot behaviors. In this approach, the Q_function is generalized by a multi-layer neural network allowing the use of continuous states and actions. The algorithm uses a database of the most recent learning samples to accelerate and guarantee the convergence. Each Neural-Q_learning function represents an independent, reactive and adaptive behavior which maps sensorial states to robot control actions. A group of these behaviors constitutes a reactive control scheme designed to fulfill simple missions. The paper centers on the description of the Neural-Q_learning based behaviors showing their performance with an underwater robot in a target following task. Real experiments demonstrate the convergence and stability of the learning system, pointing out its suitability for online robot learning. Advantages and limitations are discussed

Optimal reactive power flow via the modified barrier Lagrangian function approach

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

A decentralized approach for optimal reactive power dispatch using a Lagrangian decomposition method

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

A combinatorial approach for transmission expansion & reactive power planning

A metaheuristic technique for solving the short-term transmission network expansion and reactive power planning problems, at the same time, in regulated power systems using the AC model is presented. The problem is solved using a real genetic algorithm (RGA). For each topology proposed by RGA an indicator is employed to identify the weak buses for new reactive power sources allocation. The fitness function is calculated using the cost of each configuration as well as constraints deviation of an AC optimal power flow (OPF) in which the minimum reactive generation of new reactive sources and the active power losses are objectives. With allocation of reactive power sources at load buses, the circuit capacity increases and the cost of installation could be decreased. The method is tested in a well known test system, presenting good results when compared with other approaches. © 2011 IEEE.