Decision-making on childhood vaccination by highly educated parents

OBJECTIVE To analyze the sociocultural aspects involved in the decision-making process of vaccination in upper-class and highly educated families.METHODS A qualitative approach based on in-depth interviews with 15 couples from the city of Sao Paulo, Southeastern Brazil, falling into three categories: vaccinators, late or selective vaccinators, and nonvaccinators. The interpretation of produced empirical material was performed through content analysis.RESULTS The study showed diverse and particular aspects surrounding the three groups’ decisions whether to vaccinate their children. The vaccinators’ decision to vaccinate their children was spontaneous and raised no questions. Most late or selective vaccinators experienced a wide range of situations that were instrumental in the decision to delay or not apply certain vaccines. The nonvaccinator’s decision-making process expressed a broader context of both criticism of hegemonic obstetric practices in Brazil and access to information transmitted via social networks and the internet. The data showed that the problematization of vaccines (culminating in the decision to not vaccinate their children) occurred in the context of humanized birth, was protagonized by women and was greatly influenced by health information from the internet.CONCLUSIONS Sociocultural aspects of the singular Brazilian context and the contemporary society were involved in the decision-making on children’s vaccination. Understanding this process can provide a real basis for a deeper reflection on health and immunization practices in Brazil in light of the new contexts and challenges of the world today.

Participate (or not) in international trade fairs? Decision factors of Portuguese managers

Portugal is a small economy, with an open domestic market that needs competitive exporters to prosper. Trade fairs are an international promotion tool that can be used by firms when considering export development and expansion. This study identifies and evaluates the critical factors that influenced the decision making process of Portuguese SME’s (Small and Medium-Sized Enterprises) managers to participate (or not) in international trade fairs. The results indicate that the firm’s critical decisions factors to select an international trade fair were value for money and the stand (location, typology and size)

Railway vehicle modelling for the vehicle-track interaction compatibility analysis

Railway vehicle homologation, with respect to running dynamics, is addressed via dedicated norms. The results required, such as, accelerations and/or wheel-rail contact forces, obtained from experimental tests or simulations, must be available. Multibody dynamics allows the modelling of railway vehicles and their representation in real operations conditions, being the realism of the multibody models greatly influenced by the modelling assumptions. In this paper, two alternative multibody models of the Light Rail Vehicle 2000 (LRV) are constructed and simulated in a realistic railway track scenarios. The vehicle-track interaction compatibility analysis consists of two stages: the use of the simplified method described in the norm "UIC 518-Testing and Approval of Railway Vehicles from the Point of View of their Dynamic Behaviour-Safety-Track Fatigue-Running Behaviour" for decision making; and, visualization inspection of the vehicle motion with respect to the track via dedicated tools for understanding the mechanisms involved.

Scenarios Generation for Multi-Agent simulation of Electricity Markets based on Intelligent Data Analysis

This document presents a tool able to automatically gather data provided by real energy markets and to generate scenarios, capture and improve market players’ profiles and strategies by using knowledge discovery processes in databases supported by artificial intelligence techniques, data mining algorithms and machine learning methods. It provides the means for generating scenarios with different dimensions and characteristics, ensuring the representation of real and adapted markets, and their participating entities. The scenarios generator module enhances the MASCEM (Multi-Agent Simulator of Competitive Electricity Markets) simulator, endowing a more effective tool for decision support. The achievements from the implementation of the proposed module enables researchers and electricity markets’ participating entities to analyze data, create real scenarios and make experiments with them. On the other hand, applying knowledge discovery techniques to real data also allows the improvement of MASCEM agents’ profiles and strategies resulting in a better representation of real market players’ behavior. This work aims to improve the comprehension of electricity markets and the interactions among the involved entities through adequate multi-agent simulation.

Strategic Bidding in Electricity Markets: An agent-based simulator with game theory for scenario analysis

Electricity markets are complex environments, involving a large number of different entities, with specific characteristics and objectives, making their decisions and interacting in a dynamic scene. Game-theory has been widely used to support decisions in competitive environments; therefore its application in electricity markets can prove to be a high potential tool. This paper proposes a new scenario analysis algorithm, which includes the application of game-theory, to evaluate and preview different scenarios and provide players with the ability to strategically react in order to exhibit the behavior that better fits their objectives. This model includes forecasts of competitor players’ actions, to build models of their behavior, in order to define the most probable expected scenarios. Once the scenarios are defined, game theory is applied to support the choice of the action to be performed. Our use of game theory is intended for supporting one specific agent and not for achieving the equilibrium in the market. MASCEM (Multi-Agent System for Competitive Electricity Markets) is a multi-agent electricity market simulator that models market players and simulates their operation in the market. The scenario analysis algorithm has been tested within MASCEM and our experimental findings with a case study based on real data from the Iberian Electricity Market are presented and discussed.

How composite indicators of innovation can influence technology policy decision?

Based on the report for Project III of the PhD programme on Technology Assessment and prepared for the Winter School that took place at Universidade Nova de Lisboa, Caparica Campus on the 6th and 7th of December 2010.

Negotiation context analysis in electricity markets

Contextualization is critical in every decision making process. Adequate responses to problems depend not only on the variables with direct influence on the outcomes, but also on a correct contextualization of the problem regarding the surrounding environment. Electricity markets are dynamic environments with increasing complexity, potentiated by the last decades' restructuring process. Dealing with the growing complexity and competitiveness in this sector brought the need for using decision support tools. A solid example is MASCEM (Multi-Agent Simulator of Competitive Electricity Markets), whose players' decisions are supported by another multiagent system – ALBidS (Adaptive Learning strategic Bidding System). ALBidS uses artificial intelligence techniques to endow market players with adaptive learning capabilities that allow them to achieve the best possible results in market negotiations. This paper studies the influence of context awareness in the decision making process of agents acting in electricity markets. A context analysis mechanism is proposed, considering important characteristics of each negotiation period, so that negotiating agents can adapt their acting strategies to different contexts. The main conclusion is that context-dependant responses improve the decision making process. Suiting actions to different contexts allows adapting the behaviour of negotiating entities to different circumstances, resulting in profitable outcomes.

Decision Support for Energy Contracts Negotiation with Game Theory and Adaptive Learning

This paper presents a decision support methodology for electricity market players’ bilateral contract negotiations. The proposed model is based on the application of game theory, using artificial intelligence to enhance decision support method’s adaptive features. This model is integrated in AiD-EM (Adaptive Decision Support for Electricity Markets Negotiations), a multi-agent system that provides electricity market players with strategic behavior capabilities to improve their outcomes from energy contracts’ negotiations. Although a diversity of tools that enable the study and simulation of electricity markets has emerged during the past few years, these are mostly directed to the analysis of market models and power systems’ technical constraints, making them suitable tools to support decisions of market operators and regulators. However, the equally important support of market negotiating players’ decisions is being highly neglected. The proposed model contributes to overcome the existing gap concerning effective and realistic decision support for electricity market negotiating entities. The proposed method is validated by realistic electricity market simulations using real data from the Iberian market operator—MIBEL. Results show that the proposed adaptive decision support features enable electricity market players to improve their outcomes from bilateral contracts’ negotiations.

Decision making processes based on innovation indicators: which implications for technology assessment?

Based on the report for “Project IV” unit of the PhD programme on Technology Assessment. This thesis research has the supervision of António Moniz (FCT-UNL and ITAS-KIT) and Manuel Laranja (ISEG-UTL). Other members of the thesis committee are Stefan Kuhlmann (Twente University), Leonhard Hennen (Karlsruhe Institute of Technology-ITAS), Tiago Santos Pereira (Universidade de Coimbra/CES) and Cristina Sousa (FCT-UNL).

Risk-based decision support system for life cycle management of industrials plants

Dissertação para obtenção do Grau de Doutor em Engenharia Electrotécnica e de Computadores

Urban sprawl analysis and modeling in Asmara, Eritreia: Application of Geospatial Tools

Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.

Urban land cover change detection analysis and modeling spatio-temporal Growth dynamics using Remote Sensing and GIS Techniques: A case study of Dhaka, Bangladesh

Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.

Environmental Decision-making utilizing a Web GIS to Monitor Hazardous Industrial Emissions in the Valencian community of Spain

Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.

Hydrologic modeling and uncertainty analysis of an ungauged watershed using mapwindow-swat

Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies

A study on reducing digital piracy: an analytical network process approach with benefits, opportunities, costs and risks analysis

Dissertação para obtenção do Grau de Mestre em Engenharia e Gestão Industrial