878 resultados para Observational techniques and algorithms


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This chapter focuses on the development of organizational creativity, using the CPS methodology, aiming at demonstrating its effectiveness in using the individual and team divergent thinking improvement in identifying organizational problems. A study was undertaken using problem solving teams in seven companies, in which each individual was submitted to a pre-post test in attitudes towards divergent thinking and asked to express the evaluation of the method. All the information reported in the sessions was recorded. The results indicate a change in attitude favourable to divergent thinking, the provision of a professional, efficient method of organizing knowledge in such a way that can help individuals to find original solutions to problems, and an important way to lead teams to creativity and innovation, according with companies different orientations.

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This research focuses on creativity and innovation management in organizations. We present a model of intervention that aims at establishing a culture of organizational innovation through the internal development of individual and team creativity focusing on problem solving. The model relies on management’s commitment and in the organization’s talented people (creative leaders and employees) as a result of their ability in defining a better organization. The design follows Min Basadur’s problem solving approach consisting of problem finding, fact finding, problem definition, solution finding and decision implementation. These steps are carried out using specific techniques and procedures that will link creative people and management in order to initiate the process until problems are defined. For each defined problem, project teams will develop possible solutions and implement these decisions. Thus, a system of transformation of the individual and team creativity into organizational innovation can be established.

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Dissertação de mestrado, Aquacultura e Pescas, Faculdade de Ciências e Tecnologia, Universidade do Algarve, 2015

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Tese de doutoramento, Sistemas Sustentáveis de Energia, Universidade de Lisboa, Faculdade de Ciências, 2015

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Tese de doutoramento, Informática (Bioinformática), Universidade de Lisboa, Faculdade de Ciências, 2014

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Thesis (Master's)--University of Washington, 2014

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Tese de doutoramento, Biologia (Biologia do Desenvolvimento), Universidade de Lisboa, Faculdade de Ciências, 2015

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Report produced as part of the Green Logistics project (EPSRC and Department for Transport funded). This report is based on a review of studies in which data has been collected to obtain an understanding of road-based urban freight transport activities and patterns of operation. Studies from the UK and other countries have been included in this review. While it may be thought that relatively few such studies have been conducted, approximately 60 such studies have been identified as taking place in the UK and approximately 100 elsewhere since the 1960s. In addition, other studies have been carried out in order to assess industry and policy maker opinions about urban freight transport , however this type of study and survey work is not the focus of this report. Gaining an understanding of road-based urban freight transport activities is an important element in determining the current sustainability of such activity (in economic, social and environmental terms) and how best to go about enhancing its sustainability. By reviewing the existing survey work in this subject it has been possible to draw together the methodologies developed and implemented. This should therefore be of help in understanding which techniques are most commonly used, the strengths and limitations of the various techniques, and in assessing the most suitable urban freight survey techniques for a given study.

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Tese de mestrado, Neurociências, Faculdade de Medicina, Universidade de Lisboa, 2015

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Coping with an ageing population is a major concern for healthcare organisations around the world. The average cost of hospital care is higher than social care for older and terminally ill patients. Moreover, the average cost of social care increases with the age of the patient. Therefore, it is important to make efficient and fair capacity planning which also incorporates patient centred outcomes. Predictive models can provide predictions which their accuracy can be understood and quantified. Predictive modelling can help patients and carers to get the appropriate support services, and allow clinical decision-makers to improve care quality and reduce the cost of inappropriate hospital and Accident and Emergency admissions. The aim of this study is to provide a review of modelling techniques and frameworks for predictive risk modelling of patients in hospital, based on routinely collected data such as the Hospital Episode Statistics database. A number of sub-problems can be considered such as Length-of-Stay and End-of-Life predictive modelling. The methodologies in the literature are mainly focused on addressing the problems using regression methods and Markov models, and the majority lack generalisability. In some cases, the robustness, accuracy and re-usability of predictive risk models have been shown to be improved using Machine Learning methods. Dynamic Bayesian Network techniques can represent complex correlations models and include small probabilities into the solution. The main focus of this study is to provide a review of major time-varying Dynamic Bayesian Network techniques with applications in healthcare predictive risk modelling.

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Trabalho de Projeto para obtenção do grau de Mestre em Engenharia Informática e de Computadores

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Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia Informática e Computadores

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Localization is a fundamental task in Cyber-Physical Systems (CPS), where data is tightly coupled with the environment and the location where it is generated. The research literature on localization has reached a critical mass, and several surveys have also emerged. This review paper contributes on the state-of-the-art with the proposal of a new and holistic taxonomy of the fundamental concepts of localization in CPS, based on a comprehensive analysis of previous research works and surveys. The main objective is to pave the way towards a deep understanding of the main localization techniques, and unify their descriptions. Furthermore, this review paper provides a complete overview on the most relevant localization and geolocation techniques. Also, we present the most important metrics for measuring the accuracy of localization approaches, which is meant to be the gap between the real location and its estimate. Finally, we present open issues and research challenges pertaining to localization. We believe that this review paper will represent an important and complete reference of localization techniques in CPS for researchers and practitioners and will provide them with an added value as compared to previous surveys.

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The goal of this study is the analysis of the dynamical properties of financial data series from worldwide stock market indexes during the period 2000–2009. We analyze, under a regional criterium, ten main indexes at a daily time horizon. The methods and algorithms that have been explored for the description of dynamical phenomena become an effective background in the analysis of economical data. We start by applying the classical concepts of signal analysis, fractional Fourier transform, and methods of fractional calculus. In a second phase we adopt the multidimensional scaling approach. Stock market indexes are examples of complex interacting systems for which a huge amount of data exists. Therefore, these indexes, viewed from a different perspectives, lead to new classification patterns.

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The goal of this study is the analysis of the dynamical properties of financial data series from worldwide stock market indices. We analyze the Dow Jones Industrial Average ( ∧ DJI) and the NASDAQ Composite ( ∧ IXIC) indexes at a daily time horizon. The methods and algorithms that have been explored for description of physical phenomena become an effective background, and even inspiration, for very productive methods used in the analysis of economical data. We start by applying the classical concepts of signal analysis, Fourier transform, and methods of fractional calculus. In a second phase we adopt a pseudo phase plane approach.