e-Recruitment: descrição e inferência sobre oferta e procura

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

Long-run consumption risk with durable goods : UK evidence for equity and bond markets

"It is a widely accepted fact that the consumption-based capital asset pricing model (CCAPM) fails to provide a good explanation of many important features of the behaviour of financial market returns in a large range of countries over a long period of time. However, within a representative consumer/investor model, it is hard to see how the basic structure of the consumption based model can be safely abandoned." [introdução]

Improving a Cluster Based Directional Channel Model in Realistic Macro-Cell Environment

In this paper a realistic directional channel model that is an extension of the COST 273 channel model is presented. The model uses a cluster of scatterers and visibility region generation based strategy with increased realism, due to the introduction of terrain and clutter information. New approaches for path-loss prediction and line of sight modeling are considered, affecting the cluster path gain model implementation. The new model was implemented using terrain, clutter, street and user mobility information for the city of Lisbon, Portugal. Some of the model's outputs are presented, mainly path loss and small/large-scale fading statistics.

MDAI: Model based Design in Automobile Industry

It is proposed a new approach based on a methodology, assisted by a tool, to create new products in the automobile industry based on previous defined processes and experiences inspired on a set of best practices or principles: it is based on high-level models or specifications; it is component-based architecture centric; it is based on generative programming techniques. This approach follows in essence the MDA (Model Driven Architecture) philosophy with some specific characteristics. We propose a repository that keeps related information, such as models, applications, design information, generated artifacts and even information concerning the development process itself (e.g., generation steps, tests and integration milestones). Generically, this methodology receives the users' requirements to a new product (e.g., functional, non-functional, product specification) as its main inputs and produces a set of artifacts (e.g., design parts, process validation output) as its main output, that will be integrated in the engineer design tool (e.g. CAD system) facilitating the work.

A model updating technique based on FRFs for damped structures

Model updating methods often neglect that in fact all physical structures are damped. Such simplification relies on the structural modelling approach, although it compromises the accuracy of the predictions of the structural dynamic behaviour. In the present work, the authors address the problem of finite element (FE) model updating based on measured frequency response functions (FRFs), considering damping. The proposed procedure is based upon the complex experimental data, which contains information related to the damped FE model parameters and presents the advantage of requiring no prior knowledge about the damping matrix structure or its content, only demanding the definition of the damping type. Numerical simulations are performed in order to establish the applicability of the proposed damped FE model updating technique and its results are discussed in terms of the correlation between the simulated experimental complex FRFs and the ones obtained from the updated FE model.

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.

Building a person home behavior model based on data from smart house sensors 2015

Dissertação para a obtenção do grau de Mestre em Engenharia Electrotécnica Ramo de Energia

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.