Hausmannian Buildings Rehabilitation and Strengthening

Hausmannian buildings architecture spreads throughout the city of Paris. These buildings were constructed in the 19th century, being presently centenarians. However, they present several pathologies which prevent their adequate use, moreover, an update regarding users security, sound, thermal and fire requirements is, among others, urgently needed. Additionally, there is presently, in Paris, an increasing demand for hotel rooms. For those previous reasons, Hausmannian buildings are presently submitted to heavy operations related to rehabilitation, strengthening, use change and conservation. In this paper, rehabilitation and strengthening works presently carried out in those buildings are described. This description is the result of a technical survey on several Hausmannian building construction sites which occurred between 2015 and 2018. The knowledge from this study should be very useful for the development of sustainable rehabilitation and strengthening techniques and guidelines, aiming to preserve this important building heritage or similar ones existing in other countries. Keywords: Hausmannian buildings, Rehabilitation, Strengthening, Sustainabilit

Hints to Improve Motivation in Construction Companies

AbstractMotivation in work teams has a key role to play for the survival and competitiveness of businesses in the harsh environment of economic recession. This paper characterizes motivation in small and medium-sized construction companies in Portugal. It draws on data collected from in-person surveys which were carried out to employees of 32 companies. Results reveal the presence of some motivating factors specific to the profession such as the fact that the work requires a wide range of skills and is not very routine. Also, although employees in general feel a sense of equity and recognize that managers provide constant feedback, results show the need for improvement in motivation's management, particularly in regard to more autonomy and participation in setting goals

Features selection in Discrete Discriminant Analysis

Resumo de comunicação em póster apresentada em 14th International Conference on Applied Stochastic Models and Data Analysis (ASMDA2011), Rome, June 7-10 2011In discrete discriminant analysis dimensionality problems occur, particularly when dealing with data from the social sciences, humanities and health. In these domains, one often has to classify entities with a high number of explanatory variables when compared to the number of observations available. In the present work we address the problem of features selection in classification, aiming to identify the variables that most discriminate between the a priori defined classes, reducing the number of parameters to estimate, turning the results easier to interpret and reducing the runtime of the methods used. We specially address classification using a recently methodological approach based on a linear combination of the First-order Independence Model (FOIM) and the Dependence Trees Model (DTM). Data of small and moderate size are considered

Classification and combining models

Trabalho apresentado em SMTDA 2010: Stochastic Modeling Techniques and Data Analysis International Conference, Chania, Crete, Greece, 8-11 june 2010In the context of Discrete Discriminant Analysis (DDA) the idea of combining models is present in a growing number of papers aiming to obtain more robust and more stable models. This seems to be a promising approach since it is known that different DDA models perform differently on different subjects. Furthermore, the idea of combining models is particularly relevant when the groups are not well separeted, which often occurs in practice. Recently, we proposed a new DDA approach which is based on a linear combination of the First-order Independence Model (FOIM) and the Dependence Trees Model (DTM). In the present work we apply this new approach to classify consumers of a Portuguese cultural institution. We specifically focus on the performance of alternative models' combinations assessing the error rate and the Huberty index in a test sample. We use the R software for the algorithms' implementation and evaluation

Combining models in discrete discriminant analysis in the multiclass case

Resumo de comunicação oral em póster apresentado em COMPSTAT2008 - 18th International Conference on Computational Statistics, Porto, Portugal, 24 a 29 de Agosto 2008The idea of combining models in Discrete Discriminant Analysis (DDA) is present in a growing number of papers which aim to obtain more robust and more stable models than any of the competing ones. This seems to be a promising approach since it is known that different DDA models perform differently on different subjects (Brito et al.(2006)). In particular, this will be a more relevant issue if the groups are not well separated, which often occurs in practice. In the present work a new methodological approach is suggested which is based on DDA models' combination. The multiclass problem is decomposed into several dichotomous problems that are nested in a hierarchical binary tree (Sousa Ferreira (2000), Brito et al. (2006)) and at each level of the binary tree a new combining model is proposed to derive the decision rule. This combining model is based on two well known models in the literature - the First-order Independence Model (FOIM) and the Dependence Trees Model (DTM) (Celeux and Nakache (1994)). The MATLAB software is used for the algorithms' implementation and the proposed approach is illustrated in a DDA application

Combining Models in Discrete Discriminant Analysis

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Combining models in supervised classification: New developments

Resumo da comunicação oral apresentada em XVIII Jornadas de Classificação e Análise de Dados (JOCLAD2011), Vila Real, de 7 a 9 de Abril de 2011In Discrete Discriminant Analysis dimensionality problems often occur. In this context, we propose a combining models approach, taking profit from several potential models. In the bi-class case, a single combination coefficient is considered and estimated using several strategies. In the multi-class case, the decomposition into several bi-class problems embedded in a binary tree is implemented. New developments of this approach are presented and their performances assessed on real or simulated data

Combining models in discrete discriminant analysis

Resumo da comunicação em póster apresentada em International Conference on Trends and Perspectives in Linear Statistical Inference (LinStat'2010), Tomar, Portugal, 27-31 July, 2010Diverse Discrete Discriminant Analysis (DDA) models perform differently on different sample observations (Brito et al. (2006)). This fact has encouraged research in combined models for DDA. This research seems to be specially promising when the a priori classes are not well separated or when small or moderate sized samples are considered, which often occurs in practice. In this work we evaluate the performance of a linear combination of two DDA models (Marques et al. (2008)): the First-Order Independence Model (FOIM) and the Dependence Trees Model (DTM) (Celeux and Nakache (1994). The pro- posed methodology also uses a Hierarchical Coupling Model (HIERM) when addressing multiclass classification problems, decomposing the multiclass problems into several bi-class problems, using a binary tree structure (Sousa Ferreira (2000)). The analysis is based both on simulated and real datasets. Results include measures of precision regarding a training set, a test set and cross-validation. The R software is used for the algorithm's implementation

A participação docente e colegiada no processo de construção e implementação do currículo de tempo integral.

O trabalho do mestrado fez uma reflexão sobre a participação docente e colegiada no processo de construção e implementação do currículo de tempo integral. A abordagem teve o enfoque quantitativo do tipo descritivo, os resultados apontaram que os docentes da fase de construção do currículo da escola de tempo integral tiveram uma formação mais consistente sobre currículo. Nas instâncias colegiadas (conselhos escolares) mesmo com parte de representantes cientes do seu papel, destacou-se algumas discussões sobre currículo e a sistemática de avaliação, prevalecendo a função financeira e disciplinar nos contextos de atuação. Contudo, pouco se discute nos processos decisórios em relação à parte diversificada do currículo ou discussões dos grandes temas curriculares da atualidade na escola para ampliar o diálogo sociocultural para uma educação alternativa

Integration between EVM and Risk Management: proposal of an automated framework

"World Conference on Information Systems and Technologies (WorldCIST 2017)The integration between Earned Value Management (EVM) and Project Risk Management immediately raises the question of the relationship between the two methods, even though EVM and project risk management share the same function in project management: promote the project success. At first glance it seems to be no further connection between these two methodologies, but the fundamentals of EVM are fully influenced by both risk management and risk analyses. This paper seeks to clarify the mechanisms of this function, and in which points they meet or affect each other, with reference to PMBoK®. The several techniques and methods are somewhat disperse and not always coherent. With the several assumptions resulting from the interconnection between the two methods, a framework of integration between them is proposed, as well as its practical implementation in Excel, resulting in a set of tools that can be useful in monitoring and controlling a project.This work has been supported by COMPETE: POCI-01-0145-FEDER-007043 and FCT – Fundação para a Ciência e Tecnologia within the Project Scope: UID/CEC/00319/2013.info:eu-repo/semantics/publishedVersio