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.

Petri net model decomposition - a model based approach supporting distributed execution

Dissertação apresentada para obtenção do Grau de Doutor em Engenharia Electrotécnica, Especialidade de Sistemas Digitais, pela Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia

Using perspective schema and a reference model to design the ETL process

Dissertação apresentada para a obtenção do Grau de Doutor em Informática

Men’s purchase intention of shampoo: a model based on the theory of planned behavior and self-concept

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA – School of Business and Economics

Optimization based design of LC voltage controlled oscilators

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

E-Health individual adoption - empirical model based on UTAUT 2.

The future of health care delivery is becoming more citizen-centred, as today’s user is more active, better informed and more demanding. The European Commission is promoting online health services and, therefore, member states will need to boost deployment and use of online services. This makes e-health adoption an important field to be studied and understood. This study applied the extended unified theory of acceptance and usage technology (UTAUT2) to explain patients’ individual adoption of e-health. An online questionnaire was administrated Portugal using mostly the same instrument used in UTAUT2 adapted to e-health context. We collected 386 valid answers. Performance expectancy, effort expectancy, social influence, and habit had the most significant explanatory power over behavioural intention and habit and behavioural intention over technology use. The model explained 52% of the variance in behavioural intention and 32% of the variance in technology use. Our research helps to understand the desired technology characteristics of ehealth. By testing an information technology acceptance model, we are able to determine what is more valued by patients when it comes to deciding whether to adopt e-health systems or not.

Qualitative and quantitative formal model-based safety analysis : push the safety button

Magdeburg, Univ., Fak. für Informatik, Diss., 2011

Experimental and model-based analysis of the steady-state and dynamic operating behaviour of the direct methanol fuel cell (DMFC)

Direct methanol fuel cell, DMFC, model, mass transport, Maxwell-Stefan, Flory-Huggins, crossover, polymer electrolyte membrane, Nafion

Model-based measurement and control of fluidised bed spray granulation processes

Magdeburg, Univ., Fak. für Verfahrens- und Systemtechnik, Diss., 2012

A model-based cortical parcellation scheme for high-resolution 7 Tesla MRI data

Magdeburg, Univ., Fak. für Informatik, Diss., 2015

Control and model-based analysis of microaerobic processes - using Rhodospirillum rubrum as model organism

Magdeburg, Univ., Fak. für Elektrotechnik und Informationstechnik, Diss., 2015

Model-based diagnosis system: application to constructed wetlands

Report for the scientific sojourn carried out at the Model-based Systems and Qualitative Reasoning Group (Technical University of Munich), from September until December 2005. Constructed wetlands (CWs), or modified natural wetlands, are used all over the world as wastewater treatment systems for small communities because they can provide high treatment efficiency with low energy consumption and low construction, operation and maintenance costs. Their treatment process is very complex because it includes physical, chemical and biological mechanisms like microorganism oxidation, microorganism reduction, filtration, sedimentation and chemical precipitation. Besides, these processes can be influenced by different factors. In order to guarantee the performance of CWs, an operation and maintenance program must be defined for each Wastewater Treatment Plant (WWTP). The main objective of this project is to provide a computer support to the definition of the most appropriate operation and maintenance protocols to guarantee the correct performance of CWs. To reach them, the definition of models which represent the knowledge about CW has been proposed: components involved in the sanitation process, relation among these units and processes to remove pollutants. Horizontal Subsurface Flow CWs are chosen as a case study and the filtration process is selected as first modelling-process application. However, the goal is to represent the process knowledge in such a way that it can be reused for other types of WWTP.

MB-MDR: Model-Based Multifactor Dimensionality Reduction for detecting interactions in high-dimensional genomic data

L’anàlisi de l’efecte dels gens i els factors ambientals en el desenvolupament de malalties complexes és un gran repte estadístic i computacional. Entre les diverses metodologies de mineria de dades que s’han proposat per a l’anàlisi d’interaccions una de les més populars és el mètode Multifactor Dimensionality Reduction, MDR, (Ritchie i al. 2001). L’estratègia d’aquest mètode és reduir la dimensió multifactorial a u mitjançant l’agrupació dels diferents genotips en dos grups de risc: alt i baix. Tot i la seva utilitat demostrada, el mètode MDR té alguns inconvenients entre els quals l’agrupació excessiva de genotips pot fer que algunes interaccions importants no siguin detectades i que no permet ajustar per efectes principals ni per variables confusores. En aquest article il•lustrem les limitacions de l’estratègia MDR i d’altres aproximacions no paramètriques i demostrem la conveniència d’utilitzar metodologies parametriques per analitzar interaccions en estudis cas-control on es requereix l’ajust per variables confusores i per efectes principals. Proposem una nova metodologia, una versió paramètrica del mètode MDR, que anomenem Model-Based Multifactor Dimensionality Reduction (MB-MDR). La metodologia proposada té com a objectiu la identificació de genotips específics que estiguin associats a la malaltia i permet ajustar per efectes marginals i variables confusores. La nova metodologia s’il•lustra amb dades de l’Estudi Espanyol de Cancer de Bufeta.

A musculoskeletal shoulder model based on pseudo-inverse and null-space optimization.

The goal of the present work was assess the feasibility of using a pseudo-inverse and null-space optimization approach in the modeling of the shoulder biomechanics. The method was applied to a simplified musculoskeletal shoulder model. The mechanical system consisted in the arm, and the external forces were the arm weight, 6 scapulo-humeral muscles and the reaction at the glenohumeral joint, which was considered as a spherical joint. The muscle wrapping was considered around the humeral head assumed spherical. The dynamical equations were solved in a Lagrangian approach. The mathematical redundancy of the mechanical system was solved in two steps: a pseudo-inverse optimization to minimize the square of the muscle stress and a null-space optimization to restrict the muscle force to physiological limits. Several movements were simulated. The mathematical and numerical aspects of the constrained redundancy problem were efficiently solved by the proposed method. The prediction of muscle moment arms was consistent with cadaveric measurements and the joint reaction force was consistent with in vivo measurements. This preliminary work demonstrated that the developed algorithm has a great potential for more complex musculoskeletal modeling of the shoulder joint. In particular it could be further applied to a non-spherical joint model, allowing for the natural translation of the humeral head in the glenoid fossa.