An immunity based configuration for multilayer single featured biometric authentication algorithms

Immune systems have been used in the last years to inspire approaches for several computational problems. This paper focus on behavioural biometric authentication algorithms’ accuracy enhancement by using them more than once and with different thresholds in order to first simulate the protection provided by the skin and then look for known outside entities, like lymphocytes do. The paper describes the principles that support the application of this approach to Keystroke Dynamics, an authentication biometric technology that decides on the legitimacy of a user based on his typing pattern captured on he enters the username and/or the password and, as a proof of concept, the accuracy levels of one keystroke dynamics algorithm when applied to five legitimate users of a system both in the traditional and in the immune inspired approaches are calculated and the obtained results are compared.

Bidirectional battery charger with grid-to-vehicle, vehicle-to-grid and vehicle-to-home technologies

This paper presents the development of na on-board bidirectional battery charger for Electric Vehicles (EVs) targeting Grid-to-Vehicle (G2V), Vehicle-to-Grid (V2G), and Vehicle-to-Home (V2H) technologies. During the G2V operation mode the batteries are charged from the power grid with sinusoidal current and unitary power factor. During the V2G operation mode the energy stored in the batteries can be delivered back to the power grid contributing to the power system stability. In the V2H operation mode the energy stored in the batteries can be used to supply home loads during power outages, or to supply loads in places without connection to the power grid. Along the paper the hardware topology of the bidirectional battery charger is presented and the control algorithms are explained. Some considerations about the sizing of the AC side passive filter are taken into account in order to improve the performance in the three operation modes. The adopted topology and control algorithms are accessed through computer simulations and validated by experimental results achieved with a developed laboratory prototype operating in the different scenarios.

Algorithms and tools for in silico design of cell factories

PhD thesis in Bioengineering

Testing Nelder-Mead based repulsion algorithms for multiple roots of nonlinear systems via a two-level factorial design of experiments

This paper addresses the challenging task of computing multiple roots of a system of nonlinear equations. A repulsion algorithm that invokes the Nelder-Mead (N-M) local search method and uses a penalty-type merit function based on the error function, known as 'erf', is presented. In the N-M algorithm context, different strategies are proposed to enhance the quality of the solutions and improve the overall efficiency. The main goal of this paper is to use a two-level factorial design of experiments to analyze the statistical significance of the observed differences in selected performance criteria produced when testing different strategies in the N-M based repulsion algorithm. The main goal of this paper is to use a two-level factorial design of experiments to analyze the statistical significance of the observed differences in selected performance criteria produced when testing different strategies in the N-M based repulsion algorithm.

Prediction of drug targets in human pathogens

The identification of new and druggable targets in bacteria is a critical endeavour in pharmaceutical research of novel antibiotics to fight infectious agents. The rapid emergence of resistant bacteria makes today's antibiotics more and more ineffective, consequently increasing the need for new pharmacological targets and novel classes of antibacterial drugs. A new model that combines the singular value decomposition technique with biological filters comprised of a set of protein properties associated with bacterial drug targets and similarity to protein-coding essential genes of E. coli has been developed to predict potential drug targets in the Enterobacteriaceae family [1]. This model identified 99 potential target proteins amongst the studied bacterial family, exhibiting eight different functions that suggest that the disruption of the activities of these proteins is critical for cells. Out of these candidates, one was selected for target confirmation. To find target modulators, receptor-based pharmacophore hypotheses were built and used in the screening of a virtual library of compounds. Postscreening filters were based on physicochemical and topological similarity to known Gram-negative antibiotics and applied to the retrieved compounds. Screening hits passing all filters were docked into the proteins catalytic groove and 15 of the most promising compounds were purchased from their chemical vendors to be experimentally tested in vitro. To the best of our knowledge, this is the first attempt to rationalize the search of compounds to probe the relevance of this candidate as a new pharmacological target.

Bootstrap performance profiles in stochastic algorithms assessment

Optimization with stochastic algorithms has become a relevant research field. Due to its stochastic nature, its assessment is not straightforward and involves integrating accuracy and precision. Performance profiles for the mean do not show the trade-off between accuracy and precision, and parametric stochastic profiles require strong distributional assumptions and are limited to the mean performance for a large number of runs. In this work, bootstrap performance profiles are used to compare stochastic algorithms for different statistics. This technique allows the estimation of the sampling distribution of almost any statistic even with small samples. Multiple comparison profiles are presented for more than two algorithms. The advantages and drawbacks of each assessment methodology are discussed.

Segmentação do tecido tumoral cerebral em imagens de ressonância magnética

Dissertação de mestrado integrado em Engenharia Biomédica (área de especialização em Eletrónica Médica)

Realidade virtual no tratamento do transtorno de pânico

O uso de realidade virtual (RV) é útil no tratamento de exposição em pacientes com transtorno de pânico (TP). Em ambientes virtuais, os pacientes experimentam alterações fisiológicas, psíquicas e somáticas similares aos sintomas em situações da vida real, facilitando o processo de habituação. OBJETIVO: Divulgar o panorama atual do uso de RV no tratamento do TP. MÉTODO: A literatura sobre o tratamento do TP a partir da RV foi revisada com metodologia sistemática na base de dados PubMed, por meio das palavras-chave: virtual reality e panic disorder. RESULTADOS: O tratamento do TP com RV está em geral associado a bons resultados e à boa aceitabilidade por parte dos pacientes. São poucos os estudos que mensuram respostas fisiológicas durante a exposição, apesar da importância destes dados para avaliação da eficácia do tratamento. CONCLUSÕES: Apesar da utilidade do tratamento do TP por RV ser verificada nos estudos, constata-se necessidade de estudos controlados e protocolos de tratamento padronizados.

Brincar de Internet: a vivência lúdica infantil em ambiente virtual

Tese de Doutoramento em Ciências da Educação (Especialidade em Tecnologia Educativa)

Development of procedures for the design, optimization and manufacturing of customized orthopaedic and trauma implants: Geometrical/anatomical modelling from 3D medical imaging

Tese de Doutoramento (Programa Doutoral em Engenharia Biomédica)

Algorithms and computational tools for metabolic flux analysis

PhD thesis in Biomedical Engineering

A survey of distributed data aggregation algorithms

Distributed data aggregation is an important task, allowing the de- centralized determination of meaningful global properties, that can then be used to direct the execution of other applications. The resulting val- ues result from the distributed computation of functions like count, sum and average. Some application examples can found to determine the network size, total storage capacity, average load, majorities and many others. In the last decade, many di erent approaches have been pro- posed, with di erent trade-o s in terms of accuracy, reliability, message and time complexity. Due to the considerable amount and variety of ag- gregation algorithms, it can be di cult and time consuming to determine which techniques will be more appropriate to use in speci c settings, jus- tifying the existence of a survey to aid in this task. This work reviews the state of the art on distributed data aggregation algorithms, providing three main contributions. First, it formally de nes the concept of aggrega- tion, characterizing the di erent types of aggregation functions. Second, it succinctly describes the main aggregation techniques, organizing them in a taxonomy. Finally, it provides some guidelines toward the selection and use of the most relevant techniques, summarizing their principal characteristics.

Flow updating: fault-tolerant aggregation for dynamic networks

Documento submetido para revisão pelos pares. A publicar em Journal of Parallel and Distributed Computing. ISSN 0743-7315

Virtual reality in assessment and treatment of schizophrenia: a systematic review

Objective To conduct a systematic review about the use of virtual reality (VR) for evaluation, treatment and/or rehabilitation of patients with schizophrenia, focused on: areas, fields and objectives; methodological issues; features of the VR used; viability and efficiency of this resource. Methods Searches were performed about schizophrenia and virtual reality in PsycINFO, Academic Search Complete, MEDLINE Complete, CINAHL with Full Text, Web of Science and Business Source Premier databases, using the following keywords: [“schizophrenia”] AND [“virtual reality” OR “serious game”] AND [“treatment” OR “therapy” OR “rehabilitation”]. The search was carried out between November 2013 and June 2014 without using any search limiters. Results A total of 101 papers were identified, and after the application of exclusion criteria, 33 papers remained. The studies analysed focused on the use of VR for the evaluation of cognitive, social, perceptual and sensory skills, and the vast majority were experimental studies, with virtual reality specifically created for them. All the reviewed papers point towards a reliable and safe use of VR for evaluating and treating cognitive and social deficits in patients with schizophrenia, with different results in terms of generalisation, motivation, assertiveness and task participation rate. Some problems were highlighted, such as its high cost and a constant need for software maintenance. Conclusion The studies show that using the virtual reality may streamline traditional evaluation/rehabilitation programmes, allowing to enhance the results achieved, both in the cognitive and in the social field, helping for the legitimisation of this population’s psycho-social inclusion.

Improving diagnostic yield in obscure gastrointestinal bleeding - how virtual chromoendoscopy may be the answer

Background and aim: A significant proportion of patients presenting with obscure gastrointestinal bleeding (OGIB) have negative small bowel capsule endoscopy (SBCE) examinations, and yet remain at risk of rebleeding. We aimed to evaluate whether a second-look review of SBCE images using flexible spectral color enhancement (FICE) may improve the detection of potentially bleeding lesions. Materials and methods: This was a retrospective, single-center study including consecutive patients with OGIB subjected to SBCE, whose standard white light examination was nondiagnostic. Each SBCE was reviewed using FICE 1. New findings were labeled as either P1 or P2 lesions according to bleeding potential. Patients were followed up to assess the incidence of rebleeding. Results: A total of 42 consecutive patients were included. Sixteen patients (38%) experienced rebleeding after a mean follow-up of 26 months. Review of SBCE images using FICE 1 enabled the identification of previously unrecognized P2 lesions, mainly angioectasias, in nine patients (21%) and P1 lesions, mainly erosions, in 26 patients (62%). Among patients who experienced rebleeding, 13/16 (81%) were diagnosed with P1 lesions with FICE 1 (P=0.043), whereas 3/16 (19%) had confirmed nondiagnostic SBCE and only 1/16 (6%) had newly diagnosed P2 (plus P1) lesions. An alternative source of bleeding outside the small bowel was found in only 3/16 (19%) patients with rebleeding during the follow-up. Conclusion: In a significant proportion of patients with OGIB, FICE 1 may detect potentially bleeding lesions previously missed under conventional white light SBCE. Review of nondiagnostic SBCE with FICE 1 may be a valuable strategy to obviate the need for further investigations in patients with OGIB, particularly for those who experience rebleeding.