Emoções, inteligência emocial e parentalidade : a avaliação da promoção de competências sócio-emocionais em pais

Dissertação de Mestrado, Psicologia da Educação, especialidade de Contextos Comunitários, 5 de Outubro de 2015, Universidade dos Açores.

Programa de promoção da inteligência emocional na ansiedade infantil

Trabalho apresentado em XIII Congreso Internacional Galego-Portugués de Psicopedagoxía, Área 5 Familia, Escuela y Comunidad. Universidad da Coruña, 2 de Setembro de 2015.

Programa de promoção da inteligência emocional na ansiedade infantil

Trabalho apresentado em XIII Congreso Internacional Galego-Portugués de Psicopedagoxía, Área 5 Familia, Escuela y Comunidad. Universidad da Coruña, 2 de Setembro de 2015.

Mixed integer non linear programming and artificial neural network based approach to ancillary services dispatch in competitive electricity markets

Ancillary services represent a good business opportunity that must be considered by market players. This paper presents a new methodology for ancillary services market dispatch. The method considers the bids submitted to the market and includes a market clearing mechanism based on deterministic optimization. An Artificial Neural Network is used for day-ahead prediction of Regulation Down, regulation-up, Spin Reserve and Non-Spin Reserve requirements. Two test cases based on California Independent System Operator data concerning dispatch of Regulation Down, Regulation Up, Spin Reserve and Non-Spin Reserve services are included in this paper to illustrate the application of the proposed method: (1) dispatch considering simple bids; (2) dispatch considering complex bids.

Environmental Decision Support: a Distributed Artificial Intelligence Approach

Decision making in any environmental domain is a complex and demanding activity, justifying the development of dedicated decision support systems. Every decision is confronted with a large variety and amount of constraints to satisfy as well as contradictory interests that must be sensibly accommodated. The first stage of a project evaluation is its submission to the relevant group of public (and private) agencies. The individual role of each agency is to verify, within its domain of competence, the fulfilment of the set of applicable regulations. The scope of the involved agencies is wide and ranges from evaluation abilities on the technical or economical domains to evaluation competences on the environmental or social areas. The second project evaluation stage involves the gathering of the recommendations of the individual agencies and their justified merge to produce the final conclusion. The incorporation and accommodation of the consulted agencies opinions is of extreme importance: opinions may not only differ, but can be interdependent, complementary, irreconcilable or, simply, independent. The definition of adequate methodologies to sensibly merge, whenever possible, the existing perspectives while preserving the overall legality of the system, will lead to the making of sound justified decisions. The proposed Environmental Decision Support System models the project evaluation activity and aims to assist developers in the selection of adequate locations for their projects, guaranteeing their compliance with the applicable regulations.

Multiple Linear Regression and Artificial Neural Networks to Predict Time and Efficiency of Soil Vapor Extraction

The prediction of the time and the efficiency of the remediation of contaminated soils using soil vapor extraction remain a difficult challenge to the scientific community and consultants. This work reports the development of multiple linear regression and artificial neural network models to predict the remediation time and efficiency of soil vapor extractions performed in soils contaminated separately with benzene, toluene, ethylbenzene, xylene, trichloroethylene, and perchloroethylene. The results demonstrated that the artificial neural network approach presents better performances when compared with multiple linear regression models. The artificial neural network model allowed an accurate prediction of remediation time and efficiency based on only soil and pollutants characteristics, and consequently allowing a simple and quick previous evaluation of the process viability.

Solar Intensity Forecasting using Artificial Neural Networks and Support Vector Machines

This paper presents several forecasting methodologies based on the application of Artificial Neural Networks (ANN) and Support Vector Machines (SVM), directed to the prediction of the solar radiance intensity. The methodologies differ from each other by using different information in the training of the methods, i.e, different environmental complementary fields such as the wind speed, temperature, and humidity. Additionally, different ways of considering the data series information have been considered. Sensitivity testing has been performed on all methodologies in order to achieve the best parameterizations for the proposed approaches. Results show that the SVM approach using the exponential Radial Basis Function (eRBF) is capable of achieving the best forecasting results, and in half execution time of the ANN based approaches.

A inteligência emocional na formação em gestão da saúde : estudo de caso e proposta de modelo de avaliação

RESUMO - Introdução: A Inteligência Emocional (IE) é considerada um factor preditivo de sucesso, mais significativo do que outros tipos de inteligência e o seu estudo tem recebido cada vez maior relevância com o objectivo de aumentar os níveis de desempenho em gestão (Goleman, 2009). O desenvolvimento da IE no âmbito da formação em gestão apresenta resultados contraditórios sendo necessário confirmar o potencial de desenvolvimento da IE em programas de formação específicos. Objectivos: Confirmar a importância da IE para a gestão da saúde e perceber o seu potencial de desenvolvimento em programas de formação específicos; analisar o módulo opcional de Emoção, Liderança e Coaching na Gestão em Saúde; e construir uma proposta de modelo que avalie se a participação nessa Unidade Curricular permite aumentar os níveis de IE. Metodologia: Realizou-se uma revisão da literatura, que permitiu ter acesso aos conceitos e teorias e, posteriormente, o estudo de caso do módulo opcional que permitiu compará-lo com outras teorias existentes. Finalmente, construiu-se uma proposta de modelo de avaliação da IE, com um desenho quasi-experimental. Conclusões: A IE é um factor essencial para o sucesso, principalmente na Gestão da Saúde, pelas características do mercado e das organizações. Os instrumentos de avaliação da IE com recurso à medição de competências são os que apresentam menos limitações. O peso do módulo opcional no Curso de Mestrado em Gestão da Saúde, é pouco significativo (3,33% dos ECTS) e apenas 36,6% dos alunos o frequentaram. A estrutura do módulo está alinhada com as directrizes de outras teorias, mas a sua curta duração poderá constituir uma limitação. Sugere-se a criação de apoio tutorial individualizado e prolongado. O modelo de avaliação proposto representa a primeira tentativa de avaliação do desenvolvimento da IE na formação em Gestão da Saúde em Portugal e a sua aplicação permitiria a o aprimoramento do potencial de desenvolvimento das competências dos gestores. ---------------------------------- ABSTRACT - Introduction: Emotional Intelligence (EI) is the most predictive factor of success when compared with other types of intelligence. Since it is believed to increase performance levels, EI study has been given more relevance (Goleman, 2009). EI development studies show contradictory results, becoming necessary to prove the benefits of the development programs. Purposes: This study aimed to confirm the importance of the EI in health care management; to perceive the EI development potential of specific programs; to analyze the optional curricular unit of Emotion, Coaching and Leadership in Health Management; and to build a model that proposes to evaluate the student’s EI development. Methods: After the Literature Revision, the Case Study of the Curricular Unit allowed to compare it with other existing theories. The Model of EI evaluation consists on a quasi-experimental study. Conclusions: EI is an essential factor for success, mainly in Health Care Management, because of its market and organizations characteristics. The ability instruments of EI evaluation are those which show the least limitations. The Curricular Unit represents only 3,33% of the ECTS provided by this Health Management Master. Only 36.6% of master’s students chose to participate in this curricular unit. The structure of the curricular unit is lined up with the guide-lines of other theories. However, being a 6 weeks program, it could represent a limitation. It is suggested to create an individual and longitudinal tutorial support. The EI evaluation model proposed represents the first attempt to evaluate de EI development in Health Management programs in Portugal. Its application could increase the manager’s development efficacy.

Artificial Intelligence in geospatial analysis: applications of self-organizing maps in the context of geographic information science.

A thesis submitted in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Information Systems.

Trypanosoma cruzi parasitemia observed in immunocompromised patients: the importance of the artificial xenodiagnosis

Trypanosoma cruzi parasitemia observed in immunocompromised patients (transplant or positive HIV) occurred more frequently by the artificial xenodiagnosis method (10/38) compared with hemoculture (2/38), given the same quantity of blood. Other ways of diagnosis, like mice inoculation (5/38), QBC and buffy coat (2/38), were evaluated also. This result showed the importance of the artificial xenodiagnosis. The other techniques increased only one more patient positive.

Artificial antibodies for troponin T by its imprinting on the surface of multiwalled carbon nanotubes: Its use as sensory surfaces

A novel artificial antibody for troponin T (TnT) was synthesized by molecular imprint (MI) on the surface of multiwalled carbon nanotubes (MWCNT). This was done by attaching TnT to the MWCNT surface, and filling the vacant spaces by polymerizing under mild conditions acrylamide (monomer) in N,N′-methylenebisacrylamide (cross-linker) and ammonium persulphate (initiator). After removing the template, the obtained biomaterial was able to rebind TnT and discriminate it among other interfering species. Stereochemical recognition of TnT was confirmed by the non-rebinding ability displayed by non-imprinted (NI) materials, obtained by imprinting without a template. SEM and FTIR analysis confirmed the surface modification of the MWCNT. The ability of this biomaterial to rebind TnT was confirmed by including it as electroactive compound in a PVC/plasticizer mixture coating a wire of silver, gold or titanium. Anionic slopes of 50 mV decade−1 were obtained for the gold wire coated with MI-based membranes dipped in HEPES buffer of pH 7. The limit of detection was 0.16 μg mL−1. Neither the NI-MWCNT nor the MWCNT showed the ability to recognize the template. Good selectivity was observed against creatinine, sucrose, fructose, myoglobin, sodium glutamate, thiamine and urea. The sensor was tested successfully on serum samples. It is expected that this work opens new horizons on the design of new artificial antibodies for complex protein structures.

Biomimetic Sensor Potentiometric System for Doxycycline Antibiotic Using a Molecularly Imprinted Polymer as an Artificial Recognition Element

Molecular imprinting is a useful technique for the preparation of functional materials with molecular recognition properties. A Biomimetic Sensor Potentiometric System was developed for assessment of doxycycline (DOX) antibiotic. The molecularly imprinted polymer (MIP) was synthesized by using doxycycline as a template molecule, methacrylic acid (MAA) and/or acrylamide (AA) as a functional monomer and ethylene glycol dimethacrylat (EGDMA) as a cross-linking agent. The sensing elements were fabricated by the inclusion of DOX imprinted polymers in polyvinyl chloride (PVC) matrix. The sensors showed a high selectivity and a sensitive response to the template in aqueous system. Electrochemical evaluation of these sensors under static (batch) mode of operation reveals near-Nernstian response. MIP/MAA membrane sensor was incorporated in flow-through cells and used as detectors for flow injection analysis (FIA) of DOX. The method has the requisite accuracy, sensitivity and precision to assay DOX in tablets and biological fluids.

BoaVista – Sensor Dedicado de Visão Artificial Baseado em Hardware (Re)configurável

4º Festival Nacional de Robótica - Actas do Encontro Científico - Proceedings of the Scientific Meeting, Biblioteca Almeida Garrett, Palácio de Cristal – Porto, 23-24 Abril 2004