Generic system for human-computer gesture interaction: applications on sign language recognition and robotic soccer refereeing

Hand gestures are a powerful way for human communication, with lots of potential applications in the area of human computer interaction. Vision-based hand gesture recognition techniques have many proven advantages compared with traditional devices, giving users a simpler and more natural way to communicate with electronic devices. This work proposes a generic system architecture based in computer vision and machine learning, able to be used with any interface for human-computer interaction. The proposed solution is mainly composed of three modules: a pre-processing and hand segmentation module, a static gesture interface module and a dynamic gesture interface module. The experiments showed that the core of visionbased interaction systems could be the same for all applications and thus facilitate the implementation. For hand posture recognition, a SVM (Support Vector Machine) model was trained and used, able to achieve a final accuracy of 99.4%. For dynamic gestures, an HMM (Hidden Markov Model) model was trained for each gesture that the system could recognize with a final average accuracy of 93.7%. The proposed solution as the advantage of being generic enough with the trained models able to work in real-time, allowing its application in a wide range of human-machine applications. To validate the proposed framework two applications were implemented. The first one is a real-time system able to interpret the Portuguese Sign Language. The second one is an online system able to help a robotic soccer game referee judge a game in real time.

Generic system for human-computer gesture interaction

Hand gestures are a powerful way for human communication, with lots of potential applications in the area of human computer interaction. Vision-based hand gesture recognition techniques have many proven advantages compared with traditional devices, giving users a simpler and more natural way to communicate with electronic devices. This work proposes a generic system architecture based in computer vision and machine learning, able to be used with any interface for humancomputer interaction. The proposed solution is mainly composed of three modules: a pre-processing and hand segmentation module, a static gesture interface module and a dynamic gesture interface module. The experiments showed that the core of vision-based interaction systems can be the same for all applications and thus facilitate the implementation. In order to test the proposed solutions, three prototypes were implemented. For hand posture recognition, a SVM model was trained and used, able to achieve a final accuracy of 99.4%. For dynamic gestures, an HMM model was trained for each gesture that the system could recognize with a final average accuracy of 93.7%. The proposed solution as the advantage of being generic enough with the trained models able to work in real-time, allowing its application in a wide range of human-machine applications.

Using data mining for prediction of hospital length of stay: an application of the CRISP-DM Methodology

Hospitals are nowadays collecting vast amounts of data related with patient records. All this data hold valuable knowledge that can be used to improve hospital decision making. Data mining techniques aim precisely at the extraction of useful knowledge from raw data. This work describes an implementation of a medical data mining project approach based on the CRISP-DM methodology. Recent real-world data, from 2000 to 2013, were collected from a Portuguese hospital and related with inpatient hospitalization. The goal was to predict generic hospital Length Of Stay based on indicators that are commonly available at the hospitalization process (e.g., gender, age, episode type, medical specialty). At the data preparation stage, the data were cleaned and variables were selected and transformed, leading to 14 inputs. Next, at the modeling stage, a regression approach was adopted, where six learning methods were compared: Average Prediction, Multiple Regression, Decision Tree, Artificial Neural Network ensemble, Support Vector Machine and Random Forest. The best learning model was obtained by the Random Forest method, which presents a high quality coefficient of determination value (0.81). This model was then opened by using a sensitivity analysis procedure that revealed three influential input attributes: the hospital episode type, the physical service where the patient is hospitalized and the associated medical specialty. Such extracted knowledge confirmed that the obtained predictive model is credible and with potential value for supporting decisions of hospital managers.

Integrated management systems as complex adaptive systems

It is a difficult task to avoid the “smart systems” topic when discussing smart prevention and, similarly, it is a difficult task to address smart systems without focusing their ability to learn. Following the same line of thought, in the current reality, it seems a Herculean task (or an irreparable omission) to approach the topic of certified occupational health and safety management systems (OHSMS) without discussing the integrated management systems (IMSs). The available data suggest that seldom are the OHSMS operating as the single management system (MS) in a company so, any statement concerning OHSMS should mainly be interpreted from an integrated perspective. A major distinction between generic systems can be drawn between those that learn, i.e., those systems that have “memory” and those that have not. These former systems are often depicted as adaptive since they take into account past events to deal with novel, similar and future events modifying their structure to enable success in its environment. Often, these systems, present a nonlinear behavior and a huge uncertainty related to the forecasting of some events. This paper seeks to portray, for the first time as we were able to find out, the IMSs as complex adaptive systems (CASs) by listing their properties and dissecting the features that enable them to evolve and self-organize in order to, holistically, fulfil the requirements from different stakeholders and thus thrive by assuring the successful sustainability of a company. Based on the revision of literature carried out, this is the first time that IMSs are pointed out as CASs which may develop fruitful synergies both for the MSs and for CASs communities. By performing a thorough revision of literature and based on some concepts embedded in the “DNA” of the subsystems implementation standards it is intended, specifically, to identify, determine and discuss the properties of a generic IMS that should be considered to classify it as a CAS.

Hand gesture recognition system based in computer vision and machine learning

"Lecture notes in computational vision and biomechanics series, ISSN 2212-9391, vol. 19"

Epidemic store for massive scale systems

The MAP-i doctoral program of the Universities of Minho, Aveiro and Porto

O ensino em grupo de instrumentos musicais: um estudo de caso múltiplo em Portugal e no Brasil

Tese de Doutoramento em Estudos da Criança (área de especialização em Educação Musical)

Design de superfície biomimética para aplicação em atividades desportivas

Tese de Doutoramento Engenharia Têxtil.

Pharmaceutical regulation and pseudo - generics

Dissertação de mestrado em Economia Industrial e da Empresa

Search for new phenomena in events with three or more charged leptons in pp collisions at TeV with the ATLAS detector

A generic search for anomalous production of events with at least three charged leptons is presented. The data sample consists of pp collisions at s√=8 TeV collected in 2012 by the ATLAS experiment at the CERN Large Hadron Collider, and corresponds to an integrated luminosity of 20.3 fb−1. Events are required to have at least three selected lepton candidates, at least two of which must be electrons or muons, while the third may be a hadronically decaying tau. Selected events are categorized based on their lepton flavour content and signal regions are constructed using several kinematic variables of interest. No significant deviations from Standard Model predictions are observed. Model-independent upper limits on contributions from beyond the Standard Model phenomena are provided for each signal region, along with prescription to re-interpret the limits for any model. Constraints are also placed on models predicting doubly charged Higgs bosons and excited leptons. For doubly charged Higgs bosons decaying to eτ or μτ, lower limits on the mass are set at 400 GeV at 95% confidence level. For excited leptons, constraints are provided as functions of both the mass of the excited state and the compositeness scale Λ, with the strongest mass constraints arising in regions where the mass equals Λ. In such scenarios, lower mass limits are set at 3.0 TeV for excited electrons and muons, 2.5 TeV for excited taus, and 1.6 TeV for every excited-neutrino flavour.

Is honey able to potentiate the antioxidant and cytotoxic properties of medicinal plants consumed as infusions for hepatoprotective effects?

Due to the enormous variety of phytochemicals present in plants, their extracts have been used for centuries in the treatment of innumerous diseases, being perceived as an invaluable source of medicines for humans. Furthermore, the combination of different plants was reported as inducing an improved effect (synergism) in comparison to the additive activity of the plants present in those mixtures. Nevertheless, information regarding the effects of plant infusions added with honey is still rather scarce. Accordingly, the aim of this study was evaluating the interaction between chestnut honey, a natural product with well-reported beneficial properties, and three medicinal plants (either as single plant or as combinations of two and three plants), with regard to their antioxidant activity and hepatotoxicity. Antioxidant activity was evaluated by comparing the results from four different assays; the hepatotoxicity was assessed in two different cell lines. Results were compared by analysis of variance and linear discriminant analysis. The addition of honey to the infusions had a beneficial result in both cases, producing a synergistic effect in all samples, except beta-carotene bleaching inhibition for artichoke+milk thistle+honey preparation and also preparations with lower hepatotoxicity, except in the case of artichoke+honey. Moreover, from discriminant linear analysis output, it became obvious that the effect of honey addition overcame that resulting from using single plant or mixed plants based infusions. Also, the enhanced antioxidant activity of infusions containing honey was convoyed by a lower hepatotoxicity.

Document-based databases: estudo comparativo no âmbito das bases de dados NoSql

Dissertação de mestrado integrado em Engenharia e Gestão de Sistemas de Informação

Modelação de governo electrónico para países emergentes: O caso de São Tomé e Príncipe

Tese de Doutoramento em Tecnologias e Sistemas de Informação

Hand gesture recognition system based in computer vision and machine learning: Applications on human-machine interaction

Tese de Doutoramento em Engenharia de Eletrónica e de Computadores

O setor de distribuição farmacêutica em Portugal estrutura e estratégias

A presente investigação desenvolveu uma análise profunda do setor da distribuição farmacêutica, no período compreendido entre 2000 e 2009, procurando identificar as possíveis relações de interdependência entre o meio envolvente e as opções de estratégia das empresas que constituíram a amostra de estudo e entre as referidas opções de estratégia e as estruturas e o desempenho dessas empresas. A dinâmica do mercado do medicamento na economia nacional, com um valor de 3,2 mil milhões de euros anuais (Infarmed, 2010), apresenta um impacto significativo na esperança de vida e na qualidade de vida dos cidadãos. Segundo a OCDE, os produtos farmacêuticos são responsáveis por quase um quinto de todos os gastos com saúde, em média, nos países da OCDE. Neste contexto, a distribuição farmacêutica representa uma componente crítica. A disponibilização de medicamentos em ambulatório num curto espaço de tempo só é possível devido a uma estrutura logística com características muito específicas. A qualidade do armazenamento e do transporte dos medicamentos desde a saída dos laboratórios até à chegada às farmácias é rigorosamente monitorizada e controlada. O setor da distribuição farmacêutica assume assim uma postura elementar na cadeia do medicamento, contribuindo para a melhoria da qualidade do sistema de saúde que se tem vindo a verificar nas últimas décadas e prestando um serviço com valor para a comunidade, uma vez que se compromete a assegurar um adequado e contínuo fornecimento de medicamentos para que as necessidades dos doentes e das populações em geral sejam satisfeitas. As alterações verificadas ao longo dos últimos anos estimularam a dinâmica concorrencial entre os diferentes agentes neste mercado, bastante regulamentado e com elevado entrosamento financeiro com o Estado, o que obrigou a rápidas mudanças. Neste contexto, a sobrevivência das empresas, o seu crescimento e a sua perenidade futura têm constituído um desafio abordado de forma diversa por cada empresa.