Uma linguagem para descrição de missões em sistema-de-sistemas

Sistema-de-sistemas (System-of-Systems - SoS) é um tipo emergente de sistema computacional formado por um grupo de sistemas constituintes, que são independentes e heterogêneos e se unem para compor um sistema de larga escala visando alcançar uma missão global. Cada sistema constituinte possui seus próprios objetivos, missões individuais, e colaboram para a realização da missão do SoS, chamada missão global. Existe uma complexidade inerente no conjunto de missões que estão envolvidas em um SoS, esse deve-se principalmente à natureza independente dos sistemas constituintes, que tendem a evoluir independentemente, potencialmente mantidos por organizações distintas, além dos conflitos de interesse que podem surgir com essa evolução. Com isso, torna-se essencial prover uma linguagem bem definida para descrição e avaliação dessas missões, relacionando-as entre si e provendo um documento comum que possa ser utilizado por todas as partes envolvidas. Essa linguagem deve ser capaz de expressar as missões individuais e globais, dando suporte a todos os relacionamentos existentes entre essas missões, além de expressar informações relacionadas a realização dessas missões. O objetivo desse trabalho é apresentar e avaliar uma linguagem para descrição de missões. Visando a definição dessa linguagem, esse trabalho apresenta um mapeamento sistemático acerca dos mecanismos existentes para descrição de missões em SoS, identificando os elementos-chave que compõem a descrição de uma missão nesse contexto. A partir desse mapeamento, propõe-se um modelo conceitual para missões e uma linguagem para descrição de missões. Essa linguagem independe de documentos de arquitetura e outros tipos de modelos de software, visando possibilitar a integração da linguagem de definição de missões em diferentes modelos de desenvolvimento.

Análise da atividade cognitiva do operador de sala de controle da produção de controle da produção de petróleo on-shore: uma abordagem da ergonomia para a gestão das restrições do sistema sociotécnico

This master's thesis aims to analyze the activity of the operators in a control room of the processes of production on-shore petroleum, with a focus on sociotechnical restrictions that interfere in the decision-making process and the actions of operators and therefore, the strategies (individual and collective) to regulate and maintain the operator action required and the safety of the system, together. The activity in focus involves the supervision and control of the production of thousands of barrels of oil/day in a complex and dispersed production’s structures built in an extension of 80 km. This operational framework highlights the importance of this activity for the fulfilment of the targets local and corporate efficiency, good management of the environment, health and safety of operators. This is an exploratory research and in the field, which uses the methodology of Ergonomic Analysis of the Work, composed of observational techniques and interactional, having as locus control room of the processes of production on-shore oil of an oil company. The population of this research is formed by operators in the control room of an Brazilian oil company. The results showed that the supervisory activity and control of the superheated steam injection is an complex context, demands greater attention, concentration, calculations, comparisons, trend analysis and decision making. The activity is collectively constructed between the control room operator, field operator and the supplier of steam. The research showed that the processes of communication and collaboration between the control room , fields and support staff are the key elements of this activity. The study shows that the operators have the autonomy and the elements necessary for work; and that there is continuous investments to improve the technology used and that the operators report sleep disturbances as a result of chronic exposure to night work. The study contributed with proposals for transformation of this activity: with regard to the installation of a area reserved for food in control room, the update the screens of the supervisory current operating condition, the periodic visits by room operators in the field, standardization of production reports, development assistance and standardization of nomenclature of controlling stations steam systems, to improve the conditions of realization of the activity, improve the quality of products produced by operators and contribute to reduce the possibility of slips or shifts in the activity.

Sistema mecatrônico de tempo real para monitoramento da qualidade da água embarcado em veleiro robótico autônomo

We propose a mechatronic system for monitoring water quality in rivers, lakes, dams and sea, able to perform the acquisition, processing and presentation of data via the web in real time, in order to facilitate analysis quickly and needs by interested communities. The hardware architecture and software monitoring system has been developed so that it can be generic, that is, supporting different applications. Nevertheless, as a validation of the proposed system, we built a prototype that operates embarked on an autonomous robotic sailboat, a responsible platform for collecting the data in multiple predefined points from a ground station with a planning system navigation. This final application combines the advantages of autonomy of a robotic sailboat with the need for fast and accurate monitoring of water quality, in addition to the use of an autonomous robotic sailboat unmanned facilitate the development of other research in this area.

LCD-OpenPACS: sistema integrado de telerradiologia com auxílio ao diagnóstico de nódulos pulmonares em exames de tomografia computadorizada

Lung cancer is one of the most common types of cancer and has the highest mortality rate. Patient survival is highly correlated with early detection. Computed Tomography technology services the early detection of lung cancer tremendously by offering aminimally invasive medical diagnostic tool. However, the large amount of data per examination makes the interpretation difficult. This leads to omission of nodules by human radiologist. This thesis presents a development of a computer-aided diagnosis system (CADe) tool for the detection of lung nodules in Computed Tomography study. The system, called LCD-OpenPACS (Lung Cancer Detection - OpenPACS) should be integrated into the OpenPACS system and have all the requirements for use in the workflow of health facilities belonging to the SUS (Brazilian health system). The LCD-OpenPACS made use of image processing techniques (Region Growing and Watershed), feature extraction (Histogram of Gradient Oriented), dimensionality reduction (Principal Component Analysis) and classifier (Support Vector Machine). System was tested on 220 cases, totaling 296 pulmonary nodules, with sensitivity of 94.4% and 7.04 false positives per case. The total time for processing was approximately 10 minutes per case. The system has detected pulmonary nodules (solitary, juxtavascular, ground-glass opacity and juxtapleural) between 3 mm and 30 mm.

Análise de confiabilidade de um moto-ventilador centrífugo: aplicação no sistema de pressurização de subestação industrial para garantia da segurança operacional na indústria petroquímica

The need of the oil industry to ensure the safety of the facilities, employees and the environment, not to mention the search for maximum efficiency of its facilities, makes it seeks to achieve a high level of excellence in all stages of its production processes in order to obtain the required quality of the final product. Know the reliability of equipment and what it stands for a system is of fundamental importance for ensuring the operational safety. The reliability analysis technique has been increasingly applied in the oil industry as fault prediction tool and undesirable events that can affect business continuity. It is an applied scientific methodology that involves knowledge in engineering and statistics to meet and or analyze the performance of components, equipment and systems in order to ensure that they perform their function without fail, for a period of time and under a specific condition. The results of reliability analyzes help in making decisions about the best maintenance strategy of petrochemical plants. Reliability analysis was applied on equipment (bike-centrifugal fan) between the period 2010-2014 at the Polo Petrobras Guamaré Industrial, situated in rural Guamaré municipality in the state of Rio Grande do Norte, where he collected data field, analyzed historical equipment and observing the behavior of faults and their impacts. The data were processed in commercial software reliability ReliaSoft BlockSim 9. The results were compared with a study conducted by the experts in the field in order to get the best maintenance strategy for the studied system. With the results obtained from the reliability analysis tools was possible to determine the availability of the centrifugal motor-fan and what will be its impact on the security of process units if it will fail. A new maintenance strategy was established to improve the reliability, availability, maintainability and decreased likelihood of Moto-Centrifugal Fan failures, it is a series of actions to promote the increased system reliability and consequent increase in cycle life of the asset. Thus, this strategy sets out preventive measures to reduce the probability of failure and mitigating aimed at minimizing the consequences.

Classificador máquina de suporte vetorial com análise de Fourier aplicada em dados de EEG e EMG

The classifier support vector machine is used in several problems in various areas of knowledge. Basically the method used in this classier is to end the hyperplane that maximizes the distance between the groups, to increase the generalization of the classifier. In this work, we treated some problems of binary classification of data obtained by electroencephalography (EEG) and electromyography (EMG) using Support Vector Machine with some complementary techniques, such as: Principal Component Analysis to identify the active regions of the brain, the periodogram method which is obtained by Fourier analysis to help discriminate between groups and Simple Moving Average to eliminate some of the existing noise in the data. It was developed two functions in the software R, for the realization of training tasks and classification. Also, it was proposed two weights systems and a summarized measure to help on deciding in classification of groups. The application of these techniques, weights and the summarized measure in the classier, showed quite satisfactory results, where the best results were an average rate of 95.31% to visual stimuli data, 100% of correct classification for epilepsy data and rates of 91.22% and 96.89% to object motion data for two subjects.

Sistema inteligente para o processamento de imagens digitais intrabucais oclusais

Several are the areas in which digital images are used in solving day-to-day problems. In medicine the use of computer systems have improved the diagnosis and medical interpretations. In dentistry it’s not different, increasingly procedures assisted by computers have support dentists in their tasks. Set in this context, an area of dentistry known as public oral health is responsible for diagnosis and oral health treatment of a population. To this end, oral visual inspections are held in order to obtain oral health status information of a given population. From this collection of information, also known as epidemiological survey, the dentist can plan and evaluate taken actions for the different problems identified. This procedure has limiting factors, such as a limited number of qualified professionals to perform these tasks, different diagnoses interpretations among other factors. Given this context came the ideia of using intelligent systems techniques in supporting carrying out these tasks. Thus, it was proposed in this paper the development of an intelligent system able to segment, count and classify teeth from occlusal intraoral digital photographic images. The proposed system makes combined use of machine learning techniques and digital image processing. We first carried out a color-based segmentation on regions of interest, teeth and non teeth, in the images through the use of Support Vector Machine. After identifying these regions were used techniques based on morphological operators such as erosion and transformed watershed for counting and detecting the boundaries of the teeth, respectively. With the border detection of teeth was possible to calculate the Fourier descriptors for their shape and the position descriptors. Then the teeth were classified according to their types through the use of the SVM from the method one-against-all used in multiclass problem. The multiclass classification problem has been approached in two different ways. In the first approach we have considered three class types: molar, premolar and non teeth, while the second approach were considered five class types: molar, premolar, canine, incisor and non teeth. The system presented a satisfactory performance in the segmenting, counting and classification of teeth present in the images.

Sistema inteligente para o processamento de imagens digitais intrabucais oclusais

Several are the areas in which digital images are used in solving day-to-day problems. In medicine the use of computer systems have improved the diagnosis and medical interpretations. In dentistry it’s not different, increasingly procedures assisted by computers have support dentists in their tasks. Set in this context, an area of dentistry known as public oral health is responsible for diagnosis and oral health treatment of a population. To this end, oral visual inspections are held in order to obtain oral health status information of a given population. From this collection of information, also known as epidemiological survey, the dentist can plan and evaluate taken actions for the different problems identified. This procedure has limiting factors, such as a limited number of qualified professionals to perform these tasks, different diagnoses interpretations among other factors. Given this context came the ideia of using intelligent systems techniques in supporting carrying out these tasks. Thus, it was proposed in this paper the development of an intelligent system able to segment, count and classify teeth from occlusal intraoral digital photographic images. The proposed system makes combined use of machine learning techniques and digital image processing. We first carried out a color-based segmentation on regions of interest, teeth and non teeth, in the images through the use of Support Vector Machine. After identifying these regions were used techniques based on morphological operators such as erosion and transformed watershed for counting and detecting the boundaries of the teeth, respectively. With the border detection of teeth was possible to calculate the Fourier descriptors for their shape and the position descriptors. Then the teeth were classified according to their types through the use of the SVM from the method one-against-all used in multiclass problem. The multiclass classification problem has been approached in two different ways. In the first approach we have considered three class types: molar, premolar and non teeth, while the second approach were considered five class types: molar, premolar, canine, incisor and non teeth. The system presented a satisfactory performance in the segmenting, counting and classification of teeth present in the images.

Projeto CLIK2GET - sistema agregador de tecnologias que facilitem a integração de aplicativos gamificados

Relatório de estágio para obtenção de grau de mestre na área de Educação e Comunicação Multimédia

Classificação de atividade eletromiográfia facial de indivíduos saudáveis e com hanseníese por meio de máquina de vetores de suporte

A number of studies in the areas of Biomedical Engineering and Health Sciences have employed machine learning tools to develop methods capable of identifying patterns in different sets of data. Despite its extinction in many countries of the developed world, Hansen’s disease is still a disease that affects a huge part of the population in countries such as India and Brazil. In this context, this research proposes to develop a method that makes it possible to understand in the future how Hansen’s disease affects facial muscles. By using surface electromyography, a system was adapted so as to capture the signals from the largest possible number of facial muscles. We have first looked upon the literature to learn about the way researchers around the globe have been working with diseases that affect the peripheral neural system and how electromyography has acted to contribute to the understanding of these diseases. From these data, a protocol was proposed to collect facial surface electromyographic (sEMG) signals so that these signals presented a high signal to noise ratio. After collecting the signals, we looked for a method that would enable the visualization of this information in a way to make it possible to guarantee that the method used presented satisfactory results. After identifying the method's efficiency, we tried to understand which information could be extracted from the electromyographic signal representing the collected data. Once studies demonstrating which information could contribute to a better understanding of this pathology were not to be found in literature, parameters of amplitude, frequency and entropy were extracted from the signal and a feature selection was made in order to look for the features that better distinguish a healthy individual from a pathological one. After, we tried to identify the classifier that best discriminates distinct individuals from different groups, and also the set of parameters of this classifier that would bring the best outcome. It was identified that the protocol proposed in this study and the adaptation with disposable electrodes available in market proved their effectiveness and capability of being used in different studies whose intention is to collect data from facial electromyography. The feature selection algorithm also showed that not all of the features extracted from the signal are significant for data classification, with some more relevant than others. The classifier Support Vector Machine (SVM) proved itself efficient when the adequate Kernel function was used with the muscle from which information was to be extracted. Each investigated muscle presented different results when the classifier used linear, radial and polynomial kernel functions. Even though we have focused on Hansen’s disease, the method applied here can be used to study facial electromyography in other pathologies.

Classificação de atividade eletromiográfia facial de indivíduos saudáveis e com hanseníase por meio de máquina de vetores de suporte

A number of studies in the areas of Biomedical Engineering and Health Sciences have employed machine learning tools to develop methods capable of identifying patterns in different sets of data. Despite its extinction in many countries of the developed world, Hansen’s disease is still a disease that affects a huge part of the population in countries such as India and Brazil. In this context, this research proposes to develop a method that makes it possible to understand in the future how Hansen’s disease affects facial muscles. By using surface electromyography, a system was adapted so as to capture the signals from the largest possible number of facial muscles. We have first looked upon the literature to learn about the way researchers around the globe have been working with diseases that affect the peripheral neural system and how electromyography has acted to contribute to the understanding of these diseases. From these data, a protocol was proposed to collect facial surface electromyographic (sEMG) signals so that these signals presented a high signal to noise ratio. After collecting the signals, we looked for a method that would enable the visualization of this information in a way to make it possible to guarantee that the method used presented satisfactory results. After identifying the method's efficiency, we tried to understand which information could be extracted from the electromyographic signal representing the collected data. Once studies demonstrating which information could contribute to a better understanding of this pathology were not to be found in literature, parameters of amplitude, frequency and entropy were extracted from the signal and a feature selection was made in order to look for the features that better distinguish a healthy individual from a pathological one. After, we tried to identify the classifier that best discriminates distinct individuals from different groups, and also the set of parameters of this classifier that would bring the best outcome. It was identified that the protocol proposed in this study and the adaptation with disposable electrodes available in market proved their effectiveness and capability of being used in different studies whose intention is to collect data from facial electromyography. The feature selection algorithm also showed that not all of the features extracted from the signal are significant for data classification, with some more relevant than others. The classifier Support Vector Machine (SVM) proved itself efficient when the adequate Kernel function was used with the muscle from which information was to be extracted. Each investigated muscle presented different results when the classifier used linear, radial and polynomial kernel functions. Even though we have focused on Hansen’s disease, the method applied here can be used to study facial electromyography in other pathologies.

Recomendações para o desenvolvimento de uma ferramenta de suporte às primeiras decisões projetuais visando ao desempenho energético de edificações de escritório em clima quente

PEDRINI, Aldomar; SZOKOLAY, Steven. Recomendações para o desenvolvimento de uma ferramenta de suporte às primeiras decisões projetuais visando ao desempenho energético de edificações de escritório em clima quente. Ambiente Construído, Porto Alegre, v. 5, n. 1, p.39-54, jan./mar. 2005. Trimestral. Disponível em: . Acesso em: 04 out. 2010.

Complicações do Alcoolismo na Família: Intervenções de Enfermagem

Desde há muito, o alcoolismo tem sido um tema em voga. No entanto, não deixa de ser um tema atual, objeto de preocupação e discussão de profissionais de diversas áreas do saber. Não obstante as respostas e os contributos que os profissionais trazem à mesa e que muito contribuem para a compreensão do fenómeno “alcoolismo” enquanto problema de Saúde Pública, sabe-se bem que um pouco por todo lado, e Cabo Verde não foge a regra, tem havido um aumento do consumo de álcool e os efeitos nefastos que este acarreta são cada vez mais frequentes e assustadores. Essa problemática é, na sua maioria, abordada sob o ponto de vista do alcoólico, e muito pouco abordada sob a perspetiva da família que tem no seu seio um elemento identificado como alcoólico. Assim com o objetivo de identificar as intervenções de Enfermagem perante as complicações do alcoolismo na família, foi realizado um estudo de caso abordado de forma qualitativa com uma família que tem no seu seio um elemento identificado alcoólico. Os dados foram recolhidas através da observação não estruturada, entrevistas semiestruturadas e questionários. Os resultados demonstram que as complicações do alcoolismo na família giram em torno de perturbações na harmonia e no equilíbrio familiar, violência verbal, problemas financeiros, conflitos interpessoais e sofrimento. Tais complicações demandam intervenção de uma equipa multidisciplinar onde a enfermagem tem um papel proactivo no ensino: processo de doença, no aumento da disponibilidade de aprendizagem, na redução da ansiedade, aumento do sistema de apoio e da autoestima, assistência de autocuidado, motivação do comportamento, facilitação de auto responsabilidade, apoio a tomada de decisão, promoção do envolvimento familiar, suporte a família, apoio ao cuidador, entre outras. As intervenções de enfermagem versadas neste trabalho figuram como ferramentas necessárias no cuidado ao alcoólico e sua família com vista a melhorar a qualidade de vida dos mesmos.

A tomada de decisão nas instituições particulares de solidariedade social

Introdução e objetivo: Atualmente as Instituições Particulares de Solidariedade Social deparam-se com mudanças de caracter social, económico e legislativo, que têm afetado o seu funcionamento e financiamento. Pelo que, impõe-se às suas direções responder às necessidades sociais com maior responsabilidade e eficiência num contexto de maior escassez de recursos. Neste sentido, o presente estudo tem como objetivo compreender o modo como as Instituições Particulares de Solidariedade Social tomam decisões, ao nível do financiamento, para um funcionamento eficiente das mesmas. Metodologia: Optou-se por realizar estudos de caso com uma amostra constituída por quatro Instituições Particulares de Solidariedade Social. A recolha de dados foi feita através de entrevistas semiestruturadas e análise documental. O tratamento de dados foi feito através de análise de conteúdo e com recurso ao software QRS Nvivo versão 10. Resultados: Os principais resultados indicam que: a) as necessidades sociais influenciam decisões de aumento e diminuição da capacidade de respostas das instituições; b) o sistema legal influencia a perpetuação de intervenções de caracter institucional; c) a conjuntura económica influencia a pressão sobre o preço da comparticipação familiar e o aumento da concorrência entre instituições; d) a escassez de recursos constitui-se como denominador comum entre instituições, influenciando decisões de investimento que assumem o financiamento público como um facto consumado; e) as práticas de liderança e gestão desenvolvidas por direções com elementos que têm conhecimentos na área financeira são mais propensas a assumir o risco e a aumentar a complexidade operativa das instituições f) as práticas de envolvimento de stakeholders internos e externos contribuem para a aquisição de apoio na prossecução dos seus objetivos. Conclusão: As tomadas de decisão das instituições com acordos com a segurança social assemelham-se por prevalecer o desenvolvimento de respostas tipificadas, com acordo com a segurança social. Apesar disso, os resultados evidenciam a importância de práticas de liderança e gestão desenvolvidas com a presença de elementos com conhecimentos na área financeira, para o desenvolvimento de respostas tipificadas com rentabilidade económica. Salienta-se ainda que o desenvolvimento de práticas de envolvimento de stakeholders internos e externos, baseados na responsabilização e transparência, promovem o alcance de apoios para assegurar o desenvolvimento das atividades institucionais, com maior incidência na instituição sem acordos com a segurança social, mas que os mesmos não asseguram a sua eficiência económica.

Sistema de predição de alarmes em processos industriais por classificação não-supervisionada

Um sistema de predição de alarmes com a finalidade de auxiliar a implantação de uma política de manutenção preditiva industrial e de constituir-se em uma ferramenta gerencial de apoio à tomada de decisão é proposto neste trabalho. O sistema adquire leituras de diversos sensores instalados na planta, extrai suas características e avalia a saúde do equipamento. O diagnóstico e prognóstico implica a classificação das condições de operação da planta. Técnicas de árvores de regressão e classificação não-supervisionada são utilizadas neste artigo. Uma amostra das medições de 73 variáveis feitas por sensores instalados em uma usina hidrelétrica foi utilizada para testar e validar a proposta. As medições foram amostradas em um período de 15 meses.