878 resultados para cancer detection and diagnosis


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The industries are getting more and more rigorous, when security is in question, no matter is to avoid financial damages due to accidents and low productivity, or when it s related to the environment protection. It was thinking about great world accidents around the world involving aircrafts and industrial process (nuclear, petrochemical and so on) that we decided to invest in systems that could detect fault and diagnosis (FDD) them. The FDD systems can avoid eventual fault helping man on the maintenance and exchange of defective equipments. Nowadays, the issues that involve detection, isolation, diagnose and the controlling of tolerance fault are gathering strength in the academic and industrial environment. It is based on this fact, in this work, we discuss the importance of techniques that can assist in the development of systems for Fault Detection and Diagnosis (FDD) and propose a hybrid method for FDD in dynamic systems. We present a brief history to contextualize the techniques used in working environments. The detection of fault in the proposed system is based on state observers in conjunction with other statistical techniques. The principal idea is to use the observer himself, in addition to serving as an analytical redundancy, in allowing the creation of a residue. This residue is used in FDD. A signature database assists in the identification of system faults, which based on the signatures derived from trend analysis of the residue signal and its difference, performs the classification of the faults based purely on a decision tree. This FDD system is tested and validated in two plants: a simulated plant with coupled tanks and didactic plant with industrial instrumentation. All collected results of those tests will be discussed

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Induction motors are one of the most important equipment of modern industry. However, in many situations, are subject to inadequate conditions as high temperatures and pressures, load variations and constant vibrations, for example. Such conditions, leaving them more susceptible to failures, either external or internal in nature, unwanted in the industrial process. In this context, predictive maintenance plays an important role, where the detection and diagnosis of faults in a timely manner enables the increase of time of the engine and the possibiity of reducing costs, caused mainly by stopping the production and corrective maintenance the motor itself. In this juncture, this work proposes the design of a system that is able to detect and diagnose faults in induction motors, from the collection of electrical line voltage and current, and also the measurement of engine speed. This information will use as input to a fuzzy inference system based on rules that find and classify a failure from the variation of thess quantities

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Esta dissertação apresenta uma técnica para detecção e diagnósticos de faltas incipientes. Tais faltas provocam mudanças no comportamento do sistema sob investigação, o que se reflete em alterações nos valores dos parâmetros do seu modelo matemático representativo. Como plataforma de testes, foi elaborado um modelo de um sistema industrial em ambiente computacional Matlab/Simulink, o qual consiste em uma planta dinâmica composta de dois tanques comunicantes entre si. A modelagem dessa planta foi realizada através das equações físicas que descrevem a dinâmica do sistema. A falta, a que o sistema foi submetido, representa um estrangulamento gradual na tubulação de saída de um dos tanques. Esse estrangulamento provoca uma redução lenta, de até 20 %, na seção desse tubo. A técnica de detecção de falta foi realizada através da estimação em tempo real dos parâmetros de modelos Auto-regressivos com Entradas Exógenas (ARX) com estimadores Fuzzy e de Mínimos Quadrados Recursivos. Já, o diagnóstico do percentual de entupimento da tubulação foi obtido por um sistema fuzzy de rastreamento de parâmetro, realimentado pela integral do resíduo de detecção. Ao utilizar essa metodologia, foi possível detectar e diagnosticar a falta simulada em três pontos de operação diferentes do sistema. Em ambas as técnicas testadas, o método de MQR teve um bom desempenho, apenas para detectar a falta. Já, o método que utilizou estimação com supervisão fuzzy obteve melhor desempenho, em detectar e diagnosticar as faltas aplicadas ao sistema, constatando a proposta do trabalho.

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Desde a incorporação da automação no processo produtivo, a busca por sistemas mais eficientes, objetivando o aumento da produtividade e da qualidade dos produtos e serviços, direcionou os estudos para o planejamento de estratégias que permitissem o monitoramento de sistemas com o intuito principal de torna-los mais autônomos e robustos. Por esse motivo, as pesquisas envolvendo o diagnóstico de faltas em sistemas industriais tornaram-se mais intensivas, visto a necessidade da incorporação de técnicas para monitoramente detalhado de sistemas. Tais técnicas permitem a verificação de perturbações, falta ou mesmo falhas. Em vista disso, essa trabalho investiga técnicas de detecção e diagnostico de faltas e sua aplicação em motores de indução trifásicos, delimitando o seu estudo em duas situações: sistemas livre de faltas, e sobre atuação da falta incipiente do tipo curto-circuitoparcial nas espiras do enrolamento do estator. Para a detecção de faltas, utilizou-se analise paramétrica dos parâmetros de um modelo de tempo discreto, de primeira ordem, na estrutura autoregressivo com entradas exógenas (ARX). Os parâmetros do modelo ARX, que trazem informação sobre a dinâmica dominante do sistema, são obtidos recursivamente pela técnica dos mínimos quadrados recursivos (MQR). Para avaliação da falta, foi desenvolvido um sistema de inferência fuzzy (SIF) intervala do tipo-2, cuja mancha de incerteza ou footprint of uncertainty (FOU), características de sistema fuzzy tipo-2, é ideal como forma de representar ruídos inerentes a sistemas reais e erros numéricos provenientes do processo de estimação paramétrica. Os parâmetros do modelo ARX são entradas para o SIF. Algoritmos genéricos (AG’s) foram utilizados para otimização dos SIF intervalares tipo-2, objetivando reduzir o erro de diagnóstico da falta identificada na saída desses sistemas. Os resultados obtidos em teste de simulação computacional demonstram a efetividade da metodologia proposta.

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The best way to detect breast cancer is by screening mammography. The mammography equipments are dedicated and require a rigorous quality control in order to have a good quality image and to early detect this disease. The digital equipment is relatively new in the market and there isn’t a national rule for quality control for several types of digital detectors. This study has proposed to compare two different tests manuals for quality control provided by the manufacturers of digital mammography equipments, and also compare them to the “European guidelines for quality assurance in breast cancer screening and diagnosis “(2006). The studied equipments were: Senographe 2000D from General Electric (GE) and the Hologic Selenia Lorad. Both were digital mammography equipments, the GE unit presents an indirect digital system and the other presents a direct digital system. Physical parameters of the image have been studied, such as spatial resolution, contrast resolution, noise, signal-tonoise ratio, contrast-to-noise ratio and modulation transfer function. After that, a study of the importance of quality control and the requirement to implement a Quality Assurance Program has been done. One data collection was done to compare those manual, it was done by checking which tests are indicated and the minimum frequency which they should be conducted in accordance with each manufacturer. The tests were performed by different methodologies and the results were compared. The examined tests were: the breast entrance skin dose, mean glandular dose, contrast-to-noise ratio, signal-to-noise ratio, automatic exposure control and automatic control of density, modulation transfer function, equipment resolution, homogeneity and ghost

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This paper presents a multi-agent architecture that was designed to develop processes supervision and control systems, with the main objective to automate tasks that are repetitive and stressful, and error prone when performed by humans. A set of agents were identified, based on the study of a number of applications found in the literature, that use the approach of multi-agent systems for data integration and process monitoring to faults detection and diagnosis, these agents are used as basis of the proposed multi-agent architecture. A prototype system for the analysis of abnormalities during oil wells drilling was developed.

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Il cancro batterico dell’actinidia causato da Pseudomonas syringae pv.actinidiae (Psa) suscita grande interesse a livello globale a partire dal 2008. La malattia è comparsa in Giappone e in due anni ha avuto una diffusione epidemica in tutte le aree di coltivazione mondiale di actinidia. Gravi perdite economiche hanno attirato l’attenzione internazionale su questa problematica e grandi sforzi sono stati rivolti allo studio di questo patosistema ancora poco conosciuto. E’ emerso infatti che il patogeno può rimanere in fase latente per lunghi periodi senza causare sintomi caratteristici nelle piante infette, e che dalla comparsa dei sintomi la pianta muore nell’arco di un paio d’anni. Il monitoraggio ed il controllo della situazione è perciò di fondamentale importanza ed è ancora più importante prevenire la comparsa di nuovi focolai di infezione. A questo proposito sarebbe opportuno l’impiego di materiale vegetale di propagazione non infetto, ma in molti casi questo diventa difficile, dal momento che il materiale impiegato è generalmente quello asintomatico, non analizzato precedentemente per la presenza del patogeno. Negli ultimi anni sono state perciò messe a punto molte tecniche molecolari per l’identificazione di Psa direttamente da materiale vegetale. L’obiettivo di questo lavoro è stato quello di studiare l’epidemiologia di Psa in piante adulte infette e di verificare l’efficacia di metodi di diagnosi precoce per prevenire la malattia. A tale scopo il lavoro sperimentale è stato suddiviso in diverse fasi: i) studio della localizzazione, traslocazione e sopravvivenza di Psa nelle piante, a seguito di inoculazione in piante adulte di actinidia di ceppi marcati Psa::gfp; ii) studio della capacità di Psa di essere mantenuto in germogli di actinidia attraverso sette generazioni di micropropagazione dopo l’inoculazione delle piante madri con lo stesso ceppo marcato Psa::gfp; iii) studio ed applicazioni di un nuovo metodo di diagnosi precoce di Psa basato sull’analisi molecolare del “pianto”.

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OBJECTIVES: To assess the use and appropriateness of medical advice for smoking cessation provided by registrars in a General Medicine Outpatient Department to an unselected patient population in Switzerland. METHODS: A prospective observational study in which 314 consecutive outpatients were contacted by phone within 24h after their consultation. Questions and information concerning smoking asked and/or provided by the registrar to patients were collected. RESULTS: Eleven registrars (mean age 34 years (range 29-40), 54% females, mean of 5 years (range 3.5-6 years) postgraduate medical training) worked in the Basel University Hospital Medical Outpatient Department during the study period from 01.01.2006 to 31.03.2006. In total 314 participants (mean 48 years, age range 16-71 years, 50% females) completed the study. Registrars queried 81% of the patients about smoking, but inquired about smoking duration only in 44% of the patients. Twenty-eight percent of the patients received information about the risks related to smoking, whereas cessation was discussed only with 10% and offered to 9% of the patients. CONCLUSION: Though most junior physicians in the survey asked about smoking, they failed to appropriately address tobacco-related health issues and offer cessation advice in the majority of cases. Extended regular training for physicians on smoking-related issues will be necessary in order to improve counselling of smokers and meet the global tobacco challenge.

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Esta tesis doctoral presenta un procedimiento integral de control de calidad en centrales fotovoltaicas, que comprende desde la fase inicial de estimación de las expectativas de producción hasta la vigilancia del funcionamiento de la instalación una vez en operación, y que permite reducir la incertidumbre asociada su comportamiento y aumentar su fiabilidad a largo plazo, optimizando su funcionamiento. La coyuntura de la tecnología fotovoltaica ha evolucionado enormemente en los últimos años, haciendo que las centrales fotovoltaicas sean capaces de producir energía a unos precios totalmente competitivos en relación con otras fuentes de energía. Esto hace que aumente la exigencia sobre el funcionamiento y la fiabilidad de estas instalaciones. Para cumplir con dicha exigencia, es necesaria la adecuación de los procedimientos de control de calidad aplicados, así como el desarrollo de nuevos métodos que deriven en un conocimiento más completo del estado de las centrales, y que permitan mantener la vigilancia sobre las mismas a lo largo del tiempo. Además, los ajustados márgenes de explotación actuales requieren que durante la fase de diseño se disponga de métodos de estimación de la producción que comporten la menor incertidumbre posible. La propuesta de control de calidad presentada en este trabajo parte de protocolos anteriores orientados a la fase de puesta en marcha de una instalación fotovoltaica, y las complementa con métodos aplicables a la fase de operación, prestando especial atención a los principales problemas que aparecen en las centrales a lo largo de su vida útil (puntos calientes, impacto de la suciedad, envejecimiento…). Además, incorpora un protocolo de vigilancia y análisis del funcionamiento de las instalaciones a partir de sus datos de monitorización, que incluye desde la comprobación de la validez de los propios datos registrados hasta la detección y el diagnóstico de fallos, y que permite un conocimiento automatizado y detallado de las plantas. Dicho procedimiento está orientado a facilitar las tareas de operación y mantenimiento, de manera que se garantice una alta disponibilidad de funcionamiento de la instalación. De vuelta a la fase inicial de cálculo de las expectativas de producción, se utilizan los datos registrados en las centrales para llevar a cabo una mejora de los métodos de estimación de la radiación, que es la componente que más incertidumbre añade al proceso de modelado. El desarrollo y la aplicación de este procedimiento de control de calidad se han llevado a cabo en 39 grandes centrales fotovoltaicas, que totalizan una potencia de 250 MW, distribuidas por varios países de Europa y América Latina. ABSTRACT This thesis presents a comprehensive quality control procedure to be applied in photovoltaic plants, which covers from the initial phase of energy production estimation to the monitoring of the installation performance, once it is in operation. This protocol allows reducing the uncertainty associated to the photovoltaic plants behaviour and increases their long term reliability, therefore optimizing their performance. The situation of photovoltaic technology has drastically evolved in recent years, making photovoltaic plants capable of producing energy at fully competitive prices, in relation to other energy sources. This fact increases the requirements on the performance and reliability of these facilities. To meet this demand, it is necessary to adapt the quality control procedures and to develop new methods able to provide a more complete knowledge of the state of health of the plants, and able to maintain surveillance on them over time. In addition, the current meagre margins in which these installations operate require procedures capable of estimating energy production with the lower possible uncertainty during the design phase. The quality control procedure presented in this work starts from previous protocols oriented to the commissioning phase of a photovoltaic system, and complete them with procedures for the operation phase, paying particular attention to the major problems that arise in photovoltaic plants during their lifetime (hot spots, dust impact, ageing...). It also incorporates a protocol to control and analyse the installation performance directly from its monitoring data, which comprises from checking the validity of the recorded data itself to the detection and diagnosis of failures, and which allows an automated and detailed knowledge of the PV plant performance that can be oriented to facilitate the operation and maintenance of the installation, so as to ensure a high operation availability of the system. Back to the initial stage of calculating production expectations, the data recorded in the photovoltaic plants is used to improved methods for estimating the incident irradiation, which is the component that adds more uncertainty to the modelling process. The development and implementation of the presented quality control procedure has been carried out in 39 large photovoltaic plants, with a total power of 250 MW, located in different European and Latin-American countries.

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Near infrared diffuse optical spectroscopy and diffuse optical imaging are promising methods that eventually may enhance or replace existing technologies for breast cancer screening and diagnosis. These techniques are based on highly sensitive, quantitative measurements of optical and functional contrast between healthy and diseased tissue. In this study, we examine whether changes in breast physiology caused by exogenous hormones, aging, and fluctuations during the menstrual cycle result in significant alterations in breast tissue optical contrast. A noninvasive quantitative diffuse optical spectroscopy technique, frequency-domain photon migration, was used. Measurements were performed on 14 volunteer subjects by using a hand-held probe. Intrinsic tissue absorption and reduced scattering parameters were calculated from frequency-domain photon migration data. Wavelength-dependent absorption (at 674, 803, 849, and 956 nm) was used to determine tissue concentration of oxyhemoglobin, deoxyhemoglobin, total hemoglobin, tissue hemoglobin oxygen saturation, and bulk water content. Results show significant and dramatic differences in optical properties between menopausal states. Average premenopausal intrinsic tissue absorption and reduced scattering values at each wavelength are 2.5- to 3-fold higher and 16–28% greater, respectively, than absorption and scattering for postmenopausal subjects. Absorption and scattering properties for women using hormone replacement therapy are intermediate between premenopausal and postmenopausal populations. Physiological properties show differences in mean total hemoglobin (7.0 μM, 11.8 μM, and 19.2 μM) and water concentration relative to pure water (10.9%, 15.3%, and 27.3%) for postmenopausal, hormone replacement therapy, and premenopausal subjects, respectively. Because of their unique, quantitative information content, diffuse optical methods may play an important role in breast diagnostics and improving our understanding of breast disease.

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The detection and diagnosis of faults, ie., find out how , where and why failures occur is an important area of study since man came to be replaced by machines. However, no technique studied to date can solve definitively the problem. Differences in dynamic systems, whether linear, nonlinear, variant or invariant in time, with physical or analytical redundancy, hamper research in order to obtain a unique solution . In this paper, a technique for fault detection and diagnosis (FDD) will be presented in dynamic systems using state observers in conjunction with other tools in order to create a hybrid FDD. A modified state observer is used to create a residue that allows also the detection and diagnosis of faults. A bank of faults signatures will be created using statistical tools and finally an approach using mean squared error ( MSE ) will assist in the study of the behavior of fault diagnosis even in the presence of noise . This methodology is then applied to an educational plant with coupled tanks and other with industrial instrumentation to validate the system.

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Oncological patients are submitted to invasive exams in order to obtain an accurate diagnosis; these procedures may cause maladaptative reactions (fear, anxiety and pain). Particularly in breast cancer, the most common diagnose technique is the incisional biopsy. Most of the patients are unaware about the procedure and for that reason they may focus their thoughts on possible events such as pain, bleeding, the anesthesia, or the later surgical wound care. Anxiety and pain may provoke physiological, behavioral and emotional complications, and because of this reason, the Behavioral Medicine trained psychologist takes an active role before and after the biopsy. The aim of this study was to evaluate the effect of a cognitive-behavioral program to reduce anxiety in women submitted to incisional biopsy for the first time. There were 10 participants from the Hospital Juárez de México, Oncology service; all of them were treated as external patients. The intervention program focused in psycho-education and passive relaxation training using videos, tape-recorded instructions and pamphlets. Anxiety measures were performed using the IDARE-State inventory, and a visual-analogue scale of anxiety (EEF-A), and the measurement of blood pressure and heart rate). Data were analyzed both intrasubject and intersubject using the Wilcoxon test (p≤0.05). The results show a reduction in anxiety (as in punctuation as in ranges) besides, a reduction in the EEF-A.

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A violência doméstica define-se como aquela que ocorre em contexto familiar, seja entre os elementos de uma mesma família, seja entre aqueles que partilham a mesma habitação. Exige uma resposta multidisciplinar no que se refere ao atendimento, ao acompanhamento, à orientação, à reinserção social e à estabilização em situação de crise das vítimas. Isto exige do Médico Dentista não só a sua responsabilidade pelo cuidado da saúde pública, como a sua responsabilidade social perante situações que identifica de abuso e violência. O objetivo deste trabalho consistiu em salientar o contributo do Médico Dentista na deteção, no diagnóstico e na sinalização de situações de violência doméstica, sistematizando os fatores de risco e os indicadores. Para o efeito, foi realizada uma pesquisa bibliográfica, onde se delimitou o intervalo de tempo a artigos, a teses de Mestrado e a outra bibliografia da especialidade publicados entre 2001 e 2015. Após se proceder a uma breve revisão sobre o conceito “violência doméstica” e identificar os seus indicadores clínicos e as lesões nas vítimas, este trabalho concentra-se na dinâmica estabelecida entre a violência doméstica e os aspetos clínicos com interesse na Medicina Dentária, particularmente nos indicadores clínicos da violência sobre crianças, jovens, homens, mulheres e idosos. Foi possível verificar que os Médicos Dentistas desempenham um papel essencial na identificação dos sinais de violência doméstica, uma vez que as principais lesões se localizam na região da cabeça e da face, sendo as escoriações e equimoses as lesões mais frequentes.

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This master dissertation presents the study and implementation of inteligent algorithms to monitor the measurement of sensors involved in natural gas custody transfer processes. To create these algoritmhs Artificial Neural Networks are investigated because they have some particular properties, such as: learning, adaptation, prediction. A neural predictor is developed to reproduce the sensor output dynamic behavior, in such a way that its output is compared to the real sensor output. A recurrent neural network is used for this purpose, because of its ability to deal with dynamic information. The real sensor output and the estimated predictor output work as the basis for the creation of possible sensor fault detection and diagnosis strategies. Two competitive neural network architectures are investigated and their capabilities are used to classify different kinds of faults. The prediction algorithm and the fault detection classification strategies, as well as the obtained results, are presented

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Aim: A nested case-control discovery study was undertaken 10 test whether information within the serum peptidome can improve on the utility of CA125 for early ovarian cancer detection. Materials and Methods: High-throughput matrix-assisted laser desorption ionisation mass spectrometry (MALDI-MS) was used to profile 295 serum samples from women pre-dating their ovarian cancer diagnosis and from 585 matched control samples. Classification rules incorporating CA125 and MS peak intensities were tested for discriminating ability. Results: Two peaks were found which in combination with CA125 discriminated cases from controls up to 15 and 11 months before diagnosis, respectively, and earlier than using CA125 alone. One peak was identified as connective tissue-activating peptide III (CTAPIII), whilst the other was putatively identified as platelet factor 4 (PF4). ELISA data supported the down-regulation of PF4 in early cancer cases. Conclusion: Serum peptide information with CA125 improves lead time for early detection of ovarian cancer. The candidate markers are platelet-derived chemokines, suggesting a link between platelet function and tumour development.