ABSTRACT
BACKGROUND: Different modalities of quarantines were one of the main measures implemented worldwide to avoid the spread of SARS-CoV2 virus. AIM: To analyze and compare retrospectively the implementation of the Step- to-Step plan devised by the Chilean Ministry of Health during the pandemic. To propose a decision-making path based on an artificial intelligence fuzzy system to determine confinements in specific territories. MATERIAL AND METHODS: The Step-to-Step Plan threshold values such hospital network capacity, epidemic spreading, testing and contact tracing capability were modeled using fuzzy numbers and fuzzy rule-based systems. RESULTS: Ministry of Health's decision-making opportuneness were unrelated with the Step-to-Step Plan indicators for deconfinement. Such disagreements undermined epidemiological indicators. CONCLUSIONS: Using an artificial intelligence system could improve decision-making transparency, emergency governance, and risk communication to the population.
Subject(s)
Humans , Artificial Intelligence , Quarantine , RNA, Viral , Retrospective Studies , Fuzzy LogicABSTRACT
ObjectiveAiming at the need of control strategy switching of intelligent above-knee prosthetic, taking the plantar pressure of human walking as the research object, and based on fuzzy logic algorithm, a gait phase division method based on plantar pressure of prosthetic is proposed. MethodsThree flexible force sensors installed on the soles of the false feet were used to collect the plantar pressure information of the test object under three different walking modes (walking on the flat road, walking downhill and walking down the stairs). After data fusion processing, it was sent to the fuzzy logic controller, and the recognition results were output according to the IF-THEN rule, the scale and sensitivity factor. ResultsThrough the testing of five healthy people as substitute, the results showed that the accuracy of gait phase recognition for walking on the flat road, walking down the stairs and walking downhill were (95.3±2.4)%, (81.5±6.3)% and (90.7±3.5)%, respectively. ConclusionThe accuracy of recognition basically meets the requirements in this project. This method can be applied in the gait phase recognition of intelligent above-knee prosthetic.
ABSTRACT
ABSTRACT Objective: Based on the evaluation method with fuzzy integrals, this paper analyzes the results of physical health tests of college students. Methods: Principal component analysis was used to extract the psychological factors. The evaluation model was organized into three levels to evaluate the physical health of college students. Results: The physical health status of University Q students is below average. Most of the students' physical examination results are concentrated in the passing areas, and few students have an excellent to good ratio. Conclusion: The fitness assessment model of university students, based on an assessment with fuzzy integrals, has certain generalizability and applicability. The established index system and the comprehensive evaluation model are suitable for thoroughly evaluating each student and comprehensive fitness evaluation of all boys and girls in a class or college. Level of evidence II; Therapeutic studies - investigation of treatment results.
RESUMO Objetivo: Com base no método de avaliação com integrais fuzzy, este documento analisa os resultados dos testes de saúde física dos estudantes universitários. Métodos: Foi utilizada a análise de componentes principais para extrair os fatores psicológicos. O modelo de avaliação foi organizado em três níveis para avaliar a saúde física dos estudantes universitários. Resultados: O estado de saúde física dos estudantes da Universidade Q está abaixo da média. A maioria dos resultados dos exames físicos dos estudantes está concentrada nas áreas de aprovação, e poucos estudantes têm uma proporção excelente e boa. Conclusão: O modelo de avaliação da aptidão física dos estudantes universitários, baseado em uma avaliação com integrais fuzzy, tem certa generalização e aplicabilidade. O sistema de índice estabelecido e o modelo de avaliação abrangente não só são adequados para avaliação abrangente de cada estudante, mas também para avaliação abrangente da aptidão física de todos os meninos e meninas de uma classe ou faculdade. Nível de evidência II; Estudos terapêuticos - investigação de resultados de tratamento.
Resumen Objetivo: Basándose en el método de evaluación con integrales difusas, este artículo analiza los resultados de las pruebas de salud física de los estudiantes universitarios. Métodos: Se utilizó el análisis de componentes principales para extraer los factores psicológicos. El modelo de evaluación se organizó en tres niveles para evaluar la salud física de los estudiantes universitarios. Resultados: El estado de salud física de los estudiantes de la Universidad Q está por debajo de la media. La mayoría de los resultados de los exámenes físicos de los estudiantes se concentran en las zonas de aprobado, y son pocos los que tienen una proporción excelente y buena. Conclusión: El modelo de evaluación de la aptitud física de los estudiantes universitarios basado en una evaluación con integrales difusas tiene cierta generalizabilidad y aplicabilidad. El sistema de índices establecido y el modelo de evaluación integral no sólo son adecuados para la evaluación integral de cada estudiante, sino también para la evaluación integral de la aptitud de todos los chicos y chicas de una clase o colegio. Nivel de evidencia II; Estudios terapéuticos - investigación de resultados de tratamiento.
ABSTRACT
Objective:To explore artificial intelligence technology and propose an algorithm for automatic identification of dicentric chromosomes to realize fast and high-throughput biodosimetry. In order to solve the time-consuming and laborious problem of manual analysis of dicentric chromosomes.Methods:Combining artificial intelligence technology and image processing technology, based on MATLAB software, algorithms like image preprocessing, threshold segmentation algorithm, binarization processing, area identification algorithm, convolutional neural network algorithm and double centripetal recognition algorithm were applied. A fuzzy membership function was defined to describe the degree of each chromosome belonging to a dicentric chromosome, and the discrimination threshold was set to realize the automatic identification of dicentric chromosomes.Results:Through the test on 1 471 chromosome images, compared with manual recognition, the detection rate of dicentric chromosomes cells of this algorithm reached 70.7%.Conclusions:This algorithm method carries out a preliminary study on the automatic identification of dicentric chromosomes with good result.
ABSTRACT
Abstract: Microgrids (MD) is a new technology to improve efficiency, resilience, and reliability in the electricity sector. MD are most likely to have a clean energy generation, but the increase of microgrids with this kind of generation brings new challenges for energy management (EMS), especially concerning load uncertainties and variation of energy generation. In this context, this study has the main objective to propose a method of how to attend this matter, verifying the difference between the day before and real-time. The EMS proposed analyses the MD in real-time, calculating the deviation between dispatched and what was predicted to happen in the operation point in a three-dimensional analysis approach, considering renewable energy generation, battery State of Charge (SOC) and load curve. The system categorized the deviation in three possible quantities (small, medium, or high) and it acts accordingly. For the Next Operation Point predictor are used an artificial neural network (ANN) methodology. For the Decision Support System, it's used a fuzzy logic system to adjust the next operation point, and it uses a mixed-integer linear programming (MILP) approach when the deviation is too high, and the dispatched operation is unfeasible. Simulations with real data and information of a pilot project of MD are carried out to test and validate the proposed method. Results show that the methodology used to attend the matters of uncertainties and variation of energy generation. A reduction of operational cost is observed in the simulations.
ABSTRACT
RESUMEN La lógica difusa trata de copiar la forma en que los humanos toman decisiones. Específicamente en el área médica, se utiliza desde hace varios años en estudios aplicados a áreas como: ingeniería biomédica, sistemas expertos, modelos epidemiológicos y sistemas diagnósticos. Se confeccionó un cuestionario para medir la calidad de vida relacionada con la salud oral en adolescentes cubanos; se utilizó la lógica difusa en el proceso de validación por expertos, mediante el software PROCESA_CE (2013). En el nivel de concordancia de los expertos se rechazó la hipótesis nula de que no existe comunidad de preferencia entre ellos, para un nivel de significación de 0,01; esto garantizó, con un 99% de confiabilidad, que es posible hacer valoraciones a partir del consenso de estos expertos. Además, se corroboró la existencia de un consenso de 5 en todos los ítems.
ABSTRACT Fuzzy logic tries to copy the way humans make decisions. It has been used for several years, specifically in the medical field, in studies applied to areas such as biomedical engineering, expert systems, epidemiological models and diagnostic systems. A questionnaire was prepared to measure the quality of life related to oral health in Cuban adolescents; Fuzzy logic was used in the validation process based on expert criteria, using the PROCESA_CE (2013) software. According to expert agreements, the null hypothesis that there is no community of preference among them was rejected, for a significance level of 0.01; this guaranteed, with 99% reliability, that it is possible to make assessments based on their consensuses. In addition, the existence of a consensus of five in all items was corroborated.
Subject(s)
Peer Review , Fuzzy Logic , Oral MedicineABSTRACT
Abstract This paper aims to evaluate the perception of residents of a rural quilombola community, about the impacts of distributed energy generation (DG) on the social, economic and environmental dimensions. The main challenge of the proposed model was to quantify the main perceptions of the target population of the research, as well as maintain the coherence of the specifications of the sustainability parameters. Diffuse modeling allows the transformation of linguistic variables into numerical values, the disadvantage is the dependence of the specialist to construct the rules. The methodology used was the application of a semi-structured questionnaire, and the results were used as a reference to build the discourse domain of the input variables of the Fuzzy inference system, which generated an index of 54.1% classified in the category partially sustainable. Specifically, the economic and social dimensions obtained an index of 46.7% and the environmental dimension of 69%. From the perspective of the perception of the respondents, the variables with the greatest impact were: landscape change (LCH) 92%, environmental awareness (EA) and reduction of global warming (GW) with values of both 69%. The variable of the most prominent economic dimension was: cost of the system with a value of 69%. In the social dimension, the variables with the greatest impact were: Community Acceptability (AC), Expansion of the support network (ESN) with values of 69%. The proposed model allowed us to interpret the respondents' perception, and can be used to generate effective actions that solve the identified demands.
ABSTRACT
RESUMEN México se encuentra entre los países con mayor prevalencia de sobrepeso y obesidad entre los niños y adolescentes. Por tanto, surge la necesidad de una técnica económica, rápida, reproducible y de fácil implementación que permita detectar tempranamente en el ámbito escolar el sobrepeso y la obesidad en niños y adolescentes. En este trabajo se presenta una técnica que cumple con esas expectativas basada en un modelo de inferencia difuso con un conjunto de 81 reglas para la clasificación de la composición corporal de 92 niñas y 88 niños entre las edades de 10 y 14 años. Como atributos se tomaron, el peso, el índice de masa corporal, el porciento de masa grasa y el porciento de peso habitual. Para cada atributo se definieron tres conjuntos difusos, normal, sobrepeso y obeso y para clasificar el valor del atributo se usaron las referencias que más se utilizan en la literatura y por los nutriólogos y pediatras de la zona de estudio. Como resultado de la aplicación del modelo difuso, se obtuvo una precisión promedio de 97,6% con un 4,2% de error para la clasificación corporal de las niñas y de 93,4% con un 4,6% de error para niños.
ABSTRACT Mexico is among the countries with the highest prevalence of overweight and obesity among children and adolescents. Therefore, an economical, rapid, reproducible and easy to implement technique that allows early detection in the school environment of overweight and obesity in children and adolescents is need. This paper presents a technique that meets these expectations based on a diffuse inference model with a set of 81 rules for the classification of body composition among 92 girls and 88 boys between the ages of 10 and 14 years. Weight, body mass index, fat mass percentage and the percentage of habitual weight were taken as attributes. For each attribute three diffuse sets were defined: normal, overweight and obese. To classify the value of the attribute, the most used references in the literature and those used by consulted nutritionists and pediatricians were used. As a result of the application of the diffuse model, an average accuracy of 97.6% was obtained with a 4.2% error for the corporal classification of girls and 93.4% with a 4.6% error for boys.
Subject(s)
Child , Adolescent , Child , Adolescent , Obesity , Diet , Overweight , Child NutritionABSTRACT
RESUMEN Fundamento: el control es fundamental para que un hospital logre alcanzar sus objetivos y metas trazadas, de lo contrario sería imposible que se puedan definir las medidas que se deben adoptar para alcanzarlos. Objetivo: evaluar las actividades de control como componente interno en una entidad hospitalaria cubana, mostrando la mejor dirección a seguir a la hora de la toma de las decisiones, con un bajo nivel de incertidumbres en los resultados. Métodos: se diseñó un modelo a través de la lógica difusa compensatoria, compuesto por los elementos fundamentales de la norma actividades de control. Resultados: las actividades de control en el hospital se encuentran en una categoría deficiente de algo verdadero, al influir de manera negativa la rotación del personal y los indicadores de rendimiento en el desempeño. Conclusiones: se obtuvo el índice de la gestión del control, al evidenciar que existen deficiencias notables en la implementación del mismo. Lo que permite al hospital establecer una estrategia de mejora, basadas en un plan de acción.
ABSTRACT Background: the control is essential for a hospital to achieve its objectives and goals, otherwise it would be impossible to define the measures to be taken to achieve them. Objective: to evaluate control activities as a component of internal control in a Cuban hospital entity, showing the best direction to follow when making decisions, with a low level of uncertainty in the results. Methods: a model was designed through Diffuse Compensatory Logic, composed of the fundamental elements of the control activities standard. Results: the control activities in the hospital are in a deficient category of something true, negatively influencing staff turnover and performance indicators. Conclusions: the control management index was obtained, showing that there are notable deficiencies in its implementation. Allowing the hospital to establish an improvement strategy based on an action plan.
ABSTRACT
RESUMO A divulgação de informações sobre qualidade das águas para um público não especialista é fundamental para subsidiar ações políticas e institucionais de gestão dos ambientes aquáticos. Para tanto, índices de qualidade de água têm sido propostos por serem capazes de sintetizar em um único valor ou categoria a informação, normalmente descrita a partir de um conjunto extenso de variáveis de qualidade de água. Este trabalho propõe um novo índice de qualidade de água, IQAFAL, baseado em lógica nebulosa, direcionado para o ambiente lótico, desenvolvido com a colaboração do quadro de especialistas da área de qualidade de água do Instituto Estadual do Ambiente (INEA). O índice proposto foi aplicado a dados de qualidade de água do Rio Paraíba do Sul, obtidos pelo INEA, nos anos de 2002 a 2009. Os resultados do IQAFAL mostraram que esse índice foi capaz de descrever a qualidade da água desse trecho do Rio Paraíba do Sul, correspondendo satisfatoriamente às avaliações de qualidade de água contidas nos relatórios disponíveis. Verificou-se também que com essa metodologia foi possível evitar que a influência de uma variável em condições críticas fosse atenuada pela influência das outras variáveis em condições favoráveis, produzindo um resultado impreciso no índice final.
ABSTRACT The dissemination of information on water quality for a non-specialist audience is essential to support political and institutional actions for the management of aquatic environments. Therefore, water quality indices have been proposed since they are able to synthesize into a single value or category information, usually described from an extensive set of water quality variables. This research proposes a new water quality index, based on fuzzy logic, aimed at lotic environments, developed through the collaboration of experts in water quality of the Rio de Janeiro Environmental Agency (Instituto Estadual do Ambiente - INEA). The proposed index was applied to water quality data from the Paraíba do Sul River, obtained by INEA, in the years 2002 to 2009. The results of IQAFAL showed that the index was able to synthesize the water quality of this stretch of the Paraíba do Sul, satisfactorily matching the assessments of the water quality assessments contained in the reports available. It was also noticed that with this methodology it was possible to avoid the attenuation of the influence of a variable in critical condition was attenuated by the influence of other variables in favorable conditions, producing an inaccurate result in the final index.
ABSTRACT
ABSTRACT: Vertical screw conveyors have low energy efficiency but this is generally acceptable within the normally low power range. Previously, a fuzzy logic approach was used to model volumetric efficiency and specific energy consumption in screw conveyors. The performance of conveyors in different working conditions and the geometry of the screw were studied. It was reported that increasing the screw speed, pitch, and loading angle also increases specific energy consumption. In this study, an intelligent fuzzy model based on the Mamdani approach was developed to predict volumetric efficiency and specific energy consumption. The model inputs included the slope, speed, and pitch of screw conveyors. The fuzzy model consists of 27 rules in which three parameters, namely the goodness of fit (η), relative error (ε), and coefficient of correlation (R), are used to evaluate the model. The goodness of fit, relative error, and coefficient of correlation values were 0.986, 5.28%, and 0.99, respectively, for volumetric efficiency and 0.987, 4.93%, and 0.99, respectively, for specific energy consumption. Results revealed that the developed model is capable of predicting volumetric efficiency and specific energy consumption in barley transport under different working conditions with high accuracy.
RESUMO: Os transportadores de parafuso verticais têm baixa eficiência energética, mas isso geralmente é aceitável dentro da faixa de potência normalmente baixa. Anteriormente, uma abordagem lógica fuzzy era usada para modelar a eficiência volumétrica e o consumo específico de energia em transportadores de parafuso. O desempenho dos transportadores em diferentes condições de trabalho e a geometria do parafuso foram estudados. Verificou-se que aumentar a velocidade do parafuso, a inclinação e o ângulo de carga também aumenta o consumo de energia específico. Neste estudo, um modelo fuzzy inteligente baseado na abordagem de Mamdani é desenvolvido para prever a eficiência volumétrica e o consumo específico de energia. As entradas do modelo incluem a inclinação, velocidade e inclinação dos transportadores de parafuso. O modelo fuzzy consiste em 27 regras, nas quais três parâmetros, a saber, qualidade do ajuste (η), erro relativo (ε) e coeficiente de correlação (R), são usados para avaliar o modelo. Os valores de ajuste, erro relativo e coeficiente de correlação são de 0,986, 5,28% e 0,99, respectivamente, para eficiência volumétrica e 0,987, 4,93% e 0,99, respectivamente, para consumo específico de energia. Os resultados revelam que o modelo desenvolvido é capaz de prever eficiência volumétrica e consumo específico de energia no transporte de cevada sob diferentes condições de trabalho com alta precisão.
ABSTRACT
Resumen Introducción. La gestión del conocimiento como proceso innovador y clave para organizaciones inteligentes permitió llevar su aplicación a centros de investigación de educación superior, basados en el capital intelectual (CI), como eje fundamental en la creación de activos intangibles, haciendo uso del modelo Intellectus, el cual enfatiza como componentes del CI: el Capital Humano (CH), Estructural (CE) y Relacional (CR). Objetivo. Desarrollar una metodología en la medición del CH y CE para centros de investigación. Materiales y métodos. Haciendo uso de la técnica de lógica difusa 2 y el toolbox Matlab®, se generaron algoritmos para obtener una herramienta inteligente. Para su validación, el modelo se aplicó al grupo de investigaciones de Ciencias Administrativas del Instituto Tecnológico Metropolitano de Medellín. Mediante la técnica Delfi, seis expertos dictaminaron que las variables decisivas a evaluar son, del CH: valores y aptitudes, actitudes, y conocimiento; del CE organizativo: aprendizaje organizativo y del CE tecnológico: I+D. La información se obtuvo de la aplicación en 16 investigadores en un formato con 54 preguntas, medidas en escala de Likert. Resultados. Con lógica difusa 2 se logró una base de reglas que, junto al tipo de reducción Karnik-Mendel, permitieron la toma de decisiones sobre las variables, a través de la superficie de control. Conclusión. La combinación entre capacidades y esfuerzo, I+D aporta mayor valor. La relación actitudes con aprendizaje organizativo es significativa, aunque no prioritaria en la generación de valor y la generación de valor, entre las variables valores y aptitudes, con aprendizaje organizativo, no es significativa.
Abstract Introduction: Knowledge management as an innovative and key process for smart organizations allowed its application in higher education research centers, based on intellectual capital (IC), as a fundamental axis in the creation of intangible assets, using the Intellectus model, which emphasizes as components of the IC: Human Capital (HC), Structural Capital (SC) and Relational Capital(RC). Objective: The work seeks to develop a measurement methodology for HC and SC for research centers. Materials and methods: Using the fuzzy logic technique 2 and the Matlab® toolbox, algorithms were generated to obtain an intelligent tool. The model validation was applied to the Administrative Sciences research group of the Metropolitan Technological Institute of Medellin. Through the Delphi technique, six experts determined that the decisive variables to be evaluated, according to the model, were from the HC: values and aptitudes, attitudes, and knowledge; from organizational SC: organizational learning; and from technological SC: R&D. The information was obtained from the application of a questionnaire with 54 questions to 16 researchers, measured with a Likert scale. Results: With fuzzy logic 2, a base of rules was achieved that, together with the Karnik-Mendel type of reduction, allowed decision making on the variables through the control surface. Conclusion: The combination of capabilities and effort and R&D brings greater value. The relationship between attitudes and organizational learning is significant, although not a priority in the generation of value; and the generation of value, between the values and skills variables, with organizational learning, is not significant.
Resumo Introdução. A gestão do conhecimento como processo inovador e chave para organizações inteligentes permitiu levar sua aplicação à centros de pesquisa de educação superior, baseados no capital intelectual (CI), como eixo fundamental na criação de ativos intangíveis, fazendo uso do modelo Intellectus, o qual enfatiza como componentes do CI: o Capital Humano (CH), Estrutural (CE) e Relacional (CR). Objetivo. Desenvolver uma metodologia na medição do CH e CE para centros de pesquisa. Materiais e métodos. Fazendo o uso da técnica de lógica difusa 2 e o toolbox Matlab®, se geraram algoritmos para obter uma ferramenta inteligente. Para a sua validação, o modelo se aplicou ao grupo de pesquisas de Ciências Administrativas do Instituto Tecnológico Metropolitano de Medellín. Mediante a técnica Delfi, seis expertos ditaram que as variáveis decisivas à avaliar são, do CH: valores e aptidões, atitudes e conhecimento; do CE organizativo: aprendizagem organizativo e do CE tecnológico: P&D. A informação se obteve da aplicação em 16 pesquisadores em um formato com 54 perguntas, medidas em escala de Likert. Resultados. Com lógica difusa 2 se conseguiu uma base de regras que, junto ao tipo de redução Karnik-Mendel, permitiram a tomada de decisões sob as variáveis, através da superfície de controle. Conclusão. A combinação entre as capacidades e o esforço, P&D aporta maior valor. A relação atitudes com aprendizagem organizativo é significativa, embora não seja prioritária na geração de valor, e a geração de valor entre as variáveis valores e aptidões, com aprendizagem organizativo, não é significativa.
ABSTRACT
Introduction: Humans have recreated intelligence foreffective human decision making and to unburden themselvesof the stupendous workload. Artificial intelligence can act asa supplemental tool to improve diagnosis and treatment carebut intelligent machines can never be 'human'. The field ofartificial intelligence is relatively young but has still comea long way in the fields of medicine and dentistry. Hence,there is a need for the dentists to be aware about its potentialimplications for a lucrative clinical practice in the future.
ABSTRACT
Aim: To enhance the productivity of lovastatin from Fusarium nectrioides isolate with liquid cheese whey as a major carbon source and to optimize the media components using Response Surface Methodology (RSM) and Fuzzy Logic System (FLS). Methodology: Euphorbia hirta was collected, surface sterilized and incubated on potato dextrose agar medium amended with ampicillin and streptomycin sulphate. F. nectrioides was isolated from E. hirta and identified using morphological and molecular methods. Primarily, media components were screened by Plackett Burman design (PBD). Further, the effect of significant nutrients was predicted using RSM and FLS and compared with experimental yield. Results: Molecular identification by gene sequencing confirmed the isolate to be F. nectrioides, given an accession number (MH173849) the sequence was submitted in the gene bank. PBD revealed that peptonized milk (which is an enzymic digest of high grade skimmed milk powder), corn steep liquor, liquid cheese whey and histidine were significant variables. The optimum levels of these significant variables in different combinations were studied by RSM in which the predicted yield of lovastatin was 1.2 gl-1. Further, it was analyzed by FLS with 14 set of fuzzy rules and the maximum production obtained was 1.8 g100 ml-1 which was closer to the experimental yield of 1.75 g100 ml-1. Therefore, compared to RSM, FLS was more suitable technique to determine the optimum levels of significant nutrients for enhanced lovastatin production. Interpretation: This study suggests that F. nectrioides (MH173849) can be used as a potent producer of lovastatin and the production highly influenced by glucose, corn steep liquor, liquid cheese whey and histidine.
ABSTRACT
The use of Remote patient monitoring (RPM) systems to monitor critically ill patients in the Intensive Care Unit (ICU) has enabled quality and real-time healthcare management. Fuzzy logic as an approach to designing RPM systems provides a means for encapsulating the subjective decision-making process of medical experts in an algorithm suitable for computer implementation. In this paper, a remote monitoring system for preterm in neonatal ICU incubators is modeled and simulated. The model was designed with 4 input variables (body temperature, heart rate, respiratory rate, and oxygen level saturation), and 1 output variable (action performed represented as ACT). ACT decides whether an alert is generated or not and also determines the message displayed when a notification is required. ACT classifies the clinical priority of the monitored preterm into 5 different fields: code blue, code red, code yellow, code green, and code black. The model was simulated using a fuzzy logic toolbox of MATLAB R2015A. About 216 IF_THEN rules were formulated to monitor the inputs data fed into the model. The performance of the model was evaluated using the confusion matrix to determine the model’s accuracy, precision, sensitivity, specificity, and false alarm rate. The experimental results obtained shows that the fuzzy-based system is capable of producing satisfactory results when used for monitoring and classifying the clinical statuses of neonates in ICU incubators.
ABSTRACT
RESUMO O transporte fluvial é um dos principais meios de locomoção de pessoas e cargas na Região Amazônica. Este trabalho tem como objetivo principal analisar por meio da Lógica Fuzzy o risco ao meio ambiente e à saúde em relação aos efluentes sanitários das embarcações fluviais de passageiros da Região Amazônica e da água para consumo humano distribuída a bordo. Para alcançar os objetivos, foram feitas coletas de água superficial em pontos específicos do rio Amazonas e da água para consumo humano a bordo durante uma viagem de 830 km entre Santarém (PA) e Belém (PA), em uma embarcação fluvial de passageiros. Os resultados mostraram que as embarcações que operam na linha regular Belém/Santarém/Belém não dispõem de mecanismos de captação, armazenamento e tratamento de efluentes sanitários e da água servida, lançando-os diretamente nos rios. A água consumida pelos passageiros e tripulantes, que foi objeto de estudo, é de péssima qualidade, apresentando 89% de amostras contaminadas por coliformes totais e 84% pela bactéria Escherichia coli. Todas as amostras da água superficial apresentaram contaminação por coliformes totais e E. coli. As estatísticas e o modelo propostos, utilizando a lógica fuzzy, apontaram que o risco para o meio ambiente e para a saúde é muito alto em razão da falta de saneamento nas embarcações fluviais de passageiros na Amazônia.
ABSTRACT Fluvial transportation is one of the main ways of transportation for people and loads in the Amazon region. This work has as its main goal to analyze, through the Fuzzy Logic, the risks to the environment and to people's health regarding the sanitary effluents of fluvial passengers ships in the Amazon Region, as well as the human consumable water distributed on board. To achieve these goals, superficial water collections in specific points of the Amazonas river and collections of human consumable water on board during a trip of 830 km between Santarém/PA and Belém/PA in a fluvial passenger ship were performed. The results showed that the ship that goes through the regular line Belém/Santarém/Belém does not have any methods of caption, storage and sanitary treatment of the effluents and the water served, throwing dejects directly into the river. The consumable water used by the passengers and the crew on board has a terrible quality, because 89% of the samples were contaminated with total coliforms and 84% with Escherichia coli. All superficial water samples were contaminated by total coliforms and E. coli. Statistics and the Fuzzy Logic model pointed that the risks are very high for the environment and for human health due of the lack of sanitation of these fluvial passenger ships in Amazon.
ABSTRACT
Abstract Hospitalizations due to respiratory diseases generate financial costs for the Health System in addition to social costs. Objective of this study was to develop and validate a fuzzy linguistic model for prediction of hospitalization due to respiratory diseases. We constructed a fuzzy model for prediction of hospitalizations due to pneumonia, bronchitis, bronchiolitis and asthma second exposure to fine particulate matter (PM2.5) in residents of Volta Redonda, RJ, in 2012. The model contains two inputs, PM2.5 and temperature, with three membership functions for each input, and an output with three membership functions for admissions, which were obtained from DATASUS. There were 752 hospitalizations in the period, the average concentration of PM2.5 was 17.1 µg/m3 (SD = 4.4). The model showed a good accuracy with PM2.5, the result was between 90% and 76.5% for lags 1, 2 and 3, a sensitivity of up to 95%. This study provides support for creating executable software with a low investment, along with the use of a portable instrument could allow number of hospital admission due to respiratory diseases and provide support to local health managers. Furthermore, the fuzzy model is very simple and involves low computational costs, an implementation making possible.
Resumo Internações por doenças respiratórias geram custos financeiros para o Sistema de Saúde além de custos sociais. O objetivo deste estudo foi elaborar e validar um modelo linguístico "fuzzy" para previsão do número de internações por doenças respiratórias. Foi construído um modelo "fuzzy" para predição de internações por pneumonias, bronquite, bronquiolite e asma segundo exposição ao material particulado fino (PM2,5) em residentes de Volta Redonda, RJ, em 2012. O modelo contém duas entradas PM2,5 e temperatura, com três funções de pertinência para cada entrada, e uma saída com três funções de pertinência para internações, que foram obtidas do DATASUS. Foram 752 internações no período, a concentração média do PM2,5 foi 17,1 µg/m3 (dp = 4,4). O modelo mostrou uma boa acurácia com PM2,5, o resultado foi entre 90% e 76,5% para os lags 1, 2 e 3, com sensibilidade de até 95%. Este estudo fornece subsídios para a criação de programa executável, que não exige um grande investimento, juntamente com o uso de um instrumento portátil pode permitir uma estimativa do número de internações e prestar apoio aos gestores municipais de saúde. Além disso, o modelo "fuzzy" é muito simples e implica em baixas despesas computacionais, tornando possível uma implementação.
Subject(s)
Humans , Respiratory Tract Diseases/epidemiology , Fuzzy Logic , Hospitalization/statistics & numerical data , Models, Theoretical , Patient Admission/statistics & numerical data , Respiratory Tract Diseases/etiology , Respiratory Tract Diseases/physiopathology , Brazil/epidemiology , Reproducibility of Results , Sensitivity and Specificity , Air Pollutants/toxicity , Air Pollution/adverse effects , Environmental Exposure/adverse effects , Particulate Matter/toxicity , Hospitalization/economicsABSTRACT
Objetivos: avaliar se as intervenções propostas na tecnologia de cuidados de enfermagem ao cliente com dermatoses imunobolhosas contribuem para reduzir o desconforto, reconhecer padrões de desconforto antes e após aplicação da tecnologia. Método: aplicação do protocolo de avaliação em 14 clientes hospitalizados em enfermarias de dermatologia do Rio de Janeiro e Mato Grosso do Sul, Brasil. Os cuidados foram realizados mediante diagnósticos identificados e recomendações da tecnologia. A subjetividade em reco¬nhecer padrões de conforto em clientes com doenças raras direcionou o uso da lógica fuzzy em função dos atributos dor, mobilidade, padrão de sono, exposição do corpo/lesões. Aprovado conforme CAAE: 0258.0.228.000-11. Resultados: dos 14 participantes, oito verbalizaram redução da dor após 24 horas. Após uma semana, três declararam maior redução, cinco manutenção e cinco aumento. Conclusão: a análise inferencial fuzzy propiciou avaliar padrões de desconforto, apontando para a veracidade da hipótese de que a tecnologia contribui para promover o conforto da clientela.
Objectives: to evaluate whether interventions proposed in nursing care technology for clients with immunobullous dermatoses contribute to reducing discomfort, and to recognize patterns of discomfort before and after application of the technology. Method: the evaluation protocol was applied to 14 patients hospitalized in dermatology wards in Rio de Janeiro and Mato Grosso do Sul, Brazil, from June 2012 to April 2013. Care was performed by way of identified diagnoses and recommendations in the technology. The role of subjectivity in rec¬ognizing comfort patterns in clients with rare diseases indicated the use of fuzzy logic with attributes of pain, mobility, sleep pattern, and body exposure/lesions. The study was approved under CAAE: 0258.0.228.000-11. Results: of the 14 patients, eight reported diminished pain after 24 hours. After one week, three reported larger reductions; five, no change; and five, increased pain. Conclusion: evaluation of patterns of discomfort by fuzzy inferential analysis supported the hypothesis that the technology contributes to promoting client comfort.
Objetivos: evaluar si las intervenciones propuestas en la tecnología de cuidados de enfermería al cliente con dermatosis inmunoampollares contribuyen a reducir el incómodo; reconocer patrones de incomodidad antes y después de la aplicación de la tecnología. Método: aplica¬ción del protocolo de evaluación en 14 pacientes hospitalizados en enfermerías de dermatología de Río de Janeiro y Mato Grosso do Sul, Brasil, de junio/2012 a abril/2013. Los cuidados se han realizado mediante diagnósticos identificados y recomendaciones de la tecnología. La subjetividad en reconocer patrones de comodidad en pacientes con enfermedades raras dirigió el uso de la lógica fuzzy en función de los atributos dolor, movilidad, patrón de sueño, exposición del cuerpo / lesiones. Aprobado conforme CAAE: 0258.0.228.000-11. Resultados: de los 14, ocho reportaron reducción del dolor después de 24 horas. Tras una semana, tres declararon una mayor reducción, cinco mantu¬vieron y cinco aumentaron. Conclusión: el análisis inferencial fuzzy propició evaluar patrones de incomodidad, señalando la veracidad de la hipótesis de que la tecnología contribuye a promover la comodidad de los pacientes.
Subject(s)
Humans , Male , Female , Adult , Middle Aged , Aged , Aged, 80 and over , Skin Diseases, Vesiculobullous/nursing , Pemphigoid, Bullous/nursing , Pemphigus/nursing , Patient Comfort , Fuzzy Logic , Models, Theoretical , Nursing Care/methodsABSTRACT
Abstract: In neuroimaging, brain tissue segmentation is a fundamental part of the techniques that seek to automate the detection of pathologies, the quantification of tissues or the evaluation of the progress of a treatment. Because of its wide availability, lower cost than other imaging techniques, fast execution and proven efficacy, Non-contrast Cerebral Computerized Tomography (NCCT) is the most used technique in emergency room for neuroradiology examination, however, most research on brain segmentation focuses on MRI due to the inherent difficulty of brain tissue segmentation in NCCT. In this work, three brain tissues were characterized: white matter, gray matter and cerebrospinal fluid in NCCT images. Feature extraction of these structures was made based on the radiological attenuation index denoted by the Hounsfield Units using fuzzy logic techniques. We evaluated the classification of each tissue in NCCT images and quantified the feature extraction technique in synthetic images from real tissues with a sensitivity of 92% and a specificity of 96% for images from cases with slice thickness of 1 mm, and 96% and 98% respectively for those of 1.5 mm, demonstrating the ability of the method as feature extractor of brain tissues.
Resumen: En neuroimagen, la segmentación de tejidos cerebrales es una parte fundamental de las técnicas que buscan automatizar la detección de patologías, la cuantificación de tejidos o la evaluación del progreso de un tratamiento. Debido a su amplia disponibilidad, menor costo que otras técnicas de imagen, rápida ejecución y eficacia probada, la tomografía computarizada cerebral sin contraste (TCNC) es la técnica mayormente utilizada en emergencias para el examen neurorradiológico, sin embargo, la dificultad inherente que representa la segmentación de los tejidos cerebrales, hace que la mayoría de las investigaciones sobre la segmentación del cerebro se centren en la resonancia magnética. En este trabajo se realizó la caracterización de tres tejidos cerebrales: sustancia blanca, sustancia gris y líquido cefalorraquídeo en imágenes TCNC. Dichas estructuras fueron caracterizadas con base en el índice de atenuación radiológica denotadas por las Unidades Hounsfield utilizando técnicas de lógica difusa. Se evaluó la caracterización de cada tejido en diversos cortes de TCNC y se cuantificó la técnica de extracción de características en imágenes sintéticas a partir de tejidos reales con una sensibilidad de 92% y una especificidad de 96% para tejidos en cortes de 1 mm de grosor y 96% y 98% para los de 1.5 mm demostrando la habilidad del método como extractor de características de los tejidos cerebrales.
ABSTRACT
RESUMO Objetivo: Construir um modelo computacional fuzzy para estimar o número de internações de crianças até 10 anos por doenças respiratórias, com base nos dados de poluentes e fatores climáticos da cidade de São José do Rio Preto, Brasil. Métodos: Foi construído modelo computacional utilizando a lógica fuzzy. O modelo tem 4 entradas, cada uma com 2 funções de pertinência gerando 16 regras, e a saída com 5 funções de pertinência, baseado no método de Mamdani, para estimar a associação entre os poluentes e o número de internações. Os dados de internações, de 2011-2013, foram obtidos no Departamento de Informática do Sistema de Saúde (DATASUS) e os poluentes material particulado (PM10) e dióxido de nitrogênio (NO2), a velocidade do vento e a temperatura foram obtidos pela Companhia Ambiental do Estado de São Paulo (Cetesb). Resultados: Foram internadas 1.161 crianças no período analisado, e a média dos poluentes foi 36 e 51 µg/m3 - PM10 e NO2, respectivamente. Os melhores valores da correlação de Pearson (0,34) e da acurácia avaliada pela curva Receiver Operating Characteristic - ROC (NO2 - 96,7% e PM10 - 90,4%) foram para internações no mesmo dia da exposição. Conclusões: O modelo mostrou-se eficaz na predição do número de internações de crianças, podendo ser utilizado como ferramenta na gestão hospitalar da região estudada.
ABSTRACT Objective: To build a fuzzy computational model to estimate the number of hospitalizations of children aged up to 10 years due to respiratory conditions based on pollutants and climatic factors in the city of São José do Rio Preto, Brazil. Methods: A computational model was constructed using the fuzzy logic. The model has 4 inputs, each with 2 membership functions generating 16 rules, and the output with 5 pertinence functions, based on the Mamdani's method, to estimate the association between the pollutants and the number of hospitalizations. Data from hospitalizations, from 2011-2013, were obtained in DATASUS - and the pollutants Particulate Matter (PM10) and Nitrogen Dioxide (NO2), wind speed and temperature were obtained by the Environmental Company of São Paulo State (Cetesb). Results: A total of 1,161 children were hospitalized in the period and the mean of pollutants was 36 and 51 µg/m3 - PM10 and NO2, respectively. The best values of the Pearson correlation (0.34) and accuracy measured by the Receiver Operating Characteristic (ROC) curve (NO2 - 96.7% and PM10 - 90.4%) were for hospitalizations on the same day of exposure. Conclusions: The model was effective in predicting the number of hospitalizations of children and could be used as a tool in the hospital management of the studied region.