Sensorless Speed Estimation of Induction Motors through Signal Analysis Based on Chaos Using Density of Maxima.

Three-phase induction motors are widely used in various industrial sectors and are responsible for a significant portion of the total electrical energy consumed. To ensure their efficient operation, it is necessary to apply control systems with specific algorithms able to estimate rotation speed accurately and with an adequate response time. However, the angular speed sensors used in induction motors are generally expensive and unreliable, and they may be unsuitable for use in hostile environments. This paper presents an algorithm for speed estimation in three-phase induction motors using the chaotic variable of maximum density. The technique used in this work analyzes the current signals from the motor power supply without invasive sensors on its structure. The results show that speed estimation is achieved with a response time lower than that obtained by classical techniques based on the Fourier Transform. This technique allows for the provision of motor shaft speed values when operated under variable load.

Misfire Detection in Automotive Engines Using a Smartphone through Wavelet and Chaos Analysis.

Besides the failures that cause accidents, there are the ones responsible for preventing the car's motion capacity. These failures cause inconveniences to the passengers and expose them to the dangers of the road. Although modern vehicles are equipped with a failure detection system, it does not provide an online approach to the drivers. Third-party devices and skilled labor are necessary to manage the data for failure characterization. One of the most common failures in engines is called misfire, and it happens when the spark is weak or inexistent, compromising the whole set. In this work, two algorithms are compared, based on Wavelet Multiresolution Analysis (WMA) and another using an approach performing signal analysis based on Chaos using the density of maxima (SAC-DM) to identify misfare in a combustion engine of a working automotive vehicle. Experimental tests were carried out in a car to validate the techniques for the engine without failure, with failure in one piston, and with two failed pistons. The results made it possible to obtain the failure diagnosis for 100% of the cases for both WMA and SAC-DM methods, but a shorter time window when using the last one.

Cox model and decision trees: an application to breast cancer data.

Objective: To evaluate, using semiparametric methodologies of survival analysis, the relationship between covariates and time to death of patients with breast cancer, as well as the determination discriminatory power in the conditional inference tree of patients who had cancer. Methods: A retrospective cohort study was conducted using data collected from medical records of women who had breast cancer and underwent treatment between 2005 and 2015 at the Hospital da Fundação de Assistencial da Paraíba in Campina Grande, State of Paraiba, Brazil. Survival curves were estimated using the Kaplan-Meier method, Cox regression, and conditional decision tree. Results: Women with triple-negative molecular subtypes had a shorter survival time compared to women with positive hormone receptors. The addition of hormone therapy reduced the risk of a patient dying by 5.5%, and the risk of a HER2-positive patient dying was 34.5% lower compared to those who were negative for this gene. Patients undergoing hormone therapy had a median survival time of 4 753 days. Conclusions: This paper shows a favorable scenario for the use of immunotherapy for patients with HER2 overexpression. Further studies could assess the effectiveness of immunotherapy in patients with other conditions, to favor the prognosis and better quality of life for the patient.

Cox model and decision trees: an application to breast cancer data

[ABSTRACT]. Objective. To evaluate, using semiparametric methodologies of survival analysis, the relationship between covariates and time to death of patients with breast cancer, as well as the determination discriminatory power in the conditional inference tree of patients who had cancer. Methods. A retrospective cohort study was conducted using data collected from medical records of women who had breast cancer and underwent treatment between 2005 and 2015 at the Hospital da Fundação de Assistencial da Paraíba in Campina Grande, State of Paraiba, Brazil. Survival curves were estimated using the Kaplan–Meier method, Cox regression, and conditional decision tree. Results. Women with triple-negative molecular subtypes had a shorter survival time compared to women with positive hormone receptors. The addition of hormone therapy reduced the risk of a patient dying by 5.5%, and the risk of a HER2-positive patient dying was 34.5% lower compared to those who were negative for this gene. Patients undergoing hormone therapy had a median survival time of 4 753 days. Conclusions. This paper shows a favorable scenario for the use of immunotherapy for patients with HER2 overexpression. Further studies could assess the effectiveness of immunotherapy in patients with other conditions, to favor the prognosis and better quality of life for the patient.

[RESUMEN]. Objetivo. Evaluar, mediante métodos semiparamétricos del análisis de supervivencia, la relación entre las covariables y el tiempo hasta la muerte de las pacientes con cáncer de mama, así como la determinación del poder discriminatorio en el árbol de inferencia condicional de las pacientes con cáncer. Métodos. Se llevó a cabo un estudio retrospectivo de cohortes con datos recogidos de los expedientes médicos de mujeres con cáncer de mama que recibieron tratamiento entre los años 2005 y 2015 en el Hospital da Fundação de Assistencial da Paraíba en Campina Grande, en el estado de Paraíba (Brasil). Se calcularon las curvas de supervivencia mediante el método Kaplan–Meier, el modelo de regresión de Cox y un árbol de decisiones condicionales. Resultados. Las mujeres con subtipos moleculares triple negativos tuvieron un período de supervivencia más corto en comparación con las mujeres con receptores hormonales positivos. La adición del tratamiento hormonal redujo en 5,5 % el riesgo de muerte de la paciente y en un 34,5% el riesgo de muerte de pacientes con cáncer HER2-positivo en comparación con las pacientes negativas para este gen. Las pacientes en tratamiento hormonal tuvieron un tiempo medio de supervivencia de 4 753 días. Conclusiones. Este estudio muestra un escenario favorable para el uso de la inmunoterapia en las pacientes con sobreexpresión del HER2. En futuros estudios se podría evaluar la eficacia de la inmunoterapia en pacientes con otras enfermedades, con el fin de favorecer el pronóstico y mejorar la calidad de vida de la paciente.

[RESUMO]. Objetivo. Avaliar, por meio de métodos semiparamétricos de análise de sobrevida, a relação entre covariáveis e tempo até a morte em pacientes com câncer de mama e determinar o poder discriminatório na árvore de inferência condicional em pacientes que tiveram câncer. Métodos. Estudo de coorte retrospectivo realizado a partir de dados coletados de prontuários médicos de mulheres com câncer de mama, tratadas entre 2005 e 2015 no Hospital da Fundação Assistencial da Paraíba em Campina Grande, no estado da Paraíba, Brasil. As curvas de sobrevida foram estimadas pelo método de Kaplan-Meier, regressão de Cox e árvore de decisão condicional. Resultados. As pacientes com subtipos moleculares de tumor triplo-negativo tiveram uma sobrevida menor em comparação com as que apresentavam tumor com receptores hormonais. O acréscimo de hormonioterapia reduziu o risco de morte em 5,5%. O risco de morte foi 34,5% menor em pacientes com HER2+ quando comparadas às que tinham tumores sem a expressão desse gene. A mediana de sobrevida das pacientes tratadas com hormonioterapia foi de 4 753 dias. Conclusões. A presente análise revela um cenário favorável para o uso de imunoterapia em pacientes com superexpressão de HER2. Outros estudos devem ser realizados para avaliar a eficácia da imunoterapia em outras doenças e os fatores que favorecem o prognóstico e melhoram a qualidade de vida dessas pessoas.

Cox model and decision trees: an application to breast cancer data / El modelo de regresión de Cox y los árboles de decisiones: su aplicación a los datos sobre cáncer de mama / Modelo de Cox e árvores de decisão: utilização com dados de câncer de mama

ABSTRACT Objective. To evaluate, using semiparametric methodologies of survival analysis, the relationship between covariates and time to death of patients with breast cancer, as well as the determination discriminatory power in the conditional inference tree of patients who had cancer. Methods. A retrospective cohort study was conducted using data collected from medical records of women who had breast cancer and underwent treatment between 2005 and 2015 at the Hospital da Fundação de Assistencial da Paraíba in Campina Grande, State of Paraiba, Brazil. Survival curves were estimated using the Kaplan-Meier method, Cox regression, and conditional decision tree. Results. Women with triple-negative molecular subtypes had a shorter survival time compared to women with positive hormone receptors. The addition of hormone therapy reduced the risk of a patient dying by 5.5%, and the risk of a HER2-positive patient dying was 34.5% lower compared to those who were negative for this gene. Patients undergoing hormone therapy had a median survival time of 4 753 days. Conclusions. This paper shows a favorable scenario for the use of immunotherapy for patients with HER2 overexpression. Further studies could assess the effectiveness of immunotherapy in patients with other conditions, to favor the prognosis and better quality of life for the patient.

RESUMEN Objetivo. Evaluar, mediante métodos semiparamétricos del análisis de supervivencia, la relación entre las covariables y el tiempo hasta la muerte de las pacientes con cáncer de mama, así como la determinación del poder discriminatorio en el árbol de inferencia condicional de las pacientes con cáncer. Métodos. Se llevó a cabo un estudio retrospectivo de cohortes con datos recogidos de los expedientes médicos de mujeres con cáncer de mama que recibieron tratamiento entre los años 2005 y 2015 en el Hospital da Fundação de Assistencial da Paraíba en Campina Grande, en el estado de Paraíba (Brasil). Se calcularon las curvas de supervivencia mediante el método Kaplan-Meier, el modelo de regresión de Cox y un árbol de decisiones condicionales. Resultados. Las mujeres con subtipos moleculares triple negativos tuvieron un período de supervivencia más corto en comparación con las mujeres con receptores hormonales positivos. La adición del tratamiento hormonal redujo en 5,5 % el riesgo de muerte de la paciente y en un 34,5% el riesgo de muerte de pacientes con cáncer HER2-positivo en comparación con las pacientes negativas para este gen. Las pacientes en tratamiento hormonal tuvieron un tiempo medio de supervivencia de 4 753 días. Conclusiones. Este estudio muestra un escenario favorable para el uso de la inmunoterapia en las pacientes con sobreexpresión del HER2. En futuros estudios se podría evaluar la eficacia de la inmunoterapia en pacientes con otras enfermedades, con el fin de favorecer el pronóstico y mejorar la calidad de vida de la paciente.

RESUMO Objetivo. Avaliar, por meio de métodos semiparamétricos de análise de sobrevida, a relação entre covariáveis e tempo até a morte em pacientes com câncer de mama e determinar o poder discriminatório na árvore de inferência condicional em pacientes que tiveram câncer. Métodos. Estudo de coorte retrospectivo realizado a partir de dados coletados de prontuários médicos de mulheres com câncer de mama, tratadas entre 2005 e 2015 no Hospital da Fundação Assistencial da Paraíba em Campina Grande, no estado da Paraíba, Brasil. As curvas de sobrevida foram estimadas pelo método de Kaplan-Meier, regressão de Cox e árvore de decisão condicional. Resultados. As pacientes com subtipos moleculares de tumor triplo-negativo tiveram uma sobrevida menor em comparação com as que apresentavam tumor com receptores hormonais. O acréscimo de hormonioterapia reduziu o risco de morte em 5,5%. O risco de morte foi 34,5% menor em pacientes com HER2+ quando comparadas às que tinham tumores sem a expressão desse gene. A mediana de sobrevida das pacientes tratadas com hormonioterapia foi de 4 753 dias. Conclusões. A presente análise revela um cenário favorável para o uso de imunoterapia em pacientes com superexpressão de HER2. Outros estudos devem ser realizados para avaliar a eficácia da imunoterapia em outras doenças e os fatores que favorecem o prognóstico e melhoram a qualidade de vida dessas pessoas.

Análise espacial da distribuição dos casos de dengue e sua relação com fatores socioambientais no estado da Paraíba, Brasil, 2007-2016 / Spatial analysis of the distribution of dengue cases and its relationship with socio-environmental factors in the state of Paraíba, Brazil, 2007-2016

RESUMO A dengue é um grave problema de saúde pública, principalmente em países que apresentam condições socioambientais propícias para o desenvolvimento e proliferação do seu agente transmissor. Este estudo teve como objetivo analisar a distribuição espacial da incidência da dengue no estado da Paraíba entre 2007 e 2016, avaliando a existência de dependência geográfica e sua relação com fatores socioeconômicos e ambientais. Estudo ecológico, tendo com unidade de análise os 223 municípios do estado. Utilizaram-se o Índice de Moran global e local e a estatística c de Geary para avaliar a autocorrelação espacial da dengue e a associação com variáveis socioambientais. As análises foram realizadas por meio do software estatístico R Core Team versão 3.3.2. Ao analisar a distribuição de casos de dengue nos municípios da Paraíba, pode-se identificar que a doença vem avançando e acometendo maior número de cidades a cada ano. A doença esteve presente em todos as cidades analisadas, o que demonstrou a necessidade de implementar ações de prevenção da doença em todo o estado. Mediante esta pesquisa, ficou claro que a dengue, no estado da Paraíba, não é determinada por fator único e isolado, mas sim, pela combinação de vários fatores do contexto socioeconômico e ambiental.

ABSTRACT Dengue is a serious public health problem, especially in countries that have favorable socio-environmental conditions for the development and proliferation of its transmitting agent. This study aimed to analyze the spatial distribution of the incidence of dengue in the state of Paraíba between 2007 and 2016, evaluating the existence of geographic dependence and its relationship with socioeconomic and environmental factors. Ecological study, with the unit of analysis of the 223 municipalities in the state. The global and local Moran Index and the Geary c statistic were used to assess the spatial autocorrelation of dengue and the association with socioenvironmental variables. The analyzes were performed using statistical software R Core Team version 3.3.2. When analyzing the distribution of dengue cases in the municipalities of Paraíba, it can be identified that the disease has been advancing and affecting a greater number of cities each year. The disease was present in all the cities analyzed, which demonstrated the need to implement disease prevention actions across the state. Through this research, it became clear that dengue, in the state of Paraíba, is not determined by a single and isolated factor, but, rather, by the combination of several factors of the socioeconomic and environmental context.