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Classifying pulmonary nodule CT images as either benign or malignant, using a trained Residual Neural Network.

Adaptación de la plantilla IEEE for journals, para ser utilizada en los cursos de Ingeniería de Sistemas en la Universidad Minuto de Dios.

Scientific publication template or paper for beginners.

Laboratory where LEX is compared to C

The viscosity of a particular fluid is an interesting parameter that plays an important role in fluid dynamics of that fluid. We chose the common household cooking item canola oil. Using a ball drop, we set out to measure viscosity at various temperatures and create a model for the viscosity of canola oil as a function of temperature, as well as an accurate measurement for viscosity at room temperature. It was found that the viscosity between 0 and 40 degrees Celsius can be approximated using an exponential function and that an estimation for viscosity at room temperature was not very difficult to obtain. The precision of this measurement was limited by uncertainty in lab equipment used to measure various quantities as well as the image analysis software we used and the limited frame-rate of our camera.

Although the analysis of data is a task that has gained the interest of the statistical community in recent years and whose familiarity with the statistical computing environment, they encourage the current statistical community (to students and teachers of the area) to complete statistical analysis reproducible by means of the tool R. However for years there has been a gap between the calculation of matrices on a large scale and the term "big data", in this work the Normalized Cut algorithm for images is applied. Despite the expected, the R environment to do image analysis is poorly, in comparison with other computing platforms such as the Python language or with specialized software such as OpenCV. Being well known the absence of such function, in this work we share an implementation of the Normalized Cut algorithm in the R environment with extensions to programs and processes performed in C ++, to provide the user with a friendly interface in R to segment images. The article concludes by evaluating the current implementation and looking for ways to generalize the implementation for a large scale context and reuse the developed code. Key words: Normaliced Cut, image segmentation, Lanczos algorithm, eigenvalues and eigenvectors, graphs, similarity matrix, R (the statistical computing environment), open source, large scale and big data.

O conceito de automação residencial é definido como o conjunto de serviços proporcionados por sistemas tecnológicos integrados, sendo a melhor maneira de satisfazer as necessidades básicas de segurança, comunicação, gestão energética e conforto de uma habitação. Seguindo essa concepção, surgiu-se a ideia da criação de um Kit automatizado para janelas utilizando a plataforma Arduíno, visando a solução de problemas do dia a dia como o transtorno causado pela chuva e principalmente, gerando praticidade e comodidade para os cidadãos.

se presenta el desarrollo de un algoritmo bajo código fuente JavaScript para la solución de la ecuación de flujo crítico (2). Se implementó un lenguaje de programación orientado a objetos para sistemas Android 4.0 o superiores a partir de procesos iterativos e incrementales (Desarrollo ágil). Se utilizó el método numérico de Newton-Raphson para determinar la profundidad crítica de sietes secciones hidráulicas (Rectangular, trapezoidal, trapezoidal asimétrico, triangular, triangular asimétrico, parabólico y circular). Con el propósito de acelerar y garantizar el nivel de convergencia para cada una de las secciones se obtuvo una función potencial para establecer el valor semilla en el proceso iterativo, este valor se asocia de manera directa a las condiciones preestablecidas del problema hidráulico. La aplicación calcula la profundidad crítica, velocidad crítica, área

This paper describes the use of the LaTeX2e sagej.cls class file for setting papers to be submitted to a SAGE Publications journal. The template can be downloaded here. v1.2, 14 Jan 2017