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	<title><![CDATA[Scipedia: Boletín Sociedad Mexicana de Computación Científica y sus Aplicaciones]]></title>
	<link>https://www.scipedia.com/sj/smcca</link>
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	<guid isPermaLink="true">https://www.scipedia.com/public/Aranda_2025a</guid>
	<pubDate>Tue, 09 Dec 2025 17:26:43 +0100</pubDate>
	<link>https://www.scipedia.com/public/Aranda_2025a</link>
	<title><![CDATA[Hacia un Método de Tractografía Basado en Información Microestructura por Medio de Optimización Convexa]]></title>
	<description><![CDATA[<p><span style="font-size: 10.24px;">This work presents a method to estimate the structure of white matter (axon bundles) by integrating microstructural information through convex optimization. The approach locally validates each segment using a physical diffusion model that assigns weights to possible trajectories, reducing spurious connections from the early stages of the process. The method is evaluated against classical algorithms using metrics such as LiFE, connectivity correlation, and the area under the ROC curve. The results show greater structural coherence and a reduction in false positives, with robust performance under noise. The study demonstrates the feasibility of incorporating microstructural information into the estimations, although it also reveals a higher number of false negatives and a high computational demand.</span></p>]]></description>
	<dc:creator>Ramón Aranda</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://www.scipedia.com/public/Balam_et_al_2025a</guid>
	<pubDate>Thu, 20 Nov 2025 15:51:24 +0100</pubDate>
	<link>https://www.scipedia.com/public/Balam_et_al_2025a</link>
	<title><![CDATA[A simple overview of least squares]]></title>
	<description><![CDATA[<div>In this work we aim to give an overview of least squares for curve fitting. The idea is to illustrate, for a broad audience, the mathematical foundations and practical methods used to solve this simple problem. We will consider four methods: the normal equations method, the QR factorization, the singular value decomposition (SVD), as well as a new approach based on neural networks. The last approach is not as common as the others, but it is very interesting because, in modern days, it has become a very important tool in many branches of modern knowledge, like data science (DS), machine learning (ML) and artificial intelligence (AI).</div><div>&nbsp;</div>]]></description>
	<dc:creator>R. Itza Balam</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://www.scipedia.com/public/Azofeifa_Moreles_2025a</guid>
	<pubDate>Tue, 02 Dec 2025 18:01:43 +0100</pubDate>
	<link>https://www.scipedia.com/public/Azofeifa_Moreles_2025a</link>
	<title><![CDATA[Hybrid Discontinuous Galerkin method for perturbations of the modified Helmholtz equation]]></title>
	<description><![CDATA[<p>The application of the Discontinuous Galerkin Method to elliptic problems usually leads to underdetermined linear systems, and penalization or suitable constraints are necessary. In this work, we address this issue for the modified Helmholtz equation. For this elliptic problem, we propose a hybrid numerical flux in the Discontinuous Galerkin method to introduce unknowns on the edges of the mesh, yielding a well-determined linear system. Performance is tested as a Poisson solver. Additionally, accurate approximations are presented for certain Helmholtz problems in Coastal Ocean Modeling.</p>]]></description>
	<dc:creator>Gerardo Tinoco-Guerrero</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://www.scipedia.com/public/Calderon_Juarez_2025a</guid>
	<pubDate>Mon, 15 Dec 2025 06:34:53 +0100</pubDate>
	<link>https://www.scipedia.com/public/Calderon_Juarez_2025a</link>
	<title><![CDATA[Coloración en gráficas de mapas en la Tierra y mapas en la Luna]]></title>
	<description><![CDATA[<p>La &#39;&#39;coloraci&oacute;n de mapas&#39;&#39; es un problema cl&aacute;sico en la &#39;&#39;Teor&iacute;a de Grafos&#39;&#39;, donde cada pa&iacute;s se modela como un v&eacute;rtice y las fronteras entre pa&iacute;ses como aristas. El &#39;&#39;Teorema de los Cuatro Colores&#39;&#39; establece que cualquier mapa plano puede colorearse con cuatro colores sin que dos regiones adyacentes compartan el mismo color. En este art&iacute;culo, exploramos la generalizaci&oacute;n del problema de coloraci&oacute;n de mapas al caso de la Tierra y la Luna, conocido como el &#39;&#39;&#39;Earth Moon Problem&#39;&#39;&#39;, propuesto por Ringel. Este problema busca determinar el n&uacute;mero m&iacute;nimo de colores necesarios para colorear un mapa donde cada pa&iacute;s en la Tierra y su colonia lunar deben recibir el mismo color, respetando la restricci&oacute;n de que las regiones adyacentes en cualquiera de los dos cuerpos celestes deben tener colores distintos. Nuestro principal aporte es demostrar que el problema de la &#39;&#39;3-coloraci&oacute;n&#39;&#39; de la Tierra-Luna es &#39;&#39;NP-completo&#39;&#39;, mediante una reducci&oacute;n desde &#39;&#39;3-SAT&#39;&#39;, lo que implica que no existe un algoritmo eficiente para resolverlo en general (suponiendo P &ne;&nbsp;NP). Adem&aacute;s, complementamos demostraciones previas que aparec&iacute;an incompletas en la literatura y modelamos el problema como un &#39;&#39;problema de satisfacci&oacute;n de restricciones&#39;&#39; (CSP), lo que permite un an&aacute;lisis m&aacute;s profundo de su complejidad computacional. Este trabajo no solo aporta una nueva demostraci&oacute;n de que el problema de coloraci&oacute;n de la Tierra-Luna con 3 colores es NP-completo, sino que tambi&eacute;n abre la puerta a futuros estudios sobre su dificultad para diferentes n&uacute;meros de colores. Por &uacute;ltimo, describir el problema de coloraci&oacute;n de la Tierra-Luna a trav&eacute;s de grafos, un caso abierto en la coloraci&oacute;n de grafos que extiende el problema de la coloraci&oacute;n de mapas planos. En t&eacute;rminos de grafos, esto se puede reformular como la b&uacute;squeda del &#39;&#39;&#39;n&uacute;mero crom&aacute;tico m&aacute;ximo&#39;&#39;&#39; de un grafo G que es la uni&oacute;n de dos grafos planares (sobre el mismo conjunto de v&eacute;rtices). Se demuestra mediante inducci&oacute;n que G es 12-coloreable, como observ&oacute; Heawood. Ringel conjetur&oacute; que el Problema de la Tierra-Luna era 8-coloreable pero Sulanke report&oacute; un ejemplo que requiere 9 colores, a&uacute;n no se conoce si existen configuraciones que requieran 10, 11 o 12 colores.</p>]]></description>
	<dc:creator>Ana Teresa Calderón Juárez</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://www.scipedia.com/public/Gonzaga_Sierra_Jimenez-Hernandez_2025a</guid>
	<pubDate>Tue, 09 Dec 2025 03:21:24 +0100</pubDate>
	<link>https://www.scipedia.com/public/Gonzaga_Sierra_Jimenez-Hernandez_2025a</link>
	<title><![CDATA[Cuantificación de incertidumbre sobre parámetros en modelos no lineales]]></title>
	<description><![CDATA[<p><span style="color: rgb(34, 34, 34); font-size: small; font-style: normal; font-weight: 400;">En este trabajo se estudia la cuantificaci&oacute;n de incertidumbre en par&aacute;metros de modelos no lineales mediante el enfoque bayesiano. Se parte del planteamiento cl&aacute;sico de problemas inversos, en los cuales los par&aacute;metros del modelo deben inferirse a partir de observaciones ruidosas y de un modelo directo formulado como un sistema de ecuaciones diferenciales. Dado que estos problemas suelen estar mal planteados, se introduce la inferencia bayesiana como estrategia de regularizaci&oacute;n, permitiendo incorporar informaci&oacute;n&nbsp;</span><em style="font-weight: 400; font-size: small; color: rgb(34, 34, 34);">a priori</em><span style="color: rgb(34, 34, 34); font-size: small; font-style: normal; font-weight: 400;">&nbsp;y actualizarla con datos mediante la distribuci&oacute;n&nbsp;</span><em style="font-weight: 400; font-size: small; color: rgb(34, 34, 34);">a posteriori</em><span style="color: rgb(34, 34, 34); font-size: small; font-style: normal; font-weight: 400;">. Se presentan los fundamentos te&oacute;ricos del enfoque bayesiano, as&iacute; como su aplicaci&oacute;n al caso particular del modelo de crecimiento log&iacute;stico, destacando el uso de m&eacute;todos computacionales para aproximar las distribuciones resultantes de los par&aacute;metros del modelo.</span></p>]]></description>
	<dc:creator>Gerardo Tinoco-Guerrero</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://www.scipedia.com/public/Rosas_Olivares-Quiroz_2024a</guid>
	<pubDate>Wed, 25 Sep 2024 06:48:14 +0200</pubDate>
	<link>https://www.scipedia.com/public/Rosas_Olivares-Quiroz_2024a</link>
	<title><![CDATA[Robustez y componente gigante de la red aeroportuaria de la República Mexicana mediante un análisis en Teoría de Grafos]]></title>
	<description><![CDATA[<p><span style="font-size: 14px; font-style: normal; font-weight: 400;">La robustez de un grafo es un par&aacute;metro que cuantifica la vulnerabilidad de una red bajo ataque en alguno de sus nodos. La robustez se define como la fracci&oacute;n de la componente gigante despu&eacute;s de que se eliminan ciertos nodos ya sea de forma aleatoria o bien de forma espec&iacute;fica. Usando estas dos &uacute;ltimas definiciones y un script de programaci&oacute;n en Python y NetworkX analizamos la din&aacute;mica de la componente conectada principal de la red de tr&aacute;fico a&eacute;reo de la Rep&uacute;blica Mexicana cuando se realizan ataques aleatorios y dirigidos en sus nodos. Asimismo, y a manera de comparaci&oacute;n, calcularemos la fracci&oacute;n cr&iacute;tica de nodos eliminados&nbsp;en funci&oacute;n de la densidad de la red para diferentes redes aleatorias usando el modelo de Gilbert y la red de tr&aacute;fico a&eacute;reo de la Rep&uacute;blica Mexicana con el fin de decidir si &eacute;sta &uacute;ltima es o no es vulnerable a dichos ataques. Los resultados obtenidos muestran el grado de vulnerabilidad de la red de tr&aacute;fico a&eacute;reo en la Rep&uacute;blica Mexicana.</span></p>]]></description>
	<dc:creator>Omar Martínez Rosas</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://www.scipedia.com/public/Gonzalez_et_al_2024b</guid>
	<pubDate>Tue, 19 Nov 2024 21:07:04 +0100</pubDate>
	<link>https://www.scipedia.com/public/Gonzalez_et_al_2024b</link>
	<title><![CDATA[Numerical Turing Patterns Formation on 3D Surfaces with a Linear Finite Element Method]]></title>
	<description><![CDATA[<p><span style="font-size: 12.8px; font-style: normal; font-weight: 400;">The purpose of this article is the numerical generation of Turing like patterns on 3D bounded surfaces, based on the analysis of Turing instability in certain types of reaction-diffusion systems in planar regions. We first include a well known 2D-study and analysis of these systems that yield the mathematical conditions under which spatial patterns arise, and which is based on temporal solutions where the classical Laplace diffusion operator is considered. Then, we extend the numerical study to 3D surfaces, employing the Laplace-Beltrami operator to simulate diffusion while keeping the same reaction terms, thus generating similar Turing patterns. The solutions to the involved systems will be calculated numerically using a semi-implicit time discretization in combination with a linear finite element method for spatial discretization using triangular meshes. Details about the numerical implementation are provided for clearness to a broader audience.</span></p>]]></description>
	<dc:creator>David Israel González Mena</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://www.scipedia.com/public/Vazquez-Pena_et_al_2024a</guid>
	<pubDate>Tue, 10 Sep 2024 01:42:04 +0200</pubDate>
	<link>https://www.scipedia.com/public/Vazquez-Pena_et_al_2024a</link>
	<title><![CDATA[Bayesian Estimation of the Basic Reproductive Number in a Chikungunya Outbreak in Acapulco, Guerrero]]></title>
	<description><![CDATA[<p><span style="font-size: 10.24px;">Chikungunya is a vector-borne viral disease caused by the mosquitoes&nbsp; <em>Aedes aegypti</em>&nbsp;and&nbsp; <em>Aedes albopictus</em>. There is no specific medical treatment or available vaccine. This work presents a host-vector model that considers two age structures: chronological age and asymptomatic infection age. This model accounts for variability in the relapse period and susceptibility to the chikungunya virus. From this system of integro-differential equations, a particular case is derived in the form of ordinary differential equations (ODEs). The objective of this study is to estimate the basic reproductive number </span><span style="font-size: 12.8px; font-style: normal; font-weight: 400;">R</span><span style="font-weight: 400; font-style: normal; font-size: 10.24px;">0</span><span style="font-size: 10.24px;">&nbsp;of the ODE model for a chikungunya outbreak that occurred in 2015 in Acapulco, Mexico. A Bayesian approach using Hamiltonian Monte Carlo methods is applied to estimate the parameters of the ODE model and subsequently estimate R0. We estimate that </span>R<span style="font-size: 10.24px;">0&nbsp;is 2.61, with a 95% credibility interval of (1.66, 3.80), which is consistent with other reports in the literature.</span></p>]]></description>
	<dc:creator>Cruz Vargas-De-León</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://www.scipedia.com/public/Dominguez_Perez_LOPEZ_2024a</guid>
	<pubDate>Thu, 12 Sep 2024 20:55:09 +0200</pubDate>
	<link>https://www.scipedia.com/public/Dominguez_Perez_LOPEZ_2024a</link>
	<title><![CDATA[A mathematical model of the formation of urine]]></title>
	<description><![CDATA[<p>In this work, a mathematical model of renal hemodynamics involved in urine production is studied. The model is formed by three sub-models: one corresponds to the glomerular filtration stage, which gives input to the blood that is processed in the kidney; another one is the corresponding to the renal autoregulation process which defines the blood flow that must enter the kidney, to maintain its correct functioning, even in the face of blood pressure variations; and the last sub-model corresponding to the reabsorption and secretion stages, the former corresponds to the process by which the kidneys recover useful substances from the glomerular filtrate and return them to the blood and in the latter the kidneys eliminate unwanted substances from the blood into the peritubular capillaries.</p>]]></description>
	<dc:creator>Fernanda Isabel Domínguez Pérez</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://www.scipedia.com/public/Zapata_et_al_2024a</guid>
	<pubDate>Wed, 09 Oct 2024 05:43:06 +0200</pubDate>
	<link>https://www.scipedia.com/public/Zapata_et_al_2024a</link>
	<title><![CDATA[Multicolor Parallel Fourth-Order Implicit Finite Difference for Solving the 2D Poisson Equation]]></title>
	<description><![CDATA[<p>The Poisson equation is central in numerous physics and engineering applications, such as computational fluid dynamics and acoustic wave propagation, where efficient and accurate solutions are essential. This study focuses on the numerical solution of the 2D Poisson equation with Dirichlet boundary conditions using a fourth-order compact Implicit Finite Difference scheme. Finite difference methods, particularly high-order schemes, are advantageous for solving the Poisson equation due to their efficiency and suitability for structured grids. To address the computational demands of large-scale problems, we incorporate domain decomposition and the Multicolor Successive Over Relaxation method, facilitating parallel computation. Through numerical experiments, we demonstrate that our approach significantly enhances both accuracy and computational efficiency when compared to traditional second-order methods.</p>]]></description>
	<dc:creator>R. Itza Balam</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://www.scipedia.com/public/Lopez_Perez_et_al_2024a</guid>
	<pubDate>Thu, 16 Nov 2023 01:23:05 +0100</pubDate>
	<link>https://www.scipedia.com/public/Lopez_Perez_et_al_2024a</link>
	<title><![CDATA[Seismic behavior of a six-story reinforced concrete building with base isolation in the City of Morelia]]></title>
	<description><![CDATA[<p>Base isolation is currently acknowledged as an effective strategy for controlling the seismic response of buildings. However, its implementation is usually limited to buildings considered essential or vital to society, resulting in these systems being rarely regarded as a feasible structural option. This study examines the impact of a base isolation system on the seismic response of a six-story building situated in a moderately seismic zone. Parameters such as floor drift and shear force demand were assessed to quantify the seismic response. These aspects are not only associated with potential damage but also play a critical role in predicting the initial construction cost. Additionally, these parameters are used as design criteria in building codes and regulations.</p>]]></description>
	<dc:creator>Juan Ignacio López Pérez</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://www.scipedia.com/public/Arias_et_al_2024a</guid>
	<pubDate>Thu, 23 Nov 2023 19:15:04 +0100</pubDate>
	<link>https://www.scipedia.com/public/Arias_et_al_2024a</link>
	<title><![CDATA[Blade's parameterization of a Francis 99 turbine using Bernstein polynomials]]></title>
	<description><![CDATA[<p>One of the fundamental problems in the manufacturing processes of turbomachine components is to provide them with an appropriate coordinate system. In other words, to provide them with a suitable mesh. Among the mesh generation processes and the resulting geometries for blades, there are methods that use functions related to the dynamics of the fluid&#39;s streamlines, and others, more practical, that are based on parameterization using &ldquo;natural&rdquo; coordinates on the surface of the element. This work demonstrates the implementation of Bernstein polynomials to parameterize the geometry of a Francis 99 turbine blade through a suitable least-squares problem. The methodology used is versatile and can be applied to blades of various geometries commonly used in turbomachine design.</p>]]></description>
	<dc:creator>Heriberto Arias</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://www.scipedia.com/public/Soule_Hernandez-Vela_2023a</guid>
	<pubDate>Sun, 29 Oct 2023 17:39:03 +0100</pubDate>
	<link>https://www.scipedia.com/public/Soule_Hernandez-Vela_2023a</link>
	<title><![CDATA[Influencia de los factores socioeconómicos en la mortalidad por COVID-19 en México]]></title>
	<description><![CDATA[<p><span style="font-weight: 400; font-style: normal; font-size: 10.24px;">La pandemia por el virus SARS-CoV-2 mostr&oacute; la necesidad de realizar estudios multidisciplinarios que ayudaran&nbsp;a entender el riesgo de mortalidad por COVID-19. En este trabajo se busc&oacute; determinar la influencia de los factores socioecon&oacute;micos que exist&iacute;an dentro de la poblaci&oacute;n mexicana mediante la aplicaci&oacute;n del modelo de regresi&oacute;n lineal m&uacute;ltiple, para esto el an&aacute;lisis se hizo a nivel municipal en las 3 primeras olas de la pandemia, definiendo grupos poblacionales homog&eacute;neos para identificar cu&aacute;les son los factores socioecon&oacute;micos&nbsp;que tienen mayor influencia y&nbsp;</span><span style="font-weight: 400; font-style: normal; font-size: 10.24px;">nos ayudan a describir</span><span style="font-weight: 400; font-style: normal; font-size: 10.24px;">&nbsp;el riesgo de fallecer por COVID-19 en M&eacute;xico.</span></p>]]></description>
	<dc:creator>Vanessa Soulé</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://www.scipedia.com/public/Peregrino_et_al_2023a</guid>
	<pubDate>Wed, 18 Oct 2023 05:59:10 +0200</pubDate>
	<link>https://www.scipedia.com/public/Peregrino_et_al_2023a</link>
	<title><![CDATA[A Mathematical Model to Estimate the COVID-19 Pandemic in Red Lights of México]]></title>
	<description><![CDATA[<p>The goal of this work is a dynamic and numerical study of a compartmental mathematical model in order to know the evolution of state variables of the pandemic caused by COVID-19 on red spotlights in M&eacute;xico. The model include 7 compartments and the results were compared with the classic SIR model, resulting that our predictions adjusted better the official data. A parameter sensitivity analysis is included.</p>]]></description>
	<dc:creator>JORGE LOPEZ LOPEZ</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://www.scipedia.com/public/Fraga_Almanza_et_al_2023a</guid>
	<pubDate>Thu, 26 Oct 2023 19:08:39 +0200</pubDate>
	<link>https://www.scipedia.com/public/Fraga_Almanza_et_al_2023a</link>
	<title><![CDATA[Simulación numérica sobre el efecto del plasmón localizado de nanopartículas de plata (Ag), bajo el marco de la teoría de Mie]]></title>
	<description><![CDATA[<p style="text-align: justify;"><span style="font-size: 10.24px;">Las nanopart&iacute;culas (Nps) de metales nobles como plata (Ag) y oro (Au) en las &uacute;ltimas d&eacute;cadas son objeto de extensa investigaci&oacute;n en el contexto de las nanociencias y la nanotecnolog&iacute;a, principalmente esto se debe a sus propiedades &oacute;pticas &uacute;nicas. En las Nps, el gas de electrones libres en ellas presenta propiedades de oscilaci&oacute;n resonante, fen&oacute;meno conocido como el plasm&oacute;n superficial localizado (PSL). Al irradiarse las Nps en el ultravioleta y visible del espectro, la absorci&oacute;n &oacute;ptica, depende fundamentalmente del material constitutivo, la geometr&iacute;a de la Nps y su entorno. La dispersi&oacute;n de la radiaci&oacute;n electromagn&eacute;tica de una esfera, es definida por la Teor&iacute;a de Mie. Los c&aacute;lculos al usar esta teor&iacute;a pueden llegar a ser largos e incluso imposibles para aquellos con recursos hardware limitados. Por lo tanto en esta investigaci&oacute;n que actualmente, se encuentra en desarroll&oacute;, se dise&ntilde;o e implanto una simulaci&oacute;n num&eacute;rica escrita en Python 3 para la obtenci&oacute;n de los coeficientes de Mie en nanopart&iacute;culas de plata (Ag)&nbsp; y contar con una herramienta computacional que gener&eacute; escenarios permitiendo el estudio y obtenci&oacute;n de los coeficientes de extinci&oacute;n de NPs de Ag, siendo esta metodolog&iacute;a f&aacute;cilmente adaptable para otros metales donde se pueden calcular y/o simular una variedad de propiedades &oacute;pticas.</span></p>]]></description>
	<dc:creator>José Luis Fraga Almanza</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://www.scipedia.com/public/Torres_Aguirre_et_al_2023a</guid>
	<pubDate>Thu, 26 Oct 2023 19:51:06 +0200</pubDate>
	<link>https://www.scipedia.com/public/Torres_Aguirre_et_al_2023a</link>
	<title><![CDATA[El algoritmo KMeans y el problema de los centroides iniciales]]></title>
	<description><![CDATA[<p style="text-align: justify;">El gran volumen de datos en el que se vive en la actualidad, hace evidente la necesidad de clasificar los datos para obtener relaciones, asociaciones y correlaciones de ellos. Para llevar a cabo esta clasificaci&oacute;n es necesario emplear algoritmos de agrupamiento del tipo no supervisado y particionales. Un candidato de este tipo es el algoritmo KMeans, ampliamente utilizado para resolver el problema de agrupamiento. Sin embargo, este algoritmo necesita de argumentos iniciales como lo son el n&uacute;mero de grupos y un conjunto de datos llamados centroides que son los representantes de cada uno de ellos. Esto puede ser una fortaleza pero a la vez puede representar limitaciones del algoritmo. Es por ello que en este trabajo se inicia con la caracterizaci&oacute;n general del algoritmo KMeans en base a la selecci&oacute;n de los centroides iniciales para despu&eacute;s estudiar la t&eacute;cnica de an&aacute;lisis de componentes principales y con esta proporcionar centroides iniciales &oacute;ptimos, pero esa etapa a&uacute;n est&aacute; en desarrollo y por tanto solo se presenta la idea inicial. La herramienta computacional es clave para el trabajo con alta densidad de datos es por eso que en este trabajo tambi&eacute;n se tiene como objetivo implantar un marco de trabajo llamado Apache Spark.</p>]]></description>
	<dc:creator>Gael Antonio Torres Aguirre</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://www.scipedia.com/public/Gamboa_et_al_2023a</guid>
	<pubDate>Thu, 26 Oct 2023 20:33:05 +0200</pubDate>
	<link>https://www.scipedia.com/public/Gamboa_et_al_2023a</link>
	<title><![CDATA[Algoritmo no supervisado para la segmentación de imágenes digitales de micrografías de nanopartíclas de plata (Ag).]]></title>
	<description><![CDATA[<p style="text-align: justify;"><span style="font-size: 10.24px;">La segmentaci&oacute;n de im&aacute;genes es un tipo espec&iacute;fico de agrupamiento de datos. El agrupamiento en este contexto es conocer grupos de p&iacute;xeles en las im&aacute;genes para obtener informaci&oacute;n relevante que por lo general se encuentra impl&iacute;cita en ellas. La Microscop&iacute;a Electr&oacute;nica de Transmisi&oacute;n (MET o TEM, por Transmission Electron Microscopy) es un una t&eacute;cnica experimental y de alto costo monetario, en la que un haz de electrones suficientemente acelerado colisiona con una muestra (nanopart&iacute;culas de plata (Ag) en este caso) delgada convenientemente preparada. En la muestra los electrones colisionan con respecto a algunas propiedades espec&iacute;ficas (grosor y tipo de &aacute;tomos), todo este proceso forma una imagen digital con distintas intensidades de gris que corresponde al grado de dispersi&oacute;n de los electrones incidentes. Propiedades como la cantidad y el di&aacute;metro de nanopart&iacute;culas existentes en este tipo de im&aacute;genes es relevante conocer de forma automatizada, ya que por lo general conocer este tipo de propiedades se hace mediante procedimientos laboriosos. Sin embargo, analizar este tipo de im&aacute;genes utilizando algoritmos no supervisados simplifica este tipo de trabajo, pero implica enfrentarse al problema de alta densidad de pixeles existentes en ellas. El algoritmo KMeans es del tipo no supervisado y utilizado para hacer segmentaci&oacute;n de p&iacute;xeles en im&aacute;genes de micrograf&iacute;as como lo indican algunos autores y que en este trabajo en etapa inicial es utilizado para contabilizar y obtener el di&aacute;metro de nanopart&iacute;culas de plata (Ag) que son las im&aacute;genes con las que se cuenta hasta el momento y son el resultado del grupo de trabajo experimental de la Divisi&oacute;n de Ciencias e Ingenier&iacute;a de la Universidad de Guanajuato Campus Le&oacute;n. Para llevar a cabo todo el procesamiento computacional se utilizar&aacute; una computadora de nueva generaci&oacute;n llamada Parallella que es un proyecto de bajo costo monetario, poco consumo energ&eacute;tico y dise&ntilde;ado para el alto desempe&ntilde;o de c&aacute;lculo num&eacute;rico, siendo estas caracter&iacute;sticas una opci&oacute;n que beneficiar&aacute; a este proyecto por no contar con infraestructura computacional adecuada.</span></p>]]></description>
	<dc:creator>Adianez Arhely Gamboa Rivas</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://www.scipedia.com/public/Puc_et_al_2023a</guid>
	<pubDate>Tue, 19 Sep 2023 19:55:04 +0200</pubDate>
	<link>https://www.scipedia.com/public/Puc_et_al_2023a</link>
	<title><![CDATA[General foundations of high-order immersed interface methods to solve interface problems]]></title>
	<description><![CDATA[<p>This work forms the foundation for addressing high-order immersed interface methods to solve interface problems and enables us to conduct in-depth examination of this theory. Here, we focus on the introduction a fourth-order finite-difference formulation to approximate the second-order derivative of discontinuous functions. The approach is based on the combination of a high-order implicit formulation and the immersed interface method. The idea is to modify the standard schemes by introducing additional contribution terms based on jump conditions. These contributions are calculated only at grid points where the stencil intersects with the interface. Here, we discuss the issues of implementing the one-dimensional Poisson equation and the heat conduction equation with discontinuous solutions as a three-point stencil for each grid point on the computational domain. In both cases, the resulting discretization approach yields a tridiagonal linear system with matrix coefficients identical to those employed for smooth solutions. We present several numerical experiments to verify the feasibility and accuracy of the method. Thus, this high-order method provides an attractive numerical framework that can efficiently lead to the solution to more complex problems.</p>]]></description>
	<dc:creator>M. Uh Zapata</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://www.scipedia.com/public/Munive_Hernandez_Morales_2022a</guid>
	<pubDate>Wed, 19 Oct 2022 06:03:10 +0200</pubDate>
	<link>https://www.scipedia.com/public/Munive_Hernandez_Morales_2022a</link>
	<title><![CDATA[Spatio-temporal point process analysis of Mexico State wildfires]]></title>
	<description><![CDATA[<p><span style="font-size: 12.8px; font-style: normal; font-weight: 400;">Wildfires are an example of a phenomenon that can be investigated using point process theory. We analyze public data from the National Forestry Commission. It consists of wildfire records, specifically their coordinates and dates of occurrence in Mexico State from 2010 to 2018. The spatial component was examined, and we found that wildfires tend to cluster. Afterwards, a time series analysis was conducted. This shows that the data comes from a stationary stochastic process. Finally, some spatio-temporal features that demonstrate the point process&#39; regular behavior in space and time were investigated. This research could be a reference to describe wildfire behavior in a specific space and time.</span></p>]]></description>
	<dc:creator>Luis Ramón Munive Hernández</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://www.scipedia.com/public/Juarez_Valencia_ROJAS_2022a</guid>
	<pubDate>Mon, 19 Sep 2022 19:09:11 +0200</pubDate>
	<link>https://www.scipedia.com/public/Juarez_Valencia_ROJAS_2022a</link>
	<title><![CDATA[Parameter estimation in ODEs. Modelling and computational issues]]></title>
	<description><![CDATA[<p><span style="color: rgb(102, 102, 102); font-size: 14px; font-style: normal; font-weight: 400; text-align: justify;">In this work we discuss a variational approach for the determination of the parameters of systems of ordinary differential equations (ODE). We construct a model for fitting observed noisy data into the given dynamical system. Also we explain in detail the advantage of using the adjoint equation method to compute the derivatives or gradients, which are needed for the application of gradient methods and quasi-Newton algorithms to find the minimum of the cost function. In particular we consider two classic iterative algorithms: the conjugate gradient (CG) algorithm and the BFGS algorithm. For educational purposes we try to explain several numerical and computational issues with some detail and illustrate them with the SEIRD epidemiological model.</span></p>]]></description>
	<dc:creator>Lorenzo Héctor Juárez Valencia</dc:creator>
</item>
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