Towards Association Rule-based Item Selection Strategy in Computerized Adaptive Testing

One of the most important stages of Computerized Adaptive Testing is the selection of items, in which various methods are used, which have certain weaknesses at the time of implementation. Therefore, in this paper, it is proposed the integration of Association Rule Mining as an item selection criterion in a CAT system. We present the analysis of association rule mining algorithms such as Apriori, FP-Growth, PredictiveApriori and Tertius into two data set with the purpose of knowing the advantages and disadvantages of each algorithm and choose the most suitable. We compare the algorithms considering number of rules discovered, average support and confidence, and velocity. According to the experiments, Apriori found rules with greater confidence, support, in less time.Una de las etapas más importantes de las pruebas adaptativas informatizadas es la selección de ítems, en la cual se utilizan diversos métodos que presentan ciertas debilidades al momento de su aplicación. Así, en este trabajo, se propone la integración de la minería de reglas de asociación como criterio de selección de ítems en un sistema CAT. Se presenta el análisis de algoritmos de minería de reglas de asociación como Apriori, FP-Growth, PredictiveApriori y Tertius en dos conjuntos de datos con el fin de conocer las ventajas y desventajas de cada algoritmo y elegir el más adecuado. Se compararon los algoritmos teniendo en cuenta el número de reglas descubiertas, el soporte y confianza promedios y la velocidad. Según los experimentos, Apriori encontró reglas con mayor confianza y soporte en un menor tiempo

Software para el aprendizaje de la lectoescritura basado en control gestual de manos y realidad aumentada

Con los avances tecnológicos, distintos proyectos desarrollaron soluciones satisfactorias a problemáticas de aprendizaje principalmente relacionadas con el área de las matemáticas y la medicina utilizando realidad aumentada e interfaces humano-máquina, siendo un área de oportunidad la aplicación de estas tecnologías en el aprendizaje de la lectoescritura. Dado que según la última prueba PISA, aplicada en 2018, México se sitúa en el nivel 2 de comprensión lectora, por debajo del promedio de los países miembros de la Organización para la Cooperación y el Desarrollo Económico (OCDE), en respuesta a esta problemática, se desarrolló una herramienta que combina la realidad aumentada e interfaces humano-máquina aplicado a la lectoescritura. Esta aplicación despliega modelos tridimensionales renderizados a través de un dispositivo con cámara, permitiendo a los usuarios interactuar con estos modelos mediante el reconocimiento de movimientos de las manos. La aplicación fue probada exitosamente en estudiantes de jardín de niños divididos en dos grupos: rezagados y adelantados en el aprendizaje de las letras. Los resultados demostraron que esta herramienta es entretenida y efectiva, proporcionando un recurso significativo para profesores y maestros en la enseñanza de la lectoescritura

ANTENA PARA COSECHA DE ENERGÍA DENTRO Y FUERA DE BANDA EN RADIOFRECUENCIA DE 2.4 GHZ (ANTENNA FOR ENERGY HARVESTING WITHIN AND OUT OF BAND IN RADIOFREQUENCY OF 2.4 GHZ)

ResumenLa cosecha de energía en las bandas de radiofrecuencia (RF) es una solución prometedora para lograr sistemas de comunicación inalámbricos energéticamente auto-sustentables. La cosecha de energía busca captar energía del entorno que pueda ser recolectada y utilizada para alimentar dispositivos electrónicos. En este trabajo se analizan las oportunidades de cosecha de energía en RF dentro y fuera de la banda ISM de 2.4 GHz a través del diseño y simulación una de antena F-invertida impresa (PIFA). Se utiliza información de la energía disponible en el espectro en la banda de 1800 a 2600 MHz por medio de una campaña de medición espectral en la ciudad de San Luis Potosí.  Al analizar el ancho de banda de la antena se logra estimar la cantidad de energía de RF que pudiera ser cosechada dentro y fuera de la banda ISM de 2.4 GHz en el rango de 2-3 GHz.Palabras Claves: cosecha de energía, diseño de antena F-invertida impresa, radiofrecuencia. AbstractEnergy harvesting in the radio frequency (RF) bands is a promising solution to achieve self-sustaining energy-efficient wireless communication systems. The energy harvesting seeks to capture energy from the environment that can be collected and used to power electronic devices. This paper analyzes the opportunities for harvesting energy in RF inside and outside the 2.4 GHz ISM band through the design and simulation of a printed inverted F antenna (PIFA). Information on the energy available in the spectrum in the 1800-2600 MHz band is used through a spectral measurement campaign in the city of San Luis Potosí. By analyzing the bandwidth of the antenna, it is possible to estimate the amount of RF energy that could be harvested inside and outside the 2.4 GHz ISM band in the 2-3 GHz range.Keywords: energy harvesting, printed inverted F antenna design, radiofrequency

Multiple software product lines to configure applications of internet of things

Software product lines (SPL) emulate the industrial production lines that are capable of generating large volumes of products through reuse schemes and mass production. A multi product line (MPL) aims to reuse of several SPL. Feature models are often used to manage the existing resources of SPLs and define valid products through notations and relationships such as mandatory, optional, and alternative features. The main contribution of this study is a method to manage the variability of multiple SPL and generate a new portfolio of products for Internet of Things (IoT). For this, the problem of developing a universal feature model (FM) for an MPL from merging the FMs of the individual SPLs with a Search-Based Software Engineering (SBSE) technique is addressed. In addition, the authors propose a multi-objective optimisation model to maximise the reusability and compatibility between features and minimise the development cost. The model facilitates the design of an MPL-feature model. Authors' empirical results show that the proposed model solved by genetic algorithms allows to configure a variety of software products and to determine the scope of the MPL

IMPLEMENTACIÓN DE RED CELULAR DE BAJO COSTO PARA COMUNIDADES RURALES BASADA EN SDR Y OPENBTS (IMPLEMENTATION OF A LOW COST CELLULAR NETWORK FOR RURAL COMMUNITIES BASED ON SDR AND OPENBTS)

El acceso a servicios de telecomunicaciones en México es hoy en día un gran reto. Principalmente, en comunidades rurales cuya ubicación geográfica y número de habitantes hacen que el despliegue de infraestructura no sea económicamente factible para los operadores de telecomunicaciones tradicionales. En este trabajo, se aborda el problema de la falta de servicios básicos de telefonía celular (i.e. voz y mensajes SMS) a través de la implementación de una estación base celular GSM basada en transceptores de radiofrecuencia de bajo costo y software de código abierto, que permiten su despliegue e implementación en comunidades de difícil acceso y pocos habitantes. Conjugando las tecnologías de Radio Definido por Software (SDR, por sus siglas en inglés) con herramientas de software libre con base en OpenBTS, es posible configurar e implementar rápidamente una estación base de telefonía celular que permite a los usuarios realizar llamadas de voz y enviar mensajes de texto SMS entre los elementos de la red. Asimismo, la estación base les permite realizar y recibir llamadas de usuarios de operadores externos en cualquier parte del mundo a través de voz sobre IP. De este modo, es factible proporcionar telefonía celular en comunidades rurales actualmente incomunicadas.The access to telecommunications services in Mexico is nowadays a great challenge. Mainly in rural communities whose geographic location and number of inhabitants make the deployment of infrastructure not economically feasible to traditional telecommunications carriers. In this work, the problem of the lack of basic cellular telephony services (i.e. voice and SMS text messages) is addressed through the implementation of a GSM cellular base station based on low cost radio frequency transceivers and open source software, which allow their deployment and implementation in communities of difficult access and few inhabitants. By combining Software Defined Radio (SDR) technologies with free software tools based on OpenBTS, it is possible to quickly configure and implement a cellular telephone base station that allows users to make voice calls and send SMS text messages between the elements of the network. Likewise, the base station allows them to make and receive calls from users of external operators anywhere in the world through voice over IP. In this way, it is feasible to provide mobile telephony in rural communities that are currently isolated

The immunogenetic diversity of the HLA system in Mexico correlates with underlying population genetic structure

We studied HLA class I (HLA-A, -B) and class II (HLA-DRB1, -DQB1) allele groups and alleles by PCR-SSP based typing in a total of 15,318 mixed ancestry Mexicans from all the states of the country divided into 78 sample sets, providing information regarding allelic and haplotypic frequencies and their linkage disequilibrium, as well as admixture estimates and genetic substructure. We identified the presence of 4268 unique HLA extended haplotypes across Mexico and find that the ten most frequent (HF > 1%) HLA haplotypes with significant linkage disequilibrium (Δ’≥0.1) in Mexico (accounting for 20% of the haplotypic diversity of the country) are of primarily Native American ancestry (A*02~B*39~DRB1*04~DQB1*03:02, A*02~B*35~DRB1*08~DQB1*04, A*68~B*39~DRB1*04~DQB1*03:02, A*02~B*35~DRB1*04~DQB1*03:02, A*24~B*39~DRB1*14~DQB1*03:01, A*24~B*35~DRB1*04~DQB1*03:02, A*24~B*39~DRB1*04~DQB1*03:02, A*02~B*40:02~DRB1*04~DQB1*03:02, A*68~B*35~DRB1*04~DQB1*03:02, A*02~B*15:01~DRB1*04~DQB1*03:02). Admixture estimates obtained by a maximum likelihood method using HLA-A/-B/-DRB1 as genetic estimators revealed that the main genetic components in Mexico as a whole are Native American (ranging from 37.8% in the northern part of the country to 81.5% in the southeastern region) and European (ranging from 11.5% in the southeast to 62.6% in northern Mexico). African admixture ranged from 0.0 to 12.7% not following any specific pattern. We were able to detect three major immunogenetic clusters correlating with genetic diversity and differential admixture within Mexico: North, Central and Southeast, which is in accordance with previous reports using genome-wide data. Our findings provide insights into the population immunogenetic substructure of the whole country and add to the knowledge of mixed ancestry Latin American population genetics, important for disease association studies, detection of demographic signatures on population variation and improved allocation of public health resources.Fil: Barquera, Rodrigo. Max Planck Institute For The Science Of Human History; Alemania. Instituto Nacional de Antropología E Historia. Escuela Nacional de Antropología E Historia; MéxicoFil: Hernández Zaragoza, Diana Iraíz. Técnicas Genéticas Aplicadas A la Clínica (tgac); México. Instituto Nacional de Antropología E Historia. Escuela Nacional de Antropología E Historia; MéxicoFil: Bravo Acevedo, Alicia. Instituto Mexicano del Seguro Social; MéxicoFil: Arrieta Bolaños, Esteban. Universitat Essen; AlemaniaFil: Clayton, Stephen. Max Planck Institute For The Science Of Human History; AlemaniaFil: Acuña Alonzo, Víctor. Instituto Nacional de Antropología E Historia, Mexico; MéxicoFil: Martínez Álvarez, Julio César. Instituto Mexicano del Seguro Social; MéxicoFil: López Gil, Concepción. Instituto Mexicano del Seguro Social; MéxicoFil: Adalid Sáinz, Carmen. Instituto Mexicano del Seguro Social; MéxicoFil: Vega Martínez, María del Rosario. Hospital Central Sur de Alta Especialidad; MéxicoFil: Escobedo Ruíz, Araceli. Instituto Mexicano del Seguro Social; MéxicoFil: Juárez Cortés, Eva Dolores. Instituto Mexicano del Seguro Social; MéxicoFil: Immel, Alexander. Max Planck Institute For The Science Of Human History; Alemania. Christian Albrechts Universitat Zu Kiel; AlemaniaFil: Pacheco Ubaldo, Hanna. Instituto Nacional de Antropología E Historia. Escuela Nacional de Antropología E Historia; MéxicoFil: González Medina, Liliana. Instituto Nacional de Antropología E Historia. Escuela Nacional de Antropología E Historia; MéxicoFil: Lona Sánchez, Abraham. Instituto Nacional de Antropología E Historia. Escuela Nacional de Antropología E Historia; MéxicoFil: Lara Riegos, Julio. Universidad Autónoma de Yucatán; MéxicoFil: Sánchez Fernández, María Guadalupe de Jesús. Instituto Mexicano del Seguro Social; MéxicoFil: Díaz López, Rosario. Hospital Central Militar, Mexico City; MéxicoFil: Guizar López, Gregorio Ulises. Hospital Central Militar, Mexico City; MéxicoFil: Medina Escobedo, Carolina Elizabeth. Instituto Mexicano del Seguro Social; MéxicoFil: Arrazola García, María Araceli. Instituto Mexicano del Seguro Social; MéxicoFil: Montiel Hernández, Gustavo Daniel. Instituto Nacional de Antropología E Historia. Escuela Nacional de Antropología E Historia; MéxicoFil: Hernández Hernández, Ofelia. Técnicas Genéticas Aplicadas a la Clínica ; MéxicoFil: Ramos de la Cruz, Flor del Rocío. Instituto Mexicano del Seguro Social; MéxicoFil: Juárez Nicolás, Francisco. Instituto Nacional de Pediatría; MéxicoFil: Pantoja Torres, Jorge Arturo. Instituto Mexicano del Seguro Social; MéxicoFil: Rodríguez Munguía, Tirzo Jesús. Hospital General Norberto Treviño Zapata; MéxicoFil: Juárez Barreto, Vicencio. Hospital Infantil de Mexico Federico Gomez; MéxicoFil: Gonzalez-Jose, Rolando. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Centro Nacional Patagónico. Instituto Patagónico de Ciencias Sociales y Humanas; Argentin

Mis casos clínicos de especialidades odontológicas

Libro que muestra la atención de casos clínicos particulares referente a las diferentes especialidades odontológicasLibro que muestra la atención de casos clínicos particulares referente a las diferentes especialidades odontológicasUniversidad Autónoma de Campeche Universidad Autónoma del Estado de Hidalgo Universidad Autónoma del Estado de Méxic

A Model for Naturalistic Programming with Implementation

While the use of natural language for software development has been proposed since the 1960s, it was limited by the inherent ambiguity of natural languages, which people resolve using reasoning in a text or conversation. Programming languages are formal general-purpose or domain-specific alternatives based on mathematical formalism and which are at a remove from natural language. Over the years, various authors have presented studies in which they attempted to use a subset of the English language for solving particular problems. Each author approached the problem by covering particular domains, rather than focusing on describing general elements that would help other authors develop general-purpose languages, instead focusing even more on domain-specific languages. The identification of common elements in these studies reveals characteristics that enable the design and implementation of general-purpose naturalistic languages, which requires the establishment of a programming model. This article presents a conceptual model which describes the elements required for designing general-purpose programming languages and which integrates abstraction, temporal elements and indirect references into its grammar. Moreover, as its grammar resembles natural language, thus reducing the gap between problem and solution domains, a naturalistic language prototype is presented, as are three test scenarios which demonstrate its characteristics

Integration of Sentiment Analysis of Social Media in the Strategic Planning Process to Generate the Balanced Scorecard

Strategic planning (SP) requires attention and constant updating and is a crucial process for guaranteeing the efficient performance of companies. This article proposes a novel approach applied in a case study whereby a balanced scorecard (BSC) was generated that integrated sentiment analysis (SA) of social media (SM) and took advantage of the valuable knowledge of these sources. In this study, opinions were consolidated in the main dataset to incorporate sentiments regarding the strategic part of a restaurant in a tourist city. The proposed methodology began with the selection of the company. Information was then acquired to apply pre-processing, processing, evaluation, and validation that is capitalized in a BSC to support strategic decision-making. Python support was used in the model and comprised lexicon and machine learning approaches for the SA. The significant knowledge in the comments was automatically oriented toward the key performance indicators (KPIs) and perspectives of a BSC that were previously determined by a group of opinion leaders of the company. The methods, techniques, and algorithms of SA and SP showed that unstructured textual information can be processed and capitalized efficiently for optimal management and decision-making. The results revealed an improvement (reduced effort and time) to produce a more robust and comprehensive BSC with the support and validation of experts. Moreover, new resources and approaches were developed to implement more efficient SP. The model was based on the efficient coupling of both fields of study

Integration of Sentiment Analysis of Social Media in the Strategic Planning Process to Generate the Balanced Scorecard

Strategic planning (SP) requires attention and constant updating and is a crucial process for guaranteeing the efficient performance of companies. This article proposes a novel approach applied in a case study whereby a balanced scorecard (BSC) was generated that integrated sentiment analysis (SA) of social media (SM) and took advantage of the valuable knowledge of these sources. In this study, opinions were consolidated in the main dataset to incorporate sentiments regarding the strategic part of a restaurant in a tourist city. The proposed methodology began with the selection of the company. Information was then acquired to apply pre-processing, processing, evaluation, and validation that is capitalized in a BSC to support strategic decision-making. Python support was used in the model and comprised lexicon and machine learning approaches for the SA. The significant knowledge in the comments was automatically oriented toward the key performance indicators (KPIs) and perspectives of a BSC that were previously determined by a group of opinion leaders of the company. The methods, techniques, and algorithms of SA and SP showed that unstructured textual information can be processed and capitalized efficiently for optimal management and decision-making. The results revealed an improvement (reduced effort and time) to produce a more robust and comprehensive BSC with the support and validation of experts. Moreover, new resources and approaches were developed to implement more efficient SP. The model was based on the efficient coupling of both fields of study