Ranking Interesting Changes in Correlation Coefficient Matrix Results from Varying Data Partitions in Causal Graphic Modeling

Problem In life we need to compare situations in order to select the best solution. The study in this paper is about analyzing data (variables), which is also called data mining. There are situations where it is not enough to compare variables among themselves at one specific moment. Sometimes it is necessary to compare the behavior of variables at different periods of time and know how they behave at different times in order to select the best arrangements for any situation. Method To find correlation among variables, traffic intersections were simulated so they could be compared, since the correlation coefficient matrix is normalized. This type of matrix was used to compare intersections in different time variances to find the most interesting information. By comparing each point from the first matrix with each point to the second matrix one can find the intersections that are busier and have a larger difference from the others. Also, two formulas were found to help find the most interesting correlations; in one of those I modified the harmonic mean formula to obtain a balance between two important details. Results By using these two new formulas the most interesting information between variables may be found, such as those that are the most popular or least popular (average value) and those that are very different from or very similar to each other (difference value) at different times. “Rank 1” is the value of the balance between the average and the difference, with values ranging between 0 and 0.6. A 0 means that those intersections have very low values in averages and differences, and 0.6 means the opposite. The formula “Rank 2” is based on assigning weight into the average and the difference categories. Once the formula is applied, the values would be between 0 and 1, where 0 will mean that their average or their difference is low, depending on which one was assigned more weight. A value of 1 would mean the opposite. The weight depends on what is needed for a specific situation. Conclusions By comparing two correlation coefficient matrices from any type of data in different time periods (since this type of matrix is already normalized) anybody can find out very interesting information for any situations where we need to know how different and popular any types of variables may be. Finally, the most interesting information may be identified by calculating the average or the difference between variables. As an example, these formulas were used to compare traffic intersections, and the result obtained was a rank with the most popular intersections to the less important intersections, which confirmed previously observed traffic patterns

Investigating the Development of Possible Selves in Teacher Education: Candidate Perceptions of Hopes, Fears, and Strategies

The theory of possible selves, as proposed by Marcus and Nurius (1986), framed a two-staged instrumental case study designed to give voice to an often-neglected source of insight: teacher candidates. The collection and analysis of hopes, fears, and process strategies gathered from a cross-section of thirteen candidates and alumni from a private Midwestern institution informed teacher educator practice and increased understanding in regards to influences that shaped teacher identity development. The applied theoretical framework allowed for the assessment of participants’ knowledge, skills, and dispositions, aided in the identification of perceived preparation needs, and enabled an appraisal of program effectiveness. Findings affirmed the utilitarian, investigative, and evaluative qualities of the theory of possible selves. Embedded use of the reflective framework throughout coursework may motivate and regulate candidate actions and yield adaptive experts capable of nurturing identity development beyond the preparation duration

Political risk management practices of Multinational Corporations: their approaches to deal with developing countries under economic sanctions

This article explores adjustments to the traditional political risk management practices followed by Multinational Corporations (MNCs) in their international operations to incorporate an increasingly concerning risk arising from the more frequent imposition of economic sanctions on developing countries over the last ten years for political purposes. In order to identify the main determinants of this risk and its consequences, a literature review is conducted, highlighting the models proposed by Tsebelis (1990) and Kakutami (2017) as the main frameworks to understand the dynamics for sanctions impositions, their frequency and the management of this risk by traditional MNCs from developed countries. Kakutami’s model is further enhanced in this article with a game theoretical model to understand the dynamic behavior of MNCs under this context, considering evidences of a growing presence in international markets of MNCs from developing countries, whose motivations for their expansion are explored. Finally, different political risk mitigating strategies are reviewed to explore their suitability to MNCs, with particular emphasis on the use of insurance to cover this risk and its effects on MNCs’ willingness to engage with sanctioned countries. As a general finding, from a reputational point of view, MNCs should take a more active role in their network analysis to identify their direct and indirect exposure to this risk, given the more frequent imposition of sanctions with an extraterritorial reach

An Examination of External Influences and Internal Issues Challenging Teacher Education Today

Today’s educators are not solely content experts, but reflective practitioners competent in theory and complex learning processes. They are obligated to construct classrooms to meet the diverse needs of each child within a culture of global competition and increased levels of accountability. Prior studies amplify a necessary focus on preparing teachers capable of meeting the needs of each student from day one on the job. However, a myriad of obstacles facing teacher preparation identified throughout research provide clear direction for additional attention. The following is an investigation of external influences and internal issues that challenged the current model of teacher preparation programs. Insights may serve to inform teacher educator research and support programs in the professional development of future teachers. Historically teacher education programs have undergone sharp criticisms in regards to their influence on teacher effectiveness (Book & Freeman, 1986; Cochran­-Smith & Zeichner, 2005; Cole & Knowles, 1993; Hollingsworth, 1989; Holt­-Reynolds, 1992; Reynolds, Ross, & Rakow, 2002; Weinstein, 1990; Zeichner & Tabachnick, 1981). However, many researchers recognized the central role preparation programs played in equipping effective educators with important entry­-level knowledge and skills (Boyd, Grossman, Loyd, & Wyckoff, 2009; Darling-­Hammond & Bransford, 2005, Fullan & Stiegelbauer, 2007; Hamilton & Pinnegar, 2001; Korthagen, 2004; RESPECT, 2012; Sprinthall, Reiman, & Theis­Sprinthall, 1996; Wilson, 2009). Interestingly, Cochran­-Smith (2003) recognized that “teacher educators­ - those who teach the teachers­ - are now the linchpins in educational reforms of all kinds” (p. 5). Despite these noted accolades, the myriad of identified obstacles noted throughout research on the effectiveness of preparation programs warrants investigation. The following article highlights discussion of the external global and national influences and internal program issues that challenge the practice of teacher educators (TE) and the preparation of teacher candidates (TC)

Lealtad en el Aire: Factores Reales y Ficticios de la Formacion de Lealtad del Pasajero de Líneas Aereas

28 p.La lealtad del pasajero ha crecido en importancia en el servicio de líneas aéreas comerciales internacionales, debido especialmente a la crítica situación por la que atraviesa el sector turístico en los últimos años y la mayor competencia entre los proveedores del servicio en un mercado que se ha achicado. Por esta razón se ha aumentado la promoción del servicio y se han acentuado los programas de clubes destinados a crear lealtad. Sin embargo, la membresía múltiple a esos clubes y la tenue satisfacción con cada servicio han vuelto inefectivos a dichos programas, como queda demostrado en los frecuentes cambios de aerolínea o la postergación de vuelos por parte del cliente. Los estudios clásicos de la lealtad indican que éste es el resultado directo de la satisfacción del cliente, razón por la cual surgieron los “programas de lealtad.” Este vínculo directo ha sido cuestionado en estudios recientes, según los cuales la lealtad se encuentra determinada por factores relacionales y no transaccionales. Este estudio explora dichos factores respecto de la lealtad del pasajero de líneas aéreas. Los datos primarios provienen de una encuesta en el Aeropuerto Internacional de Santiago. La evidencia empírica demuestra que el proceso generador de lealtad en el servicio de líneas aéreas está determinado por el compromiso, la confianza, y la satisfacción, en ese orden de importancia

Integrals of Frullani Type and the Method of Brackets

The method of brackets is a collection of heuristic rules, some of which have being made rigorous, that provide a flexible, direct method for the evaluation of definite integrals. The present work uses this method to establish classical formulas due to Frullani which provide values of a specific family of integrals. Some generalizations are established

Predicción del rendimiento académico universitario mediante mecanismos de aprendizaje automático y métodos supervisados

Context:  In the education sector, variables have been identified which considerably affect students’ academic performance. In the last decade, research has been carried out from various fields such as psychology, statistics, and data analytics in order to predict academic performance. Method: Data analytics, especially through Machine Learning tools, allows predicting academic performance using supervised learning algorithms based on academic, demographic, and sociodemographic variables. In this work, the most influential variables in the course of students’ academic life are selected through wrapping, embedded, filter, and assembler methods, as well as the most important characteristics semester by semester using Machine Learning algorithms (Decision Trees, KNN, SVC, Naive Bayes, LDA), which were implemented using the Python language. Results: The results of the study show that the KNN is the model that best predicts academic performance for each of the semesters, followed by Decision Trees, with precision values that oscillate around 80 and 78,5% in some semesters. Conclusions: Regarding the variables, it cannot be said that a student’s per-semester academic average necessarily influences the prediction of academic performance for the next semester. The analysis of these results indicates that the prediction of academic performance using Machine Learning tools is a promising approach that can help improve students’ academic life allow institutions and teachers to take actions that contribute to the teaching-learning process.considerablemente en el rendimiento académico de los estudiantes. En la última década se han llevado a cabo investigaciones desde diversos campos como la psicología, la estadística y el análisis de datos con el fin de predecir el rendimiento académico. Método: La analítica de datos, especialmente a través de herramientas de Machine Learning, permite predecir el rendimiento académico utilizando algoritmos de aprendizaje supervisado basados ​​en variables académicas, demográficas y sociodemográficas. En este trabajo se seleccionan las variables más influyentes en el transcurso de la vida académica de los estudiantes mediante métodos de filtro, embebidos, y de ensamble, así como las características más importantes semestre a semestre utilizando algoritmos de Machine Learning (árbol de decisión, KNN, SVC, Naive Bayes, LDA), implementados en el lenguaje Python. Resultados: Los resultados del estudio muestran que el KNN es el modelo que mejor predice el rendimiento académico para cada uno de los semestres, seguido de los árboles de decisión, con valores de precisión que oscilan alrededor del 80 y 78,5 % en algunos semestres. Conclusiones: Con respecto a las variables, no se puede decir que el promedio académico semestral de un estudiante influya necesariamente en la predicción del rendimiento académico del siguiente semestre. El análisis de estos resultados indica que la predicción del rendimiento académico utilizando herramientas de Machine Learning es un enfoque promisorio que puede ayudar a mejorar la vida académica de los estudiantes y permitir a las instituciones y a los docentes adoptar acciones que ayuden al proceso de enseñanza-aprendizaje

Intersubjetividad de la realidad empresarial del sistema financiero colombiano : el caso COLPATRIA

Dentro de los aspectos más importantes para el desarrollo organizacional se encuentra el factor humano, donde existen diferentes formas para examinar la manera en que las personas perciben el desarrollo del negocio y su entorno. La intersubjetividad como asunto de la realidad empresarial se convierte entonces en una manera de recopilar la forma en que los involucrados en diferentes niveles de una organización perciben fenómenos, siendo esto fuente fundamental para la medición de la alineación de la organización con su plataforma estratégica. Este estudio busca examinar la forma en que los empleados de la empresa Colpatria perciben el sector financiero, en el cual se desempeña la empresa.One of the most important aspects of organizational development is found within the human resources, where there are different methods to examine the way people are perceiving the business development and their surroundings. Inter-subjectivity like topic of the enterprise reality is one of the methods to gather the way in which the incumbents perceive phenomenon, being this a fundamental source for measuring the organizations alignment with its strategic platform. This study seeks to examine the way Colpatrias employees perceive the financial sector, on which the enterprise exists

Prevalencia de asma en adolescentes de 14 a 16 anos con sobrepeso y obesidad del Liceo Abate Molina de la ciudad de Talca

78 p.La prevalencia de asma, sobrepeso y obesidad han tenido un importante aumento a nivel mundial y en nuestro país, demostrando relación entre estas patologías. Por tal motivo indagar en este tema, busca aportar datos estadísticos orientados en la misma línea de intervención, prevención, promoción e investigación del asma en adolescentes obesos y sobrepeso de la región del Maule y la ciudad de Talca. El siguiente estudio de tipo no experimental descriptivo, tiene como objetivo "Conocer la prevalencia de asma en los adolescentes de 14 a 16 años con sobrepeso y obesidad pertenecientes al Liceo Abate Molina de la ciudad de Talca”. Indagando par ello en el porcentaje de cada una de estas variables, describiendo por genero las características morfométricas del “n”, datos obtenidos al medir talla y peso, determinando via IMC la población con sobrepeso y obesa, todo recopilado en un tiempo único. Posteriormente los datos obtenidos se analizaron con “Statistical Product and Service Solution” (S.P.S.S.) un programa estadístico validado, del cual se realizaron mediciones de tendencia central como la media ( ), porcentajes, tablas de contingencia y cálculos de dispersión via desviación estándar (σ). Los resultados se obtuvieron de una población de 141 adolescentes de entre 14 y 16 años, de estos 39 son sintomáticos respiratorios, 7 padecían sobrepeso u obesidad, 0 individuos presentaban encuesta positiva compatible con la presencia de asma actual. A partir de estos datos se determinó que morfométricamente los adolescentes se encuentran dentro del rango de normalidad, determinando que el porcentaje de adolescentes con sobrepeso y obesos con asma es de 0, concluyendo así la no relación en el cruce de variables de estos adolescentes pertenecientes al liceo Abate Molina de la ciudad de Talca