Misofonía

La contaminación acústica es un fenómeno que afecta las grandes urbes en el mundo y que con el tiempo ha ido aumentando. Puede llegar a ser un problema para las personas, puesto que su impacto puede dañar físicamente el oído y ocasionar problemas de audición en un momento de la vida en que todavía se es joven. Según un informe en el 2015 de la Organización Mundial de la Salud, la contaminación acústica es el segundo problema ambiental después de la polución y las personas sufren no solo daños en su oído, sino problemas con relación a otras partes del cuerpo y la mente. Una reacción al sonido es la “misofonía”, que corresponde a la fobia que sienten algunas personas hacia algunos sonidos que, para el resto de la gente, pueden pasar desapercibidos. A partir de estos dos temas se creó una historia mediante el cómic como contribución a conocimiento y toma de consciencia del ruido como factor de riesgo de enfermedades acústicas.Noise pollution is a phenomenon that affects the big cities in the world and also has increased over time. It can be a problem for people, since its impact can physically damage the ear and cause hearing problems at a time in life when you are still young. According to a 2015 report by the World Health Organization, noise pollution is the second environmental problem after pollution and people suffer not only damage to their ear, but problems in relation to other parts of the body and mind. A reaction to sound is "misophony," which corresponds to the phobia that some people feel towards some sounds that, for the rest of the people, may go unnoticed. From these two themes, a story was created through a comic book, as a contribution to knowledge and awareness of noise as a risk factor for acoustic diseases.Maestro (a) en Artes VisualesPregrad

Cost-sensitive probabilistic predictions for support vector machines

Support vector machines (SVMs) are widely used and constitute one of the best examined and used machine learning models for two-class classification. Classification in SVM is based on a score procedure, yielding a deterministic classification rule, which can be transformed into a probabilistic rule (as implemented in off-the-shelf SVM libraries), but is not probabilistic in nature. On the other hand, the tuning of the regularization parameters in SVM is known to imply a high computational effort and generates pieces of information that are not fully exploited, not being used to build a probabilistic classification rule. In this paper we propose a novel approach to generate probabilistic outputs for the SVM. The new method has the following three properties. First, it is designed to be cost-sensitive, and thus the different importance of sensitivity (or true positive rate, TPR) and specificity (true negative rate, TNR) is readily accommodated in the model. As a result, the model can deal with imbalanced datasets which are common in operational business problems as churn prediction or credit scoring. Second, the SVM is embedded in an ensemble method to improve its performance, making use of the valuable information generated in the parameters tuning process. Finally, the probabilities estimation is done via bootstrap estimates, avoiding the use of parametric models as competing approaches. Numerical tests on a wide range of datasets show the advantages of our approach over benchmark procedures

Cost-sensitive probabilistic predictions for support vector machines

Support vector machines (SVMs) are widely used and constitute one of the best examined and used machine learning models for two-class classification. Classification in SVM is based on a score procedure, yielding a deterministic classification rule, which can be transformed into a probabilistic rule (as implemented in off-the-shelf SVM libraries), but is not probabilistic in nature. On the other hand, the tuning of the regularization parameters in SVM is known to imply a high computational effort and generates pieces of information that are not fully exploited, not being used to build a probabilistic classification rule. In this paper we propose a novel approach to generate probabilistic outputs for the SVM. The new method has the following three properties. First, it is designed to be cost-sensitive, and thus the different importance of sensitivity (or true positive rate, TPR) and specificity (true negative rate, TNR) is readily accommodated in the model. As a result, the model can deal with imbalanced datasets which are common in operational business problems as churn prediction or credit scoring. Second, the SVM is embedded in an ensemble method to improve its performance, making use of the valuable information generated in the parameters tuning process. Finally, the probabilities estimation is done via bootstrap estimates, avoiding the use of parametric models as competing approaches. Numerical tests on a wide range of datasets show the advantages of our approach over benchmark procedures.Comment: European Journal of Operational Research (2023

Cost-sensitive feature selection for support vector machines

Feature Selection (FS) is a crucial procedure in Data Science tasks such as Classification, since it identifies the relevant variables, making thus the classification procedures more interpretable and more effective by reducing noise and data overfit. The relevance of features in a classification procedure is linked to the fact that misclassifications costs are frequently asymmetric, since false positive and false negative cases may have very different consequences. However, off-the-shelf FS procedures seldom take into account such cost-sensitivity of errors. In this paper we propose a mathematical-optimization-based FS procedure embedded in one of the most popular classification procedures, namely, Support Vector Machines (SVM), accommodating asymmetric misclassification costs. The key idea is to replace the traditional margin maximization by minimizing the number of features selected, but imposing upper bounds on the false positive and negative rates. The problem is written as an integer linear problem plus a quadratic convex problem for SVM with both linear and radial kernels. The reported numerical experience demonstrates the usefulness of the proposed FS procedure. Indeed, our results on benchmark data sets show that a substantial decrease of the number of features is obtained, whilst the desired trade-off between false positive and false negative rates is achieved

References data on the growth and population parameters of brown trout in siliceous rivers of Galicia (NW Spain)

Brown trout is an important angling species worldwide, and its morphology, population structure and genetics can be highly variable from one location to another. In this study, we provide data for the establishment of reference range values for several population and growth parameters of brown trout in the Cantabrian-Atlantic siliceous rivers of Galicia (NW Spain). Additionally, this study tests the hypothesis that the population and growth parameters differ among sections of rivers with different exploitation statuses (unexploited, exploited-regulated and exploited-open sections). Our study revealed that such population parameters as biomass and production were higher in unexploited sections, but the differences in growth among the sections with different angling regulations were not consistent. The findings of this study are discussed in light of the present knowledge on the status of trout fisheries, as it is essential for the development of management plans. Additional studies are needed to clarify whether the differences in growth can be correlated to the angling regulations.La trucha común es una especie muy apreciada por los pescadores deportivos en todo el mundo, y su morfología, estructura poblacional y características genéticas pueden variar considerablemente entre áreas geográficas próximas. En este estudio proporcionamos datos para el establecimiento de categorías de referencia de varios parámetros poblacionales y de crecimiento de la trucha común en ríos silíceos Cantábrico-Atlánticos de Galicia (NO España). Además, con la realización de este estudio se pretende verificar la hipótesis de que los parámetros poblacionales y el crecimiento pueden variar entre tramos de ríos con diferente tipo de regulación de pesca deportiva (tramos vedados o inexplotados, tramos de pesca acotados y tramos de pesca libre). Así, nuestro estudio reveló que algunos parámetros poblacionales como la biomasa y la producción fueron más elevados en los tramos vedados, pero las diferencias en el crecimiento entre tramos con diferente regulación de pesca deportiva no fueron consistentes. Los resultados de este trabajo se discuten teniendo en cuenta el conocimiento actual sobre el estado de las poblaciones de trucha común, pues son esenciales para el desarrollo de planes de gestión. No obstante, se requieren de más estudios para aclarar si las diferencias en crecimiento se pueden relacionar con el tipo de regulación de pesca deportiva

Measuring HS in Small, Vulnerable Municipalities: A Quantitative Approach

This article presents a methodological proposal for formulating a Human Security Index (HSI), including information from institutional sources and the inhabitants' perception of security. The developed methodology uses quantitative methods to evaluate HS (Human Security) in small municipalities with large rural areas affected by the confluence of different social and economic problems. Given the security conditions in the area, it was impossible to use a random sampling mechanism. Therefore, the data collected have a sample size that cannot be considered significant enough to make inferences using a frequentist statistics approach. The method to construct the index is illustrated using Miranda's data, a Colombian municipality exposed to decades of armed conflict. With the answers given by 55 interviewees to questions related to the armed conflict such as presence-absence reminders and retained values of violent events, a proposal of 36 indices was made, and two of them were selected for the study, following some statistical criteria. In the construction of one of these selected indices, we used information from binary variables and, for the other index, we used information from count data. The values obtained by both indices for the municipality of Miranda were, respectively, 46.4 and 35.8. According to HS experts, both values can be considered moderate levels in the perception of insecurity by residents of the municipality

Propuesta de estructura financiera para la generación de valor en una empresa de transporte

Las pequeñas y medianas empresas (pymes) enfrentan retos propios de sus condiciones frente a los mercados, tales y como la volatilidad de sus clientes, el recaudo de cartera, la liquidez, la dificultad de conseguir fuentes de financiación y otros retos derivados de las prioridades en sus procesos como ejercicios limitados de planeación financiera. Este artículo propone actividades de planeación para una empresa del sector transporte en Colombia, que le permitan modificar la dinámica de su toma de decisiones. Se incluye una descripción del entorno económico de Colombia en los últimos años, con su impacto sobre el sector transporte en términos de amenazas y oportunidades para su operación operativa y financiera. Se describe la historia de una empresa de transporte objeto de estudio y se analizan los factores financieros que han determinado su crecimiento hasta la fecha, y a las debilidades propias que ha enfrentado en términos de planeación financiera. Finalmente, se propone una herramienta de análisis con el fin de ayudar a la toma de decisiones asertivas que ayuden a la generar valor para los accionistas y que permita un crecimiento sostenible en el tiempo.Small and medium-sized enterprises face challenges inherent to their market conditions, such as the volatility of their clients, portfolio collection, liquidity, the difficulty of finding sources of financing and other challenges derived from the priorities in its processes as limited financial planning exercises. This article proposes planning activities for a company in the transportation sector in Colombia that allows it to modify the dynamics of its decision making. It includes a description of the economic environment of Colombia in recent years with its impact on the transport sector, in terms of threats and opportunities for its operational and financial operation. It describes the history of the transport company under study and analyzes the financial factors that have determined its growth to date and the own weaknesses to which have been faced in terms of financial planning. Finally, an analysis tool is proposed in order to help assertive decisions that help generate value for shareholders and allow sustainable growth over time

Children with Disabilities Tend to Stay in a Highly-resourced Early Head Start/Head Start Program Longer than Children without Disabilities

Using data from 21 Educare schools, the researchers measured the rate at which children from birth to kindergarten-age enter the school and rate at which they exit the school. Educare schools are highly resourced Early Head Start/Head Start programs targeting children at risk, especially children from low-income backgrounds. About 10% of the children have a disability. Results showed that children with a disability tended to stay in the program longer, especially when enrolled in Early Head Start.https://digitalcommons.library.umaine.edu/ccids_posters/1037/thumbnail.jp