Relación entre la dirección estratégica y el compromiso laboral en una agencia bancaria, distrito de Arequipa, 2018

Las empresas en la actualidad, ameritan de una dirección orientada a implementar estrategias que sean sostenibles y que generen valor agregado a las organizaciones, sobre todo en el sector bancario, que ha sido un sector que ha experimentado crisis financieras a nivel mundial. La investigación, centra su estudio en la relación la dirección estratégica y el compromiso laboral en una agencia bancaria, distrito de Arequipa, 2018. En este sentido, el diseño del trabajo, es descriptiva-correlacional, la técnica de recolección de datos, es la encuesta, el instrumento de recolección de datos, cuestionario. Asimismo, los resultados muestran que existe correlación positiva con valores de 0,432, similar comportamiento se presentó para las hipótesis planteadas, mostrando una tendencia de correlación, por lo que puede concluirse, que la existencia de correlación entre la variable dirección estratégica y compromiso laboral, contempla valores moderado bajos, por ende, una línea de investigación desde un ámbito de gestión estratégica orientada a los recursos humanos, con el compromiso, podría contemplar valores de correlación, más próximos a la unidad, y así poder, tener por parte de los colaboradores, un nivel de respuesta más orientada, hacia el logro de los objetivos estratégicos de la organización.Companies currently deserve a direction oriented to implement strategies that are sustainable and that generate added value to organizations, especially in the banking sector, which has been a sector that has experienced financial crises worldwide. The present investigation focuses its study on the relationship between strategic management and labor commitment in a banking agency, Arequipa district, 2018. In this sense, the research design is descriptive-correlational, the data collection technique is the survey, the data collection instrument, questionnaire. In this sense, the results show that there is positive correlation with values of 0.432, similar behavior was presented for the hypotheses, showing a low correlation tendency, so it can be concluded, existence of correlation between the variable strategic direction and labor commitment with Moderately low values, therefore, a line of research from a strategic management area focused on human resources, with commitment, could generate correlation values, closer to unity, and thus be able to have on the part of employees, a level of response more oriented, towards the achievement of the strategic objectives of the organization.Trabajo de suficiencia profesionalCampus Lima Centr

Dignidad, Poder, Resistencia // Dignity, Power, Resistance

First To Go Abroad is a partnership between the Loyola Marymount University First To Go Program, LMU Study Abroad, and the Council on International Educational Exchange (CIEE), which seeks to increase study abroad opportunities for first-generation college students. In May 2017, fifteen first-gen students and two first-gen faculty mentors traveled together to Santiago, Dominican Republic, where they spent ten days exploring the country and learning about the local cultures, customs, and histories of the people who call the DR home. Travel is a privilege not all students have the same access to; for some students, this trip was the first time out of the United States. Like the first-generation college experience, the experience of international travel is marked by daily encounters with new spaces, people, and cultural practices that can be at once overwhelming and inspiring. This was a topic of exploration throughout the trip and the subject of the pages contained in this volume. The narratives published here are the product of a cross-institutional writing workshop, where students from LMU and the Pontificia Universidad Católica Madre y Maestra worked together to draft essays documenting their encounters with change that have pushed boundaries, broken down borders, and generated personal growth. We hope our readers around the world will appreciate these works, which showcase the transformative power of creative and collaborative global encounters

Live. Tell. Resist.

This edition of First-Gen Voices features the stories and work of 24 first-generation college students at multiple higher education institutions. The aim is to disseminate a story about us, for us, and consequently, the dominant cultures that have yet to learn from our power

Integrating Machine Learning Methods for Medical Diagnosis

The rapid advancement of machine learning techniques has revolutionized the field of medical diagnosis by offering powerful tools to analyze complex data sets and make accurate predictions. In this proposed method, we present a novel approach that integrates machine learning and optimization models to enhance the accuracy of medical diagnoses. Our method focuses on fine-tuning and optimizing the parameters of machine learning algorithms commonly used in medical diagnosis, such as logistic regression, support vector machines, and neural networks. By employing optimization techniques, we systematically explore the parameter space of these algorithms to discover the most optimal configurations. Moreover, by representing algorithms as computational graphs and leveraging their relationships with diagnostic outcomes, we can predict optimal properties of existing algorithms and potentially guide the development of new, highly accurate diagnostic tools. This innovative approach represents a promising avenue for enhancing the accuracy of medical diagnoses, enabling better patient care and more efficient healthcare systems. The integration of machine learning and optimization models offers a systematic and data-driven way to optimize existing algorithms and discover novel solutions, ultimately contributing to improved medical outcomes

Integrating Machine Learning Methods For Medical Diagnosis

Abstract:The rapid advancement of machine learning techniques has revolutionized the field of medical diagnosis by offering powerful tools to analyze complex data sets and make accurate predictions. In this proposed method, we present a novel approach that integrates machine learning and optimization models to enhance the accuracy of medical diagnoses. Our method focuses on fine-tuning and optimizing the parameters of machine learning algorithms commonly used in medical diagnosis, such as logistic regression, support vector machines, and neural networks. By employing optimization techniques, we systematically explore the parameter space of these algorithms to discover the most optimal configurations. Moreover, by representing algorithms as computational graphs and leveraging their relationships with diagnostic outcomes, we can predict optimal properties of existing algorithms and potentially guide the development of new, highly accurate diagnostic tools. This innovative approach represents a promising avenue for enhancing the accuracy of medical diagnoses, enabling better patient care and more efficient healthcare systems. The integration of machine learning and optimization models offers a systematic and data-driven way to optimize existing algorithms and discover novel solutions, ultimately contributing to improved medical outcomes

Forecasting Crashes, Credit Card Default, and Imputation Analysis on Missing Values by the use of Neural Networks

A neural network is a system of hardware and/or software patterned after the operation of neurons in the human brain. Neural networks,- also called Artificial Neural Networks - are a variety of deep learning technology, which also falls under the umbrella of artificial intelligence, or AI. Recent studies shows that Artificial Neural Network has the highest coefficient of determination (i.e. measure to assess how well a model explains and predicts future outcomes.) in comparison to the K-nearest neighbor classifiers, logistic regression, discriminant analysis, naive Bayesian classifier, and classification trees. In this work, the theoretical description of the neural network methodology and some practical applications which are based on real world data are presented. We used the Multilayer perceptron (often simply called neural network) to identify financial market crashes and also compute the credit card default payments of customers of a financial institution. The problem of detecting market crashes and credit card default payments were modeled as a special class of classification problem. The neural network technique is very efficient and robust compared to other classification techniques since it correctly discriminates with good accuracy

Relación entre la dirección estratégica y el compromiso laboral en una agencia bancaria, distrito de Arequipa, 2018

Companies currently deserve a direction oriented to implement strategies that are sustainable and that generate added value to organizations, especially in the banking sector, which has been a sector that has experienced financial crises worldwide. The present investigation focuses its study on the relationship between strategic management and labor commitment in a banking agency, Arequipa district, 2018. In this sense, the research design is descriptive-correlational, the data collection technique is the survey, the data collection instrument, questionnaire. In this sense, the results show that there is positive correlation with values of 0.432, similar behavior was presented for the hypotheses, showing a low correlation tendency, so it can be concluded, existence of correlation between the variable strategic direction and labor commitment with Moderately low values, therefore, a line of research from a strategic management area focused on human resources, with commitment, could generate correlation values, closer to unity, and thus be able to have on the part of employees, a level of response more oriented, towards the achievement of the strategic objectives of the organization.Trabajo de suficiencia profesionalLas empresas en la actualidad, ameritan de una dirección orientada a implementar estrategias que sean sostenibles y que generen valor agregado a las organizaciones, sobre todo en el sector bancario, que ha sido un sector que ha experimentado crisis financieras a nivel mundial. La investigación, centra su estudio en la relación la dirección estratégica y el compromiso laboral en una agencia bancaria, distrito de Arequipa, 2018. En este sentido, el diseño del trabajo, es descriptiva-correlacional, la técnica de recolección de datos, es la encuesta, el instrumento de recolección de datos, cuestionario. Asimismo, los resultados muestran que existe correlación positiva con valores de 0,432, similar comportamiento se presentó para las hipótesis planteadas, mostrando una tendencia de correlación, por lo que puede concluirse, que la existencia de correlación entre la variable dirección estratégica y compromiso laboral, contempla valores moderado bajos, por ende, una línea de investigación desde un ámbito de gestión estratégica orientada a los recursos humanos, con el compromiso, podría contemplar valores de correlación, más próximos a la unidad, y así poder, tener por parte de los colaboradores, un nivel de respuesta más orientada, hacia el logro de los objetivos estratégicos de la organización

Global economic burden of unmet surgical need for appendicitis

Background There is a substantial gap in provision of adequate surgical care in many low- and middle-income countries. This study aimed to identify the economic burden of unmet surgical need for the common condition of appendicitis. Methods Data on the incidence of appendicitis from 170 countries and two different approaches were used to estimate numbers of patients who do not receive surgery: as a fixed proportion of the total unmet surgical need per country (approach 1); and based on country income status (approach 2). Indirect costs with current levels of access and local quality, and those if quality were at the standards of high-income countries, were estimated. A human capital approach was applied, focusing on the economic burden resulting from premature death and absenteeism. Results Excess mortality was 4185 per 100 000 cases of appendicitis using approach 1 and 3448 per 100 000 using approach 2. The economic burden of continuing current levels of access and local quality was US $92 492 million using approach 1 and$73 141 million using approach 2. The economic burden of not providing surgical care to the standards of high-income countries was $95 004 million using approach 1 and$75 666 million using approach 2. The largest share of these costs resulted from premature death (97.7 per cent) and lack of access (97.0 per cent) in contrast to lack of quality. Conclusion For a comparatively non-complex emergency condition such as appendicitis, increasing access to care should be prioritized. Although improving quality of care should not be neglected, increasing provision of care at current standards could reduce societal costs substantially

Global economic burden of unmet surgical need for appendicitis

Background There is a substantial gap in provision of adequate surgical care in many low- and middle-income countries. This study aimed to identify the economic burden of unmet surgical need for the common condition of appendicitis. Methods Data on the incidence of appendicitis from 170 countries and two different approaches were used to estimate numbers of patients who do not receive surgery: as a fixed proportion of the total unmet surgical need per country (approach 1); and based on country income status (approach 2). Indirect costs with current levels of access and local quality, and those if quality were at the standards of high-income countries, were estimated. A human capital approach was applied, focusing on the economic burden resulting from premature death and absenteeism. Results Excess mortality was 4185 per 100 000 cases of appendicitis using approach 1 and 3448 per 100 000 using approach 2. The economic burden of continuing current levels of access and local quality was US $92 492 million using approach 1 and$73 141 million using approach 2. The economic burden of not providing surgical care to the standards of high-income countries was $95 004 million using approach 1 and$75 666 million using approach 2. The largest share of these costs resulted from premature death (97.7 per cent) and lack of access (97.0 per cent) in contrast to lack of quality. Conclusion For a comparatively non-complex emergency condition such as appendicitis, increasing access to care should be prioritized. Although improving quality of care should not be neglected, increasing provision of care at current standards could reduce societal costs substantially