María Gabriela González Bautista, Lizbeth Carolina Rojas Vistín, Eduardo Germán Zurita Moreano, Patricia Hernández Medina
Financial development, characterized by the growth and sophistication of the financial system, is crucial for the global economy, since it facilitates investment, savings and the efficient allocation of resources, in addition to contributing to the reduction of poverty and inequality by allowing, broader access to financial services. Ecuador has experienced significant changes in its financial system during recent decades, such as dollarization, liberalization, digitalization, diversification of services, and strengthening of regulation and supervision. The research focuses on establishing the influence of financial development on income inequality. The autoregressive distribution of lags (ARDL) methodology was used with the purpose of identifying short- and long-term relationships. The variables included are the Gini index, financial development, financial instability, public social spending, and final consumption spending by resident households, trade openness and gross fixed capital formation. After applying the ARDL model, the main results show that credit allocation to the private sector plays a significant role in reducing income inequality, and its effect intensifies over time. Received: 22 October 2023 / Accepted: 9 April 2024 / Published: 5 May 2024
{"title":"Financial Development and Income Inequality: The Case of Ecuador","authors":"María Gabriela González Bautista, Lizbeth Carolina Rojas Vistín, Eduardo Germán Zurita Moreano, Patricia Hernández Medina","doi":"10.36941/ajis-2024-0068","DOIUrl":"https://doi.org/10.36941/ajis-2024-0068","url":null,"abstract":"Financial development, characterized by the growth and sophistication of the financial system, is crucial for the global economy, since it facilitates investment, savings and the efficient allocation of resources, in addition to contributing to the reduction of poverty and inequality by allowing, broader access to financial services. Ecuador has experienced significant changes in its financial system during recent decades, such as dollarization, liberalization, digitalization, diversification of services, and strengthening of regulation and supervision. The research focuses on establishing the influence of financial development on income inequality. The autoregressive distribution of lags (ARDL) methodology was used with the purpose of identifying short- and long-term relationships. The variables included are the Gini index, financial development, financial instability, public social spending, and final consumption spending by resident households, trade openness and gross fixed capital formation. After applying the ARDL model, the main results show that credit allocation to the private sector plays a significant role in reducing income inequality, and its effect intensifies over time. \u0000 \u0000Received: 22 October 2023 / Accepted: 9 April 2024 / Published: 5 May 2024","PeriodicalId":37106,"journal":{"name":"Academic Journal of Interdisciplinary Studies","volume":"340 9","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141011967","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Diego Fernando Sendoya Losada, Julián José Soto Gómez, Julián Andrés Zúñiga Vela
Cardiovascular diseases are one of the leading causes of mortality in contemporary society. With the growth in the accumulation of medical data, new opportunities have arisen to enhance diagnostic accuracy using machine learning techniques. Heart diseases present symptoms that can be similar to other disorders or be mistaken for signs of aging. Furthermore, diagnosing based on electrocardiogram (ECG) signals can be challenging due to the variability in signal length and characteristics. This article has developed a methodology for classifying ECG signals using the k-Nearest Neighbor (kNN) algorithm and statistical techniques. 9000 ECG signal samples from the PhysioNet database were processed. The signals were normalized to a length of 9000 samples, and relevant features for classification, such as median, standard deviation, skewness, among others, were extracted. Multiple kNN models with different parameters were trained and evaluated on a test set. The models exhibited high performance in classifying normal signals but faced difficulties in correctly classifying signals with arrhythmias. The weighted kNN algorithm demonstrated the best accuracy, although all models showed a tendency to misclassify abnormal signals due to data imbalance. While significant accuracy was achieved in ECG signal classification, there is still room for improvement. Future strategies could involve extracting more relevant features, addressing data imbalance, and fine-tuning model hyperparameters. Integrating domain knowledge from the medical field and advanced signal processing techniques could further enhance classification accuracy. Received: 3 January 2024 / Accepted: 7 April 2024 / Published: 5 May 2024
{"title":"Classification of ECG Signals Using Machine Learning Techniques","authors":"Diego Fernando Sendoya Losada, Julián José Soto Gómez, Julián Andrés Zúñiga Vela","doi":"10.36941/ajis-2024-0067","DOIUrl":"https://doi.org/10.36941/ajis-2024-0067","url":null,"abstract":"Cardiovascular diseases are one of the leading causes of mortality in contemporary society. With the growth in the accumulation of medical data, new opportunities have arisen to enhance diagnostic accuracy using machine learning techniques. Heart diseases present symptoms that can be similar to other disorders or be mistaken for signs of aging. Furthermore, diagnosing based on electrocardiogram (ECG) signals can be challenging due to the variability in signal length and characteristics. This article has developed a methodology for classifying ECG signals using the k-Nearest Neighbor (kNN) algorithm and statistical techniques. 9000 ECG signal samples from the PhysioNet database were processed. The signals were normalized to a length of 9000 samples, and relevant features for classification, such as median, standard deviation, skewness, among others, were extracted. Multiple kNN models with different parameters were trained and evaluated on a test set. The models exhibited high performance in classifying normal signals but faced difficulties in correctly classifying signals with arrhythmias. The weighted kNN algorithm demonstrated the best accuracy, although all models showed a tendency to misclassify abnormal signals due to data imbalance. While significant accuracy was achieved in ECG signal classification, there is still room for improvement. Future strategies could involve extracting more relevant features, addressing data imbalance, and fine-tuning model hyperparameters. Integrating domain knowledge from the medical field and advanced signal processing techniques could further enhance classification accuracy. \u0000 \u0000 \u0000Received: 3 January 2024 / Accepted: 7 April 2024 / Published: 5 May 2024","PeriodicalId":37106,"journal":{"name":"Academic Journal of Interdisciplinary Studies","volume":"11 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141012049","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Josefina Amanda Suyo-Vega, Mónica Elisa Meneses-la-Riva, Víctor Hugo Fernández-Bedoya, Sofía Almendra Alvarado-Suyo, Ana da Costa Polonia, Angélica Inês Miotto, Giovanni Ocupa-Cabrera
The formation of a university professor's identity is a complex process, which begins with academic training and evolves through professional practice. This study explores the experiences that shape the identity of university teachers, focusing on personal, social and professional perspectives. Through the qualitative approach, using in-depth interviews with 10 participants with an average age of 50 years, the research revealed significant factors. It found a correlation between female gender and preference for teaching careers, as well as the substantial influence of parental guidance on career choice, driven by considerations of economic stability and familiar work environments. In terms of personal identity, the testimonies underscored the influential role of parental expectations in career decision making. Social identity was strongly influenced by family prestige and the broader social context. On the professional level, the research revealed that years of positive teaching experience contribute to the reinforcement of one's professional identity. However, it also highlighted the fluid nature of a university professor's teaching identity, subject to the fluctuations of positive and negative experiences encountered in daily practice. While these experiences can reinforce a sense of vocation and professional development, the lack of a cohesive teaching identity poses risks to the quality of educational services provided to students. Received: 7 September 2023 / Accepted: 23 April 2024 / Published: 5 May 2024
{"title":"Unveiling the Professional Identity of University Educators: A Qualitative Study","authors":"Josefina Amanda Suyo-Vega, Mónica Elisa Meneses-la-Riva, Víctor Hugo Fernández-Bedoya, Sofía Almendra Alvarado-Suyo, Ana da Costa Polonia, Angélica Inês Miotto, Giovanni Ocupa-Cabrera","doi":"10.36941/ajis-2024-0076","DOIUrl":"https://doi.org/10.36941/ajis-2024-0076","url":null,"abstract":"The formation of a university professor's identity is a complex process, which begins with academic training and evolves through professional practice. This study explores the experiences that shape the identity of university teachers, focusing on personal, social and professional perspectives. Through the qualitative approach, using in-depth interviews with 10 participants with an average age of 50 years, the research revealed significant factors. It found a correlation between female gender and preference for teaching careers, as well as the substantial influence of parental guidance on career choice, driven by considerations of economic stability and familiar work environments. In terms of personal identity, the testimonies underscored the influential role of parental expectations in career decision making. Social identity was strongly influenced by family prestige and the broader social context. On the professional level, the research revealed that years of positive teaching experience contribute to the reinforcement of one's professional identity. However, it also highlighted the fluid nature of a university professor's teaching identity, subject to the fluctuations of positive and negative experiences encountered in daily practice. While these experiences can reinforce a sense of vocation and professional development, the lack of a cohesive teaching identity poses risks to the quality of educational services provided to students. \u0000 \u0000Received: 7 September 2023 / Accepted: 23 April 2024 / Published: 5 May 2024","PeriodicalId":37106,"journal":{"name":"Academic Journal of Interdisciplinary Studies","volume":"302 5","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141012432","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Luigi Italo Villena Zapata, Benicio Gonzalo Acosta Enriquez, Jose Carlos Montes Ninaquispe, Jonathan Alexander Ruiz Carrillo, Lorena Stefany Villarreal Gonzales, Jenny Alva Morales, Manuel Amadeo Sevilla Angelaths
Financial education is considered an essential skill that enables students to effectively manage their economic resources. However, it is still at an embryonic stage in several countries, and the ability of young people to apply financial education in life contexts has not substantially improved. To address these challenges, this study proposes and evaluates a novel approach to improve financial education among high school students by using generative artificial intelligence tools. Following a quasi-experimental design, we randomly assigned a total of 110 high school students to two conditions: an experimental group that participated in learning experiences under the financial education approach using artificial intelligence tools such as ChatGPT and a control group that engaged in the same learning activities following the traditional teaching approach. The results of the Mann-Whitney U test indicate that there are significant differences between the scores of the experimental group and the control group (p=1.64E-19<0.05, group experimental=82.92> group control=28.08), demonstrating the effectiveness of the generative artificial intelligence approach in enhancing financial education compared to the traditional approach. Furthermore, the Kruskal-Wallis test revealed a significance p-value of less than 0.05 (p=0.000935<0.05), indicating that the use of AI significantly improves the five indicators of financial education according to the post-test evaluation phase of the experimental group. On the other hand, Dunn's test for multiple comparisons reveals a significantly greater influence of the innovative approach using artificial intelligence in the following dimensions: Financial Planning Actions, Financial Analysis Actions, Financial Behavior, and Strategic Expense Management; however, the Investment Initiative dimension shows a significantly lesser influence ( =103.46). The implementation of artificial intelligence in the classroom to promote student learning is favored by innovative approaches to pedagogical action. In this way, from the classroom, we can address the lack of skills and financial education in our students. Received: 11 December 2023 / Accepted: 19 March 2024 / Published: 5 May 2024
{"title":"Employment of Generative Artificial Intelligence in Classroom Environments to Improve Financial Education in Secondary School Students","authors":"Luigi Italo Villena Zapata, Benicio Gonzalo Acosta Enriquez, Jose Carlos Montes Ninaquispe, Jonathan Alexander Ruiz Carrillo, Lorena Stefany Villarreal Gonzales, Jenny Alva Morales, Manuel Amadeo Sevilla Angelaths","doi":"10.36941/ajis-2024-0069","DOIUrl":"https://doi.org/10.36941/ajis-2024-0069","url":null,"abstract":"Financial education is considered an essential skill that enables students to effectively manage their economic resources. However, it is still at an embryonic stage in several countries, and the ability of young people to apply financial education in life contexts has not substantially improved. To address these challenges, this study proposes and evaluates a novel approach to improve financial education among high school students by using generative artificial intelligence tools. Following a quasi-experimental design, we randomly assigned a total of 110 high school students to two conditions: an experimental group that participated in learning experiences under the financial education approach using artificial intelligence tools such as ChatGPT and a control group that engaged in the same learning activities following the traditional teaching approach. The results of the Mann-Whitney U test indicate that there are significant differences between the scores of the experimental group and the control group (p=1.64E-19<0.05, group experimental=82.92> group control=28.08), demonstrating the effectiveness of the generative artificial intelligence approach in enhancing financial education compared to the traditional approach. Furthermore, the Kruskal-Wallis test revealed a significance p-value of less than 0.05 (p=0.000935<0.05), indicating that the use of AI significantly improves the five indicators of financial education according to the post-test evaluation phase of the experimental group. On the other hand, Dunn's test for multiple comparisons reveals a significantly greater influence of the innovative approach using artificial intelligence in the following dimensions: Financial Planning Actions, Financial Analysis Actions, Financial Behavior, and Strategic Expense Management; however, the Investment Initiative dimension shows a significantly lesser influence ( =103.46). The implementation of artificial intelligence in the classroom to promote student learning is favored by innovative approaches to pedagogical action. In this way, from the classroom, we can address the lack of skills and financial education in our students. \u0000 \u0000 \u0000Received: 11 December 2023 / Accepted: 19 March 2024 / Published: 5 May 2024","PeriodicalId":37106,"journal":{"name":"Academic Journal of Interdisciplinary Studies","volume":"278 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141012617","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Gilberto Carrión-Barco, John Fuentes Adrianzén, Alejandro Chayan-Coloma, Manuel Antonio Díaz-Paredes, Alfredo Prado-Canchari, Celita Alarcon-Nuñez, Edgar Mitchel Lau-Hoyos
Public infrastructure projects hold significant social value as they provide essential services, spur economic development, create job opportunities, and enhance quality of life by facilitating access to basic amenities and reducing commute times. This study aimed to assess the social impact of public infrastructure projects in the northern region of Peru, focusing on indicators such as access to basic services, inequality reduction, poverty alleviation, economic growth, and citizen well-being. Employing a quantitative approach with a non-experimental and descriptive design, the research engaged a sample of 124 engineering professionals who were surveyed to gauge their perceptions of public infrastructure project management in the northern region of Peru. The findings reveal predominantly negative perceptions towards the management of public infrastructure projects in the northern region of Peru, indicating the presence of deficiencies or irregularities in project execution. It is recommended to propose measures aimed at enhancing transparency, fostering citizen participation, and promoting accountability in the management of public infrastructure projects. Received: 12 March 2024 / Accepted: 20 April 2024 / Published: 5 May 2024
{"title":"The Social Value of Public Infrastructure Works","authors":"Gilberto Carrión-Barco, John Fuentes Adrianzén, Alejandro Chayan-Coloma, Manuel Antonio Díaz-Paredes, Alfredo Prado-Canchari, Celita Alarcon-Nuñez, Edgar Mitchel Lau-Hoyos","doi":"10.36941/ajis-2024-0087","DOIUrl":"https://doi.org/10.36941/ajis-2024-0087","url":null,"abstract":"Public infrastructure projects hold significant social value as they provide essential services, spur economic development, create job opportunities, and enhance quality of life by facilitating access to basic amenities and reducing commute times. This study aimed to assess the social impact of public infrastructure projects in the northern region of Peru, focusing on indicators such as access to basic services, inequality reduction, poverty alleviation, economic growth, and citizen well-being. Employing a quantitative approach with a non-experimental and descriptive design, the research engaged a sample of 124 engineering professionals who were surveyed to gauge their perceptions of public infrastructure project management in the northern region of Peru. The findings reveal predominantly negative perceptions towards the management of public infrastructure projects in the northern region of Peru, indicating the presence of deficiencies or irregularities in project execution. It is recommended to propose measures aimed at enhancing transparency, fostering citizen participation, and promoting accountability in the management of public infrastructure projects. \u0000 \u0000Received: 12 March 2024 / Accepted: 20 April 2024 / Published: 5 May 2024","PeriodicalId":37106,"journal":{"name":"Academic Journal of Interdisciplinary Studies","volume":"5 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141011866","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The contemporary healthcare landscape faces unprecedented challenges, ranging from data fragmentation within health information systems to the need for timely and accurate diagnostics. This research explores the transformative potential of Artificial Intelligence (AI) in enhancing the Kosovo Health Information System (HIS). By leveraging the capabilities of AI, we aim to address existing limitations in data interoperability, predictive analytics, and personalized healthcare. The study incorporates a comprehensive literature review, methodological data collection, and analysis of the current state of the Kosovo HIS. Drawing inspiration from successful global implementations, we delve into the possibilities of AI applications in diagnosis, treatment personalization, and population health management. The research also examines ongoing initiatives and collaborations aimed at integrating AI into the Kosovo HIS. Through a critical assessment of technical challenges and ethical considerations, the paper provides insights into the opportunities and hurdles associated with the implementation of AI in healthcare. Ultimately, this research contributes to the discourse on the future prospects of healthcare in Kosovo, highlighting the potential long-term impacts of AI integration and offering recommendations for advancing the country's health information infrastructure. Received: 5 February 2024 / Accepted: 23 April 2024 / Published: 5 May 2024
{"title":"Artificial Intelligence in Enhancing the Kosovo Health Information System","authors":"A. Loku, Enver Malsia","doi":"10.36941/ajis-2024-0062","DOIUrl":"https://doi.org/10.36941/ajis-2024-0062","url":null,"abstract":"The contemporary healthcare landscape faces unprecedented challenges, ranging from data fragmentation within health information systems to the need for timely and accurate diagnostics. This research explores the transformative potential of Artificial Intelligence (AI) in enhancing the Kosovo Health Information System (HIS). By leveraging the capabilities of AI, we aim to address existing limitations in data interoperability, predictive analytics, and personalized healthcare. The study incorporates a comprehensive literature review, methodological data collection, and analysis of the current state of the Kosovo HIS. Drawing inspiration from successful global implementations, we delve into the possibilities of AI applications in diagnosis, treatment personalization, and population health management. The research also examines ongoing initiatives and collaborations aimed at integrating AI into the Kosovo HIS. Through a critical assessment of technical challenges and ethical considerations, the paper provides insights into the opportunities and hurdles associated with the implementation of AI in healthcare. Ultimately, this research contributes to the discourse on the future prospects of healthcare in Kosovo, highlighting the potential long-term impacts of AI integration and offering recommendations for advancing the country's health information infrastructure. \u0000 \u0000Received: 5 February 2024 / Accepted: 23 April 2024 / Published: 5 May 2024","PeriodicalId":37106,"journal":{"name":"Academic Journal of Interdisciplinary Studies","volume":"237 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141012842","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Alfonso Renato Vargas-Murillo, Ilda Nadia Monica de la Asuncion Pari-Bedoya, Adriana Margarita Turriate-Guzmán, Cintya Amelia Delgado-Chávez, Franshezka Sanchez-Paucar
The present literature review explores the growing impact of artificial intelligence (AI) on the justice system. It sheds light on the prospects, obstacles, and probable consequences of its assimilation. Utilizing a broad array of scholarly resources, we examine the implementation of AI in various domains, including but not limited to predictive law enforcement, risk evaluation, evidentiary analysis, and judicial decision-making. The review recognizes the advantages of artificial intelligence, such as enhanced efficacy, precision, and impartiality in legal proceedings, while also expressing apprehensions regarding potential partialities, ethical predicaments, and risks to confidentiality and human liberties. Furthermore, it is crucial to underscore the significance of interdisciplinary cooperation and comprehensive regulatory frameworks in guaranteeing the judicious and impartial integration of AI technologies in the justice system. The present study endeavors to make a significant scholarly contribution to the ongoing discourse surrounding artificial intelligence and its intersection with the legal field. By examining the opportunities and challenges of integrating AI in legal systems, this review provides specific insights into formulating policies around algorithmic accountability, transparency, and ethical safeguards to ensure responsible AI adoption. Received: 27 October 2023 / Accepted: 29 February 2024 / Published: 5 March 2024
{"title":"Transforming Justice: Implications of Artificial Intelligence in Legal Systems","authors":"Alfonso Renato Vargas-Murillo, Ilda Nadia Monica de la Asuncion Pari-Bedoya, Adriana Margarita Turriate-Guzmán, Cintya Amelia Delgado-Chávez, Franshezka Sanchez-Paucar","doi":"10.36941/ajis-2024-0059","DOIUrl":"https://doi.org/10.36941/ajis-2024-0059","url":null,"abstract":"The present literature review explores the growing impact of artificial intelligence (AI) on the justice system. It sheds light on the prospects, obstacles, and probable consequences of its assimilation. Utilizing a broad array of scholarly resources, we examine the implementation of AI in various domains, including but not limited to predictive law enforcement, risk evaluation, evidentiary analysis, and judicial decision-making. The review recognizes the advantages of artificial intelligence, such as enhanced efficacy, precision, and impartiality in legal proceedings, while also expressing apprehensions regarding potential partialities, ethical predicaments, and risks to confidentiality and human liberties. Furthermore, it is crucial to underscore the significance of interdisciplinary cooperation and comprehensive regulatory frameworks in guaranteeing the judicious and impartial integration of AI technologies in the justice system. The present study endeavors to make a significant scholarly contribution to the ongoing discourse surrounding artificial intelligence and its intersection with the legal field. By examining the opportunities and challenges of integrating AI in legal systems, this review provides specific insights into formulating policies around algorithmic accountability, transparency, and ethical safeguards to ensure responsible AI adoption. \u0000 \u0000Received: 27 October 2023 / Accepted: 29 February 2024 / Published: 5 March 2024","PeriodicalId":37106,"journal":{"name":"Academic Journal of Interdisciplinary Studies","volume":"14 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140263416","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This work models a hard economic scenario in which inflation rate is set to 7%, the price of diesel is increasing, the price of electricity purchased from the power grid is inflated and there is a top limit for daily purchasable electricity on a region, in which there is an attempt to introduce renewable energy on a private property of the size of a residential house of 5 people. The optimal microgrid configuration is approximated by the new Hybrid Genetic-Fireworks Algorithm working in conjunction with a Monte Carlo simulation to find the annual worth, and comparing results with a Genetic Algorithm and a Fireworks Algorithm. The components considered are: solar panels, wind turbines, diesel generators, electric batteries, converters, and a connection to the power grid. The objective is to maximize annual worth. The results show that a cost of energy (COE) of 2.0603 USD per kWh is achievable in such scenario, and recommends the further use of the Hybrid Genetic-Fireworks Algorithm for this type or Renewable Energy Integration studies, as it outperformed their 2 counterparts in this work. Received: 12 January 2024 / Accepted: 19 February 2024 / Published: 5 March 2024
{"title":"High Stress Economic Scenario on Renewable Energy Integration with Genetic-Firework Hybrid Algorithm","authors":"Nicolas Lopez Ramos, Altina Hoti, Takeaki Toma","doi":"10.36941/ajis-2024-0051","DOIUrl":"https://doi.org/10.36941/ajis-2024-0051","url":null,"abstract":"This work models a hard economic scenario in which inflation rate is set to 7%, the price of diesel is increasing, the price of electricity purchased from the power grid is inflated and there is a top limit for daily purchasable electricity on a region, in which there is an attempt to introduce renewable energy on a private property of the size of a residential house of 5 people. The optimal microgrid configuration is approximated by the new Hybrid Genetic-Fireworks Algorithm working in conjunction with a Monte Carlo simulation to find the annual worth, and comparing results with a Genetic Algorithm and a Fireworks Algorithm. The components considered are: solar panels, wind turbines, diesel generators, electric batteries, converters, and a connection to the power grid. The objective is to maximize annual worth. The results show that a cost of energy (COE) of 2.0603 USD per kWh is achievable in such scenario, and recommends the further use of the Hybrid Genetic-Fireworks Algorithm for this type or Renewable Energy Integration studies, as it outperformed their 2 counterparts in this work. \u0000 \u0000Received: 12 January 2024 / Accepted: 19 February 2024 / Published: 5 March 2024","PeriodicalId":37106,"journal":{"name":"Academic Journal of Interdisciplinary Studies","volume":"14 11","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140264392","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Nelson Alejandro Puyen Farias, Juan Manuel Raunelli Sander
Investment fund managers are limited by the fact that Latin American financial markets offer very few investment possibilities, which forces them to carry out operations at a global level. The objective is to optimize the portfolio management models with indexed stocks in the Lima Stock Exchange (27 stocks considering 2082 days from January 02, 2014 to April 13, 2022) applying the Markowitz models that determine the portfolios of the frontier of investment possibilities. The Sharpe model (CAPM), which calculates the expected return considering systemic risks, and the Sharpe index, which measures the stock return with total risk. Finally, the Black-Litterman (BL) model adjusts the ex-post expected return with expert opinion. By comparing the BL/CAPM ratio, an index is obtained that improves the predictability of expected returns and it is observed that the efficiency of this indicator is greater than the Sharpe index of subsequent expected returns (Sharpe BL). Therefore, the hypothesis that optimizing the portfolio management models improves the predictability of the expected returns of the indexed shares of the Lima Stock Exchange is accepted. Received: 23 July 2023 / Accepted: 10 January 2024 / Published: 5 March 2024
{"title":"Optimization of Portfolio Management Models with Indexed Stocks on the Lima Stock Exchange","authors":"Nelson Alejandro Puyen Farias, Juan Manuel Raunelli Sander","doi":"10.36941/ajis-2024-0032","DOIUrl":"https://doi.org/10.36941/ajis-2024-0032","url":null,"abstract":"Investment fund managers are limited by the fact that Latin American financial markets offer very few investment possibilities, which forces them to carry out operations at a global level. The objective is to optimize the portfolio management models with indexed stocks in the Lima Stock Exchange (27 stocks considering 2082 days from January 02, 2014 to April 13, 2022) applying the Markowitz models that determine the portfolios of the frontier of investment possibilities. The Sharpe model (CAPM), which calculates the expected return considering systemic risks, and the Sharpe index, which measures the stock return with total risk. Finally, the Black-Litterman (BL) model adjusts the ex-post expected return with expert opinion. By comparing the BL/CAPM ratio, an index is obtained that improves the predictability of expected returns and it is observed that the efficiency of this indicator is greater than the Sharpe index of subsequent expected returns (Sharpe BL). Therefore, the hypothesis that optimizing the portfolio management models improves the predictability of the expected returns of the indexed shares of the Lima Stock Exchange is accepted. \u0000 \u0000Received: 23 July 2023 / Accepted: 10 January 2024 / Published: 5 March 2024","PeriodicalId":37106,"journal":{"name":"Academic Journal of Interdisciplinary Studies","volume":"60 12","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140264434","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Tibisay Milene Lamus de Rodríguez, María Cristina Arias-Iturralde, Jisson Oswaldo Vega-Intriago, Verónica Monserrate Mendoza-Fernández, Jimmy Manuel Zambrano-Acosta, Ruben Dario Cardenas-Hinojosa, J. S. Moreira-Choez
The pedagogical methodology has evolved in recent years, moving towards approaches that integrate advances in neuroscience with educational practices. In this context, the HERVAT method emerges, aiming to consolidate these advances and apply them in the educational sphere to enhance the learning experience. The main objective of this research was to implement the HERVAT method in various educational institutions in Ecuador. For this, a qualitative methodology was adopted, with an analysis based on the systematization of experiences and grounded in the profound interpretation of a specific phenomenon. Through a rigorous data collection and analysis process, which incorporated techniques such as observations and documentary analysis, the HERVAT method was applied to students in seven renowned educational institutions in the country. The findings of the study highlight those contemporary pedagogical interventions, supported by this method, emphasize the holistic development of the student. By integrating innovative techniques, such as gamification and multisensory stimulation, the aim is to align pedagogical practices with key discoveries in neuroscience. This alignment enhances brain plasticity, facilitating adaptability and depth in learning processes. The personalization of strategies and adherence to empirical evidence emerge as fundamental components to elevate educational quality in the contemporary era. It is concluded that the HERVAT method, rooted in neuroscientific principles, revitalizes learning by activating crucial neural circuits, optimizing aspects such as student attention and concentration. Strategies based on neurodidactics, backed by empirical evidence, highlight the relevance of natural environments and varied stimuli, enhancing sensory perception and the active commitment of the student in their educational process. This approach promotes comprehensive education, aiming to maximize each student's neurocognitive potential. Received: 22 September 2023 / Accepted: 27 January 2024 / Published: 5 March 2024
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