Pub Date : 2024-06-12DOI: 10.61467/2007.1558.2024.v15i2.465
Victor Giovanni Morales-Murillo, David Pinto, Fernando Pérez-Téllez, Franco Rojas-Lopez
Recommender systems are one of the most critical applications of AI, data science, and advanced analytics techniques because it has become integrated into our daily lives. Additionally, it serves as a powerful tool for making informed, effective, and efficient decisions and choices across a wide range of items. However, traditional techniques such as content-based and collaborative filtering often fail to consider the dynamic and short-term preferences of users when generating recommendations. To address this limitation, this research focuses on a session-based recommendation task using an XLNet transformer with various training strategies based on language modeling. Moreover, a dataset containing 102 million reviews of Amazon products was pre-processed to create two new datasets, one for a single domain and another for multi-domain data. A comparison between a GRU and the training strategies of XLNet reveals that the best training strategy achieves a 136.23% improvement in NDCG@20 and a 95.69% increase in Recall@20 for multi-domain data. In a single domain, it achieves a 168.81% improvement in NDCG@20 and a 25% increase in Recall@10.
{"title":"A Transformer-Based Multi-Domain Recommender System for E-commerce","authors":"Victor Giovanni Morales-Murillo, David Pinto, Fernando Pérez-Téllez, Franco Rojas-Lopez","doi":"10.61467/2007.1558.2024.v15i2.465","DOIUrl":"https://doi.org/10.61467/2007.1558.2024.v15i2.465","url":null,"abstract":"Recommender systems are one of the most critical applications of AI, data science, and advanced analytics techniques because it has become integrated into our daily lives. Additionally, it serves as a powerful tool for making informed, effective, and efficient decisions and choices across a wide range of items. However, traditional techniques such as content-based and collaborative filtering often fail to consider the dynamic and short-term preferences of users when generating recommendations. To address this limitation, this research focuses on a session-based recommendation task using an XLNet transformer with various training strategies based on language modeling. Moreover, a dataset containing 102 million reviews of Amazon products was pre-processed to create two new datasets, one for a single domain and another for multi-domain data. A comparison between a GRU and the training strategies of XLNet reveals that the best training strategy achieves a 136.23% improvement in NDCG@20 and a 95.69% increase in Recall@20 for multi-domain data. In a single domain, it achieves a 168.81% improvement in NDCG@20 and a 25% increase in Recall@10.","PeriodicalId":42388,"journal":{"name":"International Journal of Combinatorial Optimization Problems and Informatics","volume":null,"pages":null},"PeriodicalIF":0.3,"publicationDate":"2024-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141353430","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}
Pub Date : 2024-06-12DOI: 10.61467/2007.1558.2024.v15i2.431
A. Fuentes-Penna, J. D. D. González Ibarra
The Sustainable Development Goals (SDGs) are a universal call for action to end poverty, protect the planet, and improve people's quality of life. With the approval of the 17 SDGs as part of the 2030 Agenda for Sustainable Development, a plan was established to achieve them in 15 years. Quality Education (SDG 4) is fundamental to the development of people and societies, as it enables individuals to express themselves, actively participate in society, and make decisions that benefit their lives. Access to education is a determining factor in overcoming poverty and discrimination; it can improve the quality of life through an orientation towards better job opportunities, better health conditions, and greater participation in civic activities, among other aspects in which education itself has a direct or indirect impact. In this chapter, we present the importance of the use of new technologies as facilitators to expand the positive impact of education.
{"title":"Personalized Education and Artificial Intelligence","authors":"A. Fuentes-Penna, J. D. D. González Ibarra","doi":"10.61467/2007.1558.2024.v15i2.431","DOIUrl":"https://doi.org/10.61467/2007.1558.2024.v15i2.431","url":null,"abstract":"The Sustainable Development Goals (SDGs) are a universal call for action to end poverty, protect the planet, and improve people's quality of life. With the approval of the 17 SDGs as part of the 2030 Agenda for Sustainable Development, a plan was established to achieve them in 15 years. \u0000Quality Education (SDG 4) is fundamental to the development of people and societies, as it enables individuals to express themselves, actively participate in society, and make decisions that benefit their lives. Access to education is a determining factor in overcoming poverty and discrimination; it can improve the quality of life through an orientation towards better job opportunities, better health conditions, and greater participation in civic activities, among other aspects in which education itself has a direct or indirect impact. In this chapter, we present the importance of the use of new technologies as facilitators to expand the positive impact of education.","PeriodicalId":42388,"journal":{"name":"International Journal of Combinatorial Optimization Problems and Informatics","volume":null,"pages":null},"PeriodicalIF":0.3,"publicationDate":"2024-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141351335","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}
Pub Date : 2024-06-12DOI: 10.61467/2007.1558.2024.v15i2.467
Alba Maribel Sánchez Gálvez, Francisco Javier Albores, Ricardo Álvarez González, Said González Conde, Sully Sánchez Gálvez
False information published with the intention of misleading social media users is known as fake news. These are created to appear as credible and genuine information and can manipulate opinions and be disseminated for political or financial purposes (Kaliyar et al., 2021). Fake news is especially propagated on Twitter, today X due to its great capacity for interaction with users, as well as the possibility of retweeting and commenting, which allows for greater dissemination of information. This study proposes a model for detecting fake news in Spanish, which faces challenges such as linguistic diversity and limited resources available for preprocessing. Using a database of approximately 40,000 news extracted from two acquaintances news accounts in Mexico on Twitter, such as “Reforma” and “El Deforma”, from 2019 to 2024, a model based on Natural Language Processing, Machine Learning, Deep Learning, and transformer models were developed. This model allows distinguishing whether a headline of a news article in Spanish published on Twitter is true or fake. The algorithms used include Logistic Regression, Naïve Bayes, Support Vector Machines, LSTM, Bidirectional LSTM and mBERT and BETO. After comparing their results, the best accuracy of 0.98 was obtained with BETO. Therefore, transformer-based models outperformed the other approaches used in the study in terms of accuracy. This study allowed identifying the words frequently used in the corpus of fake news, concluding that they often use expressions with exaggerated adjectives and words expressing certainty or amazement in a social, political, and entertainment context.
{"title":"A study on the Detection of Fake news in Spanish","authors":"Alba Maribel Sánchez Gálvez, Francisco Javier Albores, Ricardo Álvarez González, Said González Conde, Sully Sánchez Gálvez","doi":"10.61467/2007.1558.2024.v15i2.467","DOIUrl":"https://doi.org/10.61467/2007.1558.2024.v15i2.467","url":null,"abstract":"False information published with the intention of misleading social media users is known as fake news. These are created to appear as credible and genuine information and can manipulate opinions and be disseminated for political or financial purposes (Kaliyar et al., 2021). Fake news is especially propagated on Twitter, today X due to its great capacity for interaction with users, as well as the possibility of retweeting and commenting, which allows for greater dissemination of information. \u0000This study proposes a model for detecting fake news in Spanish, which faces challenges such as linguistic diversity and limited resources available for preprocessing. Using a database of approximately 40,000 news extracted from two acquaintances news accounts in Mexico on Twitter, such as “Reforma” and “El Deforma”, from 2019 to 2024, a model based on Natural Language Processing, Machine Learning, Deep Learning, and transformer models were developed. This model allows distinguishing whether a headline of a news article in Spanish published on Twitter is true or fake. \u0000The algorithms used include Logistic Regression, Naïve Bayes, Support Vector Machines, LSTM, Bidirectional LSTM and mBERT and BETO. After comparing their results, the best accuracy of 0.98 was obtained with BETO. Therefore, transformer-based models outperformed the other approaches used in the study in terms of accuracy. This study allowed identifying the words frequently used in the corpus of fake news, concluding that they often use expressions with exaggerated adjectives and words expressing certainty or amazement in a social, political, and entertainment context.","PeriodicalId":42388,"journal":{"name":"International Journal of Combinatorial Optimization Problems and Informatics","volume":null,"pages":null},"PeriodicalIF":0.3,"publicationDate":"2024-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141352691","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}
Pub Date : 2024-06-12DOI: 10.61467/2007.1558.2024.v15i2.472
Roberto A. Contreras-Massé, Alberto Ochoa, Irma Hernandez-Baez, Cely Ronquillo, Humberto Garcia, Rafael Torres-Escobar
The fashion industry is undergoing a paradigm shift towards sustainability, embracing Circular Economy principles. This revolution displaces the traditional linear model, focusing on reusing garments made from materials like Acrylan and Terlenka. The study examines their environmental impact and durability, while exploring innovative recycling technologies to extend their lifespan. Generation Z plays a crucial role in driving this change. Their environmental consciousness and commitment to ethical consumerism shape industry norms through social media and sustainable fashion choices. The paper also analyzes successful case studies of fashion companies integrating Circular Economy practices, highlighting benefits for both businesses and consumers. This Sustainable Fashion Revolution, with its focus on circularity, material innovation, and Gen Z's influence, envisions a future where fashion becomes a symbol of environmental responsibility, paving the way for a more ethical and conscientious industry.
时装业正在经历一场可持续发展的范式转变，拥抱循环经济原则。这场革命取代了传统的线性模式，重点是重新利用由 Acrylan 和 Terlenka 等材料制成的服装。这项研究探讨了它们对环境的影响和耐用性，同时还探索了延长其使用寿命的创新回收技术。Z 世代在推动这一变革方面发挥着至关重要的作用。他们的环保意识和对道德消费主义的承诺通过社交媒体和可持续时尚的选择塑造了行业规范。本文还分析了时尚公司整合循环经济实践的成功案例研究，强调了企业和消费者的利益。这场可持续时尚革命关注循环经济、材料创新和 Z 世代的影响，展望未来，时尚将成为环境责任的象征，为一个更具道德和良知的行业铺平道路。
{"title":"The Sustainable Fashion Revolution considering Circular Economy and targeting Generation Z by reusing garments with Acrylan and Terlenka","authors":"Roberto A. Contreras-Massé, Alberto Ochoa, Irma Hernandez-Baez, Cely Ronquillo, Humberto Garcia, Rafael Torres-Escobar","doi":"10.61467/2007.1558.2024.v15i2.472","DOIUrl":"https://doi.org/10.61467/2007.1558.2024.v15i2.472","url":null,"abstract":"The fashion industry is undergoing a paradigm shift towards sustainability, embracing Circular Economy principles. This revolution displaces the traditional linear model, focusing on reusing garments made from materials like Acrylan and Terlenka. The study examines their environmental impact and durability, while exploring innovative recycling technologies to extend their lifespan. Generation Z plays a crucial role in driving this change. Their environmental consciousness and commitment to ethical consumerism shape industry norms through social media and sustainable fashion choices. The paper also analyzes successful case studies of fashion companies integrating Circular Economy practices, highlighting benefits for both businesses and consumers. \u0000This Sustainable Fashion Revolution, with its focus on circularity, material innovation, and Gen Z's influence, envisions a future where fashion becomes a symbol of environmental responsibility, paving the way for a more ethical and conscientious industry.","PeriodicalId":42388,"journal":{"name":"International Journal of Combinatorial Optimization Problems and Informatics","volume":null,"pages":null},"PeriodicalIF":0.3,"publicationDate":"2024-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141351717","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}
Pub Date : 2024-05-24DOI: 10.61467/2007.1558.2024.v15i1.435
José Abiel Mendoza-Labastida, Mireya Clavel-Maqueda, Orlando García-Pérez, Eduardo Cornejo-Velazquez
A case study of a pharmaceutical distribution company with a relational database that is migrated to a document-oriented NoSQL database for which a hybrid distribution strategy based on fragmentation and replication is implemented. The legacy relational database schema was thoroughly analyzed and evaluated to determine the collections and documents needed to move all the data and leverage the capabilities of the document-based database. In addition, a hybrid data distribution strategy was designed to effectively balance the performance, scalability, and fault tolerance of the system. Finally, integrated operational tests were performed on the distributed system nodes to verify that they function properly and ensure their availability for the company's operations.
{"title":"An empirical hybrid strategy for NoSQL database distribution","authors":"José Abiel Mendoza-Labastida, Mireya Clavel-Maqueda, Orlando García-Pérez, Eduardo Cornejo-Velazquez","doi":"10.61467/2007.1558.2024.v15i1.435","DOIUrl":"https://doi.org/10.61467/2007.1558.2024.v15i1.435","url":null,"abstract":"\u0000A case study of a pharmaceutical distribution company with a relational database that is migrated to a document-oriented NoSQL database for which a hybrid distribution strategy based on fragmentation and replication is implemented. The legacy relational database schema was thoroughly analyzed and evaluated to determine the collections and documents needed to move all the data and leverage the capabilities of the document-based database. In addition, a hybrid data distribution strategy was designed to effectively balance the performance, scalability, and fault tolerance of the system. Finally, integrated operational tests were performed on the distributed system nodes to verify that they function properly and ensure their availability for the company's operations. \u0000","PeriodicalId":42388,"journal":{"name":"International Journal of Combinatorial Optimization Problems and Informatics","volume":null,"pages":null},"PeriodicalIF":0.3,"publicationDate":"2024-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141098716","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}
Pub Date : 2024-05-24DOI: 10.61467/2007.1558.2024.v15i1.375
Francisco J. Espinosa Garcia, Ricardo Tapia Herrera, Tonatiuh Cortés Hernández, J. A. Meda Campaña
Analytical and numerical methods have been applied to solve problems in engineering. However, in some practical cases, they usually fail when there is a certain degree of complexity, for instance, when there is a certain lack of information about the elements of the system and when the unknowns are functions. These types of problems are often called nonlinear optimization problems. As an alternative to solving them, evolutionary computation methods are usually implemented, although they do not generate an exact solution, and provide a series of approximations that are generally feasible. In this context, the objective of this work is to briefly highlight the most typical characteristics of these type of algorithms, some advantages, and the importance of its use today. Due to the wide variety of existing methods, it would become complex to explain all of them in detail, so only a description of the differential evolution (DE) algorithm will be made because it is one of the most used and because there is current research that seeks to improve its performance.
{"title":"Evolutionary computation, an alternative solution to nonlinear optimization problems","authors":"Francisco J. Espinosa Garcia, Ricardo Tapia Herrera, Tonatiuh Cortés Hernández, J. A. Meda Campaña","doi":"10.61467/2007.1558.2024.v15i1.375","DOIUrl":"https://doi.org/10.61467/2007.1558.2024.v15i1.375","url":null,"abstract":"Analytical and numerical methods have been applied to solve problems in engineering. However, in some practical cases, they usually fail when there is a certain degree of complexity, for instance, when there is a certain lack of information about the elements of the system and when the unknowns are functions. These types of problems are often called nonlinear optimization problems. As an alternative to solving them, evolutionary computation methods are usually implemented, although they do not generate an exact solution, and provide a series of approximations that are generally feasible. In this context, the objective of this work is to briefly highlight the most typical characteristics of these type of algorithms, some advantages, and the importance of its use today. Due to the wide variety of existing methods, it would become complex to explain all of them in detail, so only a description of the differential evolution (DE) algorithm will be made because it is one of the most used and because there is current research that seeks to improve its performance.","PeriodicalId":42388,"journal":{"name":"International Journal of Combinatorial Optimization Problems and Informatics","volume":null,"pages":null},"PeriodicalIF":0.3,"publicationDate":"2024-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141102191","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}
Pub Date : 2024-05-24DOI: 10.61467/2007.1558.2024.v15i1.422
Alan Alberto Silva Cornejo, David Tomás Vargas Requena, Juan Carlos Huerta Mendoza, José Lázaro Martínez Rodríguez, Wenceslao Rodriguez
The possibility of improving the learning that a student obtains considering the learning styles that he or she has, refers to the best way to retain learning based on 4 primary stimuli, such as sight, hearing, touch, and experience. In this research work, an intelligent tutoring system is described based on 2 small surveys. The system will obtain sufficient information to determine those educational strategies or techniques that favor not only the students as individuals but the classroom as a group, also favoring the teacher a route learning process focused on how students learn best. To obtain educational strategies, the intelligent tutor system makes use of one of the multiple techniques of artificial intelligence such as fuzzy logic, necessary to obtain a result with greater precision, an issue that would hardly be possible using basic logic or conventional due to the uncertainty it generates. In turn, the software is developed using the Laravel work environment using MySQL as the main database manager.
考虑到学生的学习方式，提高学生学习效果的可能性，是指基于视觉、听觉、触觉和经验等 4 种主要刺激来保持学习效果的最佳方式。在这项研究工作中，基于两项小型调查，描述了一个智能辅导系统。该系统将获得足够的信息，以确定那些不仅有利于作为个体的学生，而且有利于作为群体的课堂的教育策略或技术，同时也有利于教师根据学生的最佳学习方式确定学习路线。为了获得教育策略，智能辅导系统使用了人工智能的多种技术之一，如模糊逻辑，这是获得更精确结果所必需的。该软件使用 Laravel 工作环境开发，使用 MySQL 作为主要数据库管理器。
{"title":"An Intelligent Tutoring System for Identification of Learning Styles and Assignment Educational Strategies","authors":"Alan Alberto Silva Cornejo, David Tomás Vargas Requena, Juan Carlos Huerta Mendoza, José Lázaro Martínez Rodríguez, Wenceslao Rodriguez","doi":"10.61467/2007.1558.2024.v15i1.422","DOIUrl":"https://doi.org/10.61467/2007.1558.2024.v15i1.422","url":null,"abstract":"The possibility of improving the learning that a student obtains considering the learning styles that he or she has, refers to the best way to retain learning based on 4 primary stimuli, such as sight, hearing, touch, and experience. In this research work, an intelligent tutoring system is described based on 2 small surveys. The system will obtain sufficient information to determine those educational strategies or techniques that favor not only the students as individuals but the classroom as a group, also favoring the teacher a route learning process focused on how students learn best. To obtain educational strategies, the intelligent tutor system makes use of one of the multiple techniques of artificial intelligence such as fuzzy logic, necessary to obtain a result with greater precision, an issue that would hardly be possible using basic logic or conventional due to the uncertainty it generates. In turn, the software is developed using the Laravel work environment using MySQL as the main database manager.","PeriodicalId":42388,"journal":{"name":"International Journal of Combinatorial Optimization Problems and Informatics","volume":null,"pages":null},"PeriodicalIF":0.3,"publicationDate":"2024-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141102646","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}
Pub Date : 2024-05-24DOI: 10.61467/2007.1558.2024.v15i1.390
Jorge Santiago-Amaya, Diego Escamilla-Amador, F. Trejo-Macotela, D. Robles-Camarillo
Advances in medical technology suggest that the application of implantable medical devices or Smart Hospital Devices (SHD) can enhance the control and treatment of chronic disorders. However, most of these developments require an electrical power source for operation, making the use of batteries unfeasible. This paper presents the design and resonance analysis of four different geometries for the fabrication of planar antennas as an alternative to a contactless power supply. Previously published software [19] was used to calculate the electrical parameters for each coil design. Operating trials were executed under laboratory conditions, and a bracket manufactured using polylactic acid (PLA) through a 3D printer was used to accurately define the distances between coils to achieve correct alignment between them. Based on the experimental results, it was possible to calculate the resonant frequency of the inductive links at a 5 mm spacing. Similarly, it is possible to calculate the capacitive effect necessary to improve the resonant circuit in different transmitter-receiver planar antenna pairs. The most efficient combination to induce voltage in these links is to use the hexagonal profile design as a transmitter and receiver antenna, applying a sinusoidal signal with 8 MHz frequency.
医疗技术的进步表明，植入式医疗设备或智能医院设备（SHD）的应用可以加强对慢性疾病的控制和治疗。然而，这些开发成果大多需要电力驱动才能运行，因此使用电池是不可行的。本文介绍了用于制造平面天线的四种不同几何形状的设计和共振分析，以替代非接触式电源。本文使用以前发布的软件[19]来计算每种线圈设计的电气参数。在实验室条件下进行了操作试验，并使用 3D 打印机制造的聚乳酸（PLA）支架来精确定义线圈之间的距离，以实现线圈之间的正确对齐。根据实验结果，可以计算出间距为 5 毫米的感应链路的谐振频率。同样，也可以计算出改善不同发射器-接收器平面天线对谐振回路所需的电容效应。在这些链路中感应电压的最有效组合是使用六边形轮廓设计作为发射器和接收器天线，施加频率为 8 MHz 的正弦信号。
{"title":"Planar antenna design for contactless energizing applications: resonance analysis","authors":"Jorge Santiago-Amaya, Diego Escamilla-Amador, F. Trejo-Macotela, D. Robles-Camarillo","doi":"10.61467/2007.1558.2024.v15i1.390","DOIUrl":"https://doi.org/10.61467/2007.1558.2024.v15i1.390","url":null,"abstract":"Advances in medical technology suggest that the application of implantable medical devices or Smart Hospital Devices (SHD) can enhance the control and treatment of chronic disorders. However, most of these developments require an electrical power source for operation, making the use of batteries unfeasible. This paper presents the design and resonance analysis of four different geometries for the fabrication of planar antennas as an alternative to a contactless power supply. Previously published software [19] was used to calculate the electrical parameters for each coil design. Operating trials were executed under laboratory conditions, and a bracket manufactured using polylactic acid (PLA) through a 3D printer was used to accurately define the distances between coils to achieve correct alignment between them. Based on the experimental results, it was possible to calculate the resonant frequency of the inductive links at a 5 mm spacing. Similarly, it is possible to calculate the capacitive effect necessary to improve the resonant circuit in different transmitter-receiver planar antenna pairs. The most efficient combination to induce voltage in these links is to use the hexagonal profile design as a transmitter and receiver antenna, applying a sinusoidal signal with 8 MHz frequency.","PeriodicalId":42388,"journal":{"name":"International Journal of Combinatorial Optimization Problems and Informatics","volume":null,"pages":null},"PeriodicalIF":0.3,"publicationDate":"2024-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141102344","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}
Pub Date : 2024-05-24DOI: 10.61467/2007.1558.2024.v15i1.430
Lemlem Eyob, Tewodros Achamaleh, Muhammad Tayyab, Grigori Sidorov, Ildar Batyrshin
Stress, being a complex emotional state caused by a variety of multiple sources, has the potential for serious effects if left untreated. The primary goal of this research is to select and consider AI models that effectively recognize stress within the complicated domain of social media posts. The significance of this study is not only the categorization of stress but also the interpretation of the sophisticated methods that serve as the basis for these emotional responses. Among the traditional machine learning models, Random Forest, K-Nearest Neighbor, Logistic Regression, Decision Tree, and Support Vector Machine are used. The deep learning model’s LSTM, BiLSTM, and transformer-based models m-BERT, AL-BERT, XLM-RoBERTa, IndicBERT, and Distil-BERT were used. Of those models, LSTM proved to be the best-performing model, with an F1-score of 0.75.
{"title":"Stress Recognition in Code-Mixed Social Media Texts using Machine Learning","authors":"Lemlem Eyob, Tewodros Achamaleh, Muhammad Tayyab, Grigori Sidorov, Ildar Batyrshin","doi":"10.61467/2007.1558.2024.v15i1.430","DOIUrl":"https://doi.org/10.61467/2007.1558.2024.v15i1.430","url":null,"abstract":"Stress, being a complex emotional state caused by a variety of multiple sources, has the potential for serious effects if left untreated. The primary goal of this research is to select and consider AI models that effectively recognize stress within the complicated domain of social media posts. The significance of this study is not only the categorization of stress but also the interpretation of the sophisticated methods that serve as the basis for these emotional responses. Among the traditional machine learning models, Random Forest, K-Nearest Neighbor, Logistic Regression, Decision Tree, and Support Vector Machine are used. The deep learning model’s LSTM, BiLSTM, and transformer-based models m-BERT, AL-BERT, XLM-RoBERTa, IndicBERT, and Distil-BERT were used. Of those models, LSTM proved to be the best-performing model, with an F1-score of 0.75.","PeriodicalId":42388,"journal":{"name":"International Journal of Combinatorial Optimization Problems and Informatics","volume":null,"pages":null},"PeriodicalIF":0.3,"publicationDate":"2024-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141100508","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}
Pub Date : 2024-05-24DOI: 10.61467/2007.1558.2024.v15i1.394
Miguel Ángel Ruiz Jaimes, Maria Arely Gabriel Romero, Rodrigo Alejandro Morales López, Yadira Toledo-Navarro, J. Ruiz-Vanoye, O. Díaz-Parra, Jaime Aguilar Ortiz
Depression is a disorder that usually begins in early adulthood, having a duration according to the World Health Organization (WHO) from a couple of months to a couple of years, however, in approximately 20% of cases there is a chronic evolution that results in a high mortality rate by suicide due to lack of adequate treatment. Therefore, the objective of this project is to facilitate the tools for an adequate care of depression, mainly in young adults through the development of a mobile application that monitors patients. To carry out the project, the enhanced cascade model was implemented, because the feedback between the different phases of the system development life cycle is important to make the appropriate modifications. The application of interviews and the use of brainstorming were the selected way in which all the system requirements were designed and the goals to be met by the system were adequately defined.
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