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Optimización evolutiva de contextos para la corrección fonética en sistemas de reconocimiento del habla 语音识别系统中语音修正语境的进化优化
Res. Comput. Sci. Pub Date : 2019-12-31 DOI: 10.13053/rcs-148-8-22
R. Cámara, Diego Campos-Sobrino, Mario Campos Soberanis
{"title":"Optimización evolutiva de contextos para la corrección fonética en sistemas de reconocimiento del habla","authors":"R. Cámara, Diego Campos-Sobrino, Mario Campos Soberanis","doi":"10.13053/rcs-148-8-22","DOIUrl":"https://doi.org/10.13053/rcs-148-8-22","url":null,"abstract":"Automatic Speech Recognition (ASR) is an area of growing academic and commercial interest due to the high demand for applications that use it to provide a natural way of communication. It is common for general purpose ASR systems to fail in certain applications that use a domain specific language. Different strategies have been used to reduce the error, such as providing a context that modifies the language model and post-processing correction methods. This article explores the use of an evolutionary process to generate an optimized context for a specific application domain, as well as different correction techniques based on phonetic distance metrics. The results show the viability of a genetic algorithm as a tool for context optimization, which added to a post-processing correction based on phonetic representations is able to reduce the errors on the recognized speech.","PeriodicalId":220522,"journal":{"name":"Res. Comput. Sci.","volume":"65 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129586348","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}
引用次数: 2
Propuesta de red neuronal convolutiva para la predicción de partículas contaminantes PM10 预测PM10污染物的卷积神经网络的建议
Res. Comput. Sci. Pub Date : 2019-12-31 DOI: 10.13053/rcs-148-7-4
Ricardo Domı́nguez-Guevara, Maria del Carmen Cabrera-Hernandez, M. A. Aceves-Fernández, J. C. P. Ortega
{"title":"Propuesta de red neuronal convolutiva para la predicción de partículas contaminantes PM10","authors":"Ricardo Domı́nguez-Guevara, Maria del Carmen Cabrera-Hernandez, M. A. Aceves-Fernández, J. C. P. Ortega","doi":"10.13053/rcs-148-7-4","DOIUrl":"https://doi.org/10.13053/rcs-148-7-4","url":null,"abstract":"","PeriodicalId":220522,"journal":{"name":"Res. Comput. Sci.","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128511139","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}
引用次数: 1
Collective Behaviors in Swarms of Builder Robots 建筑机器人群体中的集体行为
Res. Comput. Sci. Pub Date : 2019-12-31 DOI: 10.13053/rcs-148-11-8
Erick Ordaz-Rivas, A. Rodríguez-Liñán, L. Torres-Treviño
{"title":"Collective Behaviors in Swarms of Builder Robots","authors":"Erick Ordaz-Rivas, A. Rodríguez-Liñán, L. Torres-Treviño","doi":"10.13053/rcs-148-11-8","DOIUrl":"https://doi.org/10.13053/rcs-148-11-8","url":null,"abstract":". Swarm robotics is inspired by the behavior of social animals for the coordination of a large number of low cost and insufficient robots that in performing a task requires collaboration. The behavior in a swarm of robots can be manipulated by changing the parameters of repulsion, attraction, orientation and influence (RAOI). In the case of repulsion, attraction and orientation modify the basic behavior of the swarm cre-ating functional groups of robots keeping them close or dispersed, even forming chains. While the influence parameter is associated with specific stimuli to guide the swarm to perform simple tasks. To demonstrate this, a simulation platform presents the impact of these parameters in a swarm of builder robots considering a task of transporting materials.","PeriodicalId":220522,"journal":{"name":"Res. Comput. Sci.","volume":"241 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121154270","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}
引用次数: 0
Propuesta de sistema de gestión inteligente basado en IoT para hidroponia 基于物联网的水培智能管理系统的建议
Res. Comput. Sci. Pub Date : 2019-12-31 DOI: 10.13053/rcs-148-10-19
Evelyn Gutierrez Leon, Jorge Erik Montiel Arguijo, Chadwick Carreto Arellano, F. R. M. García
{"title":"Propuesta de sistema de gestión inteligente basado en IoT para hidroponia","authors":"Evelyn Gutierrez Leon, Jorge Erik Montiel Arguijo, Chadwick Carreto Arellano, F. R. M. García","doi":"10.13053/rcs-148-10-19","DOIUrl":"https://doi.org/10.13053/rcs-148-10-19","url":null,"abstract":"This article proposes the design of an intelligent management system based on the Internet of Things (IoT) paradigm for the case of hydroponic crop use. The network architecture and design of prototypes are proposed, focused on obtaining the information in “real time” of the key parameters that develop the hydroponic crops of semi-commercial and self-consumption scale, as well as the first version of the graphic interface for mobile devices that will allow crop management and decision making. The premise of the project is the development of a modular, scalable, low-cost solution, easy installation and use.","PeriodicalId":220522,"journal":{"name":"Res. Comput. Sci.","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121448656","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}
引用次数: 2
Comparative Analysis of Interest Point Detectors Algorithms on Robotic Operative System 机器人操作系统兴趣点检测器算法的比较分析
Res. Comput. Sci. Pub Date : 2019-12-31 DOI: 10.13053/rcs-148-10-5
Francisco Javier Valdepeña Rivera, Dante Mújica-Vargas, M. Ruiz
{"title":"Comparative Analysis of Interest Point Detectors Algorithms on Robotic Operative System","authors":"Francisco Javier Valdepeña Rivera, Dante Mújica-Vargas, M. Ruiz","doi":"10.13053/rcs-148-10-5","DOIUrl":"https://doi.org/10.13053/rcs-148-10-5","url":null,"abstract":"Applications of robotic vision have had great advances within the artificial intelligence through the processing of images, as well as the automated systems (robots). A comparative analysis of some interest point detector algorithms will be performed, the next analysis will be about a robotic operating system called ROS, by means of a 2D object detector system. For this purpose, a physical architecture will be carried out to carry out the experimentation within a controlled work environment, in order to demonstrate which algorithm will work best in the future for the development of object recognition systems, implementing this system on Robots.","PeriodicalId":220522,"journal":{"name":"Res. Comput. Sci.","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128772397","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}
引用次数: 0
Study of Spontaneous and Acted Learn-Related Emotions Through Facial Expressions and Galvanic Skin Response 通过面部表情和皮肤电反应研究自发和行动的学习相关情绪
Res. Comput. Sci. Pub Date : 2019-12-31 DOI: 10.13053/rcs-148-5-11
Andres Mitre-Ortiz, Hugo A. Mitre-Hernández
{"title":"Study of Spontaneous and Acted Learn-Related Emotions Through Facial Expressions and Galvanic Skin Response","authors":"Andres Mitre-Ortiz, Hugo A. Mitre-Hernández","doi":"10.13053/rcs-148-5-11","DOIUrl":"https://doi.org/10.13053/rcs-148-5-11","url":null,"abstract":"In learning environments emotions can activate or deactivate the learning process. Boredom, stress and happy –learn-related emotions– are included in physiological signals datasets, but not in Facial Expression Recognition (FER) datasets. In addition to this, Galvanic Skin Response (GSR) signal is the most representative data for emotions classification. This paper presents a technique to generate a dataset of facial expressions and physiological signals of spontaneous and acted learnrelated emotions –boredom, stress, happy and neutral state– presented during video stimuli and face acting. We conducted an experiment with 22 participants (Mexicans); a dataset of 1,840 facial expressions images and 1,584 GSR registers were generated. A Convolutional Neural Network (CNN) model was trained with the facial expression dataset, then statistical analysis was performed with the GSR dataset. MobileNet’s CNN reached an overall accuracy of 94.36% in a confusion matrix, but the accuracy decreased to 28% for non-trained external images. The statistical results of GSR with significant differences in confused emotions are discussed.","PeriodicalId":220522,"journal":{"name":"Res. Comput. Sci.","volume":"148 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128932345","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}
引用次数: 2
Predictive Model as a Tool for Acquiring a Certification for Client Companies and Certifying Entities with Machine Learning 预测模型作为客户公司和机器学习认证实体获取认证的工具
Res. Comput. Sci. Pub Date : 2019-12-31 DOI: 10.13053/rcs-148-6-16
Edgar Gonzalo Cossio Franco, Jorge Alberto Delgado Cazarez, Daniel Noel Torres Godoy
{"title":"Predictive Model as a Tool for Acquiring a Certification for Client Companies and Certifying Entities with Machine Learning","authors":"Edgar Gonzalo Cossio Franco, Jorge Alberto Delgado Cazarez, Daniel Noel Torres Godoy","doi":"10.13053/rcs-148-6-16","DOIUrl":"https://doi.org/10.13053/rcs-148-6-16","url":null,"abstract":"Companies that seek to certify their processes do so with the aim of guaranteeing quality, although few seek it and least of all do so. CMMI is a model that certifies the maturity of the development of products and services. The present work has two proposals: the first is a tool in Java that determines when a client company is apt or not to a CMMI certification and the second is an intelligent analysis model based on machine learning that determines, from predictions, scenarios for decision making.","PeriodicalId":220522,"journal":{"name":"Res. Comput. Sci.","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133624901","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}
引用次数: 0
Evaluating Predictive Techniques in Educational Data Mining: An Unbalanced Data Set Case of Study 评估教育数据挖掘中的预测技术:一个不平衡数据集案例研究
Res. Comput. Sci. Pub Date : 2019-12-31 DOI: 10.13053/rcs-148-3-4
Lourdes Sánchez-Guerrero, J. F. González, B. González-Beltrán, S. González-Brambila
{"title":"Evaluating Predictive Techniques in Educational Data Mining: An Unbalanced Data Set Case of Study","authors":"Lourdes Sánchez-Guerrero, J. F. González, B. González-Beltrán, S. González-Brambila","doi":"10.13053/rcs-148-3-4","DOIUrl":"https://doi.org/10.13053/rcs-148-3-4","url":null,"abstract":". This work presents an evaluation of the predictive techniques decision trees using CART algorithm, Na¨ıve Bayes Classifier, Gradient Boosting Machine and Support Vector Machine for predicting whether a student will successfully complete a programming course or not. Factors considered for prediction were university-entrance and personal criteria like entrance age, gender, scholarship, high school GPA, mark in admission exam and other related with student’s performance in a pre-requisite introductory programming course. The predicted variable takes two values, ‘Approved’ or ‘Not Approved’, and the data record contains an unbalanced portion of the class ’Approved’. For the analysis were considered two data sets, unbalanced and balanced. Evaluation of algorithms was performed considering the concepts of accuracy and ROC area. Results show that accuracy is bigger for the unbalanced data set, but its ROC area was very poor. Using the balanced data set, results were more reliable because accuracy and ROC area are closer. Best results were obtained with Na¨ıve Bayes and Support Vector Machine algorithms. The most important factor in the prediction was whether a student had a scholarship or not.","PeriodicalId":220522,"journal":{"name":"Res. Comput. Sci.","volume":"799 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117044136","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}
引用次数: 1
Methodology for Automatic Identification of Emotions in Learning Environments 学习环境中情绪自动识别的方法
Res. Comput. Sci. Pub Date : 2019-12-31 DOI: 10.13053/rcs-148-5-10
Yesenia N. González-Meneses, Josefina Guerrero García, C. A. R. García, Iván Olmos, J. González-Calleros
{"title":"Methodology for Automatic Identification of Emotions in Learning Environments","authors":"Yesenia N. González-Meneses, Josefina Guerrero García, C. A. R. García, Iván Olmos, J. González-Calleros","doi":"10.13053/rcs-148-5-10","DOIUrl":"https://doi.org/10.13053/rcs-148-5-10","url":null,"abstract":". This paper presents a methodological proposal for automatic identification of emotions in educational environments using machine learning algorithms and physiological and behavioral signal acquisition technologies to identify relations between emotions and learning. Four of the main learning-centered emotions are considered [1]: engagement, boredom, confusion and frustration. It is proposed to make a fusion of data from two physiological and behavioral signal acquisition technologies with the objective of achieving the identification of emotions in the most precise manner. Therefore, considering the stages of the proposed methodology, the first of them is presented and the design of the experiment that will be executed for data collection. The development of an appropriate database with elements belonging to a learning environment for the study of emotions is an essential task.","PeriodicalId":220522,"journal":{"name":"Res. Comput. Sci.","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131916274","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}
引用次数: 2
Modelo para la determinación de la ruta más corta con funciones experimentales para arcos difusos 用实验函数确定扩散弧最短路径的模型
Res. Comput. Sci. Pub Date : 2019-12-31 DOI: 10.13053/rcs-148-8-24
Eduardo Chandomí-Castellanos, E. N. Escobar-Gómez, Sabino Velázquez-Trujillo, Héctor R. Hernández De León, Madaín Pérez Patricio, Carlos Pérez
{"title":"Modelo para la determinación de la ruta más corta con funciones experimentales para arcos difusos","authors":"Eduardo Chandomí-Castellanos, E. N. Escobar-Gómez, Sabino Velázquez-Trujillo, Héctor R. Hernández De León, Madaín Pérez Patricio, Carlos Pérez","doi":"10.13053/rcs-148-8-24","DOIUrl":"https://doi.org/10.13053/rcs-148-8-24","url":null,"abstract":"","PeriodicalId":220522,"journal":{"name":"Res. Comput. Sci.","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133398521","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}
引用次数: 1
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