In Mexico, school dropout is a common issue with drastic consequences for economical and social development, for this reason, it is important to address this issue from different perspectives including technological.This article presents an architecture of an automated system for monitoring and preventing school dropout, which aims to help reduce dropout rates in federalized technological baccalaureate system corresponding to the level of upper secondary education. The system tracks three main factors of dropping out of school: truancy, failing notes and misbehavior, as well as generating objective communication with parents about these activities by the student. The system has three modules, namely, a) Web site for institutional tracking of students; b) Real time embedded software that allows knowing the presence/absence of students, using facial recognition and raspberry pi, and c) mobile application, to send timely information to parents.
{"title":"Architecture of an Automated System for the Monitoring and Preventión of School DropOut","authors":"Yareli Vanessa Flores Vizcaino, Omar Zatarain Duran, Rodolfo Omar Domínguez García, Miriam González Dueñas","doi":"10.1109/CIMPS52057.2020.9390097","DOIUrl":"https://doi.org/10.1109/CIMPS52057.2020.9390097","url":null,"abstract":"In Mexico, school dropout is a common issue with drastic consequences for economical and social development, for this reason, it is important to address this issue from different perspectives including technological.This article presents an architecture of an automated system for monitoring and preventing school dropout, which aims to help reduce dropout rates in federalized technological baccalaureate system corresponding to the level of upper secondary education. The system tracks three main factors of dropping out of school: truancy, failing notes and misbehavior, as well as generating objective communication with parents about these activities by the student. The system has three modules, namely, a) Web site for institutional tracking of students; b) Real time embedded software that allows knowing the presence/absence of students, using facial recognition and raspberry pi, and c) mobile application, to send timely information to parents.","PeriodicalId":439186,"journal":{"name":"2020 9th International Conference On Software Process Improvement (CIMPS)","volume":"85 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131698296","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 : 2020-10-21DOI: 10.1109/CIMPS52057.2020.9390095
Humberto Cruz-Sanabria, M. G. Sánchez, J. P. Rivera-Caicedo, H. Avila-George
Sugarcane is a crop of great commercial and economic importance in over 130 countries, including Mexico. One of the main problems faced by sugarcane producers is how to improve the yield of the crop. In order to develop new techniques that can improve the yield of the sugarcane crop, it is key to be able to identify the critical stages of growth and to be able to make timely decisions. In this paper, a method is presented to identify the phenological stages of sugarcane crops using data from the MultiSpectral Instrument sensor onboard the Sentinel-2 satellite. For the development of the proposed method, classification some methods were evaluated: k-Nearest Neighbors, Random Forest, Support Vector Machine, and Naïve Bayes. Also, time series of five vegetation indices were used as input data; the results were validated using the cross-validation technique with k = 10 iterations. The results show that the method Random Forest achieves an accuracy = 92.45 %, which is the best suited to identify the growth stages of sugarcane crops.
{"title":"Identification of phenological stages of sugarcane cultivation using Sentinel-2 images","authors":"Humberto Cruz-Sanabria, M. G. Sánchez, J. P. Rivera-Caicedo, H. Avila-George","doi":"10.1109/CIMPS52057.2020.9390095","DOIUrl":"https://doi.org/10.1109/CIMPS52057.2020.9390095","url":null,"abstract":"Sugarcane is a crop of great commercial and economic importance in over 130 countries, including Mexico. One of the main problems faced by sugarcane producers is how to improve the yield of the crop. In order to develop new techniques that can improve the yield of the sugarcane crop, it is key to be able to identify the critical stages of growth and to be able to make timely decisions. In this paper, a method is presented to identify the phenological stages of sugarcane crops using data from the MultiSpectral Instrument sensor onboard the Sentinel-2 satellite. For the development of the proposed method, classification some methods were evaluated: k-Nearest Neighbors, Random Forest, Support Vector Machine, and Naïve Bayes. Also, time series of five vegetation indices were used as input data; the results were validated using the cross-validation technique with k = 10 iterations. The results show that the method Random Forest achieves an accuracy = 92.45 %, which is the best suited to identify the growth stages of sugarcane crops.","PeriodicalId":439186,"journal":{"name":"2020 9th International Conference On Software Process Improvement (CIMPS)","volume":"78 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122737359","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 : 2020-10-21DOI: 10.1109/cimps52057.2020.9390154
Israel Faustino, J. Mejía
La Ingeniería de Software ha evolucionado y se han desarrollado diferentes marcos de trabajo, metodologías, modelos y estándares que permiten la implementación de los diferentes procesos de desarrollo de software. En México, actualmente existen 494 organizaciones dictaminadas en la norma NMX-I-059/02-NYCE(MoProSoft) y 78 certificadas en la norma internacional ISO/IEC 29110-4-1:2011 [1] .
{"title":"Marco de trabajo de desarrollo de software con base en el estándar ISO/IEC 29110 en el sector gubernamental","authors":"Israel Faustino, J. Mejía","doi":"10.1109/cimps52057.2020.9390154","DOIUrl":"https://doi.org/10.1109/cimps52057.2020.9390154","url":null,"abstract":"La Ingeniería de Software ha evolucionado y se han desarrollado diferentes marcos de trabajo, metodologías, modelos y estándares que permiten la implementación de los diferentes procesos de desarrollo de software. En México, actualmente existen 494 organizaciones dictaminadas en la norma NMX-I-059/02-NYCE(MoProSoft) y 78 certificadas en la norma internacional ISO/IEC 29110-4-1:2011 [1] .","PeriodicalId":439186,"journal":{"name":"2020 9th International Conference On Software Process Improvement (CIMPS)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123417409","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 : 2020-10-21DOI: 10.1109/cimps52057.2020.9390106
{"title":"[Copyright notice]","authors":"","doi":"10.1109/cimps52057.2020.9390106","DOIUrl":"https://doi.org/10.1109/cimps52057.2020.9390106","url":null,"abstract":"","PeriodicalId":439186,"journal":{"name":"2020 9th International Conference On Software Process Improvement (CIMPS)","volume":"2012 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127386997","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}
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