2020 39th International Conference of the Chilean Computer Science Society (SCCC)最新文献_第3页

Information Literacy for Lifelong Learning: an experience with Personal Learning Environments 终身学习的信息素养:个人学习环境的体验

2020 39th International Conference of the Chilean Computer Science Society (SCCC) Pub Date : 2020-11-16 DOI: 10.1109/SCCC51225.2020.9281170

Elizabeth Vidal, Y. Toro

引用次数: 1

A FAIR evaluation of public datasets for stress detection systems 对应力检测系统的公共数据集进行公平评估

2020 39th International Conference of the Chilean Computer Science Society (SCCC) Pub Date : 2020-11-16 DOI: 10.1109/SCCC51225.2020.9281274

Álvaro Cuno, Nelly Condori-Fernández, Alexis Mendoza, Wilber Roberto Ramos Lovón

引用次数: 2

Portable repository for learning objects for schools without Internet connection 便携式存储库学习对象的学校没有互联网连接

2020 39th International Conference of the Chilean Computer Science Society (SCCC) Pub Date : 2020-11-16 DOI: 10.1109/SCCC51225.2020.9281212

Manuel J. Ibarra, Hesmeralda Rojas, Yonatan Mamani-Coaquira, Herwin Alayn Huillcen-Baca, Flor de Luz Palomino-Valdivia, Eliana M. Ibarra-Cabrera

引用次数: 0

An Empirical Comparison of Supervised Algorithms for Ransomware Identification on Network Traffic 基于监督算法的网络流量勒索软件识别的实证比较

2020 39th International Conference of the Chilean Computer Science Society (SCCC) Pub Date : 2020-11-16 DOI: 10.1109/SCCC51225.2020.9281283

C. Manzano, Claudio Meneses Villegas, Paul Leger

{"title":"An Empirical Comparison of Supervised Algorithms for Ransomware Identification on Network Traffic","authors":"C. Manzano, Claudio Meneses Villegas, Paul Leger","doi":"10.1109/SCCC51225.2020.9281283","DOIUrl":"https://doi.org/10.1109/SCCC51225.2020.9281283","url":null,"abstract":"Android mobile systems are currently the main target of malware attacks. In this sense, machine learning is a suitable approach to analyze network traffic, and it generally achieves good results in the identification and detection of malware. However, an underlying problem is creating a dataset with network characteristics that accurately reflect the malwareś behavior. Characterizing adequately the dataset is a relevant process to identify malware with high precision when using traditional machine learning algorithms. This paper compares empirically three supervised machine learning algorithms, in order to identify ransomware traffic based on Android mobile network traffic features. We consider 9 features related to time properties of flows and bidirectional packets in 10 families of ransomware and different benign application Android network traffic. Empirical results show that Random Forest (RF) achieved a 96% accuracy in classifying ransomware, higher than Decision Tree (DT) and K-Nearest Neighbor (KNN) approaches. We conclude that the selected features allow us to identify ransomware traffic and differentiate it from the traffic of benign applications.","PeriodicalId":117157,"journal":{"name":"2020 39th International Conference of the Chilean Computer Science Society (SCCC)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132294105","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: 7

NFT-I technique using IoT to improve hydroponic cultivation of lettuce 利用物联网技术改进生菜水培栽培

2020 39th International Conference of the Chilean Computer Science Society (SCCC) Pub Date : 2020-11-16 DOI: 10.1109/SCCC51225.2020.9281277

Manuel J. Ibarra, E. Alcarraz, Olivia Tapia, Y. P. Atencio, Yonatan Mamani-Coaquira, Herwin Alayn Huillcen-Baca

引用次数: 2

A centralized solution to the student-school assignment problem in segregated environments via a CUDA parallelized simulated annealing algorithm 采用CUDA并行模拟退火算法集中解决了隔离环境下的学生-学校分配问题

2020 39th International Conference of the Chilean Computer Science Society (SCCC) Pub Date : 2020-11-16 DOI: 10.1109/SCCC51225.2020.9281242

Ignacio Lincolao-Venegas, Julio Rojas-Mora

{"title":"A centralized solution to the student-school assignment problem in segregated environments via a CUDA parallelized simulated annealing algorithm","authors":"Ignacio Lincolao-Venegas, Julio Rojas-Mora","doi":"10.1109/SCCC51225.2020.9281242","DOIUrl":"https://doi.org/10.1109/SCCC51225.2020.9281242","url":null,"abstract":"In this work, we implemented a CUDA parallelized simulated annealing algorithm to solve the student-school assignment problem in a highly segregated environment. The objective function optimized considered the average distance from the students to their assigned school, the socio-economic segregation via the dissimilarity index, and the cost of schools partially filled. Using data from the MINEDUC, the INE, and the Municipality of Temuco (Chile), we simulated the distribution of Temuco’s student population, solving its students’ assignment to the city’s schools (29853 students to 85 schools). The results obtained were better with a high number of block (simultaneous students exploring), and a low number of threads (simultaneous schools explored by these students) instantiated in the GPU. Algorithm execution time worsens with the number of blocks and the number of threads, although it remained below 1000 seconds in the worst and below 400 seconds in the best case. However, the algorithm achieves excellent results in reducing socio-economic segregation, taking it from a high level to almost making it disappear. We achieved this result, even with a reduction of the average distance from students to their assigned school.","PeriodicalId":117157,"journal":{"name":"2020 39th International Conference of the Chilean Computer Science Society (SCCC)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131947542","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

Data Lake architecture proposal for the Analysis Directorate of a Regional University 某地区大学分析理事会的数据湖架构方案

2020 39th International Conference of the Chilean Computer Science Society (SCCC) Pub Date : 2020-11-16 DOI: 10.1109/SCCC51225.2020.9281154

A. C. Leal, Ingrid Lefiguala, Rodrigo Tralma, Sebastián González

引用次数: 0

Dynamic worksheets for learning and teaching geometry in primary school education 小学几何教学的动态工作表

2020 39th International Conference of the Chilean Computer Science Society (SCCC) Pub Date : 2020-11-16 DOI: 10.1109/SCCC51225.2020.9281228

Guillermo Guevara Bermúdez, Adriana Tapia Barraza, C. González

引用次数: 0

Using machine learning methods to identify significant variables for the prediction of first-year Informatics Engineering students dropout 使用机器学习方法识别重要变量，用于预测信息工程一年级学生的退学

2020 39th International Conference of the Chilean Computer Science Society (SCCC) Pub Date : 2020-11-16 DOI: 10.1109/SCCC51225.2020.9281280

F. Robles, Jacqueline Köhler, Karen Hinrechsen, V. Araya, Luciano Hidalgo, J. Jara

{"title":"Using machine learning methods to identify significant variables for the prediction of first-year Informatics Engineering students dropout","authors":"F. Robles, Jacqueline Köhler, Karen Hinrechsen, V. Araya, Luciano Hidalgo, J. Jara","doi":"10.1109/SCCC51225.2020.9281280","DOIUrl":"https://doi.org/10.1109/SCCC51225.2020.9281280","url":null,"abstract":"Student dropout is a phenomenon that affects all higher education institutions in Chile, with costs for people, institutions and the State. The reported retention rate of first year students for all Chilean universities was of 75%. Despite the extensive research and the implementation of various models to identify dropout causes and risk groups, few of them have been carried out in the Chilean higher education context.Our work attempts to identify, using machine learning methods, the variables with highest predictive value for student dropout by the end of the first year of study, within a 6-year Informatics Engineering programme with a rather high dropout rate of 21.9% reported on 2018. In that regard, we use the data of 4 cohorts of students (2012-2016) enrolled at the programme, to feed a random forest feature selection process. We later build a decision tree using the identified relevant features, which we later test using data of the 2017-2018 cohorts of students.Despite the fact that the decision tree is over-fitted (97,21% training accuracy against 81.01% test accuracy), the process sheds light on the nature of the variables that determine whether or not a student remains at the end of their first year of study at the University. 6 of the identified factors are academic, and the remaining one is social-cultural.","PeriodicalId":117157,"journal":{"name":"2020 39th International Conference of the Chilean Computer Science Society (SCCC)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128122926","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: 6

Evaluation of University Students Motivation in Learning Kinematics Through M-Learning 大学生移动学习运动学学习动机的评价

2020 39th International Conference of the Chilean Computer Science Society (SCCC) Pub Date : 2020-11-16 DOI: 10.1109/SCCC51225.2020.9281163

Luis A. Laurens Arredondo, Hugo Valdés Riquelme

{"title":"Evaluation of University Students Motivation in Learning Kinematics Through M-Learning","authors":"Luis A. Laurens Arredondo, Hugo Valdés Riquelme","doi":"10.1109/SCCC51225.2020.9281163","DOIUrl":"https://doi.org/10.1109/SCCC51225.2020.9281163","url":null,"abstract":"M-learning is a pedagogical tool that involves the active and dominant presence of mobile technologies in the classroom, demonstrating its effectiveness in meaningful learning, which is why its implementation is increasingly common by university professors. The purpose of this study is to investigate the relationship between motivation and learning in university students through m-learning. The Google Science Journal mobile application was used by students to determine the magnitude and direction of the acceleration vector of a previously selected motor vehicle under the ARCS instructional model. The motivation of university students was measured with the Instructional Material Motivational Survey (IMMS) instrument, which was applied to a group of 15 students from the Civil Engineering career at the Universidad Católica del Maule. The reliability of the instrument was determined by Cronbach’s alpha, giving an overall value of 0.89. The results suggest that the implementation of m-learning in university classrooms was positively valued by the majority of the students surveyed, as well as an increase in the percentage of students who achieved the expected learning compared to previous versions of the course, where the proposed methodology was not implemented. Teachers provide a validated measurement model, as well as solid scientific references that aim to stimulate the use of m-learning, as it has been shown that its implementation favorably stimulates students, as well as their interest in learning and confidence in themselves.","PeriodicalId":117157,"journal":{"name":"2020 39th International Conference of the Chilean Computer Science Society (SCCC)","volume":"41 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126855480","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: 3