Proceedings of the 13th International Conference on Intelligent Systems: Theories and Applications最新文献_第2页

Design and Development of a Microstrip Patch Antenna Array for Rectenna System 整流天线系统微带贴片天线阵列的设计与研制

Proceedings of the 13th International Conference on Intelligent Systems: Theories and Applications Pub Date : 2020-09-23 DOI: 10.1145/3419604.3419766

Salah Ihlou, H. Tizyi, A. Bakkali, A. Abbassi, J. Foshi

引用次数: 4

Evaluation of security risks using Apriori algorithm 基于Apriori算法的安全风险评估

Proceedings of the 13th International Conference on Intelligent Systems: Theories and Applications Pub Date : 2020-09-23 DOI: 10.1145/3419604.3419789

W. Abbass, Amine Baïna, M. Bellafkih

{"title":"Evaluation of security risks using Apriori algorithm","authors":"W. Abbass, Amine Baïna, M. Bellafkih","doi":"10.1145/3419604.3419789","DOIUrl":"https://doi.org/10.1145/3419604.3419789","url":null,"abstract":"The progress of IT technologies offers many means to collect and store an extremely large quantity of data and conveys a prodigious quantity of information in several sectors of activity. However, this progress is not only exposed to classic operational risks such as fire or blackouts, but also to various viruses and data theft. These extremely technologically complex risks have risen a big challenge at responding to a large-scale of intangible threats within an industry of perpetual change. Wherefore, the value of Security Risk Assessment \"SRA\" at ensuring the protection of the organizations' business services. However, conducting SRA is difficult and time-consuming and its results may not project the risky behaviors which often leads to unnecessary controls being implemented. Therefore, we tolerate using the Apriori algorithm as a prominent approach accurately determining the threat sources emerging within the risky behaviors. The Apriori algorithm is very useful at better mapping the relationship between organization critical assets and the potential threats-vulnerabilities. We use a history dataset of security risks in order to determine association rules between vulnerabilities and the potential threats. The algorithm performs classification which successfully reduces assessment time. As a result, the improved algorithm undertakes recommendations for a better SRA conduction.","PeriodicalId":250715,"journal":{"name":"Proceedings of the 13th International Conference on Intelligent Systems: Theories and Applications","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126030698","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

An implementation of a multivariate discretization for supervised learning using Forestdisc 用Forestdisc实现监督学习的多元离散化

Proceedings of the 13th International Conference on Intelligent Systems: Theories and Applications Pub Date : 2020-09-23 DOI: 10.1145/3419604.3419772

Maissae Haddouchi, A. Berrado

引用次数: 1

Latent Graph Predictor Factorization Machine (LGPFM) for modeling feature interactions weight 潜在图预测因子分解机(LGPFM)用于建模特征相互作用的权重

Proceedings of the 13th International Conference on Intelligent Systems: Theories and Applications Pub Date : 2020-09-23 DOI: 10.1145/3419604.3419618

Abdessamad Chanaa, N. E. Faddouli

引用次数: 2

Comparative Study of Arabic Text Categorization Using Feature Selection Techniques and Four Classifier Models 基于特征选择技术和四种分类器模型的阿拉伯语文本分类的比较研究

Proceedings of the 13th International Conference on Intelligent Systems: Theories and Applications Pub Date : 2020-09-23 DOI: 10.1145/3419604.3419778

Said Bahassine, Abdellah Madani, M. Kissi

{"title":"Comparative Study of Arabic Text Categorization Using Feature Selection Techniques and Four Classifier Models","authors":"Said Bahassine, Abdellah Madani, M. Kissi","doi":"10.1145/3419604.3419778","DOIUrl":"https://doi.org/10.1145/3419604.3419778","url":null,"abstract":"Text classification is the process of assigning appropriate categories to free text according to its content. It is one of the important task in Text mining. Numerous studies have been conducted for natural languages processing using Japanese, French, Latin and Turkish documents, but the number of works related to the text written in Arabic language is still limited. In this paper we conduct a comparative study of three methods of feature selection using four well-known classifiers namely: Decision Tree, Naive Bayes, K-Nearest Neighbors and Support Vector Machine. A corpus contained 250 Arabic text belonging into five classes: sport, politics, economics, culture and art, and society. The data set is used to evaluate and compare the effectiveness of the obtained model. The experimental results reveal that using improved Chi-square method as feature selection and Support Vector Machine as classifier outperforms other combinations in terms of precision. This combination significantly improves the performance of Arabic text classification model. The highest value of precision measure for this model is 89.9%.","PeriodicalId":250715,"journal":{"name":"Proceedings of the 13th International Conference on Intelligent Systems: Theories and Applications","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129733314","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: 4

Predicting Ships Estimated Time of Arrival based on AIS Data 基于AIS数据的船舶预计到达时间预测

Proceedings of the 13th International Conference on Intelligent Systems: Theories and Applications Pub Date : 2020-09-23 DOI: 10.1145/3419604.3419768

Sara El Mekkaoui, L. Benabbou, A. Berrado

引用次数: 6

Deep Learning Approach for Forecasting Athletes' Performance in Sports Tournaments 预测运动员在体育比赛中的表现的深度学习方法

Proceedings of the 13th International Conference on Intelligent Systems: Theories and Applications Pub Date : 2020-09-23 DOI: 10.1145/3419604.3419786

Hadeel T. El Kassabi, Khaled Khalil, M. Serhani

{"title":"Deep Learning Approach for Forecasting Athletes' Performance in Sports Tournaments","authors":"Hadeel T. El Kassabi, Khaled Khalil, M. Serhani","doi":"10.1145/3419604.3419786","DOIUrl":"https://doi.org/10.1145/3419604.3419786","url":null,"abstract":"Sports and international tournaments have gained world attention in the past decade. Enhancing sports activities and promoting sports to participate in international events, competitions, and tournaments play a substantial role in the development and advancement of nations around the globe. In this paper, we applied different deep learning models for predicting athletes' performance in tournaments to help them improve their results. We propose a deep learning selection algorithm to evaluate the effectiveness of the athletes' current training by predicting their race results upon completing each additional training, which potentially improves their performance. We gathered public training data for athletes who participated in the 2017 Boston Marathon within a five-month window prior to the race. Deep learning models were applied and evaluated to predict marathon finishing times. These include Recurrent Neural Networks (RNN), Long Short-Term Memory (LSTM), and Gated Recurrent Units (GRU). Results show that Deep Learning models give improved race time prediction accuracy over the baseline machine learning model, such as standard Linear Regression (LR).","PeriodicalId":250715,"journal":{"name":"Proceedings of the 13th International Conference on Intelligent Systems: Theories and Applications","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124832606","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

Construction of a database for speech recognition of isolated Arabic words 阿拉伯孤立词语音识别数据库的构建

Proceedings of the 13th International Conference on Intelligent Systems: Theories and Applications Pub Date : 2020-09-23 DOI: 10.1145/3419604.3419752

Ahmed Boumehdi, A. Yousfi

引用次数: 3

Data Flooding Intrusion Detection System for MANETs Using Deep Learning Approach 基于深度学习方法的数据泛洪入侵检测系统

Proceedings of the 13th International Conference on Intelligent Systems: Theories and Applications Pub Date : 2020-09-23 DOI: 10.1145/3419604.3419777

Oussama Sbai, M. Elboukhari

引用次数: 10

SPM SPM

Proceedings of the 13th International Conference on Intelligent Systems: Theories and Applications Pub Date : 2020-09-23 DOI: 10.1145/3419604.3419782

Aola Yousfi, Moulay Hafid El Yazidi, A. Zellou

引用次数: 1