2020 International Conference on Intelligent Systems and Computer Vision (ISCV)最新文献_第6页

Scalable multi agent system middleware for HPC of Big Data Applications 面向大数据应用HPC的可扩展多代理系统中间件

2020 International Conference on Intelligent Systems and Computer Vision (ISCV) Pub Date : 2020-06-01 DOI: 10.1109/ISCV49265.2020.9204225

Fatima Ezzahra Ezzrhari, Hassna Bensag, M. Youssfi, O. Bouattane, V. Kaburlasos

引用次数: 2

Parameters Optimization of Elastic NET for High Dimensional Data using PSO Algorithm 基于粒子群算法的高维数据弹性网络参数优化

2020 International Conference on Intelligent Systems and Computer Vision (ISCV) Pub Date : 2020-06-01 DOI: 10.1109/ISCV49265.2020.9204218

Mohammed Qaraad, Souad Amjad, P. El-Kafrawy, Hanaa Fathi, Ibrahim I. M. Manhrawy

{"title":"Parameters Optimization of Elastic NET for High Dimensional Data using PSO Algorithm","authors":"Mohammed Qaraad, Souad Amjad, P. El-Kafrawy, Hanaa Fathi, Ibrahim I. M. Manhrawy","doi":"10.1109/ISCV49265.2020.9204218","DOIUrl":"https://doi.org/10.1109/ISCV49265.2020.9204218","url":null,"abstract":"The feature selection method is regarded as an issue with the global combinatorial optimization technique, which aims to reduce the number of features, eliminate irrelevant, noisy and redundant data, such as microarray cancer data containing a small number of samples that have a large number of gene expression levels as features. To select the optimal subset of gene and reduce the dimensionality of cancer microarray data to improve the performance of the classification accuracy. This paper presents a model called PSO-ENSVM which is a hybrid between feature selection, optimization and classification methods. We use a Swarm optimization PSO algorithm which it's mainly the objective of this research is to have space to get near-optimal, optimal or solutions for optimizing the tuning parameters of Elastic Net and SVM as a classifier. To evaluate the model, we use seven microarray data sets for different cancer type, and we compared the PSO-ENSVM model with the PSO-SVM a model that optimizes RBF Kernel hyperparameter without feature selection and SVM with RBF Kernel. The experimental results were presented and showed that the ability of our model to obtain an ideal subset of the feature led to increased rates performance as it was able to reduce the number of features specified. As a result, the results show that the PSO-ENSVM model is superior compared to PSO-SVM and SVM with RBF kernel.","PeriodicalId":313743,"journal":{"name":"2020 International Conference on Intelligent Systems and Computer Vision (ISCV)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115328767","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

A Recommendation Approach in Social Learning Based on K-Means Clustering 基于k均值聚类的社会学习推荐方法

2020 International Conference on Intelligent Systems and Computer Vision (ISCV) Pub Date : 2020-06-01 DOI: 10.1109/ISCV49265.2020.9204203

Sonia Souabi, A. Retbi, M. K. Idrissi, S. Bennani

{"title":"A Recommendation Approach in Social Learning Based on K-Means Clustering","authors":"Sonia Souabi, A. Retbi, M. K. Idrissi, S. Bennani","doi":"10.1109/ISCV49265.2020.9204203","DOIUrl":"https://doi.org/10.1109/ISCV49265.2020.9204203","url":null,"abstract":"Social networks are a powerful and efficient tool for e-learning promoting collaboration between learners. Thus, to better manage the learning process within these environments, it is imperative to use recommendation systems which take a very significant role in suggesting interesting material adapted to the different needs of learners. To model the recommendation systems, the researchers relied on numerous tools such as the exploitation of Machine Learning algorithms or social interactions between learners. Yet, behaviour within a social network can actually differ from one learner to another, so we will be dealing with several categories of learners with distinct attitudes. Based on this, we raise a rather important issue which is to classify the learners according to well-defined criteria and attitudes before calculating the recommendations. In the recommendation system we advocate, we therefore use the k-means algorithm to classify learners, then we calculate the recommendations for each cluster by referring to our old recommendation system proposed in one of our previous works. The global system is thus based on three essential points: k-means, correlation and co-occurrence. We then evaluate the performance of our proposed system in order to show its performance compared to the system that does not consider the k-means algorithm.","PeriodicalId":313743,"journal":{"name":"2020 International Conference on Intelligent Systems and Computer Vision (ISCV)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123480142","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: 5

Detection of Market Manipulation using Ensemble Neural Networks 基于集成神经网络的市场操纵检测

2020 International Conference on Intelligent Systems and Computer Vision (ISCV) Pub Date : 2020-06-01 DOI: 10.1109/ISCV49265.2020.9204330

S. Sridhar, Siddartha Mootha, S. Subramanian

引用次数: 7

Road traffic mortality in Morocco: Analysis of statistical data 摩洛哥的道路交通死亡率:统计数据分析

2020 International Conference on Intelligent Systems and Computer Vision (ISCV) Pub Date : 2020-06-01 DOI: 10.1109/ISCV49265.2020.9204325

Abdelilah Mbarek, Mouna Jiber, Ali Yahyaouy, Abdelouahed Sabri

{"title":"Road traffic mortality in Morocco: Analysis of statistical data","authors":"Abdelilah Mbarek, Mouna Jiber, Ali Yahyaouy, Abdelouahed Sabri","doi":"10.1109/ISCV49265.2020.9204325","DOIUrl":"https://doi.org/10.1109/ISCV49265.2020.9204325","url":null,"abstract":"Over the last decade, around 3500 people lost their lives in road accidents each year in Morocco. Between 2008 and 2017, the number of accidents has seen an increase of 38.11%. Several factors may contribute to the so-called “war on the roads”, such as the behavior of drivers or vehicle condition. Since human behavior is not always the leading cause of traffic crashes, in this work, we propose to study the effect of the environment and road conditions on accident mortality. The study is based on statistical data of accidents that caused death or bodily injuries in Morocco in 2017. The Case Fatality Rate (CFR) indicator was used to measure the severity of accidents, and the technique involved is the well-known non-parametric Analysis of Variance (ANOVA). Thirteen factors were taken into account to describe the state of the infrastructure and the physical conditions of roads. The analysis results show that the factors studied have a significant effect on accident fatality. More specifically, the type of intersection and the location proved to be the variables that contribute more to accident fatality.","PeriodicalId":313743,"journal":{"name":"2020 International Conference on Intelligent Systems and Computer Vision (ISCV)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131359229","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

Literature Review on Driver’s Drowsiness and Fatigue Detection 驾驶员困倦与疲劳检测的文献综述

2020 International Conference on Intelligent Systems and Computer Vision (ISCV) Pub Date : 2020-06-01 DOI: 10.1109/ISCV49265.2020.9204306

Hamed Laouz, Soheyb Ayad, L. Terrissa

引用次数: 8

Multi-agent simulation of the Moroccan conventional insurance sector 摩洛哥传统保险部门的多代理模拟

2020 International Conference on Intelligent Systems and Computer Vision (ISCV) Pub Date : 2020-06-01 DOI: 10.1109/ISCV49265.2020.9204181

Karima Lamsaddak, D. Mentagui

{"title":"Multi-agent simulation of the Moroccan conventional insurance sector","authors":"Karima Lamsaddak, D. Mentagui","doi":"10.1109/ISCV49265.2020.9204181","DOIUrl":"https://doi.org/10.1109/ISCV49265.2020.9204181","url":null,"abstract":"Economic and social change in a digital era is making the insurance ecosystem more complex. It makes several agents interact for different purposes. Therefore, a reflection on the insurance ecosystem modelling through multi-agent simulation seems interesting since it allows to capture the complexity of today’s insured on the one hand and on the other hand to measure the solvency of insurance and reinsurance companies (EAR) in order to ensure the viability of the said ecosystem. Thus, this research aims at modeling the Moroccan insurance ecosystem within the framework of a new risk-based solvency directive for the case of loan death cover and on the basis of a set of exogenous and endogenous factors that influence the solvency of insurance and reinsurance companies in Morocco. This paper is carried out on the basis of a model, developed using NetLogo software, consisting of 4 agents that interact in the case of the “borrower’s death” guarantee, namely: the insured, the EAR, the banks and the Supervisory Authority of Insurance and Social Welfare (ACAPS). Each agent has a set of characteristics and seeks a defined objective. Thus, the modelling carried out allows testing the impact of endogenous and exogenous variables on the solvency of the EAR according to a simulation in three scenarios (central, rainy and risky).","PeriodicalId":313743,"journal":{"name":"2020 International Conference on Intelligent Systems and Computer Vision (ISCV)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122649493","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

Towards a semantic recommender system for cultural objects: Case study Draa-Tafilalet region 面向文物的语义推荐系统:以Draa-Tafilalet地区为例

2020 International Conference on Intelligent Systems and Computer Vision (ISCV) Pub Date : 2020-06-01 DOI: 10.1109/ISCV49265.2020.9204187

Fouad Nafis, Khalid Al Fararni, Ali Yahyaouy, Badraddine Aghoutane

{"title":"Towards a semantic recommender system for cultural objects: Case study Draa-Tafilalet region","authors":"Fouad Nafis, Khalid Al Fararni, Ali Yahyaouy, Badraddine Aghoutane","doi":"10.1109/ISCV49265.2020.9204187","DOIUrl":"https://doi.org/10.1109/ISCV49265.2020.9204187","url":null,"abstract":"In the Big data era, a large number of functionalities and applications are created. The immediate consequence is the loss of time for the user due to the difficulty of accessing relevant information, and therefore a questioning of the usefulness of the services offered. Recommender system (RS) aims to help potential users by recommending the most suitable offers according to their profiles and preferences, RSs based on collaborative filtering, or those based on content or even hybrid filtering have shown interesting results to be explored for the resolution of the problems encountered. But some limits remain unresolved which are mainly related to the ability of these techniques to build a robust and complete system capable of forming a complete idea of the user profile and then recommend them the most suitable offers. Hence, the advantage of using semantic RSs based on data web and semantic web technologies, specifically the ontologies. This paper offers a comparative study of existing semantic RSs in the field of cultural heritage in order to extract a complete vision of a RS for the scientific cultural heritage of the region of Drâa-Tafilalet in Morocco.","PeriodicalId":313743,"journal":{"name":"2020 International Conference on Intelligent Systems and Computer Vision (ISCV)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129610572","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

Dos attack forecasting: A comparative study on wrapper feature selection Dos攻击预测:包装器特征选择的比较研究

2020 International Conference on Intelligent Systems and Computer Vision (ISCV) Pub Date : 2020-06-01 DOI: 10.1109/ISCV49265.2020.9204323

Kawtar Bouzoubaa, Youssef Taher, B. Nsiri

{"title":"Dos attack forecasting: A comparative study on wrapper feature selection","authors":"Kawtar Bouzoubaa, Youssef Taher, B. Nsiri","doi":"10.1109/ISCV49265.2020.9204323","DOIUrl":"https://doi.org/10.1109/ISCV49265.2020.9204323","url":null,"abstract":"Today, individuals, business and public administrations are internet dependent. This strong dependence creates one of the important sources of threats. Among these threats, the famous Dos attack. The costs of downtime, outages and failures caused by these attacks are very important. Protecting and preventing these threats by using the conventional tools present important limits (cannot predict in real-time when, where, and how the new forms of these Dos attacks occur). To deal with these limits, cybersecurity systems based on machine learning models can analyze patterns and learn from them to forecast and prevent Dos attack. One of the key process which ensures the efficiency of these forecasting systems is feature selection. In this context, we paid particular attention to one of the efficient feature selection methods used in forecasting cybersecurity systems: Wrapper based-feature. To find the best subset of dos attack features and to optimize the accuracy of these systems, we present a comparative study between different wrapper methods applying to the dos attack forecasting. This investigation shows that a wrapper approach based on a genetic algorithm improves the forecasting accuracy more than other wrapper processes.","PeriodicalId":313743,"journal":{"name":"2020 International Conference on Intelligent Systems and Computer Vision (ISCV)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128556425","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: 5

Enhancing Machine Translation by Integrating Linguistic Knowledge in the Word Alignment Module 在词对齐模块中集成语言知识增强机器翻译

2020 International Conference on Intelligent Systems and Computer Vision (ISCV) Pub Date : 2020-06-01 DOI: 10.1109/ISCV49265.2020.9204328

Safae Berrichi, A. Mazroui

引用次数: 2