2021 Fifth International Conference On Intelligent Computing in Data Sciences (ICDS)最新文献

Reinforcement Learning-based Unpredictable Emergency Events 基于强化学习的不可预测紧急事件

2021 Fifth International Conference On Intelligent Computing in Data Sciences (ICDS) Pub Date : 2021-10-20 DOI: 10.1109/ICDS53782.2021.9626720

Omar Elfahim, El Mehdi Ben Laoula, M. Youssfi, O. Barakat, M. Mestari

引用次数: 0

Towards an Improved 3D Reconstruction by the Use of Automatic Bone Segmentation from CT Scan Images 利用CT扫描图像的自动骨分割改进三维重建

2021 Fifth International Conference On Intelligent Computing in Data Sciences (ICDS) Pub Date : 2021-10-20 DOI: 10.1109/ICDS53782.2021.9626754

Imane Zaimi, Nabila Zrira, Ibtissam Benmiloud, Imad Marzak, Kawtar Megdiche, Nabil Ngote

{"title":"Towards an Improved 3D Reconstruction by the Use of Automatic Bone Segmentation from CT Scan Images","authors":"Imane Zaimi, Nabila Zrira, Ibtissam Benmiloud, Imad Marzak, Kawtar Megdiche, Nabil Ngote","doi":"10.1109/ICDS53782.2021.9626754","DOIUrl":"https://doi.org/10.1109/ICDS53782.2021.9626754","url":null,"abstract":"Osteoarthritis is the most disabling joint disease manifested by the destruction of cartilage, bones, and synovial tissue. As a medical and surgical treatment, the knee prosthesis knows a great interest in scientific research. Indeed, knee prosthesis surgery is so delicate, therefore it would be interesting if the operating time and risks of surgery can be reduced and limited. In addition, clinicians use known clinical parameters to diagnose symptoms. Some of these parameters may be difficult to obtain with conventional X-rays. It is then possible to turn to other means of acquisition that allow visualization of bone structures in 3D and extract these parameters. The main objective of this work is to propose a new approach resides on automatic bone segmentation from CT scan images provided by the Cheikh Zaid International University Hospital in Rabat, Morocco. For this purpose, several computer vision techniques are used, namely morphological operations, edge detection, and clustering on slice-by-slice images to obtain a 3D reconstruction on Anatomage Table.","PeriodicalId":351746,"journal":{"name":"2021 Fifth International Conference On Intelligent Computing in Data Sciences (ICDS)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114924598","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

Detection of traffic anomaly in highways by using recurrent neural network 基于递归神经网络的高速公路交通异常检测

2021 Fifth International Conference On Intelligent Computing in Data Sciences (ICDS) Pub Date : 2021-10-20 DOI: 10.1109/ICDS53782.2021.9626741

Sidi Mohamed Snineh, N. E. A. Amrani, M. Youssfi, O. Bouattane, Abdelaziz Daaif

{"title":"Detection of traffic anomaly in highways by using recurrent neural network","authors":"Sidi Mohamed Snineh, N. E. A. Amrani, M. Youssfi, O. Bouattane, Abdelaziz Daaif","doi":"10.1109/ICDS53782.2021.9626741","DOIUrl":"https://doi.org/10.1109/ICDS53782.2021.9626741","url":null,"abstract":"Using deep learning in all fields has experienced spectacular dynamics in recent years. Among these fields are road traffic in cities and highways. The sensors placed on these routes generate a mine of data for analysis and exploration. In this article, we propose a model based on recurrent neural networks and Multi-Agent Systems (MAS) to find anomalies in vehicle flows on highways compared to normal flows. This model is designed around the events and contexts of cities. By event, we mean periodic events such as cultural events, and political events, etc., and by context, we mean tourist towns, mountain towns, etc. The vehicle flows during city events and contexts plus daily vehicle flow results in univariate time series, hence the choice of recurrent neural networks “Long Short-Term Memory” LSTM which is useful for learning periodic data and which has the ability to hold data in long-term and short-term memory. The different datasets, representing the different time series, will be generated by agents who receive the daily flow of vehicles from sensors placed on the highways at the entry and exit of cities. Each agent represents an event and/or a city context to generate a single time series. These datasets, considered initially as normal data, will be used for training and testing our LSTM model. By this model, we want to look for two cases of anomalies: a decrease or an excessive increase in the flow of vehicles on the highways compared to the normal value. To test our model, we used the predictive error called the standard error of prediction.","PeriodicalId":351746,"journal":{"name":"2021 Fifth International Conference On Intelligent Computing in Data Sciences (ICDS)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122024279","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

Hybrid Method Based on Metaheuristics and Interior Point for Optimal Power Flow 基于元启发式和内点的最优潮流混合算法

2021 Fifth International Conference On Intelligent Computing in Data Sciences (ICDS) Pub Date : 2021-10-20 DOI: 10.1109/ICDS53782.2021.9626722

Vincent Roberge, M. Tarbouchi

引用次数: 0

A comprehensive Study on Credit Card Fraud Prevention and Detection 信用卡欺诈预防与检测的综合研究

2021 Fifth International Conference On Intelligent Computing in Data Sciences (ICDS) Pub Date : 2021-10-20 DOI: 10.1109/ICDS53782.2021.9626749

Marouane Ben Boubker, Sara Ouahabi, Kamal Elguemmat, A. Eddaoui

{"title":"A comprehensive Study on Credit Card Fraud Prevention and Detection","authors":"Marouane Ben Boubker, Sara Ouahabi, Kamal Elguemmat, A. Eddaoui","doi":"10.1109/ICDS53782.2021.9626749","DOIUrl":"https://doi.org/10.1109/ICDS53782.2021.9626749","url":null,"abstract":"Nowadays, credit card fraud is becoming more and more challenging for financial institutions. With the era of technology and digitization, frauds are taking variety of forms remaining in perpetual growth and having a huge impact on the business gain. Financial institutions try to use standard tools and to comply with industry and payment schemes requirements. They have also started to invest fully in artificial intelligence and to integrate advanced tools such as machine learning and deep learning techniques within their system. Nevertheless, the effort remains insufficient due the various challenges of this phenomenon. In this paper, we go in details with credit card and card not present frauds, as well as standard tools and classic approaches being used to prevent against them. We also propose a recent state of art on various data mining techniques used to overcome this problem. The result of our study is a very good starting point for researchers working on the same subject since it gives a good understanding of credit card fraud phenomenon as well as presents different approaches and methodologies adopted to prevent such frauds and highlights the main challenges that were faced.","PeriodicalId":351746,"journal":{"name":"2021 Fifth International Conference On Intelligent Computing in Data Sciences (ICDS)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128962423","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

Diabetic Retinopathy Screening and Management in Morocco: Challenges and Possible Solutions. 摩洛哥糖尿病视网膜病变的筛查和管理:挑战和可能的解决方案。

2021 Fifth International Conference On Intelligent Computing in Data Sciences (ICDS) Pub Date : 2021-10-20 DOI: 10.1109/ICDS53782.2021.9626731

Safia Benamar, Yasmine Bennani, Soufiane Bencherif, Zineb Farahat, N. Souissi, Nabil Ngote, Kawtar Megdiche, M. Belmekki

引用次数: 1

Fuzzy logic obstacle avoidance by a NAO robot in unknown environment 未知环境下NAO机器人的模糊逻辑避障

2021 Fifth International Conference On Intelligent Computing in Data Sciences (ICDS) Pub Date : 2021-10-20 DOI: 10.1109/ICDS53782.2021.9626718

Waga Abderrahim, Lamini Chaymaa, Benhlima Said, Bekri Ali

引用次数: 1

Optimal predictive control model of wind turbine 风电机组最优预测控制模型

2021 Fifth International Conference On Intelligent Computing in Data Sciences (ICDS) Pub Date : 2021-10-20 DOI: 10.1109/ICDS53782.2021.9626757

Soukaina Bougdour, Rime Elhouti, S. Sefriti, I. Boumhidi

引用次数: 1

An empirical evaluation of ensemble bagging-based model for authorship attribution on Twitter 基于集合bagging的Twitter作者归属模型的实证评价

2021 Fifth International Conference On Intelligent Computing in Data Sciences (ICDS) Pub Date : 2021-10-20 DOI: 10.1109/ICDS53782.2021.9626735

Anoual El Kah, Imad Zeroual

引用次数: 2

Comparative study between a neural network, approach metaheuristic and exact method for solving Traveling salesman Problem 神经网络、逼近元启发式和精确方法求解旅行商问题的比较研究

2021 Fifth International Conference On Intelligent Computing in Data Sciences (ICDS) Pub Date : 2021-10-20 DOI: 10.1109/ICDS53782.2021.9626724

Safae Rbihou, K. Haddouch

引用次数: 0