2021 31st International Conference on Computer Theory and Applications (ICCTA)最新文献

Supervised and Unsupervised Methods in Depth Estimation 深度估计中的监督与非监督方法

2021 31st International Conference on Computer Theory and Applications (ICCTA) Pub Date : 2021-12-11 DOI: 10.1109/ICCTA54562.2021.9916635

Tarek Barhoum, Balsam Eid

引用次数: 0

Dropout Prediction System to Enhance Massive Open Online Courses 基于辍学预测系统的大规模网络开放课程

2021 31st International Conference on Computer Theory and Applications (ICCTA) Pub Date : 2021-12-11 DOI: 10.1109/ICCTA54562.2021.9916604

A. Nazif, Ahmed Ahmed Hesham Sedky, O. Badawy

引用次数: 0

Solving Kinematics of a Parallel Manipulator Using Artificial Neural Networks 用人工神经网络求解并联机械臂的运动学

2021 31st International Conference on Computer Theory and Applications (ICCTA) Pub Date : 2021-12-11 DOI: 10.1109/ICCTA54562.2021.9916234

Yasmin Khattab, Iham F. Zidane, M. El-Habrouk, S. Rezeka

引用次数: 2

Modeling and Analysis of PMSM under Regenerative Braking Operations with Fault-Tolerant for EV/HEV Applications 电动汽车/混合动力汽车再生制动容错工况下永磁同步电机建模与分析

2021 31st International Conference on Computer Theory and Applications (ICCTA) Pub Date : 2021-12-11 DOI: 10.1109/ICCTA54562.2021.9916631

Mohamed E. Elsayed, M. Hamad, H. Ashour

{"title":"Modeling and Analysis of PMSM under Regenerative Braking Operations with Fault-Tolerant for EV/HEV Applications","authors":"Mohamed E. Elsayed, M. Hamad, H. Ashour","doi":"10.1109/ICCTA54562.2021.9916631","DOIUrl":"https://doi.org/10.1109/ICCTA54562.2021.9916631","url":null,"abstract":"The modeling and simulation of both regenerative braking including a permanent magnet synchronous motor (PMSM) drivetrain for electric vehicle (EV) purposes and fault-tolerant analysis are discussed in this article. The concept for electric brake controls of such a PMSM drive system with field-oriented control (FOC) is first investigated. After that, the optimum regenerative braking torque in the recovery configuration and the braking torque for the greatest recovery power is estimated. The combination of ultra-capacitors (UCs) modules with the batteries provides fast and scalable power transmission during regenerative braking mode. This became critical to regulating the power transfer towards the DC-link since it’s a critical problem that impacts the complete performance of a system. Lastly, for a PMSM linked with an electric motor as the load, the quantities of kinetic energy which can be saved and also the performance with which it will be restored to the UCs and batteries are investigated. In addition, fault-tolerant methods for a three-phase PMSM with separate motor windings and independent voltage source inverters (VSI) are demonstrated in this work.","PeriodicalId":258950,"journal":{"name":"2021 31st International Conference on Computer Theory and Applications (ICCTA)","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126548602","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

Design and Implementation of Mobile-based Application for Appointments Systems for Vaccinations in Medical Centers 医疗中心基于移动应用程序的疫苗预约系统设计与实现

2021 31st International Conference on Computer Theory and Applications (ICCTA) Pub Date : 2021-12-11 DOI: 10.1109/ICCTA54562.2021.9916616

M. Qabajeh, Shima Mousa, H. Saleh, Jamila Abo Hasan

{"title":"Design and Implementation of Mobile-based Application for Appointments Systems for Vaccinations in Medical Centers","authors":"M. Qabajeh, Shima Mousa, H. Saleh, Jamila Abo Hasan","doi":"10.1109/ICCTA54562.2021.9916616","DOIUrl":"https://doi.org/10.1109/ICCTA54562.2021.9916616","url":null,"abstract":"The current patient registration and operating procedure in medical centers are time-consuming and somehow tiresome for patients and their families. Normally, patients have to visit the medical center or hospital to register, they have to bring their medical records, and wait to be called by the medical staff. The situation becomes worse when the patients are kids because they cannot wait for long time and their parents do not have enough time to wait for long time. In view of these problems, several appointment applications are proposed to enhance the registration systems and reduce the waiting time. However, these efforts are still face some drawbacks and limitations. In this paper, we have designed an Android-based mobile application to create appointments with doctors in medical clinics and store the patient’s health records. This mobile application is integrated with an interactive website and a comprehensive database to enable the doctors to handle vaccinations appointment, maintain and retrieve patients’ medical records. The managers also can efficiently create, manage and admin the clinic’s work progress. This mobile application will enhance appointment scheduling and improve the quality of healthcare. In addition, the application can reduce the time and effort consumed to perform the vaccinations appointment process and taking the vaccinations on time.","PeriodicalId":258950,"journal":{"name":"2021 31st International Conference on Computer Theory and Applications (ICCTA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123706664","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

Obstacles Avoidance of Self-driving Vehicle using Deep Reinforcement Learning 基于深度强化学习的自动驾驶车辆避障

2021 31st International Conference on Computer Theory and Applications (ICCTA) Pub Date : 2021-12-11 DOI: 10.1109/ICCTA54562.2021.9916640

Mahmoud Osama Radwan, Ahmed Ahmed Hesham Sedky, K. Mahar

{"title":"Obstacles Avoidance of Self-driving Vehicle using Deep Reinforcement Learning","authors":"Mahmoud Osama Radwan, Ahmed Ahmed Hesham Sedky, K. Mahar","doi":"10.1109/ICCTA54562.2021.9916640","DOIUrl":"https://doi.org/10.1109/ICCTA54562.2021.9916640","url":null,"abstract":"Nowadays, there exist different self-driving vehicle functions that allow the vehicle to perform certain actions by itself while the driver is only monitoring it. However, it is difficult in real world to acquire training data for self-driving artificial intelligence algorithms because there are a lot of risks and the need of labeled data. This paper proposes a method to collect training data from Unity game engine’s Machine Learning Toolkit (ML-Agents Toolkit). With this toolkit, Unity allows its users to incorporate Reinforcement Learning (RL) algorithms to train a learning agent. The aim of this paper is to search for the best RL algorithm in order to train the self-driving vehicle to avoid obstacles in a 3D environment. For all study cases, the learning was done by using the two RL learning algorithms Proximal Policy Optimization algorithm (PPO) and Soft Actor-Critic (SAC) algorithm, both using single-instance and multi-instance training. In the data collection from virtual environment to learn, two types of sensors in comparison had been experimented using camera sensors and Light Detection and Ranging (LiDaR) sensors. The results of the research show the advantages and limitations of the used learning algorithms for learning behaviors, the importance of the demonstration provided for the learning algorithms. Experimental results for applying the virtual driving data to drive a vehicle shows the effectiveness of the proposed methodology.","PeriodicalId":258950,"journal":{"name":"2021 31st International Conference on Computer Theory and Applications (ICCTA)","volume":"13 4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128944165","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

Keynote Speech 3: Collaboration of Cloud, Fog and Mist Computing for Real-Time Applications: Resource Allocation and Scheduling Challenges 主题演讲3:云、雾和雾计算在实时应用中的协作:资源分配和调度挑战

2021 31st International Conference on Computer Theory and Applications (ICCTA) Pub Date : 2021-12-11 DOI: 10.1109/iccta54562.2021.9916617

引用次数: 0

Chaotic Maps Based Video Encryption: A New Approach 基于混沌映射的视频加密新方法

2021 31st International Conference on Computer Theory and Applications (ICCTA) Pub Date : 2021-12-11 DOI: 10.1109/ICCTA54562.2021.9916605

Wessam M. Salama, M. Aly

{"title":"Chaotic Maps Based Video Encryption: A New Approach","authors":"Wessam M. Salama, M. Aly","doi":"10.1109/ICCTA54562.2021.9916605","DOIUrl":"https://doi.org/10.1109/ICCTA54562.2021.9916605","url":null,"abstract":"This study proposes a new encryption method for safe video transmission. The approach introduced in this paper is based on MPEG-2 compression and several chaotic maps. The Arnold map is used to encrypt an explicit chosen frame, which is then XORed with the encrypted video frames produced by the Skew Tent map. This map achieves high performance and low time consuming. Furthermore, bit shifts of pixel values are utilized to produce a more uniform histogram for the encrypted video, improve the encryption scheme’s speed, and boost security. To reduce processing time before the encryption process begins, the row vector method is applied. According to the experimental results, the encrypted video exhibits low correlation coefficients between adjacent pixels, excellent entropy, a decent histogram, a low time consumption, and resistance to differential assaults, additive noise, and cropping attacks. The average correlation coefficients between pixels are obtained as -0.0133, -0.0155 and 0.0037 for horizontal, vertical and diagonal components for foreman frame. Moreover, the entropy for the encrypted foremen frame is 7.3348. Furthermore, the processing time 0.7015 s and 1.81 s, respectively, for encryption and decryption.","PeriodicalId":258950,"journal":{"name":"2021 31st International Conference on Computer Theory and Applications (ICCTA)","volume":"28 4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114294898","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

A Robust Deep Learning based Prediction System of Heart Disease using a Combination of Five Datasets 基于五个数据集的鲁棒深度学习心脏病预测系统

2021 31st International Conference on Computer Theory and Applications (ICCTA) Pub Date : 2021-12-11 DOI: 10.1109/ICCTA54562.2021.9916601

Ritu Biswas, Abhijith Reddy Beeravolu, Asif Karim, S. Azam, M. T. Hasan, Md. Soriful Alam, Pronab Ghosh

{"title":"A Robust Deep Learning based Prediction System of Heart Disease using a Combination of Five Datasets","authors":"Ritu Biswas, Abhijith Reddy Beeravolu, Asif Karim, S. Azam, M. T. Hasan, Md. Soriful Alam, Pronab Ghosh","doi":"10.1109/ICCTA54562.2021.9916601","DOIUrl":"https://doi.org/10.1109/ICCTA54562.2021.9916601","url":null,"abstract":"All across the world, heart disease is regarded as a fatal disease. Heart disease is a condition that affects both men and women equally and may be a major cause of death around the world. Early diagnosis of this condition is critical for everyone in order to reduce mortality rates day by day. Chronic kidney disease dataset, from UCI machine learning library, having 1190 samples with 14 characteristics has been used for this study. To make this research more potent, both Machine learning (ML) and Deep learning (DL) techniques were used to detect the sickness early. The data was normalized by standard scaler for having a class varience issue. We then used three deep learning techniques namely Convolutional Neural Network (CNN), Artificial Neural Network (ANN), and Long Short Term Memory (LSTM) with two other general machine learning approaches such as Decision Tree and Support Vector Machine (SVM). To show a replication study, the overall experiments were done based on the three different random subsets. For the classification measurement, we also employ the ROC and the AUC curves. Several promising outcomes have been achieved. We calculated accuracy, precision, sensitivity, specificity, and F1-score. CNN provided the best results, with an accuracy of 99.16%.","PeriodicalId":258950,"journal":{"name":"2021 31st International Conference on Computer Theory and Applications (ICCTA)","volume":"111 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117305004","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

Keynote Speech 4: Artificial Intelligence Technology in Smart Healthcare Informatics 主题演讲4:智能医疗信息中的人工智能技术

2021 31st International Conference on Computer Theory and Applications (ICCTA) Pub Date : 2021-12-11 DOI: 10.1109/iccta54562.2021.9916609

引用次数: 0