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Type Synthesis and Dynamics Performance Evaluation of a Class of 5-DOF Redundantly Actuated Parallel Mechanisms 期刊论文
International Journal of Automation and Computing, 2021, 卷号: 18, 期号: 1, 页码: 96-109
作者:  Bing-Shan Jiang;  Hai-Rong Fang;  Hai-Qiang Zhang
浏览  |  Adobe PDF(1922Kb)  |  收藏  |  浏览/下载:207/88  |  提交时间:2021/02/23
Type synthesis  redundantly actuated parallel mechanism (PM)  lie group theory  configuration evolution  dynamics performance evaluation  
Identification and classification of driving behaviour at a signalized intersection using support vector machine 期刊论文
International Journal of Automation and Computing, 2021, 卷号: 18, 期号: 3, 页码: 480-491
作者:  Soni Lanka Karri;  Liyanage Chandratilak De Silva;  Daphne Teck Ching Lai;  Shiaw Yin Yong
Adobe PDF(1497Kb)  |  收藏  |  浏览/下载:508/309  |  提交时间:2021/05/24
Signalized intersection  driving behaviour  machine learning  support vector machine (SVM)  road accidents  
Delayed Teleoperation with Force Feedback of a Humanoid Robot 期刊论文
International Journal of Automation and Computing, 2021, 卷号: 18, 期号: 4, 页码: 605-618
作者:  Viviana Moya;  Emanuel Slawiñski;  Vicente Mut
Adobe PDF(2260Kb)  |  收藏  |  浏览/下载:120/40  |  提交时间:2021/07/20
Humanoid robot  bilateral teleoperation  time delay  force feedback  walking  manipulation  
Supervised and Semi-supervised Methods for Abdominalm Organ Segmentation: A Review 期刊论文
International Journal of Automation and Computing, 2021, 卷号: 18, 期号: 6, 页码: 887-914
作者:  Isaac Baffour Senkyire
Adobe PDF(1308Kb)  |  收藏  |  浏览/下载:200/45  |  提交时间:2021/11/26
Abdominal organ, supervised segmentation  semi-supervised segmentation  evaluation metrics  image segmentation  machine learning  
Dynamic System Identification of Underwater Vehicles Using Multi-output Gaussian Processes 期刊论文
International Journal of Automation and Computing, 2021, 卷号: 18, 期号: 5, 页码: 681-693
作者:  Wilmer Ariza Ramirez
Adobe PDF(3231Kb)  |  收藏  |  浏览/下载:130/39  |  提交时间:2021/09/13
Dependent Gaussian processes  dynamic system identification  multi-output Gaussian processes  non-parametric identification  autonomous underwater vehicle (AUV)  
Data Augmentation and Deep Neuro-fuzzy Network for Student Performance Prediction with MapReduce Framework 期刊论文
International Journal of Automation and Computing, 2021, 卷号: 18, 期号: 6, 页码: 981-992
作者:  Amlan Jyoti Baruah
Adobe PDF(1583Kb)  |  收藏  |  浏览/下载:180/48  |  提交时间:2021/11/26
Educational data mining (EDA)  MapReduce framework  deep neuro-fuzzy network  student performance  data augmentation  
Dynamic Event-triggered Control and Estimation: A Survey 期刊论文
International Journal of Automation and Computing, 2021, 卷号: 18, 期号: 6, 页码: 857-886
作者:  Xiaohua Ge;  Qing-Long Han;  Xian-Ming Zhang;  Derui Ding
Adobe PDF(3887Kb)  |  收藏  |  浏览/下载:180/33  |  提交时间:2021/11/26
Networked systems  dynamic event-triggered control  dynamic event-triggered estimation  dynamic event-triggered mechanisms  vehicle active suspension system  water distribution and supply system  
Contrastive Self-supervised Representation Learning Using Synthetic Data 期刊论文
International Journal of Automation and Computing, 2021, 卷号: 18, 期号: 4, 页码: 556-567
作者:  Dong-Yu She;  Kun Xu
Adobe PDF(993Kb)  |  收藏  |  浏览/下载:174/41  |  提交时间:2021/07/20
Self-supervised learning  contrastive learning  synthetic image  convolutional neural network  representation learning  
A Survey on Fault Diagnosis and Fault Tolerant Methodologies for Permanent Magnet Synchronous Machines 期刊论文
International Journal of Automation and Computing, 2020, 卷号: 17, 期号: 6, 页码: 763-787
作者:  Erphan A. Bhuiyan;  Md. Maeenul Azad Akhand;  Sajal K. Das;  Md. F. Ali;  Z. Tasneem;  Md. R. Islam;  D. K. Saha;  Faisal R. Badal;  Md. H. Ahamed;  S. I. Moyeen
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Permanent magnet synchronous machine (PMSM)  fault diagnosis  fault tolerant control system (FTCS)  fault detection  stability.  
Adversarial Attacks and Defenses in Images, Graphs and Text: A Review 期刊论文
International Journal of Automation and Computing, 2020, 卷号: 17, 期号: 2, 页码: 151-178
作者:  Han Xu;  Yao Ma;  Hao-Chen Liu;  Debayan Deb;  Hui Liu;  Ji-Liang Tang;  Anil K. Jain
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Adversarial example  model safety  robustness  defenses  deep learning.