2021 IEEE International Conference on Networking, Sensing and Control (ICNSC)最新文献_第4页

Deep Learning and Image Processing Combined Organization of Shirakawa’s Hand-Notated Documents on OBI Research 深度学习与图像处理结合组织Shirakawa手记OBI研究文献

2021 IEEE International Conference on Networking, Sensing and Control (ICNSC) Pub Date : 2021-12-03 DOI: 10.1109/ICNSC52481.2021.9702164

Xuebin Yue, Bing Lyu, Hengyi Li, Yoshiyuki Fujikawa, Lin Meng

{"title":"Deep Learning and Image Processing Combined Organization of Shirakawa’s Hand-Notated Documents on OBI Research","authors":"Xuebin Yue, Bing Lyu, Hengyi Li, Yoshiyuki Fujikawa, Lin Meng","doi":"10.1109/ICNSC52481.2021.9702164","DOIUrl":"https://doi.org/10.1109/ICNSC52481.2021.9702164","url":null,"abstract":"The purpose of this work is to organize Professor Shirakawa’s newly discovered hand-notated documents on his Oracle Bone Inscription (OBI) research. During the second half of the 20th-century, Professor Shirakawa was a prominent researcher on Chinese culture, especially in the field of OBIs, and he left behind many research documents he had notated by hand. However, some of these documents have not been properly organized yet. The reorganization of OBIs is not only helpful for better understanding his research but also for further studying about OBIs in general and their importance in ancient Chinese history. Part of Professor Shirakawa’s hand-notated research documents on OBIs is introduced to the world for the first time in this work. For organizing these documents, Firstly, a morphology-based segmentation method is applied to segment the characters in the documents and then the paper proposes a slight neural network for removing the noise from the mis- segmented characters. Finally, a dynamic K-means method is applied for classifying the segmented characters. Specifically, the histogram of oriented gradients (HOG) descriptors are extracted as features, and the class number of K is dynamically decided by using the silhouette coefficient. The results of this evaluation showed that the accuracy of noise and character classification after segmentation achieves 96.50%, and the accuracy of character classification achieves 74.91%. The results demonstrate the effectiveness of the proposed method.","PeriodicalId":129062,"journal":{"name":"2021 IEEE International Conference on Networking, Sensing and Control (ICNSC)","volume":"120 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124718518","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

Multi-agent Pathfinding with Local and Global Guidance 具有局部和全局指导的多智能体寻路

2021 IEEE International Conference on Networking, Sensing and Control (ICNSC) Pub Date : 2021-12-03 DOI: 10.1109/ICNSC52481.2021.9702234

Yunhong Xu, Yanjie Li, Qi Liu, Jianqi Gao, Yuecheng Liu, Meiling Chen

{"title":"Multi-agent Pathfinding with Local and Global Guidance","authors":"Yunhong Xu, Yanjie Li, Qi Liu, Jianqi Gao, Yuecheng Liu, Meiling Chen","doi":"10.1109/ICNSC52481.2021.9702234","DOIUrl":"https://doi.org/10.1109/ICNSC52481.2021.9702234","url":null,"abstract":"Multi-agent path finding (MAPF) exists in many practical applications, such as intelligent warehouses. In this type of scenario, the agents need to cooperate with each other and eventually reach the target point without collision. The existing multi-agent path planning algorithms are mainly centralized algorithms, such as Conflict-Based Search (CBS). However, this kind of approach is difficult to solve the problem in real time and its scalability is poor. In this work, we focus on solving MAPF problem in intelligent warehouse. To address this problem, instead of using time-consuming search based algorithms, we propose a novel decentralized multi-agent pathfinding method based on deep reinforcement learning. Combined with curriculum learning, the algorithm uses local and global guidance mechanisms to help agents plan feasible paths. As a result, the success rate of the algorithm has been significantly improved. Experimental results show that our algorithm generalizes well and it still performs well when the scale of problem increases. The solution efficiency is close to the centralized algorithms.","PeriodicalId":129062,"journal":{"name":"2021 IEEE International Conference on Networking, Sensing and Control (ICNSC)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124960053","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

ADDAI: Anomaly Detection using Distributed AI ADDAI:使用分布式AI进行异常检测

2021 IEEE International Conference on Networking, Sensing and Control (ICNSC) Pub Date : 2021-12-03 DOI: 10.1109/ICNSC52481.2021.9702157

Maede Zolanvari, Ali Ghubaish, R. Jain

引用次数: 5

A novel hierarchical charging algorithm for the AGV dispatching problem in a multi-robot system 针对多机器人系统中AGV调度问题，提出了一种新的分层计费算法

2021 IEEE International Conference on Networking, Sensing and Control (ICNSC) Pub Date : 2021-12-03 DOI: 10.1109/ICNSC52481.2021.9702206

Haoyi Niu, Weimin Wu, Tao Zhang

引用次数: 0

Operator-based Nonlinear Modeling and Control of Microreactor Considering Symmetry 考虑对称性的微反应器算子非线性建模与控制

2021 IEEE International Conference on Networking, Sensing and Control (ICNSC) Pub Date : 2021-12-03 DOI: 10.1109/ICNSC52481.2021.9702199

Kosuke Nishizawa, M. Deng

引用次数: 0

Design Optimization of Support Structures Based on Numerical Simulation of the Temperature Fields in Selective Laser Melting 基于选择性激光熔化温度场数值模拟的支撑结构优化设计

2021 IEEE International Conference on Networking, Sensing and Control (ICNSC) Pub Date : 2021-12-03 DOI: 10.1109/ICNSC52481.2021.9702179

Renkai Huang, C. Pan, Sukun Tian

引用次数: 1

Data-driven Industrial Robot Arm Calibration: A Machine Learning Perspective 数据驱动的工业机械臂校准:机器学习视角

2021 IEEE International Conference on Networking, Sensing and Control (ICNSC) Pub Date : 2021-12-03 DOI: 10.1109/ICNSC52481.2021.9702246

Zhibin Li, Shuai Li, Xin Luo

{"title":"Data-driven Industrial Robot Arm Calibration: A Machine Learning Perspective","authors":"Zhibin Li, Shuai Li, Xin Luo","doi":"10.1109/ICNSC52481.2021.9702246","DOIUrl":"https://doi.org/10.1109/ICNSC52481.2021.9702246","url":null,"abstract":"Robot arms have been widely used in industry. The absolute positioning error of robots without calibration can reach several millimeters, which cannot meet the application requirements of accurate operation. Therefore, it is almost a mandatory procedure for industrial robots to take on-site calibration before being used. Generally, most researchers on robot calibration have mechanical and instrumentation background as the collection of calibration data is tedious and it is usually difficult to access to industrial robots for researchers in other fields. This research explores the calibration problem from a machine learning perspective and provides the first open-access dataset called \"RobotCali\" in this area so that machine learning scientists can step into this field and verify their algorithms on this problem. In the meanwhile, a new calibration method based on the Levenberg-Marquardt (LM) algorithm and extended Kalman filter (EKF) algorithm is proposed, which can significantly improve the absolute positioning accuracy of the robot after calibration. Firstly, the error model of robot is established, and kinematic parameters are initially identified by LM algorithm. Then the EKF algorithm is used to further calibrate these parameters, which has been verified the effectiveness of the proposed method by experimental results. Lastly, the future research work is discussed.","PeriodicalId":129062,"journal":{"name":"2021 IEEE International Conference on Networking, Sensing and Control (ICNSC)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126934468","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

Experimental Study on Nonlinear Vibration Control for a Flat Plate with Multiple Piezoelectric Elements 多压电元件平板非线性振动控制实验研究

2021 IEEE International Conference on Networking, Sensing and Control (ICNSC) Pub Date : 2021-12-03 DOI: 10.1109/ICNSC52481.2021.9702263

Kazuya Tonomura, Guang Jin, M. Deng

引用次数: 0

Blind Recognition of Channel Coding Based on CNN-BLSTM 基于CNN-BLSTM的信道编码盲识别

2021 IEEE International Conference on Networking, Sensing and Control (ICNSC) Pub Date : 2021-12-03 DOI: 10.1109/ICNSC52481.2021.9702153

Shuying Zhang, Lina Zhou, Yiduo Tang, Lin Wang, Qiwang Chen

{"title":"Blind Recognition of Channel Coding Based on CNN-BLSTM","authors":"Shuying Zhang, Lina Zhou, Yiduo Tang, Lin Wang, Qiwang Chen","doi":"10.1109/ICNSC52481.2021.9702153","DOIUrl":"https://doi.org/10.1109/ICNSC52481.2021.9702153","url":null,"abstract":"In cognitive radio or military communication systems, the channel coding type recognition of the primary user signal is an important task to realize full awareness of the wireless communication environment. Previous methods to solve this problem usually have high computational complexity, which are not suitable for real-time applications and require rich experience and professional knowledge in manual feature extraction. In this paper, a blind channel coding recognition algorithm based on CNN-BLSTM is proposed. Firstly, this method uses convolutional neural network to extract the data features of coding sequence and also avoids the problem of low recognition accuracy caused by inputting the original codeword data with inconspicuous features directly into neural network. Then, the context dependence of features is obtained through bidirectional long short-term memory network. Finally, the classification task is accomplished by softmax function. The experiments use spatially coupled LDPC codes and 5G NR LDPC codes as candidate codes. The experimental results show that the algorithm achieves quite high recognition accuracy under good channel conditions.","PeriodicalId":129062,"journal":{"name":"2021 IEEE International Conference on Networking, Sensing and Control (ICNSC)","volume":"118 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116359546","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

Two-stage no-wait hybrid flow shop scheduling with inter-stage flexibility: A mathematical model 具有阶段间柔性的两阶段无等待混合流水车间调度:一个数学模型

2021 IEEE International Conference on Networking, Sensing and Control (ICNSC) Pub Date : 2021-12-03 DOI: 10.1109/ICNSC52481.2021.9702162

Mohamed Naceur Azaiez, A. Gharbi, I. Kacem, Yosra Makhlouf, Malek Masmoudi

引用次数: 0