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2020 IEEE International Conference on Artificial Intelligence and Information Systems (ICAIIS)最新文献

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Machine Fault Diagnosis Based on Wavelet Packet Coefficients and 1D Convolutional Neural Networks 基于小波包系数和一维卷积神经网络的机械故障诊断
2020 IEEE International Conference on Artificial Intelligence and Information Systems (ICAIIS) Pub Date : 2020-03-01 DOI: 10.1109/ICAIIS49377.2020.9194866
Yan Zhang, Qiaoqi Feng, Qingqing Huang
{"title":"Machine Fault Diagnosis Based on Wavelet Packet Coefficients and 1D Convolutional Neural Networks","authors":"Yan Zhang, Qiaoqi Feng, Qingqing Huang","doi":"10.1109/ICAIIS49377.2020.9194866","DOIUrl":"https://doi.org/10.1109/ICAIIS49377.2020.9194866","url":null,"abstract":"Deep neural networks are becoming popular to automatically extract discriminative features from vibration signals for the purpose of recognizing machine running state. The fact that little attention has been paid to the nature of signals as to whether the combination of preprocessing can help to achieve better diagnosis performance motivated this investigation. A fault diagnosis method based on wavelet packet coefficients and 1D convolutional neural networks (1D-CNN) is proposed in this paper. Firstly, the signal features involved in both low- and high-frequency components are extracted based on wavelet packet decomposition, and combined without changing their output sequence directly for the sake of retaining all the characteristics. Secondly, the combined features are taken as input of a 1D-CNN, which consists of several convolutional layers, to further learn the abstract features and improve classification performance. Finally, testing data were fed into the trained model to recognize the machine running state. The efficacy of the developed model and its anti-noise performance under different simulated noise levels were evaluated by analyzing the bearing vibration signals.","PeriodicalId":416002,"journal":{"name":"2020 IEEE International Conference on Artificial Intelligence and Information Systems (ICAIIS)","volume":"107 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126616073","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 verification of a micro pipe robot 微型管道机器人的设计与验证
2020 IEEE International Conference on Artificial Intelligence and Information Systems (ICAIIS) Pub Date : 2020-03-01 DOI: 10.1109/ICAIIS49377.2020.9194827
Kai-Lung Bai, Chaodong Li, Lexian Li, Cong Xi
{"title":"Design and verification of a micro pipe robot","authors":"Kai-Lung Bai, Chaodong Li, Lexian Li, Cong Xi","doi":"10.1109/ICAIIS49377.2020.9194827","DOIUrl":"https://doi.org/10.1109/ICAIIS49377.2020.9194827","url":null,"abstract":"This paper proposes a micro pipe robot with an outer diameter of 46mm and a weight of 28.6g. The micro pipe robot is mainly composed of a body, an electromagnetic solenoid, a spring, and a guide support foot. The principle of inertial impact driving and the feasibility of a direct-acting electromagnet drive are all proved by the gait analysis of the micro pipe robot, multi-body dynamics simulation of the virtual prototype and the experiment verification of the inertial impact principle. Experiments with a single electromagnet is driven without a load show that the micro pipe robot can achieve a maximum speed of 60.290mm/s in a horizontal pipe with a 10Hz sawtooth wave and an inner diameter of 51mm.","PeriodicalId":416002,"journal":{"name":"2020 IEEE International Conference on Artificial Intelligence and Information Systems (ICAIIS)","volume":"245 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125707647","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
Path Following Control for Unmanned Aerial Vehicle Based on Carrot Chasing Algorithm and PLOS 基于胡萝卜追踪算法和PLOS的无人机路径跟踪控制
2020 IEEE International Conference on Artificial Intelligence and Information Systems (ICAIIS) Pub Date : 2020-03-01 DOI: 10.1109/ICAIIS49377.2020.9194843
Xue Jin, Wu Mei, Yang Zhaolong
{"title":"Path Following Control for Unmanned Aerial Vehicle Based on Carrot Chasing Algorithm and PLOS","authors":"Xue Jin, Wu Mei, Yang Zhaolong","doi":"10.1109/ICAIIS49377.2020.9194843","DOIUrl":"https://doi.org/10.1109/ICAIIS49377.2020.9194843","url":null,"abstract":"One of the reasons that UAVs play an important role in many fields is that they can follow paths accurately. The information on the comparison of the path following algorithms is far from enough. In order to make an intensive study of path following problem, we use a kinematic model to compare and analyze Carrot chasing algorithm and PLOS algorithm. The comparison of the path following algorithms is carried out through simulations. The results show that the UAV can track the target paths accurately with each of the algorithms. We can figure out that it is important to select the proper gains in the guidance laws for great path following performances.","PeriodicalId":416002,"journal":{"name":"2020 IEEE International Conference on Artificial Intelligence and Information Systems (ICAIIS)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125230249","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
Tobacco pests monitoring system based on time sequence pattern mining* 基于时间序列模式挖掘的烟草害虫监测系统
2020 IEEE International Conference on Artificial Intelligence and Information Systems (ICAIIS) Pub Date : 2020-03-01 DOI: 10.1109/ICAIIS49377.2020.9194910
Dong Zhigang, Li Lin, W. Xuejun, Wang Guangchao, Gao Yang, Wang Guofeng
{"title":"Tobacco pests monitoring system based on time sequence pattern mining*","authors":"Dong Zhigang, Li Lin, W. Xuejun, Wang Guangchao, Gao Yang, Wang Guofeng","doi":"10.1109/ICAIIS49377.2020.9194910","DOIUrl":"https://doi.org/10.1109/ICAIIS49377.2020.9194910","url":null,"abstract":"In order to achieve rapid reporting and quantitative prediction of tobacco pests, one tobacco pests forecasting model was established to realize the prevention and control the tobacco pests' trends by time series data mining technology. The experimental result shows that the effective prediction of data is conducive to the effective tobacco pests monitoring.","PeriodicalId":416002,"journal":{"name":"2020 IEEE International Conference on Artificial Intelligence and Information Systems (ICAIIS)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131621985","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
Design and Experiment of the Explosion-proof Electric Mobile Elevating Work Platforms 防爆电动移动式升降工作平台的设计与实验
2020 IEEE International Conference on Artificial Intelligence and Information Systems (ICAIIS) Pub Date : 2020-03-01 DOI: 10.1109/ICAIIS49377.2020.9194895
J. Mao, Xuhong Gao, Liqiang Liu, Dinghua Liu, Shaowei Lu, Jin Li
{"title":"Design and Experiment of the Explosion-proof Electric Mobile Elevating Work Platforms","authors":"J. Mao, Xuhong Gao, Liqiang Liu, Dinghua Liu, Shaowei Lu, Jin Li","doi":"10.1109/ICAIIS49377.2020.9194895","DOIUrl":"https://doi.org/10.1109/ICAIIS49377.2020.9194895","url":null,"abstract":"In order to eliminate security risks in the process of aerial operation in the explosion-proof environment, the new Explosion-proof Electric Mobile Elevating Work Platforms (EEMEWP) were designed. Firstly, the power matching of the hydraulic driving system of the EEMEWP was calculated. Secondly, the dynamic operation performance of the articulating booms of the EEMEWP was analyzed by software ADAMS. Lastly, the field tests including stability test, driving test, operating test and explosion-proof test were carried out. The field tests results show that the EEMEWP have excellent stability and can climb over 20% of the slope in the condition of 300 kg load. The maximum loading capacity errors of the different oil cylinders between the test results and simulation calculation data are less than 8%. The EEMEWP were tested in accordance with Chinese national standards, and the result is satisfied. Now, the EEMEWP have been issued by the dIIBT4 explosion-proof certification.","PeriodicalId":416002,"journal":{"name":"2020 IEEE International Conference on Artificial Intelligence and Information Systems (ICAIIS)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133116933","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
Virtual Machine Scheduling in Cloud Environment Based on Annealing Algorithm and Improved Particle Swarm Algorithm 基于退火算法和改进粒子群算法的云环境下虚拟机调度
2020 IEEE International Conference on Artificial Intelligence and Information Systems (ICAIIS) Pub Date : 2020-03-01 DOI: 10.1109/ICAIIS49377.2020.9194890
Mi Zeyu, Hu Jianwei, Cui Yanpeng
{"title":"Virtual Machine Scheduling in Cloud Environment Based on Annealing Algorithm and Improved Particle Swarm Algorithm","authors":"Mi Zeyu, Hu Jianwei, Cui Yanpeng","doi":"10.1109/ICAIIS49377.2020.9194890","DOIUrl":"https://doi.org/10.1109/ICAIIS49377.2020.9194890","url":null,"abstract":"In order to reduce the power consumption in the cloud environment and the placement of virtual machines in the cloud environment, this paper proposes an annealing algorithm to optimize the placement of the particle swarm by analyzing the particle swarm algorithm. This algorithm optimizes the particle swarm algorithm in all directions, and dynamically optimizes the inertia coefficient of the particle swarm algorithm based on the Gaussian function. With the help of simulated annealing algorithm, the local optimal position is disturbed to improve the ability of jumping out of the local optimal. Optimize the total energy consumption of the data center as the objective function. Based on the relationship between the local optimal solution, the global optimal solution, and the inertia coefficient, the particle swarm algorithm is improved. The simulation experiments of CloudSim, a cloud computing simulation platform, show that the improved algorithm has better convergence speed, higher optimization accuracy, and reduced power consumption.","PeriodicalId":416002,"journal":{"name":"2020 IEEE International Conference on Artificial Intelligence and Information Systems (ICAIIS)","volume":"22 3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133320840","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
Logistics distribution vehicle path planning research 物流配送车辆路径规划研究
2020 IEEE International Conference on Artificial Intelligence and Information Systems (ICAIIS) Pub Date : 2020-03-01 DOI: 10.1109/ICAIIS49377.2020.9194800
Changhao Piao, Hao Hu, Yan Zhang
{"title":"Logistics distribution vehicle path planning research","authors":"Changhao Piao, Hao Hu, Yan Zhang","doi":"10.1109/ICAIIS49377.2020.9194800","DOIUrl":"https://doi.org/10.1109/ICAIIS49377.2020.9194800","url":null,"abstract":"Aiming at the problem of vehicle routing in logistics distribution, an improved ant colony optimization algorithm was proposed. In the distribution process, shortening the delivery mileage minimizes the path Introduction. By establishing a corresponding matlab distribution model, an improved ant colony algorithm is used to solve the optimal path. The improved ant colony algorithm sets the volatility factor according to the search stage, and considers the starting point, the end point and the distance between each node in the heuristic factor. The experimental results show that compared with the traditional manual scheme, the logistics distribution path planning model and the improved ant colony algorithm are adopted to effectively reduce the logistics distribution operation path.","PeriodicalId":416002,"journal":{"name":"2020 IEEE International Conference on Artificial Intelligence and Information Systems (ICAIIS)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131001676","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
Privacy-Preserving Task Allocation Based on QoS in Crowd Sensing 基于QoS的群体感知隐私保护任务分配
2020 IEEE International Conference on Artificial Intelligence and Information Systems (ICAIIS) Pub Date : 2020-03-01 DOI: 10.1109/ICAIIS49377.2020.9194848
Bin Gui, Burong Kang, Xinyu Meng, L. Zhang
{"title":"Privacy-Preserving Task Allocation Based on QoS in Crowd Sensing","authors":"Bin Gui, Burong Kang, Xinyu Meng, L. Zhang","doi":"10.1109/ICAIIS49377.2020.9194848","DOIUrl":"https://doi.org/10.1109/ICAIIS49377.2020.9194848","url":null,"abstract":"Crowd sensing, an important research direction in wireless communication, realizes the allocation and collection of tasks through the smart devices carried by users. However, in the task allocation process, how to protect user privacy from being leaked and select high-quality users to guarantee the quality of task completion are two major challenges. Particularly, individual quality of service (QoS) affects the quality of the task completion. In this paper, we propose a differentially private task allocation scheme. During the process of task allocation, differential privacy is utilized for the location privacy protection. In addition, in order to reduce unnecessary privacy leakage, we simplify the task allocation process and select users with higher QoS to guarantee the QoS of task. Security analysis and experimental results state that our scheme provides differential privacy protection while ensuring QoS of tasks.","PeriodicalId":416002,"journal":{"name":"2020 IEEE International Conference on Artificial Intelligence and Information Systems (ICAIIS)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123916781","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
Key Techniques of Pretreatment and Quantitative Identification of Broken Wire Detection Signal in Wire Rope 钢丝绳断丝检测信号预处理与定量识别关键技术
2020 IEEE International Conference on Artificial Intelligence and Information Systems (ICAIIS) Pub Date : 2020-03-01 DOI: 10.1109/ICAIIS49377.2020.9194945
Wang Hongyao, Tian Jie, Lv Xin, Meng Guoying, Hua Gang
{"title":"Key Techniques of Pretreatment and Quantitative Identification of Broken Wire Detection Signal in Wire Rope","authors":"Wang Hongyao, Tian Jie, Lv Xin, Meng Guoying, Hua Gang","doi":"10.1109/ICAIIS49377.2020.9194945","DOIUrl":"https://doi.org/10.1109/ICAIIS49377.2020.9194945","url":null,"abstract":"Detection of the wire rope directly relates to the personal and equipment safety. However, detection of the wire rope is confronted with some problems at present. For example, the detection result is affected by the running speed, the detection distance and the environment, the detection accuracy is not high, the versatility is not strong and so on. Therefore, key techniques of pretreatment and quantitative identification of broken wire detection signal in wire rope need to be studied. The study contents include the method of obtaining damage signal of wire rope broken wire, the pretreatment method of broken wire signal of wire rope, the detection signal feature extraction and quantitative recognition method and the key technology and implementation of detection software development. This study is of great significance to improve the safety of wire rope use.","PeriodicalId":416002,"journal":{"name":"2020 IEEE International Conference on Artificial Intelligence and Information Systems (ICAIIS)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121169535","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
Improved SegMitos framework for mitosis detection in breast cancer histopathology images 改进的SegMitos框架用于乳腺癌组织病理学图像中有丝分裂检测
2020 IEEE International Conference on Artificial Intelligence and Information Systems (ICAIIS) Pub Date : 2020-03-01 DOI: 10.1109/ICAIIS49377.2020.9194877
Meriem Sebai
{"title":"Improved SegMitos framework for mitosis detection in breast cancer histopathology images","authors":"Meriem Sebai","doi":"10.1109/ICAIIS49377.2020.9194877","DOIUrl":"https://doi.org/10.1109/ICAIIS49377.2020.9194877","url":null,"abstract":"Mitotic cell counting is the strongest predictor of tumor aggressiveness in breast cancer prognosis. Since the manual annotation of mitotic cells by pathologists is extremely hard and time-consuming, automatic mitosis detection systems are highly required in pathology laboratories. In this paper, we propose a mitosis detection system inspired by the state-of-the-art SegMitos framework for which we substitute the segmentation network by the more effective DeepLabv3+ semantic segmentation model to achieve better mitosis detection performance. The improved SegMitos model consists of a downsampling path that can capture rich contextual information at multiple scales and an upsampling path that can gradually recover the image objects boundaries. Experimental results on the 2012 ICPR MITOSIS dataset and the AMIDA13 dataset demonstrate the effectiveness of our improved SegMitos system that yields better results than the original SegMitos framework and other state-of-the-art approaches with F-scores of 0.820 and 0.695 respectively.","PeriodicalId":416002,"journal":{"name":"2020 IEEE International Conference on Artificial Intelligence and Information Systems (ICAIIS)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125041542","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
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