2022 International Conference on Cyber-Physical Social Intelligence (ICCSI)最新文献_第8页

The Smart Industrial Service System as a New Type of Smart PSS for Complex Industrial Context: A Case Study in the Mining Industry 智能工业服务系统作为一种面向复杂工业环境的新型智能PSS——以采矿业为例

2022 International Conference on Cyber-Physical Social Intelligence (ICCSI) Pub Date : 2022-11-18 DOI: 10.1109/ICCSI55536.2022.9970627

Yuan Chang, X. Ming, Zhihua Chen, T. Zhou, Wenyan Song, Pai Zheng

{"title":"The Smart Industrial Service System as a New Type of Smart PSS for Complex Industrial Context: A Case Study in the Mining Industry","authors":"Yuan Chang, X. Ming, Zhihua Chen, T. Zhou, Wenyan Song, Pai Zheng","doi":"10.1109/ICCSI55536.2022.9970627","DOIUrl":"https://doi.org/10.1109/ICCSI55536.2022.9970627","url":null,"abstract":"Servitization has prompted industrial companies to develop smart services for their manufactured products in order to maximize their economic value. The use of smart technologies proposed the product service into a more advanced smart product-service system (smart PSS). However, because current research on smart PSS is primarily focused on developing the service potential from a single core product, this poses a problem for customers who need more holistic solutions in complex contexts. Particularly for the energy and mining sectors, which do not manufacture complex products. The concept of a smart industrial service system (SISS) is proposed in this paper to analyze the various service requirements for the complex energy and mining contexts. Smart technologies bring new access to the interconnection and management of more macro contexts. A brief description of the SISS framework is provided, along with information on its conception, characteristics, elements, and explored design mode. Different from the conventional service blueprint that mainly considers the customer journey. The study emphasizes the importance of considering the activities of social and environmental stakeholders, and also expounds on the necessity of meeting the service requirements of different levels of the industrial context. A novel smart industrial service innovation (SISI) blueprint is also developed to assist the service components design. The proposed SISS model is validated in a real-life coal mining industrial case, and the SISI blueprint design method is also compared with classical methods such as traditional service blueprint. The limitations and possible future research directions are also described at the end of the study.","PeriodicalId":421514,"journal":{"name":"2022 International Conference on Cyber-Physical Social Intelligence (ICCSI)","volume":"195 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127563774","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

Cooperative Strike Target Assignment Algorithm Based on Deep Reinforcement Learning 基于深度强化学习的协同打击目标分配算法

2022 International Conference on Cyber-Physical Social Intelligence (ICCSI) Pub Date : 2022-11-18 DOI: 10.1109/ICCSI55536.2022.9970699

Weiwei Bian, Chunguang Wang, Kuihua Huang, Yanxiang Jia, Chan Liu, Ying Mi

引用次数: 1

Research of Active Vibration Control for Cantilever Beam Based on Macro Fiber Composite Actuators 基于宏纤维复合作动器的悬臂梁振动主动控制研究

2022 International Conference on Cyber-Physical Social Intelligence (ICCSI) Pub Date : 2022-11-18 DOI: 10.1109/ICCSI55536.2022.9970636

Zhenfang Xin, Dongdong Gao, Shouwei Lu, Xiaoyan Fu, Yunfei Zhu, Jiahuan Xu

{"title":"Research of Active Vibration Control for Cantilever Beam Based on Macro Fiber Composite Actuators","authors":"Zhenfang Xin, Dongdong Gao, Shouwei Lu, Xiaoyan Fu, Yunfei Zhu, Jiahuan Xu","doi":"10.1109/ICCSI55536.2022.9970636","DOIUrl":"https://doi.org/10.1109/ICCSI55536.2022.9970636","url":null,"abstract":"In this paper, the active vibration control experiment is carried out based on the fast prototype method, and the thin plate cantilever beam is taken as the experimental control object. Firstly, the mathematical model of the controlled object is established. Based on this, the controlled object is evaluated and the control effect of the control method is tested. According to the results of mathematical model simulation analysis, the experimental platform of active vibration control in the form of hardware-in-the-loop is established and simulated in the form of hardware-in-the-loop. The simulation results show that the vibration is suppressed well with the intervention of active control technology. Finally, through the construction of the control experiment platform for physical experiments, it is concluded that under the active control algorithm, the vibration attenuation of the cantilever beam takes 3s from initial vibration to rest, while it takes 30s without control. It can be seen that the active control algorithm has a good effect on vibration suppression.","PeriodicalId":421514,"journal":{"name":"2022 International Conference on Cyber-Physical Social Intelligence (ICCSI)","volume":"142 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134429510","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

Distributionally Robust Unit Commitment Based On Wind Power Scenario And Electric Vehicles Charging Station 基于风电场景和电动汽车充电站的分布式鲁棒机组承诺

2022 International Conference on Cyber-Physical Social Intelligence (ICCSI) Pub Date : 2022-11-18 DOI: 10.1109/ICCSI55536.2022.9970693

Xuanning Song, Bo Wang, Yifei Wu

引用次数: 0

Reduced-Order Generalized Extended State Observer Based Control for Discrete-Time Systems 基于降阶广义扩展状态观测器的离散系统控制

2022 International Conference on Cyber-Physical Social Intelligence (ICCSI) Pub Date : 2022-11-18 DOI: 10.1109/ICCSI55536.2022.9970623

Pengcheng Zhang, Jianyu Wang, Yun Cheng, Shiyu Jiao

引用次数: 1

Adaptive Inertia Adjustment Method Considering System Frequency Constraints 考虑系统频率约束的自适应惯性调整方法

2022 International Conference on Cyber-Physical Social Intelligence (ICCSI) Pub Date : 2022-11-18 DOI: 10.1109/ICCSI55536.2022.9970604

Xibin Wu, Guan Huang, Weijie Cao, Guohua Cui, Wei-Jing Qiu, Yiwu Ge

{"title":"Adaptive Inertia Adjustment Method Considering System Frequency Constraints","authors":"Xibin Wu, Guan Huang, Weijie Cao, Guohua Cui, Wei-Jing Qiu, Yiwu Ge","doi":"10.1109/ICCSI55536.2022.9970604","DOIUrl":"https://doi.org/10.1109/ICCSI55536.2022.9970604","url":null,"abstract":"As the modern energy system transitions towards a cleaner one, the penetration of converter-interfaced distributed resources is increased, resulting in the lack of inertia and damping. Virtual synchronous generator (VSG) control enables these resources to provide inertial support by simulating the characteristics of the synchronous generation. However, the inertia requirements evaluation of the system becomes critical yet challenging for the operator due to the uneven distribution of inertia. The inertia parameter of VSG control is difficult to be adjusted appropriately. Also, the regulation requirements of the system, including the rate of change of frequency (RoCoF) and nadir limits, tend to be ignored in the inertia adjustment process. In this paper, we propose a minimum system inertia estimation model considering the distribution characteristics of system inertia and establish the relationship between the frequency nadir and the control parameters. Also, we design an inertia adjustment method based on the RBF neural network. Significantly, the index constraints of the system are integrated into the inertia adjustment process. A case study on IEEE 9 bus system illustrates the effectiveness of the proposed method.","PeriodicalId":421514,"journal":{"name":"2022 International Conference on Cyber-Physical Social Intelligence (ICCSI)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131139230","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

Military Target Detection Method Based on Improved YOLOv5 基于改进YOLOv5的军事目标检测方法

2022 International Conference on Cyber-Physical Social Intelligence (ICCSI) Pub Date : 2022-11-18 DOI: 10.1109/ICCSI55536.2022.9970675

Xiuli Du, Li-quan Song, Yana Lv, Xutong Qin

{"title":"Military Target Detection Method Based on Improved YOLOv5","authors":"Xiuli Du, Li-quan Song, Yana Lv, Xutong Qin","doi":"10.1109/ICCSI55536.2022.9970675","DOIUrl":"https://doi.org/10.1109/ICCSI55536.2022.9970675","url":null,"abstract":"Aiming at the requirement of military target detection under the condition of limited resources of weapon hardware platform, this paper proposes a military target detection method that takes into account network lightweight, mean average precision (mAP) and detection speed. This method is based on the You Only Look Once Version 5 (YOLOv5) algorithm. First, the Stem block module is used to replace the Focus module, which can effectively improve the feature expression ability and reduce the amount of parameters and computation of the network model. Second, a MobileNetV2-Convolutional Block Attention Module (MNtV2-CBAM) structure is designed with MobileNetV2 integrated into the CBAM mechanism. The amount of network parameters and computation is reduced, while the detection performance of the model is improved. The experimental results show that compared with the YOLOv5 algorithm, the mAP value of the method in this paper is increased by 1.3%, and the amount of parameters and the amount of calculation are decreased by 67.45% and 73.17% respectively, which can be better applied to the resource-constrained weapon equipment platform. In this way, the reconnaissance and analysis capabilities of military intelligence can be improved, the decision-making time of the commander can be shortened, and the combat capability of the troops can be greatly improved.","PeriodicalId":421514,"journal":{"name":"2022 International Conference on Cyber-Physical Social Intelligence (ICCSI)","volume":"216 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122381291","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

Research on Small Face Detection in UAV Command and Control System 无人机指挥控制系统中的小人脸检测研究

2022 International Conference on Cyber-Physical Social Intelligence (ICCSI) Pub Date : 2022-11-18 DOI: 10.1109/ICCSI55536.2022.9970688

Yilei Wang, Wei Wei, Zhenfang Xin, Dashuang Li

引用次数: 0

Rail Train Number Recognition Based on Improved VGG-16 Network 基于改进VGG-16网络的列车车次识别

2022 International Conference on Cyber-Physical Social Intelligence (ICCSI) Pub Date : 2022-11-18 DOI: 10.1109/ICCSI55536.2022.9970605

Junlin Zhu, Z. Xing, Yu Duan, Zhenyu Zhang

引用次数: 0

Predicting ICU Length of Stay for Patients with Diabetes Using Machine Learning Techniques 使用机器学习技术预测糖尿病患者ICU住院时间

2022 International Conference on Cyber-Physical Social Intelligence (ICCSI) Pub Date : 2022-11-18 DOI: 10.1109/ICCSI55536.2022.9970666

Yuansi Hu, Ling Zheng, Jiacun Wang

{"title":"Predicting ICU Length of Stay for Patients with Diabetes Using Machine Learning Techniques","authors":"Yuansi Hu, Ling Zheng, Jiacun Wang","doi":"10.1109/ICCSI55536.2022.9970666","DOIUrl":"https://doi.org/10.1109/ICCSI55536.2022.9970666","url":null,"abstract":"Diabetes is a prevalent chronic disease that can result in serious damages to various organ systems gradually. Patients with diabetes in the intensive care unit (ICU) have poor health outcomes and require more intensive care with higher healthcare costs. To facilitate resource management of hospitals and to improve health outcomes of patients with diabetes, accurately estimating the length of stay at an early stage of ICU admissions is necessary. This study is aimed to predict the length of stay for patients with diabetes by applying machine learning techniques on clinical data available during the first 8 hours of ICU admissions. Two prediction tasks, the number of days in ICU and whether an ICU stay is long or short distinguished by the threshold 10 days, were explored. The neural network model achieved the best performance in predicting the number of days in ICU with a R2 value 0.3969 and a mean absolute error 1.94 days. The gradient boosting model is the best one to classify long and short ICU stays with an accuracy 0.8214. The results demonstrate that these two models are promising to estimate the length of stay at an early stage of ICU admissions for patients with diabetes.","PeriodicalId":421514,"journal":{"name":"2022 International Conference on Cyber-Physical Social Intelligence (ICCSI)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120992513","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