2017 Chinese Automation Congress (CAC)最新文献

Behavioral profiling for employees using social media: A case study based on wechat 员工使用社交媒体的行为分析——以微信为例

2017 Chinese Automation Congress (CAC) Pub Date : 2017-10-20 DOI: 10.1109/CAC.2017.8244176

Xiaochun Ni, Shuai Zeng, Rui Qin, Juanjuan Li, Yong Yuan, Feiyue Wang

{"title":"Behavioral profiling for employees using social media: A case study based on wechat","authors":"Xiaochun Ni, Shuai Zeng, Rui Qin, Juanjuan Li, Yong Yuan, Feiyue Wang","doi":"10.1109/CAC.2017.8244176","DOIUrl":"https://doi.org/10.1109/CAC.2017.8244176","url":null,"abstract":"With the continuing development and innovation of modern information and communication technologies in recent years, social media platforms, such as WeChat and Microblog, have been witnessed to play a key role in employee management for enterprises or organizations, enabling individual or groups of employees to express their viewpoints or report their works in a real-time fashion. The resulting Cyber-workspace in social media, which exists in parallel with employees' physical workspace, has the potential of greatly changing the forms and functions of the organizations, as well as the knowledge structures and behavioral patterns of employees, thus bringing unprecedented challenges to the existing research efforts on the management of organizational behavior. In this paper, we propose an approach of behavioral profiling for analyzing and better understanding employees, with the input of large amounts of real-time collected data generated by employees' daily reported works on social media. Our aim is to characterize the diversified behavior patterns of employees in an automatic and accurate fashion for organization management. We also validate our proposed method using a real-world dataset collected from WeChat, and the experimental results prove our analysis, as well as the effectiveness of our approach.","PeriodicalId":116872,"journal":{"name":"2017 Chinese Automation Congress (CAC)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125595447","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: 5

Exploring new mechanisms for demand-side platforms in real time bidding markets 探索实时竞价市场中需求方平台的新机制

2017 Chinese Automation Congress (CAC) Pub Date : 2017-10-20 DOI: 10.1109/CAC.2017.8244164

Rui Qin, Yong Yuan, Xiaochun Ni, Feiyue Wang

引用次数: 1

Knowledge and mathematical programming-based optimal scheduling for byproduct gas system in steel industry 基于知识和数学规划的钢铁工业副产气体系统优化调度

2017 Chinese Automation Congress (CAC) Pub Date : 2017-10-01 DOI: 10.1109/CAC.2017.8244133

Chunyang Sheng, Jun Zhao

引用次数: 0

Fault isolation based on Bayesian fused lasso 基于贝叶斯融合套索的故障隔离

2017 Chinese Automation Congress (CAC) Pub Date : 2017-10-01 DOI: 10.1109/CAC.2017.8243248

Shenbo Zhang, Zhengbing Yan, Ping Wu, Zhengjiang Zhang

引用次数: 2

State feedback control of T-shaped pedestrian channel t形行人通道的状态反馈控制

2017 Chinese Automation Congress (CAC) Pub Date : 2017-10-01 DOI: 10.1109/CAC.2017.8244010

Lu Chang, Liang Shan, Siyuan Xu, Chenglin Liu

引用次数: 2

Neural network control for wireless networks with nonlinear channel fading 非线性信道衰落无线网络的神经网络控制

2017 Chinese Automation Congress (CAC) Pub Date : 2017-10-01 DOI: 10.1109/CAC.2017.8243123

Cunwu Han, Mengqi Li, Lei Liu, S. Bi, Zhilei Jia

引用次数: 0

Design and implementation of a novel drive for the ultrasonic motor 一种新型超声电机驱动器的设计与实现

2017 Chinese Automation Congress (CAC) Pub Date : 2017-10-01 DOI: 10.1109/CAC.2017.8243935

Hong Zhang, H Zhao, Guojiang Zhang, Yanlin Li

引用次数: 0

Virtrul reality and artificial intelligence support future training development 虚拟现实和人工智能支持未来的培训发展

2017 Chinese Automation Congress (CAC) Pub Date : 2017-10-01 DOI: 10.1109/CAC.2017.8242803

Miao Li, Lijuan Li, Risheng Jiao, Hongguang Xiao

{"title":"Virtrul reality and artificial intelligence support future training development","authors":"Miao Li, Lijuan Li, Risheng Jiao, Hongguang Xiao","doi":"10.1109/CAC.2017.8242803","DOIUrl":"https://doi.org/10.1109/CAC.2017.8242803","url":null,"abstract":"With the developing of modern training, advanced requirements of training process such as creative, economical, realistic, safety have been proposed. It is hard for tradition training method to satisfy the training requirement of new technology and equipment in the background of modern industry. Traditional training methods were facing severe challenges. In order to solve the complex technical training problem in the modern industry background, we put forward the opinion that virtual reality and artificial intelligence support the future intelligent training. In this paper, we first presented virtual reality technology as the foundation of future training facilities. Then, we put forward artificial intelligence were the method of generation of intelligent training cases. Following that, we stated rewards the mode that it is resort to advanced big data and information technology to complete base data collection of the case and it is intelligent to generate case model with artificial intelligence and machine learning. To illustrate those points, we provided a case of virtual reality applying in training system simulation field for power system two overhaul, including problem proposition, solution concept, solution result and application prospect. In the end, we summed up the whole paper. The strategies and opinions put forward in this paper can not only help us to understand virtual reality and artificial intelligence's effects in the process of building intelligent training in the future but also render new ideas and inspirations for experts working in virtual reality researching, machine learning and artificial intelligent decision-making, power system simulation and some related areas. Furthermore, it provided the conceptual support for constructing intelligent training, intelligent manufacture, as well as intelligent China.","PeriodicalId":116872,"journal":{"name":"2017 Chinese Automation Congress (CAC)","volume":"140 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124423619","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

Design and development of intelligent operation and maintenance training system for substation based on augmented reality 基于增强现实的变电站智能运维培训系统的设计与开发

2017 Chinese Automation Congress (CAC) Pub Date : 2017-10-01 DOI: 10.1109/CAC.2017.8243621

Yong Peng, G. Yu, Wei-Chun Ni, Zhengquan Lv, Yuliang Jiang, Jing Chen

引用次数: 6

A pairwise learning to rank algorithm based on bounded loss and preference weight 基于有界损失和偏好权重的两两学习排序算法

2017 Chinese Automation Congress (CAC) Pub Date : 2017-10-01 DOI: 10.1109/CAC.2017.8244044

Xianlun Tang, Deyi Xiong, Jiaxin Li, Yali Wan

引用次数: 1