2022 3rd International Conference on Computing, Networks and Internet of Things (CNIOT)最新文献

Research on the Current Situation of Cloud Financial Applications in Small and Medium-Sized Enterprises 中小企业云金融应用现状研究

2022 3rd International Conference on Computing, Networks and Internet of Things (CNIOT) Pub Date : 2022-05-01 DOI: 10.1109/cniot55862.2022.00042

Yong Wen

{"title":"Research on the Current Situation of Cloud Financial Applications in Small and Medium-Sized Enterprises","authors":"Yong Wen","doi":"10.1109/cniot55862.2022.00042","DOIUrl":"https://doi.org/10.1109/cniot55862.2022.00042","url":null,"abstract":"The emergence of cloud finance has brought new opportunities for the financial management informatization construction of small and medium-sized enterprises. Compared with the traditional way of financial management informatization construction, cloud finance is more in line with the actual needs of small and medium-sized enterprises with complete internal organs due to the advantages of less investment, quicker results, on-demand self-service, improving the availability of business systems, and helping financial transformation. It can be said that cloud finance is a booster for the development of small and medium-sized enterprises, and will soon become the mainstream model of financial management informatization for small and medium-sized enterprises in the future. In order to help small and medium-sized enterprises to better develop cloud finance, the research group distributed questionnaires to small and medium-sized enterprises in the Guangdong-Hong Kong-Macao Greater Bay Area to investigate their satisfaction with the application of cloud finance, and to explore the practical application of cloud finance in small and medium-sized enterprises. This article uses spss to analyze the data collected to identify areas for improvement.","PeriodicalId":251734,"journal":{"name":"2022 3rd International Conference on Computing, Networks and Internet of Things (CNIOT)","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129704770","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 The Construction of Traffic IoT Simulation Teaching Environment 交通物联网模拟教学环境建设研究

2022 3rd International Conference on Computing, Networks and Internet of Things (CNIOT) Pub Date : 2022-05-01 DOI: 10.1109/cniot55862.2022.00031

Linwei He, Shiqi Li, Ziming Huang, Xiang-lin Pan

引用次数: 0

Subject-Object Aspect-Based Sentiment Analysis Model Based on News Texts 基于主客体方面的新闻文本情感分析模型

2022 3rd International Conference on Computing, Networks and Internet of Things (CNIOT) Pub Date : 2022-05-01 DOI: 10.1109/cniot55862.2022.00046

Biao Wang, Xin Xin, Jing Yang, Shun Li, Yan Shao

{"title":"Subject-Object Aspect-Based Sentiment Analysis Model Based on News Texts","authors":"Biao Wang, Xin Xin, Jing Yang, Shun Li, Yan Shao","doi":"10.1109/cniot55862.2022.00046","DOIUrl":"https://doi.org/10.1109/cniot55862.2022.00046","url":null,"abstract":"News as an important part of the open source intelligence has always played an important role in international relations and national security fields. However, the fine-grained sentiment analysis work such as Aspect-Based Sentiment Analysis (ABSA) tasks focused on the service industry and e-commerce comments and the Target Aspect-Based Sentiment Analysis (T-ABSA) tasks focused on the Twitter datasets, these two types of tasks usually limit the context to the fixed subjects or objects, simplifying the model by limiting several aspects simultaneously. In addition, the sentiment analysis work based on the news texts most focused on the chapters level. Therefore, based on the characteristics of news texts that it contains multiple subjects and objects, this paper proposed the Subject-Object Aspect-Based Sentiment Analysis (SO-ABSA) model, which can do fine-grained emotional element extraction in the context of indefinite subjects, objects and aspects. More emotional elements can be mined through SO-ABSA model. The proposed model can extract the uncertain entities efficiently and improve the accuracy of subjects and objects extraction. Moreover, the uncertain aspects also can be extracted flexibly and the sentiment analysis result can represent the subjects’ emotional tendency towards specific aspects. To evaluate our method, we built a subject-object oriented dataset (SOOD) with data sourced from 30,000 news articles. We propose a subject-object aspect emotion analysis model and evaluate the model on the SOOD dataset. The experimental results show the effectiveness of our model.","PeriodicalId":251734,"journal":{"name":"2022 3rd International Conference on Computing, Networks and Internet of Things (CNIOT)","volume":"178 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129595578","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

Human-Cascaded network for Robust Detection of Occluded Pedestrian 基于人级联网络的遮挡行人鲁棒检测

2022 3rd International Conference on Computing, Networks and Internet of Things (CNIOT) Pub Date : 2022-05-01 DOI: 10.1109/cniot55862.2022.00045

Zhewei Xu, Xiufeng Fu, Da Feng, Wei Li, Yang Liu

{"title":"Human-Cascaded network for Robust Detection of Occluded Pedestrian","authors":"Zhewei Xu, Xiufeng Fu, Da Feng, Wei Li, Yang Liu","doi":"10.1109/cniot55862.2022.00045","DOIUrl":"https://doi.org/10.1109/cniot55862.2022.00045","url":null,"abstract":"Occlusion is a key challenge in real-world on-road pedestrian detection task. Due to constrained viewpoint geometry, a pedestrian is very likely to be obstructed by other pedestrians and/or other objects such as cars and bicycles. For Advanced Driver Assistance System (ADAS), heavily occluded pedestrians are as important as reasonable pedestrians because they may burst out from crowds or roadside obstacles. In this paper, a human-cascaded network is proposed for robust detection of heavily occluded pedestrians. Specifically, a sharp-response proposal network (SRPN) is designed to refine the feature responses in a narrow area to handle crowded pedestrian detection, followed by outputting the head and full body proposals for diverse occlusion situations. After RoI-pooling, a visible-guided attention (VGA) module is developed to leverage the head and visible area information. The VGA module also suppresses the feature noise of occluded area to enhance the feature representation learning of the backbone network. Finally, a head-cascade RCNN (HRCNN) network is proposed to predict the pedestrian bounding box from the head proposal. The proposed approach is validated through a widely used pedestrian detection dataset: CityPersons. Experimental results show that our approach achieves promising detection performance (log-average miss rate, MR) improvement of 11.4% on heavy occlusion subset, compared to the baseline detector.","PeriodicalId":251734,"journal":{"name":"2022 3rd International Conference on Computing, Networks and Internet of Things (CNIOT)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129968138","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 Research of A Soft Hand Rehabilitation Robot with Multiple Training Modes 多训练模式软手康复机器人的设计与研究

2022 3rd International Conference on Computing, Networks and Internet of Things (CNIOT) Pub Date : 2022-05-01 DOI: 10.1109/cniot55862.2022.00037

Fuhao Wang, Hongbo Wang, Jingjing Luo, Xiaoyang Kang, Xueze Zhang, L. Chen, Qiqi Pan

引用次数: 2

UAV deployment algorithm for manned and unmanned cooperative airborne network 载人与无人协同机载网络无人机部署算法

2022 3rd International Conference on Computing, Networks and Internet of Things (CNIOT) Pub Date : 2022-05-01 DOI: 10.1109/cniot55862.2022.00030

Wu Pan, Na Lv

引用次数: 0

Antenna On/Off Strategy for Massive MIMO Based on User Behavior Prediction 基于用户行为预测的大规模MIMO天线开/关策略

2022 3rd International Conference on Computing, Networks and Internet of Things (CNIOT) Pub Date : 2022-05-01 DOI: 10.1109/cniot55862.2022.00027

Peng Long, Jin Li, Nan Liu, Zhiwen Pan, X. You

{"title":"Antenna On/Off Strategy for Massive MIMO Based on User Behavior Prediction","authors":"Peng Long, Jin Li, Nan Liu, Zhiwen Pan, X. You","doi":"10.1109/cniot55862.2022.00027","DOIUrl":"https://doi.org/10.1109/cniot55862.2022.00027","url":null,"abstract":"Massive multiple-input multiple-output (MIMO) is one of the promising technologies that can offer large capacities in multi-user scenarios with a large-scale antenna system. However, the base stations (BSs) consume too much energy when all of the antennas are turned on. If the users’ traffic requirements can be predicted, we may turn on/off antennas as needed to save energy while at the same time, guaranteeing users’ satisfaction. In this paper, we propose a clustering-based wavelet-LSTM method to predict the users’ traffic requirement in the next interval. According to the prediction results, we determine the number of antennas that needs to be turned on in the next interval. Our method is tested against a real-world anonymous dataset from an operator in a city in China. In comparison with some algorithms in machine learning, numerical results show that our clustering based wavelet-LSTM method achieves higher prediction precision. Furthermore, changing the on/off states of antennas by our proposed prediction method, we could get about 15% gain in energy consumption compared with the energy efficient system where states of antennas are adjusted by the number of users within the BS coverage.","PeriodicalId":251734,"journal":{"name":"2022 3rd International Conference on Computing, Networks and Internet of Things (CNIOT)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114794780","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

Intelligence Serviced Task-driven Network Architecture 智能服务任务驱动网络架构

2022 3rd International Conference on Computing, Networks and Internet of Things (CNIOT) Pub Date : 2022-05-01 DOI: 10.1109/cniot55862.2022.00014

Shenglin Jiang, Yang Guo, Ziqiang Wang, Yikui Cai

引用次数: 0

Development of equipment production information monitoring system based on electric current signal 基于电流信号的设备生产信息监控系统的开发

2022 3rd International Conference on Computing, Networks and Internet of Things (CNIOT) Pub Date : 2022-05-01 DOI: 10.1109/cniot55862.2022.00020

Yuguo Wang, Miaocong Shen, B. Han, Xiaochun Zhu, Jiaxiang Fei, Bin Xie

{"title":"Development of equipment production information monitoring system based on electric current signal","authors":"Yuguo Wang, Miaocong Shen, B. Han, Xiaochun Zhu, Jiaxiang Fei, Bin Xie","doi":"10.1109/cniot55862.2022.00020","DOIUrl":"https://doi.org/10.1109/cniot55862.2022.00020","url":null,"abstract":"Traditional machining equipment typically does not provide online production information such as part production quantities, efficiency and abnormal operating conditions. In order to solve this problem, a real-time production information monitoring system for traditional machining equipment based on electric current signal has been development. Firstly, the data acquisition hardware system using current sensors is designed to collect the electric current signal of the equipment being monitored. Next, the current data is processed by calibration algorithm to obtain production process feature vectors. Finally, a feature matching algorithm is used to identify the operating status. Based on the above algorithms, a monitoring software system is realized by C++ programming language on Qt platform. The monitoring experiment was carried out with automobile transmission shaft parts. The experimental results show that the machining start time and end time of each machined part are correctly and timely identified, and the abnormal state of the equipment could be accurately identified. The developed system is suitable for real-time monitoring of the traditional machining equipment.","PeriodicalId":251734,"journal":{"name":"2022 3rd International Conference on Computing, Networks and Internet of Things (CNIOT)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132411203","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

Stochastic-Network-Calculus-Theory-Based Road Side Unit Location Optimization at an Intersection 基于随机网络-微积分理论的交叉口路边单元选址优化

2022 3rd International Conference on Computing, Networks and Internet of Things (CNIOT) Pub Date : 2022-05-01 DOI: 10.1109/cniot55862.2022.00016

Yinsong Wang, Yunyi Liang, Zhizhou Wu, Yuyin Guan

{"title":"Stochastic-Network-Calculus-Theory-Based Road Side Unit Location Optimization at an Intersection","authors":"Yinsong Wang, Yunyi Liang, Zhizhou Wu, Yuyin Guan","doi":"10.1109/cniot55862.2022.00016","DOIUrl":"https://doi.org/10.1109/cniot55862.2022.00016","url":null,"abstract":"This paper deals with the problem of stochastic network calculus-based road side unit (RSU) location optimization at an intersection. Considering the stochasticity of data arrival rate at RSUs and RSU service capacity, the upper bound of vehicle-to-RSU (V2R) communication delay is derived using stochastic network calculus. Further, to hedge against the impact of the randomness of the traffic density on RSU location optimization, the problem is formulated as a two-stage nonlinear mixed-integer stochastic program. The objective function of this program is to minimize the investment cost of RSU location and the expectation of the penalty cost of the V2R communication delay upper bound. In the first stage of the program, the number and location of RSUs are optimized when the traffic density at the intersection is uncertain. In the second stage, when the traffic density is realized, the subareas of the intersection are assigned to the located RSUs to minimize the penalty cost. To find a global optimal solution to the problem, a Benders decomposition algorithm is proposed. The experiment results show that the proposed model is able to achieve 19.4 ms/per cost lower V2R communication delay, compared with the average-communication-delay-based model.","PeriodicalId":251734,"journal":{"name":"2022 3rd International Conference on Computing, Networks and Internet of Things (CNIOT)","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131615675","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