2022 IEEE Conference on Telecommunications, Optics and Computer Science (TOCS)最新文献_第10页

Based on D-S Evidence Theory to Calculate Pipeline Failure Probability 基于D-S证据理论的管道失效概率计算

2022 IEEE Conference on Telecommunications, Optics and Computer Science (TOCS) Pub Date : 2022-12-11 DOI: 10.1109/TOCS56154.2022.10016058

Xiao Li, Jiyin Liu, Huiyuan Ai, Jie Wang

引用次数: 0

Big Data Analysis and Calculation on Occupant Protection Based on Intelligent Sled Test System in Passenger Car 基于智能台车测试系统的乘员保护大数据分析与计算

2022 IEEE Conference on Telecommunications, Optics and Computer Science (TOCS) Pub Date : 2022-12-11 DOI: 10.1109/TOCS56154.2022.10015916

Wu Yongqiang, Liu Manli, Chen Chao

引用次数: 0

Construction of manufacturing green innovation system based on big data and artificial intelligence 构建基于大数据和人工智能的制造业绿色创新体系

2022 IEEE Conference on Telecommunications, Optics and Computer Science (TOCS) Pub Date : 2022-12-11 DOI: 10.1109/TOCS56154.2022.10016017

Yuanyuan Li, Dechao Han

引用次数: 0

Urban Road Passenger Interpretation Based on MLP and SHAP 基于MLP和SHAP的城市道路客运解译

2022 IEEE Conference on Telecommunications, Optics and Computer Science (TOCS) Pub Date : 2022-12-11 DOI: 10.1109/TOCS56154.2022.10016130

Dashuang Ji, Qianxin Dong, Yu Zhang

{"title":"Urban Road Passenger Interpretation Based on MLP and SHAP","authors":"Dashuang Ji, Qianxin Dong, Yu Zhang","doi":"10.1109/TOCS56154.2022.10016130","DOIUrl":"https://doi.org/10.1109/TOCS56154.2022.10016130","url":null,"abstract":"Road passenger transport is China's most important mode of passenger transport. Through research and analysis of people's willingness to travel by mode, and taking into account the current social structure of China and the nonlinear and stochastic characteristics of road passenger transport, a fully-connected neural network model was built using deep learning methods to forecast the passenger transport volume of over 260 cities above the municipal level in China. A system of forecasting indicators was constructed using data on road passenger traffic and related factors for all cities in 34 provinces in China. The system is based on three main aspects: socio-demographic economy, urban transport construction, and urban fiscal policy. Finally, the SHAP model was used to calculate the Shap Values of each factor to determine the degree of influence of each factor on the dependent variable and further improve the prediction accuracy. Comparing the predicted values with the true values, the R2 of the model fit is above 60%. The accurate prediction results validate the good application of the fully connected neural network model for urban road passenger transport.","PeriodicalId":227449,"journal":{"name":"2022 IEEE Conference on Telecommunications, Optics and Computer Science (TOCS)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122703456","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 Designing Outdoor Microphone Protection Structure 室外传声器保护结构设计研究

2022 IEEE Conference on Telecommunications, Optics and Computer Science (TOCS) Pub Date : 2022-12-11 DOI: 10.1109/TOCS56154.2022.10015911

Lu Ling, Wan Tao, Zhou Zhou, Cao Hao, Hu Sheng, Chen Wei, Zhou Weihua

引用次数: 0

Fine-Grained Micro-Expression Recognition Based on Hierarchical Attention Mechanism 基于层次注意机制的细粒度微表情识别

2022 IEEE Conference on Telecommunications, Optics and Computer Science (TOCS) Pub Date : 2022-12-11 DOI: 10.1109/TOCS56154.2022.10016063

L. Fu, Qiang Zhang, Rui Wang

{"title":"Fine-Grained Micro-Expression Recognition Based on Hierarchical Attention Mechanism","authors":"L. Fu, Qiang Zhang, Rui Wang","doi":"10.1109/TOCS56154.2022.10016063","DOIUrl":"https://doi.org/10.1109/TOCS56154.2022.10016063","url":null,"abstract":"Micro-Expressions can significantly reflect the psychological state of people at the current moment and have great research value. In the context of the continuous development of deep learning technology, the use of deep learning algorithms to solve the problem of micro-expression recognition(MER) has achieved obvious advantages, but there are also many problems. To address the problem of fine-grained feature extraction for micro-expressions, we propose a hierarchical attention mechanism-based micro-expression recognition(MER) model, which consists of a single ResNet18 network and the task-specific attention modules. We use the ResNet18 network as the backbone network, and insert the attention modules among multiple intermediate layers of the network for extracting fine-grained micro-expression features, so that the model focuses on task-related regions and ignores task-irrelevant regions. We designed a micro-expression recognition(MER) experiment to verify the model. Under the dual evaluation criteria of UF1 and UAR, our proposed model can reach 81.99% and 77.93%, respectively, which has achieved significant performance improvement compared to the current mainstream models.","PeriodicalId":227449,"journal":{"name":"2022 IEEE Conference on Telecommunications, Optics and Computer Science (TOCS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129009058","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

Eye-Blink Detection under Low-Light Conditions Based on Zero-DCE 基于零dce的弱光条件下眨眼检测

2022 IEEE Conference on Telecommunications, Optics and Computer Science (TOCS) Pub Date : 2022-12-11 DOI: 10.1109/TOCS56154.2022.10016013

Xiaolin Zhou

{"title":"Eye-Blink Detection under Low-Light Conditions Based on Zero-DCE","authors":"Xiaolin Zhou","doi":"10.1109/TOCS56154.2022.10016013","DOIUrl":"https://doi.org/10.1109/TOCS56154.2022.10016013","url":null,"abstract":"Eye-blink is an effective tool for human-computer interaction, and it could be a physiological index to judge human activities. Nonetheless, eye-blink reactions not only happen during the daytime, but also blink a lot during nighttime, as blink can moisten the eye when people feel fatigued. In this paper, eye-blink detection under a low-light environment is proposed, improving the success rate of detecting blinks in an insufficient light environment. After comparing two face meshes, which are generated by Dlib and MediaPipe, MediaPipe can yield an abundant and precise face landmark. Even without applying some methods of low-light image enhancement (LLIE), the method of MediaPipe can locate an approximate area of eyes in a nighttime environment. For the problem of detecting blink under a low-light environment, Zero-Reference Deep Curve Estimation (Zero-DCE), a deep learning-based method, is applied. Zero-DCE is used to improve the details of dark blurry images, the advantage of which is zero-reference, i.e., no paired or unpaired data are needed in the training process. Also, Zero-DCE can yield a pleasing result in the aspects of brightness, color, contrast, and naturalness, the details of which will be shown in the following images. When under sufficient light environment, the average success rate of detecting right eye blink is 95.9%, and for left eye blink is 91.2%; when under insufficient light environment without enhancing the image, the average success rate of detecting right eye blink is only 39.7%, and for left eye blink is only 48.8%; when under an insufficient light environment with Zero-DCE, enhancing the quality of image, the average success rate of detecting right eye blink raise to 84%, and for left eye blink raises to 92.7%.","PeriodicalId":227449,"journal":{"name":"2022 IEEE Conference on Telecommunications, Optics and Computer Science (TOCS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129082217","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

Vehicle Price Forecasting Based on Multiple Machine Learning Models 基于多机器学习模型的汽车价格预测

2022 IEEE Conference on Telecommunications, Optics and Computer Science (TOCS) Pub Date : 2022-12-11 DOI: 10.1109/TOCS56154.2022.10015958

Zhongwei Chen, Xiaofeng Li

引用次数: 1

Optical Waveguide Mode Field Diameter Measurement Method Based on Near-field Fiber Probe End-face Scanning 基于近场光纤探头端面扫描的光波导模场直径测量方法

2022 IEEE Conference on Telecommunications, Optics and Computer Science (TOCS) Pub Date : 2022-12-11 DOI: 10.1109/TOCS56154.2022.10015939

Meihua Xiang, Zhiyong Wang, Ziyan Li, Dengcai Yang, Gang Xiong

{"title":"Optical Waveguide Mode Field Diameter Measurement Method Based on Near-field Fiber Probe End-face Scanning","authors":"Meihua Xiang, Zhiyong Wang, Ziyan Li, Dengcai Yang, Gang Xiong","doi":"10.1109/TOCS56154.2022.10015939","DOIUrl":"https://doi.org/10.1109/TOCS56154.2022.10015939","url":null,"abstract":"The proposed method is based on the near-field fiber end-face scanning of the optical waveguide mode field diameter measurement method. Using the scanning fiber probe to scan the optical waveguide end-face Y direction and Z direction, to obtain the coupling efficiency distribution of the corresponding direction. Combining the mode field distribution function and relative motion of the fiber probe and the optical waveguide, the scanning process is modeled mathematically. The relationship between the Gaussian distribution of the coupling efficiency curve and the mode field distribution of the optical wave is deduced. The mode field diameter of the optical waveguide can be inverse calculated accordingly, and the arbitrary mode field distribution characteristics can be obtained by deconvolution method. A near-field optical waveguide mode field measurement system was built to measure the coupling efficiency and dislocation relationship between fiber and fiber, fiber and waveguide. And accordingly giving the mode field diameters in the Y and Z directions of the optical waveguide mode field. The feasibility and validity of the optical waveguide mode field diameter measurement method based on near-field fiber end-face scanning are experimentally verified.","PeriodicalId":227449,"journal":{"name":"2022 IEEE Conference on Telecommunications, Optics and Computer Science (TOCS)","volume":"113 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117290193","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

Substation intelligent security management and control practice based on artificial intelligence and big data analysis 基于人工智能和大数据分析的变电站智能安全管控实践

2022 IEEE Conference on Telecommunications, Optics and Computer Science (TOCS) Pub Date : 2022-12-11 DOI: 10.1109/TOCS56154.2022.10016106

Xinzhuo Li, Li Zhang, Junjie Zhang, Xian Luo

{"title":"Substation intelligent security management and control practice based on artificial intelligence and big data analysis","authors":"Xinzhuo Li, Li Zhang, Junjie Zhang, Xian Luo","doi":"10.1109/TOCS56154.2022.10016106","DOIUrl":"https://doi.org/10.1109/TOCS56154.2022.10016106","url":null,"abstract":"Using the combination of artificial intelligence and big data to provide a more efficient, safer and more accurate optimization scheme for substation intelligent security management and control. At present, there are many problems in the manual field operation of substation, such as untimely control, impractical early warning, high intensity of personnel work, uneven level of personnel skills, inefficient maintenance plan and scheme management, and difficult on-site safety supervision. There are hidden dangers in personnel and equipment to varying degrees. In order to solve the above problems, two optimization schemes are proposed for personnel operation safety and equipment maintenance safety. One is an intelligent security system that can realize the authorization management of substation operators, the orderly management of vehicle traffic and the real-time control of on-site operations. The other is an information model system that can realize intelligent management of maintenance work plan and maintenance preview simulation. The organic combination of the two systems can effectively improve the efficiency and safety of personnel and equipment management and control in the process of substation safety production. Both systems have been applied in a 220kV substation and achieved remarkable results.","PeriodicalId":227449,"journal":{"name":"2022 IEEE Conference on Telecommunications, Optics and Computer Science (TOCS)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116874748","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