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2020 5th International Conference on Information Science, Computer Technology and Transportation (ISCTT)最新文献

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Analysis of 2019-nCoV epidemic situation based on modified SEIR model and DSGE algorithm 基于改进SEIR模型和DSGE算法的2019-nCoV疫情分析
2020 5th International Conference on Information Science, Computer Technology and Transportation (ISCTT) Pub Date : 2020-11-01 DOI: 10.1109/ISCTT51595.2020.00070
Wenyi Tan, Ruifeng Bian, Weixiong Yang, Yichen Hou
{"title":"Analysis of 2019-nCoV epidemic situation based on modified SEIR model and DSGE algorithm","authors":"Wenyi Tan, Ruifeng Bian, Weixiong Yang, Yichen Hou","doi":"10.1109/ISCTT51595.2020.00070","DOIUrl":"https://doi.org/10.1109/ISCTT51595.2020.00070","url":null,"abstract":"In order to analyze the spread of novel coronavirus pneumonia., a prediction model based on the modified SEIR infectious disease transmission kinetic model for the number of confirmed and fatal cases of novel coronavirus pneumonia was constructed to predict the outbreak of the epidemic in China. Differential equations were constructed to take into account the spread of the epidemic and the assignment of each parameter in the model to obtain the prediction results for China. The prediction of the epidemic in the United States was divided into two cases with and without a home order. In order to analyze the impact of 2019-nCoV epidemic on economic development, the fiscal revenue of Hubei Province from January to July in 2020 is analyzed, and the change of GDP and tertiary industry output value in Hubei Province is predicted by combining grey prediction model with time series. In this paper, DSGE algorithm is used to study the changes of labor supply, output, investment and capital under different costs during the epidemic period. The results were analyzed with respect to the major epidemic prevention measures taken by the Chinese Ministry of Health (MOH). Finally, the reliability of the model was analyzed.","PeriodicalId":178054,"journal":{"name":"2020 5th International Conference on Information Science, Computer Technology and Transportation (ISCTT)","volume":"11 3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125763792","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
Research on Prediction of Port Cargo Throughput based on PCA-BP Neural Network Combination Model 基于PCA-BP神经网络组合模型的港口货物吞吐量预测研究
2020 5th International Conference on Information Science, Computer Technology and Transportation (ISCTT) Pub Date : 2020-11-01 DOI: 10.1109/ISCTT51595.2020.00098
Du Baochai
{"title":"Research on Prediction of Port Cargo Throughput based on PCA-BP Neural Network Combination Model","authors":"Du Baochai","doi":"10.1109/ISCTT51595.2020.00098","DOIUrl":"https://doi.org/10.1109/ISCTT51595.2020.00098","url":null,"abstract":"Effective prediction can help people make reasonable and accurate judgments about the future development level of things, and then guide and regulate production management activities. With the development of big data technology, data prediction technology is no longer limited to the traditional time series prediction and simple causal prediction, but more biased towards machine learning, AI technology and so on. However, there are some limitations in using big data for prediction, such as data size and threshold problem. In this paper, the combination model of Principal Component Analysis (PCA) method and BP Neural Network algorithm is applied to the prediction. Firstly, the dimension of a large number of index data is reduced through PCA, and the effective information is retained while the amount of data is reduced. Then the BP Neural network model is used to predict. This paper chooses Dalian port cargo throughput as an example to verify the effectiveness of the model, the results show that the model has higher accuracy and efficiency.","PeriodicalId":178054,"journal":{"name":"2020 5th International Conference on Information Science, Computer Technology and Transportation (ISCTT)","volume":"174 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123503620","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
Smart Matter: Basic introduction and its potential in the future 智能物质:基本介绍及其未来的潜力
2020 5th International Conference on Information Science, Computer Technology and Transportation (ISCTT) Pub Date : 2020-11-01 DOI: 10.1109/isctt51595.2020.00033
An Hai
{"title":"Smart Matter: Basic introduction and its potential in the future","authors":"An Hai","doi":"10.1109/isctt51595.2020.00033","DOIUrl":"https://doi.org/10.1109/isctt51595.2020.00033","url":null,"abstract":"This article gives an overall introduction to the Smart Matter, which is also referred to as Micro Electrical Mechanical Systems (MEMS). In this article, the author demonstrates some unique features of Smart Matter, including its modularity, reconfigurability, and compatibility. Its manufacturing limitations are also discussed. Then the author uses a kind of smart tiles to give an application of Smart Matters. Finally, the author states the future potential of the Smart Matter.","PeriodicalId":178054,"journal":{"name":"2020 5th International Conference on Information Science, Computer Technology and Transportation (ISCTT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130002252","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
Survey of the Image Recognition Based on Deep Learning Network for Autonomous Driving Car 基于深度学习网络的自动驾驶汽车图像识别研究
2020 5th International Conference on Information Science, Computer Technology and Transportation (ISCTT) Pub Date : 2020-11-01 DOI: 10.1109/ISCTT51595.2020.00007
Jin Liu
{"title":"Survey of the Image Recognition Based on Deep Learning Network for Autonomous Driving Car","authors":"Jin Liu","doi":"10.1109/ISCTT51595.2020.00007","DOIUrl":"https://doi.org/10.1109/ISCTT51595.2020.00007","url":null,"abstract":"Recently, autonomous driving car is a hot area of research and the image recognition technology is one of the key technologies for autonomous driving cars to drive safely on the road. With the development of times and technology, deep learning has been widely applied in image recognition technology, and it plays an important role in this field. In this paper, the development of image recognition technology in autonomous driving cars and deep learning are introduced. Different models of deep learning networks, such as Deep Neural Network (DNN), Recurrent Neural Network (RNN) and Convolutional Neural Network (CNN) are also analyzed. In addition, the theoretical basis of deep learning in image recognition are summarized and the applications of deep learning in image recognition are carried out. Finally, the paper will look into the future development of autonomous vehicles and the future of image recognition technology. It is concluded that, image recognition system, based on deep learning network has been widely used in autonomous driving cars at present, and it has a prospective future for further development.","PeriodicalId":178054,"journal":{"name":"2020 5th International Conference on Information Science, Computer Technology and Transportation (ISCTT)","volume":"83 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130501109","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
Human Skeleton Graph Attention Convolutional for Video Action Recognition 用于视频动作识别的人体骨架图注意卷积
2020 5th International Conference on Information Science, Computer Technology and Transportation (ISCTT) Pub Date : 2020-11-01 DOI: 10.1109/ISCTT51595.2020.00040
Deyuan Zhang, Hongwei Gao, Hailong Dai, Xiangbin Shi
{"title":"Human Skeleton Graph Attention Convolutional for Video Action Recognition","authors":"Deyuan Zhang, Hongwei Gao, Hailong Dai, Xiangbin Shi","doi":"10.1109/ISCTT51595.2020.00040","DOIUrl":"https://doi.org/10.1109/ISCTT51595.2020.00040","url":null,"abstract":"Action recognition based on human skeleton information is a hot topic in the field of computer vision, how to represent the human skeleton graph structure is the key of the method. Graph convolutional network is widely used to extract spatial features of human skeleton. However, the graph convolutional network shares the same weight for neighborhood of each node. In this paper, we propose Human Skeleton Graph Attention Convolutional Neural Network, which introduces graph attention convolution mechanism to extract the spatial features of human skeleton. The model improves the spatial feature extraction of skeleton graph based on the feature relationship of node neighborhood. The experimental results on Kinetics and NTU-RGB+D datasets show that the model can obtain better representation of spatial features, and can achieve better accuracy.","PeriodicalId":178054,"journal":{"name":"2020 5th International Conference on Information Science, Computer Technology and Transportation (ISCTT)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128979981","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
Coordinated Control of Multi-Permanent Magnet Synchronous Motors for Consistent Total Traction Torque 多台永磁同步电动机总牵引转矩一致的协调控制
2020 5th International Conference on Information Science, Computer Technology and Transportation (ISCTT) Pub Date : 2020-11-01 DOI: 10.1109/isctt51595.2020.00051
Jianhua Liu, Wan-Tao Yang, Changfan Zhang, Z. Zhong, Fanqi Zeng, Zijun Yuan
{"title":"Coordinated Control of Multi-Permanent Magnet Synchronous Motors for Consistent Total Traction Torque","authors":"Jianhua Liu, Wan-Tao Yang, Changfan Zhang, Z. Zhong, Fanqi Zeng, Zijun Yuan","doi":"10.1109/isctt51595.2020.00051","DOIUrl":"https://doi.org/10.1109/isctt51595.2020.00051","url":null,"abstract":"Multi-permanent magnet synchronous motors (PMSMs) traction represents the future trend for driving high power traction equipment. Instead of the existing multi-PMSMs coordination control methods that are used to ensure the synchronization of a certain variable like position or/and speed, the purpose of this work is to achieve a consistent total traction torque of multi-PMSMs based on the actual requirement. Amulti-PMSMs coordination control model is developed to reduce the influence of traction torque fluctuation, and the direct torque control strategy based on sliding mode variable structure for each PMSM was constructed to improve its dynamic response performance. The simulation results under two cases are given to verify the effectiveness and feasibility","PeriodicalId":178054,"journal":{"name":"2020 5th International Conference on Information Science, Computer Technology and Transportation (ISCTT)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124467399","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 Segmentation Algorithm of Gray Inhomogeneous Image Based on Cauchy Distribution 基于柯西分布的灰度非均匀图像分割算法研究
2020 5th International Conference on Information Science, Computer Technology and Transportation (ISCTT) Pub Date : 2020-11-01 DOI: 10.1109/ISCTT51595.2020.00057
H. Deng
{"title":"Research on Segmentation Algorithm of Gray Inhomogeneous Image Based on Cauchy Distribution","authors":"H. Deng","doi":"10.1109/ISCTT51595.2020.00057","DOIUrl":"https://doi.org/10.1109/ISCTT51595.2020.00057","url":null,"abstract":"Image segmentation has a constructive position in image engineering and other fields. Among them, the research on the segmentation of uneven grayscale images is particularly important. This is due to the fact that uneven grayscale images widely exist in the real world, such as medical images, remote sensing images, and video surveillance. However, the traditional image segmentation algorithm ignores the unevenness of the gray level of the image, and the effect of such image segmentation is poor. Therefore, this paper proposes a gray-scale uneven image segmentation algorithm based on Cauchy distribution. Based on the RSF (region-scalable fitting) active contour model, this algorithm creates a new kernel function based on the Cauchy distribution, which is the absolute value of the difference between the two Cauchy distributions. On this basis, the energy functional is re-established to fit the gray value of the image inside and outside the contour, and the contour penalty item is added. Finally, the level set theory is used to convert the energy functional into a level set form and add a level set regularization term, and use the gradient descent method to minimize the energy functional. The experimental results show that using the method in this paper to segment the gray-scale uneven image has higher segmentation accuracy and segmentation efficiency, and the segmentation speed is increased by nearly 50%.","PeriodicalId":178054,"journal":{"name":"2020 5th International Conference on Information Science, Computer Technology and Transportation (ISCTT)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123118343","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
Study on the Headgear and Seat of the Thangka Image based on the Improved YOLOv4 Algorithm 基于改进YOLOv4算法的唐卡图像头饰与坐位研究
2020 5th International Conference on Information Science, Computer Technology and Transportation (ISCTT) Pub Date : 2020-11-01 DOI: 10.1109/ISCTT51595.2020.00034
Guoyuan He, Wenjin Hu, Huiyuan Tang, Panpan Xue
{"title":"Study on the Headgear and Seat of the Thangka Image based on the Improved YOLOv4 Algorithm","authors":"Guoyuan He, Wenjin Hu, Huiyuan Tang, Panpan Xue","doi":"10.1109/ISCTT51595.2020.00034","DOIUrl":"https://doi.org/10.1109/ISCTT51595.2020.00034","url":null,"abstract":"Aiming at the problems of complex background and low accuracy in Thangka image detection tasks using deep learning algorithms, an improved object detection algorithm based on YOLOv4 is proposed. Considering that the Mish function used by YOLOv4 is static, which performs the same operation on all input samples, hence it is not enough to deal with complex scenarios. We use the DynamicReLU function to encode the global up and down into a hyperfunction, and dynamically adjust the piecewise linear activation function instead of the Mish function accordingly, which solves the defect that the activation function cannot be dynamically adjusted, and realizes the detection of the headgear and seat of the Thangka image. The experimental results in Thangka image detection show that the evaluation protocol mAP of the algorithm reaches 37.9%, which is an increase of 3.8% compared to the YOLOv4 algorithm. The algorithm improves detection accuracy without increasing the depth and width of the network.","PeriodicalId":178054,"journal":{"name":"2020 5th International Conference on Information Science, Computer Technology and Transportation (ISCTT)","volume":"185 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115481916","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
Analysis on the Applications of AI in Vehicles and the Expectation for Future 人工智能在汽车上的应用分析及未来展望
2020 5th International Conference on Information Science, Computer Technology and Transportation (ISCTT) Pub Date : 2020-11-01 DOI: 10.1109/ISCTT51595.2020.00095
Hongyu Wei
{"title":"Analysis on the Applications of AI in Vehicles and the Expectation for Future","authors":"Hongyu Wei","doi":"10.1109/ISCTT51595.2020.00095","DOIUrl":"https://doi.org/10.1109/ISCTT51595.2020.00095","url":null,"abstract":"Vehicles have become one of the most popular transportation tools. More and more vehicles occur with different AI-based systems. In order to make this mainstream transportation more comfortable, efficient, and safer for people to use, artificial intelligence technologies are applied in vehicles, leading vehicles to become much smarter and intelligent. In this paper, three main applications of AI in vehicles including the AI in Vehicle-to-Everything(V2X), AI in the vehicle control system, and AI diagnostic device for vehicles will be shown. The current technical issues when applying AI in V2X and challenges for all the AI application have to overcome. This article also analyzes the future expectations for the improvement of the application of AI in vehicles.","PeriodicalId":178054,"journal":{"name":"2020 5th International Conference on Information Science, Computer Technology and Transportation (ISCTT)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128443189","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 of BRT Eco-Driving System BRT生态驾驶系统设计
2020 5th International Conference on Information Science, Computer Technology and Transportation (ISCTT) Pub Date : 2020-11-01 DOI: 10.1109/ISCTT51595.2020.00101
Zhuoer Wang, Lan Wei, Xuewei Zhang, Zhengkang Zhou
{"title":"Design of BRT Eco-Driving System","authors":"Zhuoer Wang, Lan Wei, Xuewei Zhang, Zhengkang Zhou","doi":"10.1109/ISCTT51595.2020.00101","DOIUrl":"https://doi.org/10.1109/ISCTT51595.2020.00101","url":null,"abstract":"Eco-driving is an economical and environmentally friendly driving concept. The core of eco-driving is that the driver shifts gears in time, maintains a stable speed, predicts the state of traffic flow and the changes in traffic lights, and avoids sudden acceleration and deceleration as much as possible. However, this requires a professional level of the driver. With the growth of Internet of Things (IOT) technology, this goal can be conveniently accomplished with the help of cooperation of vehicle infrastructure technology with automated control technology. Therefore, a set of ecological driving assistance system based on cooperative vehicle infrastructure system (CVIS) is designed, indicating that the data interaction between the traffic light system and the vehicle is made at the traffic light through CVIS. On account of it, a new ecological driving solution of the traffic light section has been programmed, ensuring the stability of the bus, saving the energy, cutting the emission, and improving mobile efficiency.","PeriodicalId":178054,"journal":{"name":"2020 5th International Conference on Information Science, Computer Technology and Transportation (ISCTT)","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121635546","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
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