2020 2nd International Conference on Advances in Computer Technology, Information Science and Communications (CTISC)最新文献

Passenger flow forecast of railway station based on improved LSTM 基于改进LSTM的火车站客流预测

2020 2nd International Conference on Advances in Computer Technology, Information Science and Communications (CTISC) Pub Date : 2020-03-01 DOI: 10.1109/CTISC49998.2020.00033

Kaibei Peng, W. Bai, Liuyi Wu

引用次数: 3

CTISC 2020 Commentary CTISC 2020评论

2020 2nd International Conference on Advances in Computer Technology, Information Science and Communications (CTISC) Pub Date : 2020-03-01 DOI: 10.1109/ctisc49998.2020.00002

引用次数: 0

CTISC 2020 TOC

2020 2nd International Conference on Advances in Computer Technology, Information Science and Communications (CTISC) Pub Date : 2020-03-01 DOI: 10.1109/ctisc49998.2020.00004

Shi-Hong Shao

引用次数: 0

An Anomaly Detection Method for Outdoors Insulator in High-Speed Railway Traction Substation 高速铁路牵引变电站室外绝缘子异常检测方法研究

2020 2nd International Conference on Advances in Computer Technology, Information Science and Communications (CTISC) Pub Date : 2020-03-01 DOI: 10.1109/CTISC49998.2020.00032

Xuemin Lu, Yuchen Peng, W. Quan, N. Zhou, Dong Zou, Jim X. Chen

{"title":"An Anomaly Detection Method for Outdoors Insulator in High-Speed Railway Traction Substation","authors":"Xuemin Lu, Yuchen Peng, W. Quan, N. Zhou, Dong Zou, Jim X. Chen","doi":"10.1109/CTISC49998.2020.00032","DOIUrl":"https://doi.org/10.1109/CTISC49998.2020.00032","url":null,"abstract":"The outdoors insulator is an important component of the high-speed railway traction substation, which is of great significance to maintain the stability of transmission line and ensure the normal operation of transmission network. Once there is a fault for the insulator, it will cause serious transmission failure and economic loss. Therefore, a method is proposed to detect the abnormal areas of outdoors insulator in high-speed railway traction substation based on object detection and generative adversarial networks. First, we employ Faster RCNN to locate the area of insulator from the input image of traction substation. Then, the image of insulator obtained from the first step is fed into our designed generative adversarial networks to generate fake image, which is a normal image of insulator. Finally, multi-scale structural similarity algorithm is used to realize the anomaly detection of insulator and visualize anomalous areas. Experiments results on Heishan traction substation show that the proposed method is effective.","PeriodicalId":266384,"journal":{"name":"2020 2nd International Conference on Advances in Computer Technology, Information Science and Communications (CTISC)","volume":"185 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132869045","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

Real-Time Template Matching Based on Local Stable Pixels 基于局部稳定像素的实时模板匹配

2020 2nd International Conference on Advances in Computer Technology, Information Science and Communications (CTISC) Pub Date : 2020-03-01 DOI: 10.1109/CTISC49998.2020.00028

Xicheng Zhu, Xiao Hu, Changhong Liu, Shao-Hu Peng, Chang Zhang

引用次数: 1

Cloud-Edge-End Simulation System Architecture Study 云边缘仿真系统架构研究

2020 2nd International Conference on Advances in Computer Technology, Information Science and Communications (CTISC) Pub Date : 2020-03-01 DOI: 10.1109/CTISC49998.2020.00023

Guo Yan, Mao Shao-jie

引用次数: 2

Neurons identification of single-photon wide-field calcium fluorescent imaging data 神经元识别的单光子宽场钙荧光成像数据

2020 2nd International Conference on Advances in Computer Technology, Information Science and Communications (CTISC) Pub Date : 2020-03-01 DOI: 10.1109/CTISC49998.2020.00029

Yubing Ma, Kaifeng Shang, Qionghai Dai, Jingtao Fan

{"title":"Neurons identification of single-photon wide-field calcium fluorescent imaging data","authors":"Yubing Ma, Kaifeng Shang, Qionghai Dai, Jingtao Fan","doi":"10.1109/CTISC49998.2020.00029","DOIUrl":"https://doi.org/10.1109/CTISC49998.2020.00029","url":null,"abstract":"Tracking neurons by analyzing their calcium imaging data has enabled biological scientists to better understand the structure and working principle of the nervous system. Several algorithms have been proposed for neurons identification, but most of them become less effective when processing data recorded by single-photon wide-field fluorescence microscopes due to low signal-to-noise ratio (SNR). Moreover, defocus blur, which is common in in vivo imaging, and interference of other biological structures near the neurons have brought greater challenges. In the face of these issues, we have presented an improved method based on the extended constrained nonnegative matrix factorization (CNMF-E) framework to better identify the spatial locations and temporal activities of the neurons. To obtain more appropriate spatial components, we have introduced regularizations into the optimization problem and applied more morphological processing. For more precise temporal components, we have performed a piecewise baseline adjustment on the neurons’ fluorescence traces and suppressed the overestimated signals caused by the estimation error of background fluctuations. Our approach has been tested on the mouse brain cortex recorded by the Real-time, Ultra-large-Scale imaging at High-resolution (RUSH) macroscope. Due to the lack of existing datasets similar to the current imaging conditions, we have manually labeled some neurons and compared the results qualitatively, which show that our method has identified the neurons more accurately compared with the original CNMF-E method.","PeriodicalId":266384,"journal":{"name":"2020 2nd International Conference on Advances in Computer Technology, Information Science and Communications (CTISC)","volume":"69 6","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114037674","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

An Empirical Study of Impact Factors on the Alignment of Cloud Computing and Enterprise 云计算与企业对接影响因素的实证研究

2020 2nd International Conference on Advances in Computer Technology, Information Science and Communications (CTISC) Pub Date : 2020-03-01 DOI: 10.1109/CTISC49998.2020.00018

Mingxing Shao, Xiangqing Li

{"title":"An Empirical Study of Impact Factors on the Alignment of Cloud Computing and Enterprise","authors":"Mingxing Shao, Xiangqing Li","doi":"10.1109/CTISC49998.2020.00018","DOIUrl":"https://doi.org/10.1109/CTISC49998.2020.00018","url":null,"abstract":"In the era of big data, where cloud computing proves to be an essential technology, its ability to align itself with enterprise is the key to facilitate business process reengineering and innovation and enhance enterprise value. In order to identify the key factors influencing the alignment of cloud computing and enterprises in Zhongguancun Technology Park, this paper, based on the dynamic capability theory and taking into account the ever-changing business environment in the Zhongguancun Technology Park, focused on three factors of an enterprise, namely Enterprise Dynamic Capability, Organization Flexibility and IT Flexibility, and built a theoretical model to study how these three factors influence the alignment of cloud computing. The paper measured the impact by two dimensions, Alignment Depth and Alignment Breadth. The results were tested by data collected in questionnaires and the Structural Equation Model (SEM) empirically. The findings showed that enterprise dynamic capability and IT flexibility both have a positive impact on the alignment depth and alignment breadth of cloud computing.","PeriodicalId":266384,"journal":{"name":"2020 2nd International Conference on Advances in Computer Technology, Information Science and Communications (CTISC)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132755360","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

Sponsors and Supporters: CTISC 2020 主办单位:中国科协2020

2020 2nd International Conference on Advances in Computer Technology, Information Science and Communications (CTISC) Pub Date : 2020-03-01 DOI: 10.1109/ctisc49998.2020.00008

引用次数: 0

Image data augmentation method based on maximum activation point guided erasure 基于最大激活点引导擦除的图像数据增强方法

2020 2nd International Conference on Advances in Computer Technology, Information Science and Communications (CTISC) Pub Date : 2020-03-01 DOI: 10.1109/CTISC49998.2020.00027

Yun Jiang, Shengxin Tao, Hai Zhang, Simin Cao

{"title":"Image data augmentation method based on maximum activation point guided erasure","authors":"Yun Jiang, Shengxin Tao, Hai Zhang, Simin Cao","doi":"10.1109/CTISC49998.2020.00027","DOIUrl":"https://doi.org/10.1109/CTISC49998.2020.00027","url":null,"abstract":"Deep neural networks usually contain tens to hundreds of millions of orders of learning parameters that provide the necessary representation to solve various visual tasks. But with the increase of the representational ability, the possibility of over-fitting also increase, which bring about poor generalization. In this paper, we propose MA (Maximum Activation point processing) algorithm, a new image data augmentation method which is designed to improve the generalization ability of the model and reduce the risk of overfitting. During the training process, the most discriminative part of the input image is searched for, and the model is driven to search for the supplementary information of the most important feature information by erasing the maximum attention image block. During this process, training images with different occlusion levels are generated as new inputs to the network and the model continues to be trained. The image erasure method based on the maximum activation point guidance only needs to modify the input image, which can effectively improve the robustness of the model to occluded image recognition, and can be integrated with various network structures. The effectiveness of our method is verified on the Cifar10, Cifar100 and Fashion-MNIST datasets.","PeriodicalId":266384,"journal":{"name":"2020 2nd International Conference on Advances in Computer Technology, Information Science and Communications (CTISC)","volume":"61 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115293182","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