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2021 6th International Conference on Intelligent Computing and Signal Processing (ICSP)最新文献

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Research on Impact Assessment of Attacks on Power Terminals 电力终端攻击影响评估研究
2021 6th International Conference on Intelligent Computing and Signal Processing (ICSP) Pub Date : 2021-04-09 DOI: 10.1109/ICSP51882.2021.9408839
Xiaojun Zhou, Liming Wang, Yan Lu, Zhiwei Dong, W. Zhang, Yidong Yuan, Qi Li
{"title":"Research on Impact Assessment of Attacks on Power Terminals","authors":"Xiaojun Zhou, Liming Wang, Yan Lu, Zhiwei Dong, W. Zhang, Yidong Yuan, Qi Li","doi":"10.1109/ICSP51882.2021.9408839","DOIUrl":"https://doi.org/10.1109/ICSP51882.2021.9408839","url":null,"abstract":"The power terminal network has the characteristics of a large number of nodes, various types, and complex network topology. After the power terminal network is attacked, the impact of power terminals in different business scenarios is also different. Traditional impact assessment methods based on network traffic or power system operation rules are difficult to achieve comprehensive attack impact analysis. In this paper, from the three levels of terminal security itself, terminal network security and terminal business application security, it constructs quantitative indicators for analyzing the impact of power terminals after being attacked, so as to determine the depth and breadth of the impact of the attack on the power terminal network, and provide the next defense measures with realistic basis.","PeriodicalId":117159,"journal":{"name":"2021 6th International Conference on Intelligent Computing and Signal Processing (ICSP)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123176185","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
Pilot-aided Carrier Phase Estimator for Quadrature Amplitude Modulation in Fibre Communications 光纤通信中正交调幅的导频辅助载波相位估计
2021 6th International Conference on Intelligent Computing and Signal Processing (ICSP) Pub Date : 2021-04-09 DOI: 10.1109/ICSP51882.2021.9408735
Binghui Fu
{"title":"Pilot-aided Carrier Phase Estimator for Quadrature Amplitude Modulation in Fibre Communications","authors":"Binghui Fu","doi":"10.1109/ICSP51882.2021.9408735","DOIUrl":"https://doi.org/10.1109/ICSP51882.2021.9408735","url":null,"abstract":"With the development of optical communication technology, Quadrature Amplitude Modulation (QAM) has been widely used in fibre communication systems, However, conventional phase estimation algorithms can’t effectively estimate the phase noise of high-order QAM signals. In this paper, a pilot-aided phase noise estimator has been studied. By using pilot-aided algorithm, the proposed phase estimator can be applied to arbitrary quadrature amplitude modulation (QAM) scheme. The estimator is composed of a one-shot estimator and Wiener filter to achieve optimal performance. This paper discusses the structure and theory of this phase noise estimator.","PeriodicalId":117159,"journal":{"name":"2021 6th International Conference on Intelligent Computing and Signal Processing (ICSP)","volume":"114 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117243743","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
Rock Thin-Section Image Classification based on Residual Neural Network 基于残差神经网络的岩石薄壁图像分类
2021 6th International Conference on Intelligent Computing and Signal Processing (ICSP) Pub Date : 2021-04-09 DOI: 10.1109/ICSP51882.2021.9408983
Chen Guojian, Li Peisong
{"title":"Rock Thin-Section Image Classification based on Residual Neural Network","authors":"Chen Guojian, Li Peisong","doi":"10.1109/ICSP51882.2021.9408983","DOIUrl":"https://doi.org/10.1109/ICSP51882.2021.9408983","url":null,"abstract":"When classifying rock slices, due to the small particle size of the rock slices, the classification is difficult. When manual methods are used for identification, the efficiency is low and subject to subjective factors. Therefore, this paper proposes a rock based on residual network The method of classifying granular images. This method uses the ResNet50 and ResNet101 models in the residual network to realize the automatic extraction of image features, and establishes a classifier to realize the classification based on the size of the rock slice image. This experiment uses 10,000 rock slice images obtained from the Ordos Basin, and uses 8,000 of them as the training set The residual network model is used for training, and then another 2,000 images are used to test the model. The experimental results show that two networks The accuracy of the classification results of the structure in the test set reached 90.24% and 91.63%. By using the residual network model to classify based on the rock slice image, an efficient and accurate classification effect can be obtained.","PeriodicalId":117159,"journal":{"name":"2021 6th International Conference on Intelligent Computing and Signal Processing (ICSP)","volume":"88 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121372851","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: 8
Enabling Blind Area Coverage for the Smart Grids: Integrating Energy-efficient LoRa Technologies in the 5G 实现智能电网的盲区覆盖:在5G中集成节能LoRa技术
2021 6th International Conference on Intelligent Computing and Signal Processing (ICSP) Pub Date : 2021-04-09 DOI: 10.1109/ICSP51882.2021.9408706
Jianliang Zhang, Yang Li, Junwei Ma, Honglin Xue, Jian Wu, Min Zhao, Chao Han, Xiaoyan Dang, Sheng Bi
{"title":"Enabling Blind Area Coverage for the Smart Grids: Integrating Energy-efficient LoRa Technologies in the 5G","authors":"Jianliang Zhang, Yang Li, Junwei Ma, Honglin Xue, Jian Wu, Min Zhao, Chao Han, Xiaoyan Dang, Sheng Bi","doi":"10.1109/ICSP51882.2021.9408706","DOIUrl":"https://doi.org/10.1109/ICSP51882.2021.9408706","url":null,"abstract":"The convergence of the Internet of Things (IoT) and 5G will open a range of innovations for the deployment of enhanced sensing and novel applications, controlling and interactive systems. The current smart grid (SG) will be more reliable, secure, flexible and durable by implementing 5GIoT monitoring. However, 5GIoT, is inefficiently and costly to travel over large areas and penetrate physical structures. As a complement, the proposed 5G1oRa converged network can offer a low-cost and large scale of coverage without blind areas. There are notable concerns regarding certain energy conservation issues to be overcome in order to achieve a successful integration of multi-hop LoRa systems within 5G architectures. Based on the Charnes-Cooper transform and Lagrange Multiplier iteration algorithm, a non-convex relaxation optimization is proposed to allocate transmit power for multi-hop LoRa to further maximize the system energy efficiency. The solution has been deployed, implemented and validated in a real and integrated 5GLoRa testbed, showing its feasibility to meet the requirements of SG data collection, transmission, cloud storage, and calculation in a wide area. Simulation results also validate the efficiency of our proposed model, which significantly outperforms other benchmark algorithms in terms of energy efficiency and QoS requirements.","PeriodicalId":117159,"journal":{"name":"2021 6th International Conference on Intelligent Computing and Signal Processing (ICSP)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127300183","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
Network Topology Overlapping Group Detection Based on h-Core Pruning 基于h核剪枝的网络拓扑重叠组检测
2021 6th International Conference on Intelligent Computing and Signal Processing (ICSP) Pub Date : 2021-04-09 DOI: 10.1109/ICSP51882.2021.9408816
Qi Zhang, Y. Liu, Yu-Sheng Cai
{"title":"Network Topology Overlapping Group Detection Based on h-Core Pruning","authors":"Qi Zhang, Y. Liu, Yu-Sheng Cai","doi":"10.1109/ICSP51882.2021.9408816","DOIUrl":"https://doi.org/10.1109/ICSP51882.2021.9408816","url":null,"abstract":"The network group detection has a large number of application researches and has achieved certain results in network security, IP entity location and load balancing. However, due to the large scale of the network topology graph and the large number of terminal nodes, most of the existing overlapping group detection algorithms are relatively complex, and the data size that can be processed is limited, and cannot be directly applied to the network topology. This paper proposes a network topology overlapping group detection algorithm based on h-core pruning. This algorithm decomposes the network into smaller strong connected components, reduces the interference of noisy nodes to overlapping group discovery, and more efficiently detect the largest k-plex group on the target network. A large number of experiments show that the method in this paper is effective. Compared with the full-enum algorithm, our method increases the network size that can be handled by the largest k-plex group by two orders of magnitude, and can detect overlapping groups in the network topology more efficiently.","PeriodicalId":117159,"journal":{"name":"2021 6th International Conference on Intelligent Computing and Signal Processing (ICSP)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127376904","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
CdZnTe photon-counting detection module for multi-energy X-ray imaging 用于多能x射线成像的CdZnTe光子计数检测模块
2021 6th International Conference on Intelligent Computing and Signal Processing (ICSP) Pub Date : 2021-04-09 DOI: 10.1109/ICSP51882.2021.9408897
Xiangang Luo, Feng Li, Yuan Fei, Chengfang Qiao, Y. Di, Xiaowei Cui, Chunyan Zhou
{"title":"CdZnTe photon-counting detection module for multi-energy X-ray imaging","authors":"Xiangang Luo, Feng Li, Yuan Fei, Chengfang Qiao, Y. Di, Xiaowei Cui, Chunyan Zhou","doi":"10.1109/ICSP51882.2021.9408897","DOIUrl":"https://doi.org/10.1109/ICSP51882.2021.9408897","url":null,"abstract":"Three Cadmium Zinc Telluride (CZT) photon-counting detection modules with 1 × 16 pixels were fabricated using CZT wafers of different crystalline qualities. The thermally stimulated current (TSC) spectrum method was used to characterize wafer quality from which modules were fabricated. The wafers show different levels, corresponding to different crystalline defects, indicated by the traps appearing in the TSC spectrum. The first trap is believed to occur because of Indium doping. Others are thought to be caused by crystalline defects. By comparing the pixel counts of the three modules with TSC results, we show that the first trap contributes a positive effect to detector performance, whereas others contribute negative effects. The assembled module board comprising the best sample produces high-quality X-ray images.","PeriodicalId":117159,"journal":{"name":"2021 6th International Conference on Intelligent Computing and Signal Processing (ICSP)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125366535","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
Feature registration of large resolution difference non-homologous SAR image pairs for sea ice drift tracking 海冰漂移跟踪的大分辨率差非同源SAR图像对特征配准
2021 6th International Conference on Intelligent Computing and Signal Processing (ICSP) Pub Date : 2021-04-09 DOI: 10.1109/ICSP51882.2021.9408919
Peng Men, Hao Guo, Jubai An, Guan-yu Li
{"title":"Feature registration of large resolution difference non-homologous SAR image pairs for sea ice drift tracking","authors":"Peng Men, Hao Guo, Jubai An, Guan-yu Li","doi":"10.1109/ICSP51882.2021.9408919","DOIUrl":"https://doi.org/10.1109/ICSP51882.2021.9408919","url":null,"abstract":"At present, SAR images from same source are widely used in the field of sea ice drift tracking. Due to the longer revisit time of homologous spaceborne satellites, only an average velocity can be determined. For longer time intervals, velocities due to short-duration events such as storms are lost. Synthetic Aperture Radar (SAR) images from different sources make it easy to construct image sequences with short time intervals. However, the resolution and noise level between non-homologous SAR image pairs often differ greatly. When there is a relatively large resolution difference between image pairs, the areal features between image pairs are very different, which increases the difficulty of feature registration. In this paper, a super-resolution reconstruction method is proposed to solve the problem of resolution difference between image pairs for sea ice drift. This method can significantly improve the quality of feature registration of image pairs from different SAR sensors. We demonstrate through several examples the effectiveness of the method in feature matching of large resolution difference images from different SAR sensors.","PeriodicalId":117159,"journal":{"name":"2021 6th International Conference on Intelligent Computing and Signal Processing (ICSP)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114396230","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
Intelligent Diagnosis Method for Intermittent Fault of Digital Circuit Based on Dynamic Power Current 基于动态电源电流的数字电路间歇故障智能诊断方法
2021 6th International Conference on Intelligent Computing and Signal Processing (ICSP) Pub Date : 2021-04-09 DOI: 10.1109/ICSP51882.2021.9408641
Liang Luyue, Lv Kehong, Liu Guanjun, Qiu Jing
{"title":"Intelligent Diagnosis Method for Intermittent Fault of Digital Circuit Based on Dynamic Power Current","authors":"Liang Luyue, Lv Kehong, Liu Guanjun, Qiu Jing","doi":"10.1109/ICSP51882.2021.9408641","DOIUrl":"https://doi.org/10.1109/ICSP51882.2021.9408641","url":null,"abstract":"In this paper, a novel method of intermittent fault diagnosis based on dynamic power current in digital circuit is proposed. The intermittent fault model in digital circuit is introduced. The influence of intermittent fault of different magnitudes and types on the dynamic power current of logic gate circuit is analyzed. Then, an intelligent diagnosis method of intermittent fault based on power current information is put forward, which has been verified on ISCAS85-C17 circuit. The test shows the feasibility of using dynamic power current for digital circuit intermittent fault diagnosis.","PeriodicalId":117159,"journal":{"name":"2021 6th International Conference on Intelligent Computing and Signal Processing (ICSP)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114456763","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
Blind Quality Assessment of Tone-Mapped Images with Multi-scale Visual Feature Extraction Neural Network 基于多尺度视觉特征提取神经网络的色调映射图像质量盲评价
2021 6th International Conference on Intelligent Computing and Signal Processing (ICSP) Pub Date : 2021-04-09 DOI: 10.1109/ICSP51882.2021.9408691
Xiaomin Xu, M. Zhang, Jun Feng
{"title":"Blind Quality Assessment of Tone-Mapped Images with Multi-scale Visual Feature Extraction Neural Network","authors":"Xiaomin Xu, M. Zhang, Jun Feng","doi":"10.1109/ICSP51882.2021.9408691","DOIUrl":"https://doi.org/10.1109/ICSP51882.2021.9408691","url":null,"abstract":"To guarantee the quality of high dynamic range image (HDRI), various tone-mapped operators (TMOs) have been designed to display HDRI on traditional displays recently. Naturally, the image perceptual quality deteriorates seriously due to the inevitable distortions under different TMOs. In this paper, we propose a multi-scale visual feature extraction neural network for blind image quality assessment (BIQA) of TMIs. Specifically, hierarchical image decomposition is elaborately considered to mimic the hierarchical perception mechanism in the human visual system, expecting to better extract and fuse the multi scale features for quality prediction. Besides, under the proposed learning framework, the procedure of feature extraction, multi-scale feature fusion and quality prediction can be jointly optimized in an end-to-end manner. The experiments verify the stable performance of the proposed method on two public TMIs datasets.","PeriodicalId":117159,"journal":{"name":"2021 6th International Conference on Intelligent Computing and Signal Processing (ICSP)","volume":"74 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121994718","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
Query-by-Example on-Device Keyword Spotting using Convolutional Recurrent Neural Network and Connectionist Temporal Classification 使用卷积递归神经网络和连接主义时间分类的逐例查询设备上关键字识别
2021 6th International Conference on Intelligent Computing and Signal Processing (ICSP) Pub Date : 2021-04-09 DOI: 10.1109/ICSP51882.2021.9408857
Lian Meirong, Zhang Shaoying, Cheng Chuanxu, Xu Wen
{"title":"Query-by-Example on-Device Keyword Spotting using Convolutional Recurrent Neural Network and Connectionist Temporal Classification","authors":"Lian Meirong, Zhang Shaoying, Cheng Chuanxu, Xu Wen","doi":"10.1109/ICSP51882.2021.9408857","DOIUrl":"https://doi.org/10.1109/ICSP51882.2021.9408857","url":null,"abstract":"Keyword spotting (KWS) is an essential feature for speech-based applications on mobile devices. For the sake of reducing power consumption and improving robustness on substandard pronunciations of KWS systems, this paper proposes a query-by-example on-device keyword spotting system using Convolutional Recurrent Neural Network (CRNN) and Connectionist T emporal Classification (CTC). CRNN is to directly predict the phoneme posterior probabilities, and CTC is to calculate the scores for the output phoneme sequences. To reduce the computational costs, the CRNN-based model is then simplified, and a template generator is built for generating keyword templates based on Dynamic Time Wrapper (DTW). The proposed KWS system has low computational requirements and is well-suited for both enrollment and inference on lower-power devices. It has competitive performance in comparison with other query-byexample systems, and has achieved the standards of the commercial application level, even in the condition of noise or under far-field environment.","PeriodicalId":117159,"journal":{"name":"2021 6th International Conference on Intelligent Computing and Signal Processing (ICSP)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128681957","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
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