检索结果-内蒙古大学图书馆

IEEE International Conference on Data Science in Cyberspace (DSC)

作者： Kuan Liu Yumei Li Yuanhua Qi Ning Qi Mengran Zhai Information Research Institute of Shandong Academy of Sciences Qilu University of Technology (Shandong Academy of Sciences) Jinan China Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center (National Supercomputer Center in Jinan) Qilu University of Technology (Shandong Academy of Sciences) Shandong Institute of Economy and Informatization Development Jinan China Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center (National Supercomputer Center in Jinan) Qilu University of Technology (Shandong Academy of Sciences) Shandong Provincial Key Laboratory of Computer Networks Shandong Fundamental Research Center for Computer Science Jinan China SHANDONG SCICOM Information and Economy Research Institute Co. Ltd Jinan China Shandong Institute of Economy and Informatization Development Jinan China

ISBN: (数字)9798350391367

ISBN: (纸本)9798350391374

With the development of the digital economy and the advent of the big data era, the rapid growth of textual information in cyberspace has placed higher demands on information processing technology. This paper proposes an information extraction technique based on the Text-to-Text Transfer Transformer, known as T5, and keyBERT models, aiming to efficiently distill the key content from textual information in cyberspace. This method combines automatic summarization and keyword extraction to form information briefs. The experiments selected representative policy documents related to data elements as input data and employed information entropy and ROUGE scores as metrics to evaluate the automatic summarization model. The results were compared with the outputs of similar models. Experimental results indicate that the T5 model outperforms other models in terms of summarization effectiveness, and the proposed information extraction method shows significant advantages in readability and processing efficiency, demonstrating practical application value.

关键词： Measurement Biological system modeling Cyberspace Text summarization information processing information retrieval Transformers Data models Data mining information entropy

来源：评论

学校读者我要写书评

暂无评论

A Triangular Stable Node network based on Self-supervised Learning for personalized prediction

A Triangular Stable Node Network based on Self-supervised Le...

引用

International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Qing Liu Qian Gao Jun Fan Zhiqiang Zhang Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center (National Supercomputer Center in Jinan) Qilu University of Technology (Shandong Academy of Sciences) Jinan China Shandong Engineering Research Center of Big Data Applied Technology Faculty of Computer Science and Technology Qilu University of Technology (Shandong Academy of Sciences) Jinan China Shandong Provincial Key Laboratory of Industrial Network and Information System Security Shandong Fundamental Research Center for Computer Science Jinan China China Telecom Digital Intelligence Techonology Co Ltd Jinan China

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

In recent years, research has illuminated the potency of implicit data processing in enhancing user preferences. Nevertheless, barriers remain in breaking through the constraints of implicit information. This study aims to bridge this gap by firstly constructing a triangular stable node network model, tailored to manage implicit information with precision. Recognizing the challenge of pinpointing novel structures within large-scale graphs, we propose SLTSNN— a triangular stable node network based on self-supervised learning for personalized prediction. SLTSNN innovates by maximizing mutual information between graph-level and patch-level representations, while augmenting graph representations through extended enhanced representations. Additionally, it incorporates triangular data associations and introduces a triangular allocation attention network, which emphasizes strongly correlated preference features among similar users. Furthermore, SLTSNN employs contrastive learning to maximize mutual information between graph vectors and hidden representations, distinguishing between high-order global and local representations. The model’s effectiveness in enhancing user preferences and capturing new graph structures is evidenced by its performance on hit rate and normalized discounted cumulative gain metrics across three datasets.

关键词： Measurement Bridges Contrastive learning Signal processing Data processing Vectors Space exploration Resource management Speech processing Mutual information

来源：评论

学校读者我要写书评

暂无评论

Research on Digital Architecture of power Grid and Dynamic Analysis Technology of Digital Project 1

引用

4th International Conference on 3D Imaging Technologies- Multidimensional Signal Processing and Deep Learning, 3D IT-MSP and DL 2022

作者： Wu, Xinping Wang, Gang Lv, Changhui Zhao, Bo Pan, Jianhong Dong, Aidi State Grid Economic and Technological Research Institute Co. Ltd Beijing102209 China State Grid Smart Grid Research Institute CO. LTD Nanjing210003 China State Grid Key Laboratory of Information & Network Security Nanjing210003 China Power Economic Research Institute of Jilin Electric Power Co. Ltd Changchun30011 China State Grid Jilin Electric Power Company Limited Changchun130021 China

ISBN: (数字)9789819911455

ISBN: (纸本)9789819911448

The traditional project technical and economic evaluation only considers the business needs of the project itself, but does not consider the project construction from the overall situation of power grid construction, which makes it difficult to meet the personalized needs of power grid digital projects. This paper first analyzes the microservice architecture and the characteristics and application scenarios of power grid enterprise middle office. Secondly, aiming at the business demand scenarios such as basic resource operation, power data value-added services, and digital platform ecological construction, the paper studies the design methods of power grid digital business, technology, and security architecture, and designs the mid platform technology and security architecture system of power grid enterprises. Finally, based on the above research results, a dynamic construction and calculation method of digital project evaluation index is proposed to realize the technical and economic dynamic analysis of power grid across business domains. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Economic analysis

来源：评论

学校读者我要写书评

暂无评论

Color and Feature Space Classification Methods Solve the Problem of Covariate Semantic information Deviation in Complex Scene Detection Tasks

Color and Feature Space Classification Methods Solve the Pro...

引用

International Joint Conference on Neural networks (IJCNN)

作者： Mingle Zhou Rui Xing Min Li Delong Han Gang Li Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center (National Supercomputer Center in Jinan) Qilu University of Technology (Shandong Academy of Sciences) Jinan China Shandong Provincial Key Laboratory of Computer Networks Shandong Fundamental Research Center for Computer Science Jinan China Shandong SCICOM Information and Economy Research Institute Co. Ltd Jinan China

ISBN: (数字)9798350359312

ISBN: (纸本)9798350359329

The field weed detection task under the perspective of Plant Protection UAVs (PPU) is characterized by multi-scale targets and rich background semantic information, which belongs to the target detection task in complex scenarios. Blindly boosting the network size and overusing the attention mechanism in such tasks are not effective in improving the model accuracy. The core of the problem lies in the fact that the covariate features of the target are shifted during the transfer of the three layers of image semantic information (visual, object and conceptual layers). This phenomenon is particularly evident at the conceptual level, resulting in models that do not accurately understand the target information. Redundant semantic information and irrational attention mechanisms for complex scenarios are the cause of the problem. In this paper, we propose the Color and Feature Space Classification (CFSC) method, which aims to construct a covariate semantic information matrix that spans the visual, object and conceptual layers. Mitigating the problem of offsetting semantic information of covariate features in complex scenarios. The color and feature space classification method is applied to a one-stage detection model, YOLOv8, and experiments are conducted on three complex scene PPU weed datasets. The experimental results show that the CFSC method can improve the model accuracy, loss computation capability and accelerate the gradient descent.

关键词： Visualization Attention mechanisms Accuracy Image color analysis Computational modeling Semantics Object detection

来源：评论

学校读者我要写书评

暂无评论

Gradient-YOLO: Exploring the integration of gradient architecture into the YOLO network

Gradient-YOLO: Exploring the integration of gradient archite...

引用

International Joint Conference on Neural networks (IJCNN)

作者： Gang Li Cheng Zhang Delong Han Letian Gao Mingle Zhou Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center (National Supercomputer Center in Jinan) Qilu University of Technology (Shandong Academy of Sciences) Jinan China Shandong Provincial Key Laboratory of Computer Networks Shandong Fundamental Research Center for Computer Science Jinan China SHANDONG SCICOM Information and Economy Research Institute Co. Ltd Jinan China

ISBN: (数字)9798350359312

ISBN: (纸本)9798350359329

Object detection is an essential task in the field of computer vision. The one-stage object detection model directly completes object detection through a single forward propagation and has fast real-time object detection capabilities, making it widely used—especially the model of the You Only Look Once (YOLO) series. Improving the detection accuracy of the YOLO model has always been a research topic. The gradient architecture cascades feature information extraction and aggregates all features at the end, which can improve the feature fusion ability of the network. Combining the idea of gradient architecture, this paper proposes a YOLO based on gradient architecture: Gradient-YOLO. Specifically, this paper integrates gradient architecture into the backbone, neck, and bottleneck structures in the YOLO network, obtaining gradient backbone, gradient neck, and gradient bottleneck, respectively. By combining gradient architecture, various network parts in Gradient-YOLO can fully aggregate multi-layer features, reduce feature loss, and thus improve detection accuracy. This paper takes the mature YOLOv5 model and the latest YOLOv8 model as the baseline and combines gradient thinking to obtain Gradient-YOLOv5 and GradientYOLOv8. Moreover, conduct experimental testing on the MS COCO dataset. Regarding the mAP@.5 detection indicator, compared to YOLOv5s, Gradient-YOLOv5s increased by 5.07%. Compared to YOLOv8n, Gradient-YOLOv8n has increased by 4.63%. Therefore, the combination of gradient architecture can improve the detection accuracy of YOLO networks.

关键词： YOLO Accuracy Aggregates Computational modeling Computer architecture Feature extraction Real-time systems

来源：评论

学校读者我要写书评

暂无评论

Enhancement for Versatile Video Coding in Vehicular Ad Hoc network Scenarios

Enhancement for Versatile Video Coding in Vehicular Ad Hoc N...

引用

International Symposium on Communications and information Technologies (ISCIT)

作者： Jiacheng Wu Jiaqi Zou Songlin Sun School of Information and Communication Engineering Beijing University of Posts and Telecommunications (BUPT) Beijing China Key Laboratory of Trustworthy Distributed Computing and Service (BUPT) Ministry of Education China National Engineering Laboratory for Mobile Network Security Beijing University of Posts and Telecommunications Beijing China

ISBN: (数字)9798350353952

ISBN: (纸本)9798350353969

Vehicular Ad hoc network (VANET) allows infor-mation exchange between vehicles. In VANET, video is the most recommended medium for transmitting information. However, the characteristics of VANET and the requirements of video content in terms of quality have resulted in various challenges. Besides, the movements of vehicles introduce complex motions in videos, making them more difficult to compress. As a result, it is a challenging task to transmit as less bits of video streams as possible while maintaining their visual quality. Therefore, we analyze Affine Motion Estimation (AME), a new coding tool in the latest generation video coding standard H.266NV C. Subsequently, a fast algorithm is proposed to make it able to describe complex motions such as rotation, zoom, shear, etc but also with low complexity. Experimental results show that the algorithm reduces the encoding complexity of AME by 20.19% and the overall encoding complexity by 3.25% compared to anchor VTM21.0, with eligible coding performance loss under Random Access (RA) configurations.

关键词： Video coding Visualization Motion estimation Vehicular ad hoc networks Streaming media Feature extraction Encoding Complexity theory Streams Standards

来源：评论

学校读者我要写书评

暂无评论

A Multiple-Image Authentication Method Based on Phase-Only Hologram and Logistic Map

SSRN

引用

SSRN 2024年

作者： Liansheng, Sui Zishan, Jiang Haiwei, Lu Zhaolin, Xiao Tianyu, Zeng School of Computer Science and Engineering Xi’an University of Technology Xi’an710048 China Shaanxi Key Laboratory for Network Computing and Security Technology Xi’an710048 China Hebei Normal University Shijiazhuang050024 China Hebei Provincial Key Laboratory of Information Fusion and Intelligent Control Shijiazhuang050024 China

An interesting security method for multiple-image authentication scheme is proposed based on computer-generated holograms and logistic map. First, each original image is encoded as the complex-valued hologram under the point light source model. The resulting hologram is then converted to a phase-only hologram using the Floyd-Steinberg dithering algorithm. Second, each phase-only hologram is randomly sampled by the aid of a binary mask. Through the catenation of all selected pixels, a phase-only pixel sequence is formed. Finally, a non-periodic and non-converging sequence generated with logistic map is used to scramble this sequence. After only preserving the phase data of the scrambled sequence, the real-valued ciphertext carrying the information of all original images is obtained. In the process of authentication, although no valid information can be discerned from noisy reconstructed images at a small sampling rate, the verification of original images can be efficiently accomplished using the nonlinear correlation maps. Besides binary masks, the parameters of logistic map are served as secret keys. Due to their high sensitivity, the security of the proposed method is greatly enhanced. The proposed authentication mechanism has been demonstrated to be effective and robust through experiments. To our best knowledge, it is first time to implement multiple-image authentication using phase-only holograms, which can provide a new perspective for optical information security. © 2024, The Authors. All rights reserved.

关键词： Holograms

来源：评论

学校读者我要写书评

暂无评论

LMS Channel Estimation Algorithm for IM/DD-OFDM/OQAM-PON Systems in 5G-Enabled Industrial Internet

LMS Channel Estimation Algorithm for IM/DD-OFDM/OQAM-PON Sys...

引用

2021 IEEE Globecom Workshops, GC Wkshps 2021

作者： Liang, Siyuan Wang, Xuefen Du, Jianbo Zhao, Feng Cao, Haotong Xi'An University of Posts and Telecommunications Shanxi Key Laboratory of Information Communication Network and Security Xi'an China The Hong Kong Polytechnic University Department of Computing Hong Kong Hong Kong

ISBN: (纸本)9781665423908

Orthogonal frequency division multiplexing/offset quadrature amplitude modulation (OFDM/OQAM) passive optical network (PON) is an attractive technique for 5G-enabled Industrial Internet due to the large bandwidth and ultra-low latency. However, In the OFDM/OQAM-PON system, the intrinsic imaginary interference(IMI) induced by the chromatic dispersion (CD) and polarization mode dispersion (PMD) undermines the system performance. In this paper, we proposed least mean square channel estimation(LMS-CE) algorithm, which not only effectively improves channel estimation performance, but also mitigates the IMI effect. Simulation results show that LMS-CE algorithm exhibits more than a 30% reduction in the bit error rate (BER) than the least squares (LS) algorithm. © 2021 IEEE.

关键词： Orthogonal frequency division multiplexing

来源：评论

学校读者我要写书评

暂无评论

CTI-JE: A Joint Extraction Framework of Entities and Relations in Unstructured Cyber Threat Intelligence

CTI-JE: A Joint Extraction Framework of Entities and Relatio...

引用

International Conference on Computer Supported Cooperative Work in Design

作者： Yang Liu Xiaohui Han Wenbo Zuo Haiqing Lv Jing Guo Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center (National Supercomputer Center in Jinan) Qilu University of Technology (Shandong Academy of Sciences) Jinan China Shandong Provincial Key Laboratory of Computer Networks Shandong Fundamental Research Center for Computer Science Jinan China Quan Cheng Laboratory Jinan China Information Research Institute Qilu University of Technology(Shandong Academy of Sciences) Jinan China

ISBN: (数字)9798350349184

ISBN: (纸本)9798350349191

Advanced Persistent Threat (APT) pose an increasingly serious challenge to the security of businesses and organizations. In order to cope with these threats more effectively, effective utilization of cybers threat intelligence becomes crucial. Cyber Threat Intelligence(CTI) is characterized by fragmentation and voluminous, and information extraction can help cybersecurity researchers extract valuable information from massive cyber threat intelligence and understand the full picture of attack events. We propose a threat intelligence joint extraction model CTI-JE, which models the joint extraction problem as a table-filling task. CTI-JE uses SecBERT to generate embedding representations of words and then learns different representations for NER and RE tasks to avoid feature confusion. We construct a shared feature to enhance the interaction between subtasks, using dilated convolution and channel attention mechanism to extract fine-grained features. Experimental results on a cyber threat intelligence dataset show that our proposed model achieves better performance than existing baseline models.

关键词： Convolution Transforms Organizations Knowledge graphs Feature extraction information retrieval Vectors

来源：评论

学校读者我要写书评

暂无评论

Research on Virtual 3D Remote Sensing Technology of power Grid Station Based on 2D Vision 5

Research on Virtual 3D Remote Sensing Technology of Power Gr...

引用

5th International Conference on information Technologies and Electrical Engineering, ICITEE 2022

作者： Yu, Hai Tang, Shiyang Peng, Lin Yu, Zhen Qian, Kun School of Automation Southeast University Jiangsu Nanjing210096 China Power Grid Digitization Technology Research Institute State Grid Smart Grid Research Institute Jiangsu Nanjing210003 China State Grid Key Laboratory of Information & Network Security Nanjing210003 China

ISBN: (纸本)9781450396806

Aiming at the production safety management and control problems of substations, the digital twin 3D volume of substations is constructed based on 3D twinning technology, and the 2D/3D space fusion positioning perception technology based on existing multi-band surveillance cameras is studied. The automatic safety risk monitoring algorithm of common monitoring equipment, such as the automatic safety risk monitoring algorithm, realizes the high-precision perception analysis of the three-dimensional space of personnel/equipment in the substation, and can be applied to the safety management and control of personnel, equipment and perimeter of the substation, and improves the safety management level of the power grid. © 2022 ACM.

关键词： Risk assessment

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：