检索结果-内蒙古大学图书馆

A CPK-Based Identity Authentication Scheme for IoT

computer systems science & Engineering 2022年第3期40卷 1217-1231页

作者： Mingming Zhang Jiaming Mao Yuanyuan Ma Liangjie Xu Chuanjun Wang Ran Zhao Zhihao Li Lu Chen Wenbing Zhao State Grid Jiangsu Electric Power Co. Ltd.Information&Telecommunication BranchNanjing210008China State Grid Key Laboratory of Information&Network Security Institute of Information and CommunicationGlobal Energy Interconnection Research InstituteNanjing210003China Anhui Jiyuan Software Co.Ltd SGITGHefei230088China Engineering Research Center of Post Big Data Technology and Application of Jiangsu Province Research and Development Center of Post Industry Technology of the State Posts Bureau(Internet of Things Technology)Engineering Research Center of Broadband Wireless Communication Technology of the Ministry of EducationNanjing University of Posts and TelecommunicationsNanjing210003China Department of Electrical Engineering and Computer Science Cleveland State UniversityCleveland44115USA

As the power Internet of Things(IoT)enters the security construction stage,the massive use of perception layer devices urgently requires an identity authentication scheme that considers both security and *** existing public key infrastructure(PKI)-based security authentication scheme is currently difficult to apply in many terminals in *** key distribution and management costs are high,which hinders the development of power IoT security *** Public key(CPK)technology uses a small number of seeds to generate unlimited public *** is very suitable for identity authentication in the power Internet of *** this paper,we propose a novel identity authentication scheme for power *** scheme combines the physical unclonable function(PUF)with improved CPK technology to achieve mutual identity authentication between power IoT terminals and *** proposed scheme does not require third-party authentication and improves the security of identity authentication for power ***,the scheme reduces the resource consumption of power IoT *** improved CPK algorithm solves the key collision problem,and the third party only needs to save the private key and the public key *** results show that the amount of storage resources occupied in our scheme is *** proposed scheme is more suitable for the power IoT.

关键词： Power Internet of Things terminal equipment identity authentication CPK PUF

来源：评论

学校读者我要写书评

暂无评论

Mel-S3R: Combining Mel-spectrogram and self-supervised speech representation with VQ-VAE for any-to-any voice conversion

引用

Speech Communication 2023年 151卷 52-63页

作者： Jichen Yang Yi Zhou Hao Huang School of Cyber Security Guangdong Polytechnic Normal University Guangzhou China School of Electronics and Information Engineering South China Normal University Foshan China Department of Electrical and Computer Engineering National University of Singapore Singapore School of Information Science and Engineering Xinjiang University and Xinjiang Provincial Key Laboratory of Multilingual Information Technology Urumqi China

The self-supervised speech representation (S3R) has succeeded in many downstream tasks, such as speaker recognition and voice conversion thanks to its high-level information. Voice conversion (VC) is a task to convert the source speech into a target speaker’s voice. Though S3R features effectively encode content and speaker information, spectral features contain low-level acoustic information that is complementary to the S3R. As a result, solely relying on the S3R features for VC may not be optimal. In order to seek speech representation carrying both high-level learned information and low-level spectral details for VC, we proposed a three-level attention to combine Mel-spectrogram (Mel) and S3R, denoted as Mel-S3R. In particular, S3R features are high-level learned representations extracted by a pre-trained network with self-supervised learning. Whereas Mel is the spectral feature representing the acoustic information. Then the proposed Mel-S3R is used as the input of any-to-any VQ-VAE-based VC and the experiments are performed as a downstream task. Objective metrics and subjective listening tests have demonstrated that the proposed Mel-S3R speech representation facilitates the VC framework to achieve robust performance in terms of both speech quality and speaker similarity.

关键词： Self-supervised learning Voice conversion (VC) Self-attention VQ-VAE

来源：评论

学校读者我要写书评

暂无评论

High-Resolution Polymerization Network For Multi-Person Pose Estimation 11

High-Resolution Polymerization Network For Multi-Person Pose...

引用

11th International Conference on information technology in Medicine and Education, ITME 2021

作者： Bai, Yu-Fei Zhang, Hong-Bo Lei, Qing Du, Ji-Xiang Huaqiao University Department of Computer Science and Technology Xiamen China Huaqiao University Fujian Key Laboratory of Big Data Intelligence and Security Xiamen China

ISBN: (纸本)9781665406796

In this paper, we propose a High-Resolution Polymerization Network (HPN) for Multi-Person Pose Estimation. First, we use the separate channel convolution module High-Resolution Polymerization Block(HPB) in HPN to optimize the input features. The HPB module can segment local features on the channel multiple times and fuse different scales, learn more refined features to extract reliable keypoint coordinate representations. In addition, we observe that there is only a simple vertical identity mapping relationship among the features in the network structure. In order to further utilize the high-resolution features that contain rich spatial information, we extend the horizontal mapping of network characteristics, use parallel convolutional to link high and low resolution features across scales, enhance feature information by maintaining high-resolution representation, to achieve the purpose of precise keypoint positioning. Our method is evaluated on the COCO data set, and the current method has reached an advanced level. © 2021 IEEE.

关键词： Convolution

来源：评论

学校读者我要写书评

暂无评论

Hybrid Data-Free Knowledge Distillation 39

Hybrid Data-Free Knowledge Distillation

引用

39th Annual AAAI Conference on Artificial Intelligence, AAAI 2025

作者： Tang, Jialiang Chen, Shuo Gong, Chen School of Computer Science and Engineering Nanjing University of Science and Technology China Key Laboratory of Intelligent Perception and Systems for High-Dimensional Information of Ministry of Education China Jiangsu Key Laboratory of Image and Video Understanding for Social Security China Center for Advanced Intelligence Project RIKEN Japan Department of Automation Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University China

ISBN: (纸本)157735897X

Data-free knowledge distillation aims to learn a compact student network from a pre-trained large teacher network without using the original training data of the teacher network. Existing collection-based and generation-based methods train student networks by collecting massive real examples and generating synthetic examples, respectively. However, they inevitably become weak in practical scenarios due to the difficulties in gathering or emulating sufficient real-world data. To solve this problem, we propose a novel method called Hybrid Data-Free Distillation (HiDFD), which leverages only a small amount of collected data as well as generates sufficient examples for training student networks. Our HiDFD comprises two primary modules, i.e., the teacher-guided generation and student distillation. The teacher-guided generation module guides a Generative Adversarial Network (GAN) by the teacher network to produce high-quality synthetic examples from very few real-world collected examples. Specifically, we design a feature integration mechanism to prevent the GAN from overfitting and facilitate the reliable representation learning from the teacher network. Meanwhile, we drive a category frequency smoothing technique via the teacher network to balance the generative training of each category. In the student distillation module, we explore a data inflation strategy to properly utilize a blend of real and synthetic data to train the student network via a classifier-sharing-based feature alignment technique. Intensive experiments across multiple benchmarks demonstrate that our HiDFD can achieve state-of-the-art performance using 120 times less collected data than existing methods. Copyright © 2025, Association for the Advancement of Artificia Intelligence (***). All rights reserved.

关键词： Personnel training

来源：评论

学校读者我要写书评

暂无评论

Skeleton Based Action Quality Assessment of Figure Skating Videos 11

Skeleton Based Action Quality Assessment of Figure Skating V...

引用

11th International Conference on information technology in Medicine and Education, ITME 2021

作者： Li, Hui-Ying Lei, Qing Zhang, Hong-Bo Du, Ji-Xiang Huaqiao University Department of Computer Science and Technology Xiamen China Huaqiao University Fujian Key Laboratory of Big Data Intelligence and Security Xiamen China

ISBN: (纸本)9781665406796

Action quality assessment(AQA) aims at achieving automatic evaluation the performance of human actions in video. Compared with action recognition problem, AQA focuses more on subtle differences both in spatial and temporal dimensions during the whole executing process of actions. However, most existing AQA methods tried to extract features directly from RGB videos through a 3D ConvNets, which makes the features mixed with useless scene information. To overcome this problem, We propose a deep pose feature learning AQA method that captured detailed and meaningful representations for skeleton information to discover the subtle motion difference of AQA problem. We first apply pose estimation method to obtain human skeleton data from RGB videos. Then a spatio-temporal graph convolutional network (ST-GCN) is employed to extract the dynamic changes of skeleton data and obtain the representative pose features. Finally, a regressor composed of three fully connected layers is developed to reduce the dimension of the obtained pose features and predict the final score. Experiments on MIT figure skating dataset have been extensively conducted, and the results demonstrate that the proposed method has achieved improvements that outperformed current state-of-the-art methods. © 2021 IEEE.

关键词： Musculoskeletal system

来源：评论

学校读者我要写书评

暂无评论

Intelligent evaluation system for new energy vehicles based on sentiment analysis: An MG-PL-3WD method

引用

Engineering Applications of Artificial Intelligence 2024年 133卷

作者： Zhang, Chao Wen, Qifei Li, Deyu Sangaiah, Arun Kumar Lin, Mingwei School of Computer and Information Technology Shanxi University Taiyuan030006 China Key Laboratory of Computational Intelligence and Chinese Information Processing of Ministry of Education Shanxi University Taiyuan030006 China International Graduate Institute of Artificial Intelligence National Yunlin University of Science and Technology Yunlin64002 Taiwan Department of Electrical and Computer Engineering Lebanese American University Byblos1102-2801 Lebanon College of Computer and Cyber Security Fujian Normal University Fuzhou350117 China

As a critical strategic tool within the framework of the digital economy (DE), artificial intelligence (AI) plays a crucial role in realizing an AI-assisted economy. This novel paradigm has gained widespread acceptance from governments globally, positioning itself as a cornerstone in the practical implementation of the DE. The increasing reliance on digital means for economic transformation, the treatment of data as a critical resource, and the integration of information technologies highlight the synergy between AI and the DE. Against this backdrop, online reviews and SA play a pivotal role, offering rich data streams continually emerging on various platforms. Therefore, this article utilizes a probabilistic linguistic term set (PLTS) to establish a multi-granularity probabilistic linguistic (MG-PL) information system. This approach, through sentiment analysis (SA), enables quantitative analysis of user emotional expressions. The integration of these technological aspects holds the promise of enhancing decision-making processes, facilitating the intellectualization of economic activities, and addressing existing challenges in the application of AI within the DE domain. Initially, SA is conducted on text-based online comment data, forming a probabilistic linguistic incomplete information system. The maximum similarity method is employed to establish a probabilistic linguistic complete information system. Subsequently, an adjustable MG-PL decision-theoretic rough set (DTRS) is developed, followed by the establishment of a three-way group decision model using three-way decisions (3WD) and a directed graph. The model's applicability, stability, and feasibility are demonstrated via a case study centered on the acquisition of new energy vehicles (NEVs). © 2024 Elsevier Ltd

关键词： Sentiment analysis

来源：评论

学校读者我要写书评

暂无评论

NavG: Risk-Aware Navigation in Crowded Environments Based on Reinforcement Learning with Guidance Points

arXiv

引用

arXiv 2025年

作者： Zhang, Qianyi Luo, Wentao Liu, Boyi Zhang, Ziyang Wang, Yaoyuan Liu, Jingtai Institute of Robotics and Automatic Information System Nankai University Tianjin Key Laboratory of Intelligent Robotics Tianjin China Advanced Computing and Storage Lab Huawei 2012 Lab China Department of Electronic and Computer Engineering The Kong Kong University of Science and Technology Hong Kong

Motion planning in navigation systems is highly susceptible to upstream perceptual errors, particularly in human detection and tracking. To mitigate this issue, the concept of guidance points—a novel directional cue within a reinforcement learning-based framework—is introduced. A structured method for identifying guidance points is developed, consisting of obstacle boundary extraction, potential guidance point detection, and redundancy elimination. To integrate guidance points into the navigation pipeline, a perception-to-planning mapping strategy is proposed, unifying guidance points with other perceptual inputs and enabling the RL agent to effectively leverage the complementary relationships among raw laser data, human detection and tracking, and guidance points. Qualitative and quantitative simulations demonstrate that the proposed approach achieves the highest success rate and near-optimal travel times, greatly improving both safety and efficiency. Furthermore, real-world experiments in dynamic corridors and lobbies validate the robot’s ability to confidently navigate around obstacles and robustly avoid pedestrians. © 2025, CC BY.

关键词： Travel time

来源：评论

学校读者我要写书评

暂无评论

A Multi-Stage Vision Transformer for Fine-grained Image Classification 11

A Multi-Stage Vision Transformer for Fine-grained Image Clas...

引用

11th International Conference on information technology in Medicine and Education, ITME 2021

作者： Huang, Zheng Du, Ji-Xiang Zhang, Hong-Bo Huaqiao University Department of Computer Science and Technology Xiamen China Fujian Key Laboratory of Big Data Intelligence and Security Huaqiao University Xiamen China

ISBN: (纸本)9781665406796

Different from general image classification, Fine-grained visual classification(FGVC) aims at recognizing the subclass of an object. This task is challenging due to the differences between subcategories that might be very small. At present, Vision Transformer(ViT) achieved huge success in traditional classification tasks benefited from its innate attention mechanism. Recent works extend the vision trans-former into the FGVC task and achieve state-of-the-art performance. However, those transformer-based structures inevitably harm the discriminative regions while also requiring a high computational cost. To address these problems, we propose a pooling-based vision transformer model with overlapping patches(OP-ViT), which inserts the pooling layer into a transformer encoder to form a multi-stage hierarchical structure. In particular, the overlapping patches scheme can preserve the informational region effectively. We evaluate the model on two fine-grained mushroom datasets. The experimental results show that the proposed model achieves competitive performance with fewer parameters and computational overhead. © 2021 IEEE.

关键词： Image classification

来源：评论

学校读者我要写书评

暂无评论

AsyncSC: An Asynchronous Sidechain for Multi-Domain Data Exchange in Internet of Things

arXiv

引用

arXiv 2024年

作者： Yang, Lingxiao Dong, Xuewen Wan, Zhiguo Gao, Sheng Tong, Wei Lu, Di Shen, Yulong Du, Xiaojiang The School of Computer Science and Technology Xidian University The Engineering Research Center of Blockchain Technology Application and Evaluation Ministry of Education China The Shaanxi Key Laboratory of Blockchain and Secure Computing Xi'An710071 China The Zhejiang Lab Hangzhou311121 China The School of Information Central University of Finance and Economics Beijing100081 China The School of Information Science and Engineering Zhejiang Sci-Tech University Hangzhou310018 China The School of Computer Science and Technology Xidian University China The Shaanxi Key Laboratory of Network and System Security Xi'An710071 China The School of Engineering and Science Stevens Institute of Technology Hoboken07030 United States

Sidechain techniques improve blockchain scalability and interoperability, providing decentralized exchange and cross-chain collaboration solutions for Internet of Things (IoT) data across various domains. However, current state-of-the-art (SOTA) schemes for IoT multi-domain data exchange are constrained by the need for synchronous networks, hindering efficient cross-chain interactions in discontinuous networks and leading to suboptimal data exchange. In this paper, we propose AsyncSC, a novel asynchronous sidechain construction. It employs a committee to provide Cross-Blockchain as a Service (C-BaaS) for data exchange in multi-domain IoT. To fulfill the need for asynchronous and efficient data exchange, we combine the ideas of aggregate signatures and verifiable delay functions to devise a novel cryptographic primitive called delayed aggregate signature (DAS), which constructs asynchronous cross-chain proofs (ACPs) that ensure the security of cross-chain interactions. To ensure the consistency of asynchronous transactions, we propose a multilevel buffered transaction pool that guarantees the transaction sequencing. We analyze and prove the security of AsyncSC, simulate an asynchronous communication environment, and conduct a comprehensive evaluation. The results show that AsyncSC outperforms SOTA schemes, improving throughput by an average of 1.21 to 3.96 times, reducing transaction latency by 59.76% to 83.61%, and maintaining comparable resource overhead. Copyright © 2024, The Authors. All rights reserved.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Text information Mining in Cyberspace: An information Extraction Method Based on T5 and keyBERT

Text Information Mining in Cyberspace: An Information Extrac...

引用

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

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：