检索结果-内蒙古大学图书馆

16th International Conference on Ambient systems, Networks and Technologies Networks, ANT 2025 / 8th International Conference on Emerging Data and Industry 4.0, EDI40 2025

作者： Ismail, Leila Shahin, Nada Tesfaye, Henok Hennebelle, Alain Lab Department of Computer Science and Software Engineering College of Information Technology United Arab Emirates University United Arab Emirates

With the emergence of AI for good, there has been an increasing interest in building computer vision data-driven deep learning inclusive AI solutions. Sign language Recognition (SLR) has gained attention recently. It is an essential component of a sign-to-text translation system to support the deaf and hard-of-hearing population. This paper presents a computer VISIOn data-driven deep learning framework for Sign Language video Recognition (VisoSLR). VisioSLR provides a precise measurement of translating signs for developing an end-to-end computational translation system. Considering the scarcity of sign language datasets, which hinders the development of an accurate recognition model, we evaluate the performance of our framework by fine-tuning the very well-known YOLO models, which are built from a signs-unrelated collection of images and videos, using a small-sized sign language dataset. Gathering a sign language dataset for signs training would involve an enormous amount of time to collect and annotate videos in different environmental setups and multiple signers, in addition to the training time of a model. Numerical evaluations of VisioSLR show that our framework recognizes signs with a mean average precision of 97.4%, 97.1%, and 95.5% and 11, 12, and 12 milliseconds of recognition time on YOLOv8m, YOLOv9m, and YOLOv11m, respectively. © 2025 Elsevier B.V.. All rights reserved.

关键词： Transfer learning

来源：评论

学校读者我要写书评

暂无评论

Distributed Consensus Algorithm and Stability for LTI Multi-Agent systems on Directed Graphs 41

Distributed Consensus Algorithm and Stability for LTI Multi-...

引用

第41届中国控制会议

作者： Yahui Li Simeng Huang Jianyou Huang Mingming Jiang Baoyu Li Jun Zhang China Academy of Launch Vehicle Technology School of System Science and Engineering Sun Yat-Sen University School of Electronic and Information System Jiangsu University

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

This paper focuses on the fully-distributed consensus algorithms for a class of multi-agent systems on directed graphs,where every agent can be described by high-order linear time invariant(LTI) ***,a novel consensus algorithm is proposed for the multi-agent ***,taking use of the complex variable theories of linear multivariable feedback systems,the consensus and stability proof of the closed systems is *** the algorithm and proof,the complex roots are permitted in closed-loop characteristic equation of agents,which relaxes some assumptions commonly considered in the available literatures,such as real ***,the constraint condition for them is given,which is one of the key factors to guarantee the stability of the whole ***,designing and proof of the consensus show that the same in dimension among agents is not necessary at all,which provides another convenience for researching multi-agent *** results are provided to illustrate the effectiveness of the proposed approach.

关键词： Multi-agent Consensus,Directed Graph,Linear Time Invariant(LTI) system,Complex Variable Methods,Multivariable Feedback system

来源：评论

学校读者我要写书评

暂无评论

The Development and Industry Risks of New Energy Vehicles in China

The Development and Industry Risks of New Energy Vehicles in...

引用

2022 International Conference on Statistics, Data science, and Computational Intelligence, CSDSCI 2022

作者： Tang, Xi-Ru Wang, Bin Institute of Urban System Engineering Beijing Academy of Science and Technology Beijing100035 China Key Laboratory of Modern Measurement and Control Technology Ministry of Education Beijing Information Science and Technology University Beijing100192 China

ISBN: (纸本)9781510661325

The development of the new energy automobile industry is an important direction to accelerate the construction of a powerful automobile country, and it is also an effective means to break the constraints of energy and environment, which is of great strategic significance to China. In this article, based on the perspective of the development of the overall new energy vehicle industry, we analyze the market size and development stage of China's new energy vehicle industry, and explore the characteristics of the industry's development. Further, this paper analyzes the industry risks of the future development of new energy vehicles under the background of the imminent withdrawal of government financial subsidies and the transition of the new energy vehicle industry from policy-driven to market-driven, and provides theoretical support for the healthy and sustainable development of Chinese new energy vehicle industry. © 2023 SPIE.

关键词： Automotive industry

来源：评论

学校读者我要写书评

暂无评论

Enhancing building pattern recognition through multi-scale data and knowledge graph:a case study of C-shaped patterns

引用

International Journal of Digital Earth 2023年第1期16卷 3860-3881页

作者： Zhiwei Wei Wenjia Xu Yi Xiao Mi Shu Lu Cheng Yang Wang Chunbo Liu Key Laboratory of Network Information System Technology(NIST) Aerospace Information Research InstituteChinese Academy of SciencesBeijingPeople’s Republic of China The Aerospace Information Research Institute Chinese Academy of SciencesBeijingPeople’s Republic of China School of Information and Communication Engineering Beijing University of Posts and TelecommunicationsBeijingPeople’s Republic of China School of Software Engineering Shenzhen Institute of Information TechnologyShenzhenPeople’s Republic of China Institute of Remote Sensing and GIS Peking UniversityBeijingPeople’s Republic of China School of Geography Science and Geomatics Suzhou University of Science and TechnologySuzhouPeople’s Republic of China

Building pattern recognition is important for understanding urban forms,automating map generalization,and visualizing 3D city ***,current approaches based on object-independent methods have limitations in capturing all visually aware patterns due to the part-based nature of human ***,these approaches also suffer from inefficiencies when applying proximity graph *** address these limitations,we propose a framework that leverages multi-scale data and a knowledge graph,focusing on recognizing C-shaped building *** first employ a specialized knowledge graph to represent the relationships between buildings within and across various ***,we convert the rules for C-shaped pattern recognition and enhancement into query conditions,where the enhancement refers to using patterns recognized at one scale to enhance pattern recognition at other ***,rule-based reasoning is applied within the constructed knowledge graph to recognize and enrich C-shaped building *** verify the effectiveness of our method using multi-scale data with three levels of detail(LODs)collected from AMap,and our method achieves a higher recall rate of 26.4%for LOD1,20.0%for LOD2,and 9.1%for LOD3 compared to existing methods with similar ***,also achieve recognition efficiency improvements of 0.91,1.37,and 9.35 times,respectively.

关键词： Building pattern recognition urban form knowledge graph rule-based reasoning

来源：评论

学校读者我要写书评

暂无评论

Improved Joint Distribution Adaptation for Fault Diagnosis 8th

Improved Joint Distribution Adaptation for Fault Diagnosis

引用

8th International Conference on Data Mining and Big Data, DMBD 2023

作者： Gao, Dali Mao, Xiaobin Sheng, Long Wang, Shuangling Science and Technology on Information System Engineering Laboratory Nanjing210023 China

ISBN: (纸本)9789819708369

In the blast furnace (BF) ironmaking process, it is difficult to obtain labeled fault samples and the probability distribution drifts significantly. Therefore, transfer learning has been introduced to fault diagnosis of BF. Most of the existing transfer learning methods achieve domain adaptation by reducing the marginal and conditional distribution discrepancies, without considering the prior distribution. To address this issue, this paper provides a theoretical derivation of the effect of the prior distribution discrepancies on knowledge transfer, and proposes a new method called Improved Joint Distribution Adaptation (IJDA). The model performs reconstruction of the weighted source data to offset the discrepancies of prior distribution, and extracts domain-invariant features by aligning joint distribution to achieve knowledge transfer. In the transfer BF fault diagnosis experiments, the proposed method achieves promising performance improvement. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Failure analysis

来源：评论

学校读者我要写书评

暂无评论

Scavenger: Better Space-Time Trade-Offs for Key-Value Separated LSM-trees 40

Scavenger: Better Space-Time Trade-Offs for Key-Value Separa...

引用

40th IEEE International Conference on Data engineering, ICDE 2024

作者： Zhang, Jianshun Wang, Fang Qiu, Sheng Wang, Yi Ou, Jiaxin Huang, Junxun Li, Baoquan Fang, Peng Feng, Dan School of Computer Science and Technology Huazhong University of Science and Technology Wuhan National Laboratory for Optoelectronics Key Laboratory of Information Storage System Engineering Research Center of Data Storage Systems and Technology Ministry of Education of China China Shenzhen Huazhong University of Science and Technology Research Institute China Bytefrance Inc.

ISBN: (纸本)9798350317152

Key-Value Stores (KVS) implemented with log-structured merge-tree (LSM-tree) have gained widespread ac-ceptance in storage systems. Nonetheless, a significant challenge arises in the form of high write amplification due to the compaction process. While KV-separated LSM-trees successfully tackle this issue, they also bring about substantial space am-plification problems, a concern that cannot be overlooked in cost-sensitive scenarios. Garbage collection (GC) holds significant promise for space amplification reduction, yet existing GC strategies often fall short in optimization performance, lacking thorough consideration of workload characteristics. Additionally, current KV-separated LSM-trees also ignore the adverse effect of the space amplification in the index LSM-tree. In this paper, we systematically analyze the sources of space amplification of KV-separated LSM-trees and introduce Scavenger, which achieves a better trade-off between performance and space amplification. Scavenger initially proposes an I/O-efficient garbage collection scheme to reduce I/O overhead and incorporates a space-aware compaction strategy based on compensated size to minimize the space amplification of index LSM-trees. Extensive experiments show that Scavenger significantly improves write performance and achieves lower space amplification than other KV-separated LSM-trees (including BlobDB, Titan, and TerarkDB). © 2024 IEEE.

关键词： Economic and social effects

来源：评论

学校读者我要写书评

暂无评论

The Power of Bamboo: On the Post-Compromise Security for Searchable Symmetric Encryption 30

The Power of Bamboo: On the Post-Compromise Security for Sea...

引用

30th Annual Network and Distributed system Security Symposium, NDSS 2023

作者： Chen, Tianyang Xu, Peng Picek, Stjepan Luo, Bo Susilo, Willy Jin, Hai Liang, Kaitai National Engineering Research Center for Big Data Technology and System Services Computing Technology and System Lab China Hubei Key Laboratory of Distributed System Security Hubei Engineering Research Center on Big Data Security School of Cyber Science and Engineering China Cluster and Grid Computing Lab School of Computer Science and Technology China Huazhong University of Science and Technology Wuhan430074 China Digital Security Group Radboud University Nijmegen Netherlands Department of EECS Institute of Information Sciences The University of Kansas LawrenceKS United States Institute of Cybersecurity and Cryptology School of Computing and Information Technology University of Wollongong WollongongNSW2522 Australia Faculty of Electrical Engineering Mathematics and Computer Science Delft University of Technology Delft2628 CD Netherlands

ISBN: (纸本)1891562835

Dynamic searchable symmetric encryption (DSSE) enables users to delegate the keyword search over dynamically updated encrypted databases to an honest-but-curious server without losing keyword privacy. This paper studies a new and practical security risk to DSSE, namely, secret key compromise (e.g., a user’s secret key is leaked or stolen), which threatens all the security guarantees offered by existing DSSE schemes. To address this open problem, we introduce the notion of searchable encryption with key-update (SEKU) that provides users with the option of non-interactive key updates. We further define the notion of post-compromise secure with respect to leakage functions to study whether DSSE schemes can still provide data security after the client’s secret key is compromised. We demonstrate that post-compromise security is achievable with a proposed protocol called "Bamboo". Interestingly, the leakage functions of Bamboo satisfy the requirements for both forward and backward security. We conduct a performance evaluation of Bamboo using a real-world dataset and compare its runtime efficiency with the existing forward-and-backward secure DSSE schemes. The result shows that Bamboo provides strong security with better or comparable performance. © 2023 30th Annual Network and Distributed system Security Symposium, NDSS 2023. All Rights Reserved.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Enhanced Object Detection and Classification via Multi-Method Fusion

引用

Computers, Materials & Continua 2024年第5期79卷 3315-3331页

作者： Muhammad Waqas Ahmed Nouf Abdullah Almujally Abdulwahab Alazeb Asaad Algarni Jeongmin Park Department of Computer Science Air UniversityIslamabad44000Pakistan Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Science College of Computer Science and Information SystemNajran UniversityNajran55461Saudi Arabia Department of Computer Sciences Faculty of Computing and Information TechnologyNorthern Border UniversityRafha91911Saudi Arabia Department of Computer Engineering Tech University of Korea237 Sangidaehak-roSiheung-siGyeonggi-do15073South Korea

Advances in machine vision systems have revolutionized applications such as autonomous driving,robotic navigation,and augmented *** substantial progress,challenges persist,including dynamic backgrounds,occlusion,and limited labeled *** address these challenges,we introduce a comprehensive methodology toenhance image classification and object detection *** proposed approach involves the integration ofmultiple methods in a complementary *** process commences with the application of Gaussian filters tomitigate the impact of noise *** images are then processed for segmentation using Fuzzy C-Meanssegmentation in parallel with saliency mapping techniques to find the most prominent *** Binary RobustIndependent Elementary Features(BRIEF)characteristics are then extracted fromdata derived fromsaliency mapsand segmented *** precise object separation,Oriented FAST and Rotated BRIEF(ORB)algorithms *** Algorithms(GAs)are used to optimize Random Forest classifier parameters which lead toimproved *** method stands out due to its comprehensive approach,adeptly addressing challengessuch as changing backdrops,occlusion,and limited labeled data concurrently.A significant enhancement hasbeen achieved by integrating Genetic Algorithms(GAs)to precisely optimize *** minor adjustmentnot only boosts the uniqueness of our system but also amplifies its overall *** proposed methodologyhas demonstrated notable classification accuracies of 90.9%and 89.0%on the challenging Corel-1k and MSRCdatasets,***,detection accuracies of 87.2%and 86.6%have been *** ourmethod performed well in both datasets it may face difficulties in real-world data especially where datasets havehighly complex *** these limitations,GAintegration for parameter optimization shows a notablestrength in enhancing the overall adaptability and performance of our system.

关键词： BRIEF features saliency map fuzzy c-means object detection object recognition

来源：评论

学校读者我要写书评

暂无评论

Psychological Counseling with Integration of Knowledge Graph and Multi-Agent Collaboration

引用

Journal of Shanghai Jiaotong University (science) 2025年 1-13页

作者： Liu, Xi Zheng, Xiaohu Cui, Weiwei College of Information Science and Technology Donghua University Shanghai201620 China Institute of artificial Intelligence Donghua University Shanghai201620 China Shanghai Engineering Center of Industrial Big Data and Intelligent System Shanghai201620 China Management College Wuzhou University Guangxi Wuzhou543003 China

Applying large language models (LLMs) to psychological counseling can reduce costs and lower barriers to access. However, issues inherent to LLMs, such as output hallucinations, knowledge lags, and response biases, limit the quality of counseling services. To address these challenges, we propose a psychological counseling method that integrates a knowledge graph (KG) and multi-agent collaboration (MAC). First, we design an ontology model and use an improved convolution residual network (CRN) to extract relational triples for constructing a psychological medicine KG. Second, we perform low-rank adaptation (LoRA) on Qwen1.5-7B-chat using the Text2Cypher training set. Finally, we design MAC prompts based on the characteristics of the retrieval-based question-answering (QA) process to facilitate the collaborative implementation of psychological medicine knowledge QA and updates. The experiments showed that the improved CRN achieved an extraction accuracy of 80%. The mean squared error of the general-domain capability of the LLM before and after LoRA was only 0.738, with a Text2Cypher score of 99.8 after LoRA. The results generated after prompting received a 70.44% approval rate compared to other methods. Thus, the proposed method can effectively enhance the intelligence, accuracy, and controllability of psychological counseling. © Shanghai Jiao Tong University 2024.

关键词： Knowledge graph

来源：评论

学校读者我要写书评

暂无评论

Augmented Genetic Algorithm for Decoupling Capacitor Optimization in Power Distribution Network Design Through Improved Population Generation

IEEE Transactions on Signal and Power Integrity

引用

IEEE Transactions on Signal and Power Integrity 2024年 3卷 186-198页

作者： Juang, Jack Zhang, Ling Manoharan, Haran De Paulis, Francesco Hwang, Chulsoon Missouri University of Science and Technology Electromagnetic Compatibility Lab RollaMO65401 United States Zhejiang University College of Information Science and Electronic Engineering Hangzhou310027 China University of L'Aquila UAq Electromagnetic Compatibility Lab L'Aquila67100 Italy

In power distribution network designs, a large number of decoupling capacitors (decaps) may be needed to satisfy target impedance limits. Many algorithms have been proposed and implemented for finding the optimal decap placement, including genetic algorithms (GA), and machine learning methods. In this work, an improved GA is proposed for finding the decap placement pattern that can satisfy a target impedance using the minimum number of decaps. The distribution of capacitors expected to appear in the global minimum solution is first predicted by determining how effective each decap type is toward satisfying certain critical impedance points. This estimation is used to inform the generation of initial solutions in order to put the initial search space nearer the global minimum and ensure certain solution characteristics appear. GA search using this improved population generation is found to be an improvement over a Canonical GA implementation, by finding solutions where the latter could not, or finding a solution using fewer decaps. © 2024 The Authors.

关键词： Capacitor bank

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：