检索结果-内蒙古大学图书馆

EZchain: A Secure Scalable Blockchain Protocol via Passive Sharding

IEEE Transactions on Dependable and Secure Computing 2025年第3期22卷 2891-2908页

作者： Yang, Wei Chen, Weilin Xue, Lide Zou, Wenjie Huang, Liusheng University of Science and Technology of China School of Computer Science and Technology Hefei230027 China University of Science and Technology of China Suzhou Institute for Advanced Research Suzhou215123 China University of Science and Technology of China Hefei National Laboratory Hefei230088 China

Recently, many sharding blockchain protocols have sacrificed some important attributes to improve scalability, and this makes them complicated and insecure. Moreover, achieving a constant (rather than linear) Communication Cost Per Transaction (CCPT) is still a challenge for many sharding protocols. Motivated by this, we present EZchain, a scalable blockchain protocol via "passive sharding" with proven validity and security. We redesign the Value-Centric Blockchains (VCB) framework to achieve the passive sharding that helps EZchain reach higher security than traditional sharding protocols. With fixed initialization parameters, the expected value of EZchain's communication cost reaches a constant level, and it is independent of the network's size. Moreover, the EZchain node's storage cost without beacon chains also approaches a constant and does not change with the increase in the network's size and transactions. Cross-shard transactions, network sharding algorithm, and anti-Sybil attack verification are no longer needed in passive sharding, thus EZchain is very concise and efficient. Our experiment uses a lightweight EZchain prototype and extends the experimental network size up to 100,000 nodes. The evaluation results show that EZchain satisfies all our analyses of its performance (the constant communication and non-beacon storage cost) in large networks. In addition, the comparison experiment shows that ezchain has obvious advantages over the previous protocols in long-term operation and large network environments. © 2004-2012 IEEE.

关键词： Blockchain

来源：评论

学校读者我要写书评

暂无评论

A Survey of the Application of Neural Networks to Event Extraction

引用

Tsinghua science and technology 2025年第2期30卷 748-768页

作者： Jianye Xie Yulan Zhang Huaizhen Kou Xiaoran Zhao Zhikang Feng Lekang Song Weiyi Zhong College of Computer Science and Technology China University of Petroleum(East China)Qingdao 266000China Shandong Provincial University Laboratory for Protected Horticulture Weifang University of Science and TechnologyWeifang 261000China School of Computer Science and Engineering Nanjing University of Science and TechnologyNanjing 210000China School of Computer Science Qufu Normal UniversityRizhao 276800China

Event extraction is an important part of natural language information extraction,and it’s widely employed in other natural language processing tasks including question answering and machine reading ***,there is a lack of recent comprehensive survey papers on event *** the past few years,numerous high-quality and innovative event extraction methods have been proposed,making it necessary to consolidate these new developments with previous work in order to provide a clear overview for researchers and serve as a reference for future *** addition,event detection is a fundamental sub-task in event extraction,previous survey papers have often overlooked the related work on event ***,this paper aims to bridge these gaps by presenting a comprehensive survey of event extraction,including recent advancements and an analysis of previous research on event *** resources for event extraction are first introduced in this research,and then the numerous neural network models currently employed in event extraction tasks are divided into four types:word sequence-based methods,graph-based neural network methods,external knowledge-based approaches,and prompt-based *** compare and contrast them in depth,pointing out the flaws and difficulties with existing ***,we discuss the future of event extraction development.

关键词： event extraction natural language processing event extraction methods graph neural network prompt-based learning

来源：评论

学校读者我要写书评

暂无评论

Reduced graphene oxide-induced in-situ uniform growth of hydrated WO_(3) film for enhanced electrochromic performance

引用

Nano Research 2025年第4期18卷 569-577页

作者： Rui Fang Yang Liu Chunyu Shi Huihui Jin Zibo Chen Haohao Sun Ben Lv Daping He Xusheng Zheng Yuli Xiong State Key Laboratory of Advanced Technology for Materials Synthesis and Processing School of Materials Science and EngineeringWuhan University of TechnologyWuhan 430070China School of Science Wuhan University of TechnologyWuhan 430070China National Synchrotron Radiation Laboratory University of Science and Technology of ChinaHefei 230029China Sanya Science and Education Innovation Park of Wuhan University of Technology Sanya 572000China School of Materials Science and Engineering Wuhan University of TechnologyWuhan 430070China

WO_(3)-graphene electrochromic materials are widely used in electrochromic devices including smart windows and electronic displays,due to their ability to adjust optical transmittance in the visible and near-infrared ranges under low electrode ***,the uniformity of the film remains a challenge for the widely used physical mixing-coating *** this study,we present a two-dimensional material-assisted synthesis of a porous hydrated WO_(3) film(WH-rGO)based on reduced graphene oxide(rGO)nanosheets and WO_(3)(rGO-WO_(3))seed layer via a hydrothermal *** incorporation of rGO not only promotes the uniform growth of hydrated WO_(3) film,enhancing ion transport but also introduces oxygen vacancies,creating an efficient conduction pathway for charge *** resulting WH-rGO film exhibits impressive performance,achieving 71% optical modulation at 700 nm,with bleaching and coloring times of 4.2 and 1.0 *** coloration efficiency is calculated at 156.11 cm^(2)·C^(-1),and the optical modulation is maintained at 93% of the initial optical modulation after 1000 cycles applied in the +1.0 and -1.1 V potential *** work offers new insights into the role of oxygen vacancies in enhancing the electrochromic properties of hydrated WO_(3) films through the addition of *** also provides a promising approach for the synthesis of electrochromic materials,facilitating their application in smart window technologies.

关键词： electrochromic film hydrated tungsten oxide reduced graphene oxide oxygen vacancy

来源：评论

学校读者我要写书评

暂无评论

Deep learning-based software engineering: progress,challenges, and opportunities

引用

science china(Information sciences) 2025年第1期68卷 57-144页

作者： Xiangping CHEN Xing HU Yuan HUANG He JIANG Weixing JI Yanjie JIANG Yanyan JIANG Bo LIU Hui LIU Xiaochen LI Xiaoli LIAN Guozhu MENG Xin PENG Hailong SUN Lin SHI Bo WANG Chong WANG Jiayi WANG Tiantian WANG Jifeng XUAN Xin XIA Yibiao YANG Yixin YANG Li ZHANG Yuming ZHOU Lu ZHANG School of Journalism and Communication Sun Yat-sen University School of Software Technology Zhejiang University School of Software Engineering Sun Yat-sen University School of Software Dalian University of Technology School of Computer Science and Technology Beijing Institute of Technology Key Laboratory of High Confidence Software Technologies (Peking University) Ministry of EducationSchool of Computer Science Peking University State Key Laboratory for Novel Software Technology Nanjing University School of Computer Science and Engineering Beihang University Institute of Information Engineering Chinese Academy of Sciences School of Computer Science Fudan University State Key Laboratory of Complex & Critical Software Environment (CCSE) School of Software Beihang University School of Computer and Information Technology Beijing Jiaotong University School of Computer Science and Technology Harbin Institute of Technology School of Computer Science Wuhan University Huawei Technologies

Researchers have recently achieved significant advances in deep learning techniques, which in turn has substantially advanced other research disciplines, such as natural language processing, image processing, speech recognition, and software engineering. Various deep learning techniques have been successfully employed to facilitate software engineering tasks, including code generation, software refactoring, and fault localization. Many studies have also been presented in top conferences and journals, demonstrating the applications of deep learning techniques in resolving various software engineering tasks. However,although several surveys have provided overall pictures of the application of deep learning techniques in software engineering,they focus more on learning techniques, that is, what kind of deep learning techniques are employed and how deep models are trained or fine-tuned for software engineering tasks. We still lack surveys explaining the advances of subareas in software engineering driven by deep learning techniques, as well as challenges and opportunities in each subarea. To this end, in this study, we present the first task-oriented survey on deep learning-based software engineering. It covers twelve major software engineering subareas significantly impacted by deep learning techniques. Such subareas spread out through the whole lifecycle of software development and maintenance, including requirements engineering, software development, testing, maintenance, and developer collaboration. As we believe that deep learning may provide an opportunity to revolutionize the whole discipline of software engineering, providing one survey covering as many subareas as possible in software engineering can help future research push forward the frontier of deep learning-based software engineering more systematically. For each of the selected subareas,we highlight the major advances achieved by applying deep learning techniques with pointers to the available datasets i

关键词： deep learning software engineering software benchmark software artifact representation survey

来源：评论

学校读者我要写书评

暂无评论

Unique composite architecture of phosphor-in-glass film coated on different heat-conducting substrates for high-brightness laser lighting

引用

Journal of Advanced Ceramics 2025年第2期14卷 151-158页

作者： Xin Liu Mingxiang Chen Jiuzhou Zhao Hongjin Zhang Yang Peng Qing Wang State Key Laboratory of Intelligent Manufacturing Equipment and Technology School of Mechanical Science and EngineeringHuazhong University of Science and TechnologyWuhan 430074China School of Aerospace Engineering Huazhong University of Science and TechnologyWuhan 430074China School of Energy and Power Engineering Huazhong University of Science and TechnologyWuhan 430074China

In the development of static luminescent materials with remarkable optical-thermal performance and low cost, next-generation high-brightness laser lighting faces a key challenge. Herein, a unique composite architecture of Y3Al5O_(12):Ce^(3+) (YAG) phosphor-in-glass film coated on different heat-conducting substrates (PiGF@HCSs), i.e., PiGF@sapphire, PiGF@Al_(2)O_(3), PiGF@AlN, and PiGF@BN–AlN composites, was designed and prepared by a simple film printing and low-temperature sintering technology. The heat-conducting substrates significantly affect the luminescence saturation and phosphor conversion of PiGF@HCSs, allowing substrates with higher thermal conductivity (TC) to have a higher laser power density (LPD) and higher reflectivity to enable higher luminous efficacy (LE). As a consequence, PiGF@sapphire realizes a luminous flux (LF) of 2076 lm@12 W/mm^(2), which is higher than those of PiGF@Al_(2)O_(3) (1890 lm@15 W/mm^(2)) and PiGF@AlN (1915 lm@24 W/mm^(2)), whilePiGF@BN–AlN enables a maximum LF of 3058 lm@21 W/mm^(2). Furthermore, the LE of PiGF@BN–AlN reaches 194 lm/W, which is 1.6 times that of PiGF@AlN, while those of PiGF@sapphire and PiGF@Al_(2)O_(3) are 192 and 150 lm/W, respectively. The working temperature of PiGF@AlN is only 93.3℃ under LPD of 9 W/mm^(2), while those of PiGF@sapphire, PiGF@Al_(2)O_(3), and PiGF@BN–AlN increase to 193.8, 133.6, and 117℃, respectively. These findings provide guidance for commercial applications of PiGF@HCS converters in high-brightness laser lighting and displays.

关键词： luminescent materials phosphor-in-glass film(PiGF) heat-conducting substrate(HCS) laser lighting optical-thermal performances

来源：评论

学校读者我要写书评

暂无评论

Knowledge Probabilization in Ensemble Distillation: Improving Accuracy and Uncertainty Quantification for Object Detectors

IEEE Transactions on Artificial Intelligence

引用

IEEE Transactions on Artificial Intelligence 2025年第1期6卷 221-233页

作者： Yang, Yang Wang, Chao Gong, Lei Wu, Min Chen, Zhenghua Li, Xiang Chen, Xianglan Zhou, Xuehai University of Science and Technology of China School of Computer Science and Technology Hefei230026 China 138632 Singapore East China Normal University School of Data Science and Engineering Shanghai200062 China

Ensemble object detectors have demonstrated remarkable effectiveness in enhancing prediction accuracy and uncertainty quantification. However, their widespread adoption is hindered by significant computational and storage demands, limiting their feasibility in resource-constrained settings. To overcome this, researchers have focused on distilling the knowledge from ensemble object detectors into a single model. In this article, we introduce probabilization based ensemble distillation (ProbED), an innovative ensemble distillation framework that consolidates knowledge from multiple object detectors into a single, resource-efficient model. Unlike traditional ensemble distillation methods that average the outputs of subteachers, ProbED captures comprehensive outcome distributions from all subteachers, providing a more nuanced approach to knowledge transfer. ProbED employs knowledge probabilization to achieve a sophisticated and refined aggregation of teacher knowledge, including feature knowledge, semantic knowledge, and localization knowledge, resulting in dual improvements in prediction accuracy and uncertainty quantification for the student model. In particular, ProED's novel knowledge probabilization-based approach to aggregating teacher knowledge is inspired by our empirical observations, which demonstrate that knowledge probabilization excels in effectively representing uncertainty, improving prediction, and facilitating robust knowledge transfer. Furthermore, we introduce a random smoothing perturbation technique to modify inputs within ProbED, further enhancing the distillation process. Extensive experiments highlight ProbED's ability to significantly enhance the prediction accuracy and uncertainty quantification of various object detectors, demonstrating its superior performance compared to other state-of-the-art techniques. © 2024 IEEE.

关键词： Teaching

来源：评论

学校读者我要写书评

暂无评论

A bio-inspired optical imaging method for robotic perception in turbid water

引用

science china(Technological sciences) 2025年第1期68卷 75-77页

作者： Xudong SUN Yafeng LI Peng LIN Xiaodi SHANG Xianping FU School of Information Science and Technology Dalian Maritime UniversityDalian 116026China College of Computer Science and Technology Qingdao UniversityQingdao 266071China

In the realm of underwater robotics,optical imaging plays a pivotal role in many scientific *** to the effects of absorption and scattering,images captured in turbid water are severely ***,enhancing the quality of underwater optical images stands paramount in ensuring the continued advancement and efficacy of underwater robots across its multifarious applications.

关键词： underwater optical continued

来源：评论

学校读者我要写书评

暂无评论

Defending Federated Learning System from Poisoning Attacks via Efficient Unlearning

引用

computers, Materials & Continua 2025年第4期83卷 239-258页

作者： Long Cai Ke Gu Jiaqi Lei School of Computer and Communication Engineering Changsha University of Science and TechnologyChangsha410114China

Large-scale neural networks-based federated learning(FL)has gained public recognition for its effective capabilities in distributed ***,the open system architecture inherent to federated learning systems raises concerns regarding their vulnerability to potential *** attacks turn into a major menace to federated learning on account of their concealed property and potent destructive *** altering the local model during routine machine learning training,attackers can easily contaminate the global *** detection and aggregation solutions mitigate certain threats,but they are still insufficient to completely eliminate the influence generated by ***,federated unlearning that can remove unreliable models while maintaining the accuracy of the global model has become a *** some existing federated unlearning approaches are rather difficult to be applied in large neural network models because of their high computational ***,we propose SlideFU,an efficient anti-poisoning attack federated unlearning *** primary concept of SlideFU is to employ sliding window to construct the training process,where all operations are confined within the *** design a malicious detection scheme based on principal component analysis(PCA),which calculates the trust factors between compressed models in a low-cost way to eliminate unreliable *** confirming that the global model is under attack,the system activates the federated unlearning process,calibrates the gradients based on the updated direction of the calibration *** on two public datasets demonstrate that our scheme can recover a robust model with extremely high efficiency.

关键词： Federated learning malicious client detection model recovery machine unlearning

来源：评论

学校读者我要写书评

暂无评论

A relational triplet extraction method for constructing network security knowledge graph

引用

International Journal of Sensor Networks 2025年第1期48卷 44-53页

作者： Chen, Guanlin Xu, Jiacong Chen, Tieming Yang, Wujian Weng, Wenyong School of Computer and Computing Science Hangzhou City University Hangzhou310015 China College of Computer Science and Technology Zhejiang University of Technology Hangzhou310014 China

Faced with the challenges brought by the rapid growth of cyber threat intelligence (CTI) data, traditional information extraction methods have shown limitations regarding efficiency, accuracy, intelligence, and scalability. To help network security experts develop more solid security strategies based on reliable intelligence and improve network security defence and deterrence capability, this paper focuses on constructing a CTI knowledge graph based on a relational triplet. Besides, this paper provides a ternary extraction method for constructing a network security knowledge graph associated with a sensor system, which reduces the labour consumption of constructing a network security knowledge graph. Compared with the traditional method, the method is more efficient and accurate and can improve the performance of extracting entity relationships from complex text. Copyright © 2025 Inderscience Enterprises Ltd.

关键词： Network security

来源：评论

学校读者我要写书评

暂无评论

Towards Lifelong Learning of Large Language Models: A Survey

引用

ACM Computing Surveys 2025年第8期57卷 1-35页

作者： Zheng, Junhao Qiu, Shengjie Shi, Chengming Ma, Qianli School of Computer Science and Engineering South China University of Technology Guangzhou China

As the applications of large language models (LLMs) expand across diverse fields, their ability to adapt to ongoing changes in data, tasks, and user preferences becomes crucial. Traditional training methods with static datasets are inadequate for coping with the dynamic nature of real-world information. Lifelong learning, or continual learning, addresses this by enabling LLMs to learn continuously and adapt over their operational lifetime, integrating new knowledge while retaining previously learned information and preventing catastrophic forgetting. Our survey explores the landscape of lifelong learning, categorizing strategies into two groups based on how new knowledge is integrated: Internal Knowledge, where LLMs absorb new knowledge into their parameters through full or partial training, and External Knowledge, which incorporates new knowledge as external resources such as Wikipedia or APIs without updating model parameters. The key contributions of our survey include: (1) introducing a novel taxonomy to categorize the extensive literature of lifelong learning into 12 scenarios;(2) identifying common techniques across all lifelong learning scenarios and classifying existing literature into various technique groups;(3) highlighting emerging techniques such as model expansion and data selection, which were less explored in the pre-LLM era. © 2025 Copyright held by the owner/author(s). Publication rights licensed to ACM.

关键词： Federated learning

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：