检索结果-内蒙古大学图书馆

arXiv 2024年

作者： Li, Yang Xia, Chunhe Lin, Wanshuang Wang, Tianbo The Key Laboratory of Beijing Network Technology Beihang University Beijing100191 China The Guangxi Collaborative Innovation Center of Multi-Source Information Integration and Intelligent Processing Guangxi Normal University Guilin541004 China The School of Cyber Science and Technology Beihang University Beijing100191 China The Shanghai Key Laboratory of Computer Software Evaluating and Testing Shanghai201112 China

With the rapid development of machine learning and a growing concern for data privacy, federated learning has become a focal point of attention. However, attacks on model parameters and a lack of incentive mechanisms hinder the effectiveness of federated learning. Therefore, we propose A Privacy Protected Blockchain-based Federated Learning Model (PPBFL) to enhance the security of federated learning and encourage active participation of nodes in model training. Blockchain technology ensures the integrity of model parameters stored in the InterPlanetary File System (IPFS), providing protection against tampering. Within the blockchain, we introduce a Proof of Training Work (PoTW) consensus algorithm tailored for federated learning, aiming to incentive training nodes. This algorithm rewards nodes with greater computational power, promoting increased participation and effort in the federated learning process. A novel adaptive differential privacy algorithm is simultaneously applied to local and global models. This safeguards the privacy of local data at training clients, preventing malicious nodes from launching inference attacks. Additionally, it enhances the security of the global model, preventing potential security degradation resulting from the combination of numerous local models. The possibility of security degradation is derived from the composition theorem. By introducing reverse noise in the global model, a zero-bias estimate of differential privacy noise between local and global models is achieved. Furthermore, we propose a new mix transactions mechanism utilizing ring signature technology to better protect the identity privacy of local training clients. Security analysis and experimental results demonstrate that PPBFL, compared to baseline methods, not only exhibits superior model performance but also achieves higher security. Copyright © 2024, The Authors. All rights reserved.

关键词： Blockchain

来源：评论

学校读者我要写书评

暂无评论

A Parameter-Independent Algorithm of Finding the Maximum Clique with Continuous-Time Quantum Walks Driven by Seidel Matrix

SSRN

引用

SSRN 2023年

作者： Li, Xi Chen, Xiao Hu, Shouwei Xu, Juan Liu, Zhihao School of Computer Science and Engineering Southeast University Nanjing211189 China Key Laboratory of Computer Network and Information Integration Southeast University Ministry of Education Nanjing211189 China College of Computer Science and Technology Nanjing University of Aeronautics and Astronautics Nanjing210016 China Collaborative Innovation Center of Novel Software Technology and Industrialization Nanjing210023 China

The problem of searching the maximum clique(MC) in network analysis holds significant practical relevance. Quantum-based algorithms have recently emerged as promising approaches for addressing this problem. However, the performance of quantum-based algorithms heavily depends on the parameters of the quantum system and can vary significantly for different graph types. In order to tackle this issue, we propose an algorithm based on quantum walks. We initially demonstrate that Continuous-Time Quantum Walks (CTQW), driven by the Seidel matrix, offer valuable insights into the clique structure of a given graph, outperforming the conventional CTQW with the adjacency matrix Hamiltonian. Specifically, we conduct an in-depth analysis of CTQW applied to 4 special types of graphs, meticulously calculating the magnitudes of amplitude associated with different vertices. Our findings consistently reveal that the vertices belonging to the MC consistently exhibit the highest intensity at the frequency corresponding to the largest probability amplitude for these types of graphs. Considering the varying amplitudes of graph vertices, we propose an algorithm for determining the MC based on CTQW. We compare our algorithm with the simulated adiabatic bifurcation method, and the results indicate that our algorithm is parameter-independent and exhibits greater stability. © 2023, The Authors. All rights reserved.

关键词： Continuous time systems

来源：评论

学校读者我要写书评

暂无评论

A Survey on Extreme Multi-label Learning

arXiv

引用

arXiv 2022年

作者： Wei, Tong Mao, Zhen Shi, Jiang-Xin Li, Yu-Feng Zhang, Min-Ling The School of Computer Science and Engineering Southeast University Nanjing210096 China The Key Laboratory of Computer Network and Information Integration Southeast University Ministry of Education China The National Key Laboratory for Novel Software Technology Nanjing University Jiangsu Nanjing210023 China

Multi-label learning has attracted significant attention from both academic and industry field in recent decades. Although existing multi-label learning algorithms achieved good performance in various tasks, they implicitly assume the size of target label space is not huge, which can be restrictive for real-world scenarios. Moreover, it is infeasible to directly adapt them to extremely large label space because of the compute and memory overhead. Therefore, eXtreme Multi-label Learning (XML) is becoming an important task and many effective approaches are proposed. To fully understand XML, we conduct a survey study in this paper. We first clarify a formal definition for XML from the perspective of supervised learning. Then, based on different model architectures and challenges of the problem, we provide a thorough discussion of the advantages and disadvantages of each category of methods. For the benefit of conducting empirical studies, we collect abundant resources regarding XML, including code implementations, and useful tools. Lastly, we propose possible research directions in XML, such as new evaluation metrics, the tail label problem, and weakly supervised XML. © 2022, CC BY.

关键词： XML

来源：评论

学校读者我要写书评

暂无评论

Learngene: From Open-World to Your Learning Task

arXiv

引用

arXiv 2021年

作者： Wang, Qiufeng Geng, Xin Lin, Shuxia Xia, Shiyu Qi, Lei Xu, Ning MOE Key Laboratory of Computer Network and Information Integration China School of Computer Science and Engineering Southeast University Nanjing210096 China

Although deep learning has made significant progress on fixed large-scale datasets, it typically encounters challenges regarding improperly detecting unknown/unseen classes in the open-world scenario, over-parametrized, and overfitting small samples. Since biological systems can overcome the above difficulties very well, individuals inherit an innate gene from collective creatures that have evolved over hundreds of millions of years and then learn new skills through few examples. Inspired by this, we propose a practical collectiveindividual paradigm where an evolution (expandable) network is trained on sequential tasks and then recognize unknown classes in real-world. Moreover, the learngene, i.e., the gene for learning initialization rules of the target model, is proposed to inherit the meta-knowledge from the collective model and reconstruct a lightweight individual model on the target task. Particularly, a novel criterion is proposed to discover learngene in the collective model, according to the gradient information. Finally, the individual model is trained only with few samples on the target learning tasks. We demonstrate the effectiveness of our approach in an extensive empirical study and theoretical analysis. Copyright © 2021, The Authors. All rights reserved.

关键词： Genes

来源：评论

学校读者我要写书评

暂无评论

A Private Statistic Query Scheme for Encrypted Electronic Medical Record System *

A Private Statistic Query Scheme for Encrypted Electronic Me...

引用

International Conference on computer Supported Cooperative Work in Design

作者： Xianxian Li Xuemei Fu Feng Yu Zhenkui Shi Jie Li Junhao Yang Guangxi Key Lab of Multi-source Information Mining & Security Guilin China Key Laboratory of Computer Network and Information Integration Southeast University Nanjing China

In this paper, we propose a scheme that supports statistic query and authorized access control on an Encrypted Electronic Medical Records Databases(EMDB). Different from other schemes, it is based on Differential-Privacy(DP), which can protect the privacy of patients. By deploying an improved Multi-Authority Attribute-Based Encryption(MA-ABE) scheme, all authorities can distribute their search capability to clients under different authorities without additional negotiations. To our best knowledge, there are few studies on statistical queries on encrypted data. In this work, we consider that support differentially-private statistical queries. To improve search efficiency, we leverage the Bloom Filter(BF) to judge whether the keywords queried by users exists. Finally, we use experiments to verify and evaluate the feasibility of our proposed scheme.

关键词： Access control Data privacy Privacy Histograms Databases Conferences Cryptography

来源：评论

学校读者我要写书评

暂无评论

Low Dose CT Noise Artifact Reduction Based on Multi-scale Weighted Convolutional Coding network

Low Dose CT Noise Artifact Reduction Based on Multi-scale We...

引用

International Conference on Systems and Informatics (ICSAI)

作者： Jin Liu Zhenyu Xia Yanqin Kang Jun Qiang College of Computer and Information Anhui Polytechnic University Wuhu China Key Laboratory of Computer Network and Information Integration Ministry of Education Southeast University Nanjing China

ISBN: (纸本)9781665426251

Low dose computed tomography becomes increasingly important to alleviate X-ray radiation damage. However, low tube current or short exposure time scanning protocols often lead to degraded CT images with increased amplified spot noise and radial streak artifacts. In this paper, we aims to obtain high-quality images from LDCT image using a multi-scale weighted convolutional coding network (MW-CCN). Referenced by the iterative shrinkage thresholding algorithms (ISTA), we transformed the traditional convolutional sparse coding to its reweighted convolutional representation and learning update form. Further, to extract multi-scale image features we use a series of dilated convolution layers, which promote our model to capture the hierarchy features of different scales. To automatically correct the weights of the feature maps code, the channel attention mechanism is adopted. At last, our method combined the multi-scale image features extraction and weighted convolutional coding with a learning-based deep CNN. The whole network architecture yields better interpretation. Compared with the recent state-of-the-art methods, our network's processing effect is more significant in the experiments.

关键词： Convolutional codes Deep learning Image coding Ultrasonic imaging Convolution Computed tomography Magnetic resonance imaging

来源：评论

学校读者我要写书评

暂无评论

BEIR:A Blockchain-based Encrypted Image Retrieval Scheme

BEIR:A Blockchain-based Encrypted Image Retrieval Scheme

引用

International Conference on computer Supported Cooperative Work in Design

作者： Xianxian Li Jie Li Feng Yu Xuemei Fu JunHao Yang Yue Chen Guangxi Key Lab of Multi-source Information Mining & Security Guilin China Key Laboratory of Computer Network and Information Integration Southeast University Nanjing China

ISBN: (纸本)9781728165974;9781728165981

Encrypted image retrieval may return incorrect or incomplete results due to threats from malicious cloud servers. Most of the existing solutions focus on the efficiency and accuracy of retrieval, lack of verification of the completeness of search results, to achieve the reliability of search results and the transparency of the search process, we explore characteristic such as the decentralization and tamper-proof of blockchain, proposed a blockchain-based encrypted image retrieval scheme. This scheme stores the encrypted index on the blockchain (Ethereum), through the blockchain consensus mechanism and the function of searching on the smart contract, ensures the integrity and correctness of search results, then outsources the corresponding encrypted images to the cloud server to reduce storage cost, and designs a double-layer index structure using the bag of visual word model and simhash in the process of image similarity index. Experiments show that the reliability, high retrieval efficiency, and precision of the scheme also have a good privacy protection effect.

关键词： Privacy Visualization Image retrieval Smart contracts Blockchain Search problems Encryption

来源：评论

学校读者我要写书评

暂无评论

BCTCP:A Feedback-Based Congestion Control Method

引用

China Communications 2020年第6期17卷 13-25页

作者： Yuyu Zhao Guang Cheng Weici Zhang Xin Chen Jin Li School of Cyber Science&Engineering Southeast UniversityNanjing 211189China Key Laboratory of Computer Network and Information Integration of Ministry of Education Southeast UniversityNanjing 211189China Key Laboratory of Computer Network Technology of Jiangsu Province China Huawei Technologies Co. Ltd.No 101Software AvenueNanjing 211189China

Delay and throughput are the two network indicators that users most care *** congestion control methods try to occupy buffer aggressively until packet loss being detected,causing high delay and *** AQM and ECN can highly reduce packet drop rate and delay,however they may also lead to low *** queue size of routers properly means a lot to congestion control *** traffic size varying around bottleneck bandwidth creates some degree of persistent queue in the router,which brings in additional delay into network unwillingly,but a corporation between sender and router can keep it under *** persistent queue not only keeps routers being fully utilized all the time,but also lower the variation of throughput and delay,achieving the balance between delay and *** this paper,we present BCTCP(Buffer Controllable TCP),a congestion control protocol based on explicit feedback from *** requires sender,receiver and routers cooperating with each other,in which senders adjust their sending rate according to the multiple bit load factor information from *** keeps queue length of bottleneck under control,leading to very good delay and utilization result,making it more applicable to complex network environments.

关键词： explicit congestion control active queue management delay variation low latency high throughput

来源：评论

学校读者我要写书评

暂无评论

BFLN: A Blockchain-based Federated Learning Model for Non-IID Data

arXiv

引用

arXiv 2024年

作者： Li, Yang Xia, Chunhe Huang, Dongchi Li, Xiaojian Wang, Tianbo School of Computer Science and Engineering Beihang University Beijing100191 China Key Laboratory of Beijing Network Technology Beihang University Beijing100191 China Guangxi Collaborative Innovation Center of Multi-Source Information Integration and Intelligent Processing Guangxi Normal University Guilin541004 China College of Computer Science and Information Technology Guangxi Normal University Guilin541001 China School of Cyber Science and Technology Beihang University Beijing100191 China

As the application of federated learning becomes increasingly widespread, the issue of imbalanced training data distribution has emerged as a significant challenge. Federated learning utilizes local data stored on different training clients for model training, rather than centralizing data on a server, thereby greatly enhancing the privacy and security of training data. However, the distribution of training data across different clients may be imbalanced, with different categories of data potentially residing on different clients. This presents a challenge to traditional federated learning, which assumes data distribution is independent and identically distributed (IID). This paper proposes a Blockchain-based Federated Learning Model for Non-IID Data (BFLN), which combines federated learning with blockchain technology. By introducing a new aggregation method and incentive algorithm, BFLN enhances the model performance of federated learning on non-IID data. Experiments on public datasets demonstrate that, compared to other state-of-the-art models, BFLN improves training accuracy and provides a sustainable incentive mechanism for personalized federated learning. Copyright © 2024, The Authors. All rights reserved.

关键词： Blockchain

来源：评论

学校读者我要写书评

暂无评论

DiffRecon: Diffusion-based CT reconstruction with cross-modal deformable fusion for DR-guided non-coplanar radiotherapy

引用

computers in Biology and Medicine 2024年 179卷 108868-108868页

作者： Sun, Jiawei Cao, Nannan Bi, Hui Gao, Liugang Xie, Kai Lin, Tao Sui, Jianfeng Ni, Xinye Changzhou No.2 People's Hospital the Affiliated Hospital of Nanjing Medical University Changzhou213003 China Jiangsu Province Engineering Research Center of Medical Physics Changzhou213003 China Center of Medical Physics Nanjing Medical University Changzhou213003 China School of Computer Science and Artificial Intelligence Changzhou University Changzhou213164 China Key Laboratory of Computer Network and Information Integration Southeast University Nanjing211096 China

In non-coplanar radiotherapy, DR is commonly used for image guiding which needs to fuse intraoperative DR with preoperative CT. But this fusion task performs poorly, suffering from unaligned and dimensional differences between DR and CT. CT reconstruction estimated from DR could facilitate this challenge. Thus, We propose a unified generation and registration framework, named DiffRecon, for intraoperative CT reconstruction based on DR using the diffusion model. Specifically, we use the generation model for synthesizing intraoperative CTs to eliminate dimensional differences and the registration model for aligning synthetic CTs to improve reconstruction. To ensure clinical usability, CT is not only estimated from DR but the preoperative CT is also introduced as prior. We design a dual-encoder to learn prior knowledge and spatial deformation among pre- and intra-operative CT pairs and DR parallelly for 2D/3D feature deformable conversion. To calibrate the cross-modal fusion, we insert cross-attention modules to enhance the 2D/3D feature interaction between dual encoders. DiffRecon has been evaluated by both image quality metrics and dosimetric indicators. The high image synthesis metrics are with RMSE of 0.02±0.01, PSNR of 44.92±3.26, and SSIM of 0.994±0.003. The mean gamma passing rates between rCT and sCT for 1%/1 mm, 2%/2 mm and 3%/3 mm acceptance criteria are 95.2%, 99.4% and 99.9% respectively. The proposed DiffRecon can reconstruct CT accurately from a single DR projection with excellent image generation quality and dosimetric accuracy. These demonstrate that the method can be applied in non-coplanar adaptive radiotherapy workflows. © 2024 Elsevier Ltd

关键词： Radiotherapy

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：