检索结果-内蒙古大学图书馆

22nd IEEE International Symposium on parallel and distributed Processing with Applications, ISPA 2024

作者： Lin, Moheng Shi, Peichang Fu, Xiang Jiang, Feng Yi, Guodong National University of Defense Technology National Key Laboratory of Parallel and Distributed Computing College of Computer Science Changsha410073 China Xiangjiang Lab Changsha410073 China

ISBN: (纸本)9798331509712

Blockchain technology has been extensively uti-lized in decentralized data-sharing applications, with the immutability of blockchain providing a witness for the circulation of data. However, current blockchain data-sharing solutions still fail to address the simultaneous screening needs of both the sender and receiver with multi-keywords. Without the capability to support bilateral simultaneous filtering, the disclosure of reasons for matching failures could inadvertently expose sensitive user data. Therefore, the challenge lies in enabling ciphertexts with multiple keywords and receivers with multiple interests to achieve mutual and simultaneous matching. Based on the technical foundations of SE (Searchable Encryption), MABE (Multi-Attribute Based Encryption), and polynomial fitting, this paper proposes a scheme called DMSA (Decentralized and Multi-keyword selective Sharing and selective Acquisition). This scheme can satisfy soundness, enabling ciphertexts carrying multiple keywords and receivers representing multiple interests to match each other simultaneously. We conducted a security analysis that confirms the security of DMSA against chosen-plaintext attacks. Our experimental results demonstrate a significant efficiency improvement, with a 67% increase over single-keyword data-sharing schemes and a 16% enhancement compared to the existing multi-keyword data-sharing solution. © 2024 IEEE.

关键词： Ciphertext

来源：评论

学校读者我要写书评

暂无评论

Asycome: A JointCloud Data Asynchronous Collaboration Mechanism Based on Blockchain 3rd

Asycome: A JointCloud Data Asynchronous Collaboration Mechan...

引用

3rd International Conference on Blockchain and Trustworthy Systems, Blocksys 2021

作者： Li, Linhui Shi, Peichang Fu, Xiang Zhang, Shengtian Zhong, Tao Chen, Ming National Key Laboratory of Parallel and Distributed Processing College of Computer Science National University of Defense Technology Changsha410073 China

ISBN: (纸本)9789811679926

In the Internet of Everything (IoE), due to its issues of complexity and heterogeneity, message delay cannot be guaranteed, and it is not enough to leverage a centralized model for data collaboration. By leveraging the features of blockchain and asynchronous consensus algorithms, a new trust collaboration model can be established in an untrusted environment. Besides, the scalability issue of blockchain poses a challenge to data asynchronous collaboration. In this paper, we propose Asycome, a JointCloud data asynchronous collaboration mechanism based on Directed Acyclic Graph (DAG). This mechanism introduces the new Gossip about gossip protocol, driven by message-transmitting events, to keep data synchronized in an asynchronous environment. Through two stages of voting and committing. Transactions on the same time series do not need to reach the final confirmed state before proceeding to the next transaction processing. Over time, all transactions are connected to the DAG, ensuring that the consensus is finally reached. We evaluated the performance of the mechanism with experiments on throughput and latency. And the feasibility of Asycome is analyzed from the liveness and security. The results show that higher throughput, lower latency, and Asynchronous Byzantine Fault Tolerance (ABFT) characteristics can meet the technical requirements of complex and asynchronous data collaboration of the IoE to some extent. © 2021, Springer Nature Singapore Pte Ltd.

关键词： Blockchain

来源：评论

学校读者我要写书评

暂无评论

Modeling complex relationship paths for knowledge graph completion

Modeling complex relationship paths for knowledge graph comp...

引用

作者： Zeng, Ping Tan, Qingping Meng, Xiankai Zhang, Haoyu Xu, Jianjun College of Computer National University of Defense Technology Changsha China National Key Laboratory for Parallel and Distributed Processing Changsha China

Determining the validity of knowledge triples and filling in the missing entities or relationships in the knowledge graph are the crucial tasks for large-scale knowledge graph completion. So far, the main solutions use machine learning methods to learn the low-dimensional distributed representations of entities and relationships to complete the knowledge graph. Among them, translationmodels obtain excellent performance. However, the proposed translation models do not adequately consider the indirect relationships among entities, affecting the precision of the representation. Based on the long short-term memory neural network and existing translation models, we propose a multiple-module hybrid neural network model called TransP. By modeling the entity paths and their relationship paths, TransP can effectively excavate the indirect relationships among the entities, and thus, improve the quality of knowledge graph completion tasks. Experimental results show that TransP outperforms state-of-the-art models in the entity prediction task, and achieves the comparable performance with previous models in the relationship prediction task. © 2018 The Institute of Electronics, Information and Communication Engineers.

关键词： Knowledge graph

来源：评论

学校读者我要写书评

暂无评论

Ladder: A Blockchain Model of Low-Overhead Storage 3rd

Ladder: A Blockchain Model of Low-Overhead Storage

引用

3rd International Conference on Blockchain and Trustworthy Systems, Blocksys 2021

作者： Chen, Peng Zhang, Xunhui Liu, Hui Xiang, Liangliang Shi, Peichang National Key Laboratory of Parallel and Distributed Processing College of Computer Science National University of Defense Technology Changsha410073 China

ISBN: (纸本)9789811679926

Emerging blockchain accounting mechanism allow mutually distributed parties to transport trusted information and ensure the correctness of data. Every blockchain node stores the complete block locally. Although this measure improves security, it causes huge storage overhead. We present Ladder, a multi-level low-overhead storage model for blockchain, which can greatly reduce the storage overhead of nodes while ensuring that the blockchain cannot be tampered easily and the block information is complete. Ladder distinguishes the retrieved frequency and importance of different blocks by value-density, dividing them into Hot-Blocks, Warm-Blocks and Cold-Blocks adopting different storage strategies respectively. Through experimental verification of time and space cost of different storage strategies, Ladder can greatly reduce the local storage overhead of nodes. © 2021, Springer Nature Singapore Pte Ltd.

关键词： Blockchain

来源：评论

学校读者我要写书评

暂无评论

A Connectivity-Enhanced Multi-Task Learning based on Anatomical Priors for 3D Class-Balanced Pulmonary Airway Segmentation

A Connectivity-Enhanced Multi-Task Learning based on Anatomi...

引用

2024 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2024

作者： Jia, Yan Dou, Yong Qiao, Peng Cheng, Yuqing Xu, Kele He, Zhouyu National University of Defense Technology National Key Laboratory of Parallel and Distributed Computing College of Computer Science and Technology Changsha China National University of Defense Technology College of Systems Engineering Changsha China

ISBN: (纸本)9798350386226

Accurate and efficient airway segmentation is essential for evaluating pulmonary diseases, aiding diagnosis, reducing the preoperative burden of airway identification, and minimizing patient discomfort during prolonged surgeries. However, current pulmonary airway reconstruction techniques are hindered by two major challenges: difficulty in accurately reconstructing fine airway branches due to the tendency to overlook small targets, and insufficient structural connectivity leading to frequent branch discontinuities within the airway tree. These limitations directly affect the clinical applicability of reconstructed airways. To overcome these challenges, a novel 3D pulmonary airway segmentation multi-task framework is proposed, designed to enhance the performance of existing backbone models. This approach integrates Anatomical Prior-Based Multi-Task Learning (AP-MTL) through the use of Gaussian-constructed connectivity-enhanced isosurfaces, significantly improving the network's ability to maintain airway continuity. Additionally, a Class-Balanced CT Density Distribution Reconstruction mechanism (DDR-CB) is introduced, further refining the model's capability to detect and segment fine airway branches. As a result of these enhancements, the model demonstrates a 11.5% average improvement in segmentation accuracy and connectivity compared to the baseline. The source code is publicly accessible at https://***/inexhaustible419/APMTLAirwaySegment. © 2024 IEEE.

关键词： Pulmonary diseases

来源：评论

学校读者我要写书评

暂无评论

BCE: A privacy-preserving common-friend estimation method for distributed online social networks without cryptography

BCE: A privacy-preserving common-friend estimation method fo...

引用

2012 7th International ICST Conference on Communications and Networking in China, CHINACOM 2012

作者： Fu, Yongquan Wang, Yijie National Key Laboratory for Parallel and Distributed Processing College of Computer Science National University of Defense Technology Hunan province 410073 China

ISBN: (纸本)9781467326995

distributed online social networks (DOSN) have emerged recently. Nevertheless, recommending friends in the distributed social networks has not been exploited fully. We propose BCE (Bloom Filter based Common-Friend Estimation), a scalable and privacy-preserving common-friend estimation scheme that estimates the set of common friends without the need of cryptography techniques. First, BCE denotes each user using the identifiers created by the Peer-to-Peer underlay that are robust against the dictionary attacks. Second, BCE uses a Bloom filter to represent a friend list for scalability. Third, BCE estimates common friends of two users using the intersection of Bloom filters computed by one of their common friends, which ensures the privacy of friend lists against unknown users. Our privacy analysis shows that BCE hides the privacy of each user with a high probability. Simulations over real-world social-network data sets confirms that BCE is both accurate and scalable. © 2012 IEEE.

关键词： Social networking (online)

来源：评论

学校读者我要写书评

暂无评论

On the feasibility of common-friend measurements for the distributed online social networks

On the feasibility of common-friend measurements for the dis...

引用

2012 7th International ICST Conference on Communications and Networking in China, CHINACOM 2012

作者： Fu, Yongquan Wang, Yijie National Key Laboratory for Parallel and Distributed Processing College of Computer Science National University of Defense Technology Hunan province 410073 China

ISBN: (纸本)9781467326995

distributed social networks have emerged recently. Nevertheless, recommending friends in the distributed social networks has not been exploited fully. We propose FDist, a distributed common-friend estimation scheme that estimates the number of common-friends between any pair of users without disclosing the friends' information. FDist uses privacy-preserving common-friend measurements to collect a small number of common-friend samples, and uses low-dimensional coordinates to estimate the number of common friends to other users. Simulation results on real-world social networks confirm that FDist is both scalable and accurate. © 2012 IEEE.

关键词： Social networking (online)

来源：评论

学校读者我要写书评

暂无评论

AUModel: A conceptual model for adaptive software 5

AUModel: A conceptual model for adaptive software

引用

2014 5th IEEE International Conference on Software Engineering and Service Science, ICSESS 2014

作者： Liu, Hui Ding, Bo Shi, Dianxi Wang, Huaimin National Key Laboratory for Parallel and Distributed Processing College of Computer Science National University of Defense Technology Changsha Hunan410073 China

ISBN: (纸本)9781479932788

Pervasive software should be able to adapt itself to the changing environments and user requirements. Obviously, it will bring great challenges to the software engineering practice. This paper proposes AUModel, a conceptual model for adaptive software, which takes adaptability as an inherent feature and can act as the foundation of the engineering process. By introducing AUModel, the reuse of software adaptation infrastructure as well as the separation of adaptation concerns are enabled, which can facilitate both the development and maintenance of adaptive software. This paper also presents our initial attempts to realize this model, including a middleware prototype to support this model and an application to validate its effectiveness. © 2014 IEEE.

关键词： Middleware

来源：评论

学校读者我要写书评

暂无评论

Research on Fine-Grained Sentiment Classification 8th

Research on Fine-Grained Sentiment Classification

引用

8th CCF International Conference on Natural Language Processing and Chinese computing, NLPCC 2019

作者： Wang, Zhihui Wang, Xiaodong Chang, Tao Lv, Shaohe Guo, Xiaoting National Key Laboratory of Parallel and Distributed Processing College of Computer Science and Technology National University of Defence Technology Changsha410073 China

ISBN: (纸本)9783030322359

Aiming at the fine-grained sentiment classification that distinguishes the emotional intensity, the commonly used dataset SST-1 is analyzed in depth. Through the analysis, it is found that the dataset has serious problems such as data imbalance and small overall scale, which seriously restricts the classification effect. In order to solve the related problems, data augmentation method is adopted to realize the optimization of the dataset. The IMDB and other data which are relatively homologous to the original dataset are annotated, and the focus is to expand the categories with fewer numbers. By this way, the problem of data imbalance is effectively alleviated and the original data scale is expanded. Then, based on the Bidirectional Encoder Representations from Transformers (BERT) model, which has good overall performance on natural language processing, the benchmark classification model is built. Through multiple comparison experiments on the original dataset and the enhanced data, the influence of the deficiency of the original dataset on the classification effect is verified. And, it is fully demonstrated that the enhanced data can effectively improve the test results and solve the problem of large differences in performance between different categories well. © 2019, Springer Nature Switzerland AG.

关键词： Classification (of information)

来源：评论

学校读者我要写书评

暂无评论

HAF: a hybrid annotation framework based on expert knowledge and learning technique

引用

Science China(Information Sciences) 2022年第1期65卷 276-278页

作者： Zhixing LI Yue YU Tao WANG Gang YIN Xinjun MAO Huaimin WANG Key Laboratory of Parallel and Distributed Computing National University of Defense Technology College of Computer National University of Defense Technology

Dear editor,The increasing awareness of the potential value hidden in data has resulted in many data mining studies being conducted. In the domain of software engineering, for example, developers' behavioral data and code review data have been leveraged in social coding sites to automatically recommend relevant projects [1] and candidate reviewers [2, 3].

关键词：

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：