检索结果-内蒙古大学图书馆

Study on data de-duplication based on bloom filter in fault tolerant erasure codes

Journal of Computational and Theoretical Nanoscience 2016年第1期13卷 179-185页

作者： Yan, Xiai Zhang, Dafang Zhang, Boyun College of Computer Science and Elctronic Engineering Hunan University 410082 China Department of Information Technology Hunan Police Academy Changsha410138 China Key Laboratory of Network Crime Investigation Colleges of Hunan Province Changsha410138 China

Erasure codes have become a mainstream fault-tolerant method in the field of cloud storage fault tolerance. Erasure codes will be the data from the file level storage into a block level storage, there will be a lot of repeat encoding block. Data De-duplication technique provide an effective solution to the minimization of storage. Bloom filter is a kind of space efficient data structure, which is suitable for the query in finite space. To solve the problem of erasure codes repetition coding block, it proposes a global bloom filter array efficient methods, and through the dynamic expansion of the standard Bloom filters and set up a global dynamic bloom filter array GDBFA, so as to effectively control the system false positive rate. Experiments show that: GDBFA has the characteristics of high De-duplication rate, low false positive rate, and less influence on the performance of fault tolerance. © 2016 American Scientific Publishers All rights reserved.

关键词： Fault tolerance

来源：评论

学校读者我要写书评

暂无评论

NTE Treatment Results in Increased Fpn Expression in Hippocampus of Rats Subjected to Cerebral Ischemia

NTE Treatment Results in Increased Fpn Expression in Hippoca...

引用

第九次全国中西医结合基础理论研究学术研讨会

作者： Jun Liao Xing Xia Guo-zuo Wang Yong-mei Shi Jin-wen Ge Department of Anatomy Hunan University of Chinese Medicine Campus Network Center Hunan University of Chinese Medicine College of Integrated Medicine Hunan University of Chinese Medicine Hunan Province Key Laboratory of Integrated Medicine for Cardi-Cerebrovascular Disease Hunan University of Chinese Medicine

Objective:To observe the expression of Ferroportin（Fpn） at different time points in rats after focal cerebral ischemia treated with or without Chinese medicine NTE（extract of HuangQi,Chuan Xiong,Di Long,Jiang Can） Methods:The experiment is carried out by two steps:Firstly,SD rats were randomly divided into 2 h,6h,12 h,24 h,72 h groups after operation of Middle cerebral artery occlusion（MCAO）,mRNA and protein level of Fpn were detected by immunohistochemistry and RT-PCR at above time points;Secondly,the rats were randomly allotted five groups as following: sham operation group,model group,low dose group of NTE（3 g/kg）,medial dose group of NTE （9/kg）,large dose group of NTE（27 g/kg）.After three days of corresponding therapy by intragastric administration once a day,the regional cerebral ischemia model was reproduced by middle cerebral artery occlusion（MCAO）with suture *** days later,the rats treated by previous *** third day,Neurological behavior of rats were detected by neurobehavioral *** in Hippocampal C region was measured by immunohistochemical method and mRNA of Fpn was detected by RT-PCR. Results:Expression of Fpn in hippocamp C reaches the highest point at 12 h after operation（P<0.05）;compared with model group,the large dose group of NTE（27 g/kg） displays a lower Neurological behavior score（P<0.05）;and large dose group of NTE showes higher lever expression of Fpn both at mRNA and protein level compared with sham operation group and model group（P<0.05）. Conclusion:Disregulation of intracellular iron balance perhaps is the new mechanism of cerebral ischemia injury,the NTE can protect the neuron in Hippocampal C area by adjusting the expression of Fpn to balance the iron after cerebral ischemia.

关键词： Ferroportin(Fpn) Naotaifang extract(NTE) cerebral ischemia

来源：评论

学校读者我要写书评

暂无评论

Hexagonal Convolutional Neural network for Spatial Transcriptomics Classification

Hexagonal Convolutional Neural Network for Spatial Transcrip...

引用

2022 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2022

作者： Gao, Jing Zhang, Fa Hu, Kai Cui, Xuefeng Xiangtan University Key Laboratory of Intelligent Computing and Information Processing of Ministry of Education Xiangtan China Institute of Computing Technology Chinese Academy of Sciences Beijing China School of Medical Technology Beijing Institute of Technology Beijing China Xiangnan University Key Laboratory of Medical Imaging and Artificial Intelligence of Hunan Province Chenzhou China Shandong University School of Computer Science and Technology Qingdao China

ISBN: (纸本)9781665468190

Recent advances in spatial transcriptomics have enabled the comprehensive measurement of transcriptional profiles while retaining the spatial contextual information. Identifying spatial domains is a critical step in the analysis of spatially resolved transcriptomics. Existing unsupervised methods perform poorly on this task owing to the large amount of noise and dropout events in the transcriptomic profiles. To address this problem, we first extend an unsupervised algorithm to a supervised learning method that can identify useful features and reduce noise hindrance. Second, inspired by the classical convolution in convolutional neural networks (CNNs), we designed a regular hexagonal convolution to compensate for the missing gene expression patterns from adjacent nodes. Compared with the graph convolution in graph neural networks (GNNs), our hexagonal convolution can preserve the relative spatial location information of different nodes in graph-structured data. Third, based on the hexagonal convolution, a novel hexagonal Convolutional Neural network (hexCNN) is proposed for spatial transcriptomics classification. Finally, we compared the proposed hexCNN with existing methods on the DLPFC dataset. The results show that hexCNN achieves a classification accuracy of 87.2% and an average Rand index (ARI) of 78.2% (1.9% and 3.3% higher than those of GNNs). © 2022 IEEE.

关键词： Convolution

来源：评论

学校读者我要写书评

暂无评论

A delay-derivative-dependent approach to robust H ∞ filter design for uncertain systems with time-varying distributed delays

引用

Journal of the Franklin Institute 2011年第2期348卷 179-200页

作者： Jiyao An Guilin Wen Nianfei Gan Renfa Li State Key Laboratory of Advanced Design and Manufacture for Vehicle Body the Key Laboratory of Advanced Design and Simulation Techniques for Special Equipment Ministry of Education Hunan University Changsha 410082 PR China School of Computer and Communication Institute of Embedded Systems and Network Hunan University Changsha 410082 PR China

This paper focuses on the problem of robust H ∞ filter design for uncertain systems with time-varying state and distributed delays. System uncertainties are considered as norm-bounded time-varying parametric uncertainties . The delays are assumed to be time-varying delays being differentiable uniformly bounded with delay-derivative bounded by a constant, which may be greater than one. A new delay-derivative-dependent approach of filter design for the systems is proposed. A novel Lyapunov–Krasovskii functional (LKF) is employed, and a tighter upper bound of its derivative is obtained by employing an inequality and using free-weighting matrices technique, then the proposed result has advantages over some existing results, in that it has less conservatism and it enlarges the application scope. An improved sufficient condition for the existence of such a filter is established in terms of linear matrix inequality (LMI). Finally, illustrative examples are given to show the effectiveness and reduced conservatism of the proposed method.

关键词：

来源：评论

学校读者我要写书评

暂无评论

TS-ENAS:Two-Stage Evolution for Cell-based network Architecture Search

arXiv

引用

arXiv 2023年

作者： Zou, Juan Wu, Shenghong Xia, Yizhang Jiang, Weiwei Wu, Zeping Zheng, Jinhua Engineering Research Center of Hunan Province for Optimization and Security of Intelligent System Key Laboratory of Intelligent Computing and Information Processing Ministry of Education of China Key Laboratory of Hunan Province for Internet of Things and Information Security Xiangtan University Hunan Province Xiangtan411105 China The College of Aerospace Science and Engineering National University of Defense Technology Hunan Changsha410073 China

Neural network architecture search provides a solution to the automatic design of network structures. However, it is difficult to search the whole network architecture directly. Although using stacked cells to search neural network architectures is an effective way to reduce the complexity of searching, these methods do not able find the global optimal neural network structure since the number of layers, cells and connection methods is fixed. In this paper, we propose a Two-Stage Evolution for cell-based network Architecture Search(TS-ENAS), including one-stage searching based on stacked cells and second-stage adjusting these cells. In our algorithm, a new cell-based search space and an effective two-stage encoding method are designed to represent cells and neural network structures. In addition, a cell-based weight inheritance strategy is designed to initialize the weight of the network, which significantly reduces the running time of the algorithm. The proposed methods are extensively tested and compared on four image classification dataset, Fashion-MNIST, CIFAR10, CIFAR100 and ImageNet and compared with 22 state-of-the-art algorithms including hand-designed networks and NAS networks. The experimental results show that TS-ENAS can more effectively find the neural network architecture with comparative performance. Copyright © 2023, The Authors. All rights reserved.

关键词： Image classification

来源：评论

学校读者我要写书评

暂无评论

BGRA-Net: Boundary-Guided and Region-Aware Convolutional Neural network for the Segmentation of Breast Ultrasound Images

BGRA-Net: Boundary-Guided and Region-Aware Convolutional Neu...

引用

IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

作者： Xiang Zhang Xuanya Li Kai Hu Xieping Gao Key Laboratory of Intelligent Computing and Information Processing of Ministry of Education Xiangtan University Xiangtan China Baidu Inc. Beijing China Key Laboratory of Medical Imaging and Artifical Intelligence of Hunan Province Xiangnan University Chenzhou China Hunan Provincial Key Laboratory of Intelligent Computing and Language Information Processing Hunan Normal University Changsha China

ISBN: (纸本)9781665429825

In this paper, we propose a novel convolutional neural network based on boundary-guided and region-aware (BGRA-Net) for breast tumor segmentation in ultrasound images. In particular, in the encoding stage, we propose a boundary-guided module (BGM) to guide the learning of boundary features in the decoding stage by explicitly strengthening the extracted boundary information. Meanwhile, in the decoding stage, we propose a region-aware module (RAM) to integrate different levels of detailed and semantic features to improve the comprehensive representation of tumor regional features. Besides, a scale-adaptive module (SAM) is further proposed to capture the characteristics of tumors with different sizes between the encoding and decoding stages. To evaluate the effectiveness of our BGRA-Net, we conduct extensive experiments on the UDIAT dataset and compare it with eight state-of-the-art methods. The experimental results show that our BGRA-Net outperforms the state-of-the-art methods and can achieve accurate segmentation of breast tumors with ambiguous boundaries.

关键词： Deep learning Image segmentation Breast tumors Ultrasonic imaging Semantics Feature extraction Visual effects

来源：评论

学校读者我要写书评

暂无评论

A recommendation method of educational resources based on knowledge structure 4

A recommendation method of educational resources based on kn...

引用

4th IEEE International Conference on Computer and Communications, ICCC 2018

作者： Shi, Ronghua Mao, Lei Hu, Chao Li, Sixiang Information and Network Center Central South University Changsha China School of Information Science and Engineering Central South University Changsha China Key Laboratory of Medical Information Research of Hunan Province Central South University Changsha China School of Software Central South University Changsha China

ISBN: (纸本)9781538683392

With the development of online learning platform, network education resources become more and more rich. It makes online learners easier to choose the time, place and content of learning. Because of the huge number of educational re-sources in learning platform, it is difficult for learners to find learning re-sources quickly and efficiently. The user-based collaborative filtering recommendation algorithm is improved by knowledge structure. A new method of education resource recommendation is brought up in this paper. In this method, not only the recommendation result accords with the learner's interest, but also accords with the existing knowledge system of the learner. It better meets the learner's individualized learning needs and improves the learning efficiency. In this paper, the experiment was carried out by the method of controlled experiment. The experimental results are evaluated through two aspects of correlation score and learning process score, and good experimental results have been obtained. © 2018 IEEE.

关键词： Collaborative filtering

来源：评论

学校读者我要写书评

暂无评论

Improvement on masked S-box hardware implementation

Improvement on masked S-box hardware implementation

引用

International Conference on Innovations in Information Technology

作者： Juanli Zeng Yi Wang Cheng Xu Renfa Li College of Information Science and Engineering Hunan University Changsha Hunan P. R. China Department of Electrical & Computer Engineering National University of Singapore Singapore Hunan Province Key Laboratory of Network and Information Security

Masking in gate level could efficiently protect AES S-box out of power analysis attack. But there still exists a kind of attack, called glitch attack, to achieve the sensitive information from gate cell leakage. Some works had been done to resist against glitch attack, which carefully masked AND gate or used Wave Dynamic Differential Logic (WDDL) cell. In this paper, we propose an improved masked AND gate, in which the relationship between input masked values and masks is nonlinear. Usually, when converting S-box operations from GF(2 8 ) to GF(((2 2 ) 2 ) 2 ), all the necessary computations become XOR and AND operations. Therefore, to fully mask AES S-box is to substitute the unmasked XOR and AND operations with the proposed masked AND gate and protected XOR gate. Although the proposed masked AND gate take up one extra XOR gate than Trichina's design and Baek's design, it can resist against glitch attack without using specific gate cell, such as WDDL.

关键词： Logic gates Hardware CMOS integrated circuits Encryption Field programmable gate arrays Computer architecture

来源：评论

学校读者我要写书评

暂无评论

AR-CNN: an attention ranking network for learning urban perception

引用

Science China(Information Sciences) 2022年第1期65卷 164-174页

作者： Zhetao LI Ziwen CHEN Wei-Shi ZHENG Sangyoon OH Kien NGUYEN Key Laboratory of Hunan Province for Internet of Things and Information Security Xiangtan University Key Laboratory of Intelligent Computing & Information Processing of Ministry of Education Xiangtan University School of Data and Computer Science Sun Yat-sen University Department of Computer and Information Engineering Ajou University Graduate School of Engineering Chiba University

An increasing number of deep learning methods is being applied to quantify the perception of urban environments, study the relationship between urban appearance and resident safety, and improve urban appearance. Most advanced methods extract image feature representations from street-level images through conventional visual computation algorithms or deep convolutional neural networks and then directly predict the results using features. Unfortunately, these methods take color and texture information together during processing. Color and texture are prime image features, and they affect human perception and judgment differently. We argue that color and texture should be operated differently; therefore, we formulate an end-to-end learning methodology to process input images according to color and texture information before inputting it into the neural network. The processed images and the original image constitute three input streams for the triad attention ranking convolutional neural network(AR-CNN) model proposed in this *** accordance with the aspects of color and texture, an improved attention mechanism in the convolution layer is proposed. Our objective is to obtain the scores of humans on urban appearance in accordance with the prediction results computed from pairwise comparisons generated by the AR-CNN model.

关键词： ranking network urban perception attribute learning attention network colour and texture

来源：评论

学校读者我要写书评

暂无评论

Efficient group signature scheme without pairings

引用

International Journal of network Security 2020年第3期22卷 504-515页

作者： Gu, Ke Liu, Dianxing Yin, Bo School of Computer and Communication Engineering Changsha University of Science and Technology Wangjiali Rd Tianxin district Changsha Hunan Province410114 China Key Laboratory of Network Crime Investigation of Hunan Provincial Colleges Hunan Police Academy Wangjiali Rd Tianxin district Changsha Hunan Province410114 China

Although currently many group signature schemes have been proposed, most of them are constructed on pair-ings. In this paper, we present an efficient group signature scheme without pairings under the model of verifier-local revocation, which is based on the modified EDL signature (first proposed by D. Chaum et al. in Crypto 92). Com-pared with other group signature schemes, the proposed scheme does not employ pairing computation and has the constant signing time and signature size, whose secu-rity can be reduced to the computational Diffie-Hellman (CDH) assumption in the random oracle model. Also, we give a formal security model for group signature and prove that the proposed scheme has the properties of traceabil-ity and anonymity. © 2020 Femto Technique Co., Ltd.

关键词： Authentication

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：