检索结果-内蒙古大学图书馆

您好，读者！请登录

内蒙古大学图书馆

首页
概况
党建
资源
服务
科研支持
- 论文收录引用证明
- 科技查新
知识产权
档案馆
帮助

咨询与建议

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

您的常用邮箱：*

您的手机号码：*

问题描述：

当前已输入0个字，您还可以输入200个字

全部搜索
期刊论文
图书
学位论文
标准
纸本馆藏
外文资源发现
数据库导航
超星发现

高级检索

时间限定

出版年份：

文献类型

图书期刊文献学位论文多媒体

馆藏选择

电子馆藏纸本馆藏

核心期刊

全部期刊 SCI 收录期刊 SSCI 收录期刊 EI 收录期刊 CSCD 收录期刊 CSSCI 收录期刊

语言

中文英文

文献类型

期刊文献图书学位论文标准纸本馆藏

帮助

文字说明：

T=题名（书名、题名），A=作者（责任者），K=主题词，P=出版物名称，PU=出版社名称，O=机构（作者单位、学位授予单位、专利申请人），L=中图分类号，C=学科分类号，U=全部字段，Y=年（出版发行年、学位年度、标准发布年）

检索规则说明：

AND代表“并且”；OR代表“或者”；NOT代表“不包含”；(注意必须大写,运算符两边需空一格)

检索范例：

范例一：(K=图书馆学 OR K=情报学) AND A=范并思 AND Y=1982-2016
范例二：P=计算机应用与软件 AND (U=C++ OR U=Basic) NOT K=Visual AND Y=2011-2016

分类表

所选分类

>> <<

限定检索结果

文献类型

4,286 篇 会议
47 篇 期刊文献
3 册 图书

馆藏范围

4,336 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

2,433 篇 工学
- 2,168 篇 计算机科学与技术...
- 1,078 篇 软件工程
- 608 篇 电气工程
- 586 篇 信息与通信工程
- 185 篇 仪器科学与技术
- 138 篇 控制科学与工程
- 119 篇 电子科学与技术（可...
- 64 篇 生物工程
- 59 篇 机械工程
- 43 篇 动力工程及工程热...
- 38 篇 交通运输工程
- 31 篇 生物医学工程（可授...
- 27 篇 安全科学与工程
- 26 篇 网络空间安全
- 24 篇 光学工程
- 23 篇 土木工程
- 22 篇 材料科学与工程（可...
- 20 篇 建筑学
- 19 篇 航空宇航科学与技...
418 篇 理学
- 253 篇 数学
- 86 篇 物理学
- 72 篇 生物学
- 51 篇 系统科学
- 42 篇 统计学（可授理学、...
262 篇 管理学
- 180 篇 管理科学与工程(可...
- 97 篇 图书情报与档案管...
- 66 篇 工商管理
35 篇 医学
- 30 篇 临床医学
33 篇 法学
- 19 篇 社会学
18 篇 经济学
- 18 篇 应用经济学
11 篇 农学
7 篇 教育学
7 篇 文学
2 篇 军事学

主题

545 篇 parallel process...
259 篇 computer archite...
240 篇 computational mo...
207 篇 distributed comp...
186 篇 concurrent compu...
180 篇 computer network...
164 篇 network topology
158 篇 graphics process...
156 篇 hardware
148 篇 routing
131 篇 bandwidth
124 篇 application soft...
121 篇 protocols
119 篇 neural networks
107 篇 scalability
107 篇 multicore proces...
104 篇 throughput
103 篇 algorithm design...
102 篇 kernel
101 篇 computer science

机构

15 篇 institute of inf...
14 篇 institute of com...
14 篇 science and tech...
13 篇 college of compu...
13 篇 school of cyber ...
13 篇 shandong fundame...
12 篇 school of comput...
10 篇 science and tech...
9 篇 univ chinese aca...
9 篇 university of ch...
9 篇 natl univ def te...
9 篇 natl univ def te...
8 篇 shenyang aerospa...
8 篇 beijing univ pos...
8 篇 nanjing univ aer...
8 篇 beijing universi...
7 篇 shanghai jiao to...
7 篇 college of compu...
7 篇 chinese acad sci...
7 篇 national key lab...

作者

17 篇 bagherzadeh nade...
16 篇 kotenko igor
14 篇 j. duato
12 篇 wang yijie
11 篇 daneshtalab maso...
10 篇 ebrahimi masoume...
10 篇 yijie wang
10 篇 nader bagherzade...
10 篇 igor kotenko
10 篇 lexi xu
9 篇 li dongsheng
9 篇 marco aldinucci
9 篇 matsutani hiroki
8 篇 hiroki matsutani
8 篇 masoumeh ebrahim...
8 篇 plosila juha
8 篇 marco danelutto
8 篇 wang huaimin
7 篇 tenhunen hannu
7 篇 xinzhou cheng

语言

4,092 篇 英文
235 篇 其他
11 篇 中文
1 篇 乌克兰文

检索条件"任意字段=Euromicro Conference on Parallel, Distributed and Network-Based Processing"

共 4336 条记录，以下是1271-1280 订阅

全选清除本页清除全部题录导出标记到"检索档案"

详细简洁

排序：

Performance and Consistency Analysis for distributed Deep Learning Applications

Performance and Consistency Analysis for Distributed Deep Le...

引用

IEEE International conference on Performance, Computing and Communications (IPCCC)

作者： Danlin Jia Manoj Pravakar Saha Janki Bhimani Ningfang Mi Northeastern University Boston USA Florida International University Miami USA

ISBN: (数字)9781728198293

ISBN: (纸本)9781728198309

Accelerating the training of Deep Neural network (DNN) models is very important for successfully using deep learning techniques in fields like computer vision and speech recognition. distributed frameworks help to speed up the training process for large DNN models and datasets. Plenty of works have been done to improve model accuracy and training efficiency, based on mathematical analysis of computations in the Con-volutional Neural networks (CNN). However, to run distributed deep learning applications in the real world, users and developers need to consider the impacts of system resource distribution. In this work, we deploy a real distributed deep learning cluster with multiple virtual machines. We conduct an in-depth analysis to understand the impacts of system configurations, distribution typologies, and application parameters, on the latency and correctness of the distributed deep learning applications. We analyze the performance diversity under different model consistency and data parallelism by profiling run-time system utilization and tracking application activities. based on our observations and analysis, we develop design guidelines for accelerating distributed deep-learning training on virtualized environments.

关键词： Deep learning Training Computational modeling Neural networks parallel processing Resource management Load modeling

来源：评论

学校读者我要写书评

暂无评论

BGElasor: Elastic-Scaling Framework for distributed Streaming processing with Deep Neural network 16th

BGElasor: Elastic-Scaling Framework for Distributed Streamin...

引用

16th IFIP WG 10.3 International conference on network and parallel Computing, NPC 2019

作者： Mu, Weimin Jin, Zongze Wang, Junwei Zhu, Weilin Wang, Weiping Institute of Information Engineering Chinese Academy of Sciences Beijing China School of Cyber Security University of Chinese Academy of Sciences Beijing China

ISBN: (纸本)9783030307080

In face of constant fluctuations and sudden bursts of data stream, elasticity of distributed stream processing system has become increasingly important. The proactive policy offers a powerful means to realize the effective elastic scaling. The existing methods lack the latent features of data stream, it leads the poor prediction. Furthermore, the poor prediction results in the high cost of adaptation and the instability. To address these issues, we propose the framework named BGElasor, which is a proactive and low-cost elastic-scaling framework based on the accurate prediction using deep neural networks. It can capture the potentially-complicated pattern to enhance the accuracy of prediction, reduce the cost of adaptation and avoid adaptation bumps. The experimental results show that BGElasor not only improves the prediction accuracy with three kinds of typical loads, but also ensure the end-to-end latency on QoS with low cost. © 2019, IFIP International Federation for Information processing.

关键词： Deep neural networks

来源：评论

学校读者我要写书评

暂无评论

CUDA-based parallel Computation Model for State Estimation

CUDA-Based Parallel Computation Model for State Estimation

引用

Chinese Control conference (CCC)

作者： Yueqi Liu Xiangyu Kong Yao Jin Key Laboratory of Smart Grid of Ministry of Education Tianjin University Tianjin China State Grid Tianjin Chengnan Electric Power Supply Company Tianjin China

ISBN: (数字)9789881563903

ISBN: (纸本)9781728165233

With the development of the active distribution network (ADN), distributed state estimation (DSE) has become an inevitable trend for state estimation (SE). The efficient partitioned strategy is an essential prerequisite for DSE. However, the existing methods only consider the basic requirements of equilibrium connectivity, and the similarity of buses in one sub-region is ignored. A new partitioned strategy is proposed in this paper, this method learns from the idea of hierarchical clustering, the buses of the distribution network are aggregated to form sub-regions, and CUDA platform is used to realize the parallel computation of SE. The improved IEEE33-node system and a real distribution network are analyzed as a case study. The results show that, compared with traditional CSE, the estimation accuracy of DSE is higher than that of CSE, which indicates that the estimation accuracy of the proposed method is higher than that of CSE. Besides, compared with serial computation, this method can effectively reduce the running time of DSE in each sub-region and improve the overall calculation efficiency.

关键词： Graphics processing units Instruction sets Clustering algorithms Partitioning algorithms Voltage measurement Power measurement State estimation

来源：评论

学校读者我要写书评

暂无评论

Accelerated Inference Framework of Sparse Neural network based on Nested Bitmask Structure 28

Accelerated Inference Framework of Sparse Neural Network Bas...

引用

28th International Joint conference on Artificial Intelligence

作者： Zhang, Yipeng Du, Bo Zhang, Lefei Li, Rongchun Dou, Yong Wuhan Univ Sch Comp Sci Wuhan Peoples R China Natl Univ Def Technol Natl Lab Parallel & Distributed Proc Changsha Peoples R China

ISBN: (纸本)9780999241141

In order to satisfy the ever-growing demand for high-performance processors for neural networks, the state-of-the-art processing units tend to use application-oriented circuits to replace processing Engine (PE) on the GPU under circumstances where low-power solutions are required. The application-oriented PE is fully optimized in terms of the circuit architecture and eliminates incorrect data dependency and instructional redundancy. In this paper, we propose a novel encoding approach on a sparse neural network after pruning. We partition the weight matrix into numerous blocks and use a low-rank binary map to represent the validation of these blocks. Furthermore, the elements in each nonzero block are also encoded into two submatrices: one is the binary stream discriminating the zero/nonzero position, while the other is the pure nonzero elements stored in the FIFO. In the experimental part, we implement a well pre-trained sparse neural network on the Xilinx FPGA VC707. Experimental results show that our algorithm outperforms the other benchmarks. Our approach has successfully optimized the throughput and the energy efficiency to deal with a single frame. Accordingly, we contend that Nested Bitmask Neural network (NBNN), is an efficient neural network structure with only minor accuracy loss on the SoC system.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Key Technology Research of Distribution Automation System based on Cloud Architecture

Key Technology Research of Distribution Automation System Ba...

引用

2018 IEEE International conference of Safety Produce Informatization, IICSPI 2018

作者： Que, Bo Su, Biaolong Sun, Shiming Chen, Lei He, Mingyi Zhou, Yanghao State Grid ZheJiang Electric Power CO. LTD Hangzhou China NARI Group Corporation State Grid Electric Power Research Institute Nanjing China

ISBN: (纸本)9781538655139

China's economic development has higher requirements for the power supply capability and reliability of distribution network. At present, the management scope of distribution automation system cannot cover the whole distribution network and many regional electric companies cannot manage the operation state of distribution network through the existing distribution automation system, which restricts the development of distribution network construction. It is necessary to develop a new system construction scheme to cope with the different data capacity and function requirements of distribution networks in different cities. This paper proposes a technical scheme of main station of distribution automation system based on cloud architecture in aspects of system architecture, elastic data processing, safe access of distribution terminals and optimal operation control. With the distributed collaboration between core cloud and regional cloud as well as data fragmentation parallel processing technology, the problem of massive access and application of distribution network will be solved. © 2018 IEEE.

关键词： Cloud computing architecture

来源：评论

学校读者我要写书评

暂无评论

Sia-RAE: A Siamese network based on Recursive AutoEncoder for Effective Clone Detection

Sia-RAE: A Siamese Network based on Recursive AutoEncoder fo...

引用

Asia-Pacific conference on Software Engineering

作者： Chenhui Feng Tao Wang Yue Yu Yang Zhang Yanzhi Zhang Huaimin Wang National Laboratory for Parallel and Distributed Processing College of Computer National University of Defense Technology Changsha China

ISBN: (数字)9781728195537

ISBN: (纸本)9781728195544

Code clone helps improving programming productivity, while at the same time leads to many negative effects on software maintenance. Many approaches have been proposed to detect clones, but most of them fail on detecting low similarity code snippets. In this paper, we propose a Siamese network which links two recursive autoencoders (RAE) with a comparator network for clone detection. The unweighted recursive autoencoder is designed to learn code representation and then the comparator network is employed for similarity evaluation. In this Siamese network, it takes full advantages of lexical, semantic and structure information, and achieves high accuracy in revealing tiny similarity. We conduct comprehensive experiments on BigCloneBench using tagged clones as well as the whole repository respectively. The results suggest that our approach achieves good accuracy, and its recall reaches 93.02 % in WT3/T4, which outperforms state-of-the-art.

关键词： Productivity Software maintenance Semantics Cloning Programming Software engineering

来源：评论

学校读者我要写书评

暂无评论

MapReduce-based Convolutional Neural network for Text Categorization 11th

MapReduce-Based Convolutional Neural Network for Text Catego...

引用

11th International conference on Computational Collective Intelligence (ICCCI)

作者： Ferjani, Eman Hidri, Adel Sassi Hidri, Minyar Frihida, Ali Imam Abdulrahman Bin Faisal Univ Deanship Preparatory Year & Supporting Studies Dammam Saudi Arabia Tunis El Manar Univ Natl Engn Sch Tunis Tunis Tunisia

ISBN: (纸本)9783030283742;9783030283735

Convolutional Neural network (CNN) is an algorithm among deep learning. It is an effective method of solving common Natural Language processing tasks such as text categorization. In this paper, we investigate the text categorization problem using a deep learning approach in particular CNN method. However, due to the rise of Big Data and increased complexity of tasks, the efficiency of CNNs have been severely impacted because of their extensive training time and high computational cost. To overcome these obstacles, we propose a MapReducebased CNN by reformulating the CNN's training from a single training network to a series of parallel trained smaller networks. Each smaller network processes a sub-sample of input text.

关键词： distributed text representation CNN Word2vec MapReduce Text categorization

来源：评论

学校读者我要写书评

暂无评论

Back-Propagated Neural network on MapReduce Frameworks: A Survey 2nd

Back-Propagated Neural Network on MapReduce Frameworks: A Su...

引用

2nd International conference on Smart Innovations in Communications and Computational Sciences ICSICCS-2018

作者： Dhanani, Jenish Mehta, Rupa Rana, Dipti Tidke, Bharat S. V. National Institute of Technology Surat India

ISBN: (纸本)9789811324130

Back-propagated Neural network (BPNN) is a popular supervised learning technique utilized in machine learning and deep learning to extract knowledge. However, BPNN has shown poor time and space complexity with large volume of data due to its in-memory processing. Huge amount of data sourced by ample of applications and services on the Internet needs to be distributed and parallel environment like MapReduce framework for processing and storage. The large volume of data is divided into smaller chunks and MapReduce framework exploits the cluster of commodity hardware to process these chunks. This research focuses on various MapReduce-based BPNN algorithms such as single-pass and multi-pass MapReduce-based BPNN. The research is intended to perform in-depth comparisons of these techniques considering various parameters such as computation complexity of Mapper and Reducer, granularity of Mapper’s output, number of MapReduce jobs required to build BPNN, and Mapper’s pairs. © 2019, Springer Nature Singapore Pte Ltd.

关键词： MapReduce

来源：评论

学校读者我要写书评

暂无评论

Smart Approach to Build A Deep Neural network based IDS for Cloud Environment Using an Optimized Genetic Algorithm 19

Smart Approach to Build A Deep Neural Network Based IDS for ...

引用

2nd International conference on networking, Information Systems and Security (NISS)

作者： Chiba, Zouhair Abghour, Noreddine Moussaid, Khalid El Omri, Amina Rida, Mohamed Hassan II Univ Casablanca Fac Sci LIMSAD Labs Casablanca 20100 Morocco

ISBN: (纸本)9781450366458

In recent years cloud computing has revolutionized the IT world with rapidly emerging and widely accepted paradigm for computing systems, and it has become popular among users in organizations and companies. Nowadays, numerous organizations have begun to upload their massive amount of prominent data into public cloud. Nevertheless, uploading sensitive data to open and distributed public cloud storage services poses security risks such as availability, confidentiality and integrity to organizations. Moreover, non-stop cloud services have caused high levels of intrusion and abuse. Thereby, protecting network accessible Cloud resources and services from various threats and attacks is of great concern. To address this issue, it is imperative to develop a powerful network Intrusion System (NIDS) to detect both outsider and insider intruders with high detection precision in the cloud environment. In this work, we propose a smart approach using an Improved Genetic Algorithm (IGA) to build a Deep Neural network (DNN) based anomaly NIDS. Genetic Algorithm (GA) is improved through optimization strategies, namely parallel processing and Fitness Value Hashing, which reduce execution time, convergence time and save processing power. Our approach consists to use IGA in order to search the optimal or near optimal combination of most relevant values of the parameters included in construction of DNN based IDS or impacting its performance, like feature selection, data normalization, architecture of DNN, activation function, learning rate and Momentum term, which ensure high detection rate, high accuracy and low false alarm rate. CloudSim 4.0 simulator platform and CICIDS 2017 benchmark dataset were used for simulation and validation of the proposed system. The experimental results obtained demonstrate that in comparison to several traditional and recent approaches, our proposed IDS achieves higher detection rate and lower false positive rate.

关键词： Cloud computing network intrusion detection system Anomaly detection Deep neural network Back propagation learning algorithm Optimization Genetic algorithm CICIDS2017 dataset

来源：评论

学校读者我要写书评

暂无评论

Optimizing Performance of Aggregate Query processing with Histogram Data Structure 8th

Optimizing Performance of Aggregate Query Processing with Hi...

引用

8th Computer Science On-Line conference (CSOC)

作者： Liang Yong Mu Zhaonan Guizhou Univ Commerce Network & Informat Ctr Guiyang 550014 Guizhou Peoples R China

ISBN: (纸本)9783030198077;9783030198060

In today's big data era, the capability of analyze massive data efficient and return the results within an short time limit is critical to decision making, thus many big data system proposed and various distributed and parallel processing techniques are heavily investigated. Among previous research, most of them are working on precise query processing, while approximate query processing (AQP) techniques which make interactive data exploration more efficiently and allows users to tradeoff between query accuracy and response time have not been investigate comprehensively. In this paper, we study the characteristics of aggregate query, a typical type of analytical query, and proposed an approximate query processing approach to optimize the execution of massive data based aggregate query with a histogram data structure. We implemented this approach into big data system Hive and compare it with Hive and AQP-enabled big data system BlinkDB, the experimental results verified that our approach is significantly fast than these existing systems in most scenarios.

关键词： Massive data Approximate query processing Histogram Aggregate query Performance optimization

来源：评论

学校读者我要写书评

暂无评论

没有更多数据了...

全选清除本页清除全部题录导出标记到“检索档案”

共434页 << < 124 125 126 127 128 129 130 131 132 133 > >>

检索报告对象比较合并检索0

隐藏清空

合并搜索

回到顶部

执行限定条件

内容：

评分：

请选择保存的检索档案：

请选择收藏分类：

订阅名称：

通借通还

温馨提示：

图书名称：

借书校区：

取书校区：

手机号码：

邮箱地址：

一卡通帐号：

电话和邮箱必须正确填写，我们会与您联系确认。

联系人：

所在院系：

联系邮箱：

联系电话：

内蒙古自治区呼和浩特市赛罕区大学西街235号邮编: 010021

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：