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

23,961 篇 会议
400 篇 期刊文献
285 册 图书
1 篇 学位论文

馆藏范围

24,647 篇 电子文献
1 种 纸本馆藏

日期分布

学科分类号

14,497 篇 工学
- 13,367 篇 计算机科学与技术...
- 5,952 篇 软件工程
- 2,508 篇 电气工程
- 2,171 篇 信息与通信工程
- 916 篇 控制科学与工程
- 532 篇 电子科学与技术（可...
- 412 篇 机械工程
- 327 篇 生物工程
- 261 篇 动力工程及工程热...
- 219 篇 仪器科学与技术
- 207 篇 生物医学工程（可授...
- 155 篇 材料科学与工程（可...
- 152 篇 力学（可授工学、理...
- 150 篇 建筑学
- 147 篇 土木工程
- 123 篇 网络空间安全
- 117 篇 环境科学与工程（可...
- 112 篇 交通运输工程
2,956 篇 理学
- 2,034 篇 数学
- 449 篇 物理学
- 397 篇 生物学
- 343 篇 系统科学
- 313 篇 统计学（可授理学、...
- 145 篇 化学
2,037 篇 管理学
- 1,501 篇 管理科学与工程(可...
- 712 篇 工商管理
- 667 篇 图书情报与档案管...
249 篇 医学
- 190 篇 临床医学
- 111 篇 基础医学(可授医学...
173 篇 经济学
- 172 篇 应用经济学
153 篇 法学
85 篇 农学
82 篇 教育学
41 篇 文学
11 篇 军事学
8 篇 艺术学

主题

2,974 篇 distributed comp...
1,756 篇 parallel process...
1,703 篇 concurrent compu...
1,632 篇 cloud computing
1,229 篇 computational mo...
1,086 篇 computer archite...
954 篇 grid computing
932 篇 computer science
783 篇 application soft...
757 篇 computer network...
615 篇 scalability
519 篇 distributed data...
514 篇 algorithm design...
507 篇 hardware
503 篇 peer to peer com...
494 篇 parallel algorit...
477 篇 high performance...
450 篇 software enginee...
445 篇 parallel computi...
442 篇 parallel program...

机构

52 篇 university of ch...
46 篇 institute of com...
41 篇 college of compu...
36 篇 department of co...
36 篇 college of intel...
31 篇 department of co...
29 篇 school of comput...
29 篇 national laborat...
29 篇 natl univ def te...
27 篇 school of comput...
24 篇 school of comput...
24 篇 shandong provinc...
23 篇 institute of par...
23 篇 institute of inf...
22 篇 univ chinese aca...
21 篇 university of sc...
21 篇 school of comput...
20 篇 shanghai jiao to...
20 篇 department of co...
19 篇 graduate univers...

作者

35 篇 li dongsheng
29 篇 dongsheng li
28 篇 liu jie
27 篇 duerr frank
26 篇 m. takizawa
26 篇 rajkumar buyya
26 篇 zomaya albert y.
24 篇 fahringer thomas
21 篇 jack dongarra
19 篇 yang yang
19 篇 prodan radu
18 篇 wei li
17 篇 li kenli
17 篇 wang guojun
17 篇 badia rosa m.
16 篇 liu yang
16 篇 p. banerjee
16 篇 dou yong
15 篇 lei wang
15 篇 xuejun yang

语言

23,954 篇 英文
592 篇 其他
89 篇 中文
17 篇 俄文
2 篇 土耳其文
2 篇 乌克兰文
1 篇 德文
1 篇 西班牙文
1 篇 法文

检索条件"任意字段=International Conference on Advances in Parallel and Distributed Computing"

共 24647 条记录，以下是4831-4840 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：

Incremental Analysis of Large-Scale System Logs for Anomaly Detection

Incremental Analysis of Large-Scale System Logs for Anomaly ...

引用

IEEE international conference on Big Data (Big Data)

作者： Astekin, Merve Ozcan, Selim Sozer, Hasan TUBITAK BILGEM Inst Informat Technol Kocaeli Turkey Ozyegin Univ Dept Comp Sci Istanbul Turkey

ISBN: (纸本)9781728108582

Anomalies during system execution can be detected by automated analysis of logs generated by the system. However, large scale systems can generate tens of millions of lines of logs within days. Centralized implementations of traditional machine learning algorithms are not scalable for such data. Therefore, we recently introduced a distributed log analysis framework for anomaly detection. In this paper, we introduce an extension of this framework, which can detect anomalies earlier via incremental analysis instead of the existing offline analysis approach. In the extended version, we periodically process the log data that is accumulated so far. We conducted controlled experiments based on a benchmark dataset to evaluate the effectiveness of this approach. We repeated our experiments with various periods that determine the frequency of analysis as well as the size of the data processed each time. Results showed that our online analysis can improve anomaly detection time significantly while keeping the accuracy level same as that is obtained with the offline approach. The only exceptional case, where the accuracy is compromised, rarely occurs when the analysis is triggered before all the log data associated with a particular session of events are collected.

关键词： log analysis distributed systems parallel processing anomaly detection big data machine learning

来源：评论

学校读者我要写书评

暂无评论

High-Performance Mining of COVID-19 Open Research Datasets for Text Classification and Insights in Cloud computing Environments

High-Performance Mining of COVID-19 Open Research Datasets f...

引用

IEEE international conference on Utility and Cloud computing (UCC)

作者： Jie Zhao Maria A. Rodriguez Rajkumar Buyya Cloud Computing and Distributed Systems Laboratory School of Computing and Information Systems The University of Melbourne Australia

ISBN: (数字)9780738123943

ISBN: (纸本)9781665415637

The COVID-19 global pandemic is an unprecedented health crisis. Many researchers around the world have produced an extensive collection of literature since the outbreak. Analysing this information to extract knowledge and provide meaningful insights in a timely manner requires a considerable amount of computational power. Cloud platforms are designed to provide this computational power in an on-demand and elastic manner. Specifically, hybrid clouds, composed of private and public data centers, are particularly well suited to deploy computationally intensive workloads in a cost-efficient, yet scalable manner. In this paper, we developed a system utilising the Aneka Platform as a Service middleware with parallel processing and multi-cloud capability to accelerate the data process pipeline and article categorising process using machine learning on a hybrid cloud. The results are then persisted for further referencing, searching and visualising. The performance evaluation shows that the system can help with reducing processing time and achieving linear scalability. Beyond COVID-19, the application might be used directly in broader scholarly article indexing and analysing.

关键词： Cloud computing Unified modeling language Task analysis COVID-19 Data visualization Computer architecture Scalability

来源：评论

学校读者我要写书评

暂无评论

distributed Artificial Neural Network Model for Neutron Flux Mapping in Nuclear Reactors

Distributed Artificial Neural Network Model for Neutron Flux...

引用

international conference on computing and Networking Technology (ICCNT)

作者： S. K. Bahuguna S. Mukhopadhyay A.P. Tiwari Bhabha Atomic Research Centre Homi Bhabha National Institute Mumbai

ISBN: (数字)9781728168517

ISBN: (纸本)9781728168524

Neutron flux distribution inside the core of large size nuclear reactors is a function of space and time. An online Flux Mapping System (FMS) is needed to monitor the core during the reactor operation. FMS estimates the core flux distribution from the measurements of few in-core detectors using an appropriate algorithm. Here, a distributed Artificial Neural Network (D-ANN) model is developed using parallel-forward multi-layer perceptron architecture to capture the spatial core flux variation in a nuclear reactor. The proposed D-ANN model is tested with simulated test case data of Advanced Heavy Water Reactor (AHWR) for multiple operating conditions of the reactor. The model estimates the neutron flux in all horizontal mesh locations (2-D) from the multiple networks distributed spatially across AHWR core. Estimation error using the proposed D-ANN model is found to be significantly lower than that with lumped ANN model. Validation exercises establish that this D-ANN model could effectively capture the spatial variations in the reactor core and therefore could be utilized for efficient flux mapping. The real time implementation of D-ANN based flux mapping method is also proposed.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Secure Door on Cloud: A Secure Data Transmission Scheme to Protect Kafka's Data

Secure Door on Cloud: A Secure Data Transmission Scheme to P...

引用

international conference on parallel and distributed Systems (ICPADS)

作者： Hanyi Zhang Liming Fang Keyu Jiang Weiting Zhang Minghui Li Lu Zhou Nanjing University of Aeronautics and Astronautics Nanjing China University of Aizu Fukushima-Ken Japan

ISBN: (数字)9781728190747

ISBN: (纸本)9781728183824

Apache Kafka, which is a high-throughput distributed message processing system, has been leveraged by the majority of enterprise for its outstanding performance. Unlike common cloud-based access control architectures, Kafka service providers often need to build their systems on other enterprises' high-performance cloud platforms. However, since the cloud platform belongs to a third party, it is not necessarily reliable. Paradoxically, it has been demonstrated that Kafka's data is stored in the cloud in the plaintext form, and thus poses a serious risk of user privacy leakage. In this paper, we propose a secure fine-grained data transmission scheme called Secure Door on Cloud (SDoC) to protect the data from being leaked in Kafka. SDoC is not only more secure than Kafka's built-in security mechanism, but also can effectively prevent third-party cloud from stealing plaintext data. To evaluate the performance of the SDoC, we simulate normal inter-entity communication and show that Kafka with SDoC integration has a lower data transfer time overhead than that of Kafka with built-in security mechanism opened.

关键词： Cloud computing Data security Data transfer Service-oriented architecture Security Reliability Secure storage

来源：评论

学校读者我要写书评

暂无评论

Proceedings of MLHPC 2019: 5th Workshop on Machine Learning in HPC Environments - Held in conjunction with SC 2019: The international conference for High Performance computing, Networking, Storage and Analysis

Proceedings of MLHPC 2019: 5th Workshop on Machine Learning ...

引用

5th IEEE/ACM Workshop on Machine Learning in HPC Environments, MLHPC 2019

ISBN: (纸本)9781728159850

The proceedings contain 8 papers. The topics discussed include: scalable hyperparameter optimization with lazy Gaussian processes;understanding scalability and fine-grain parallelism of synchronous data parallel training;DisCo: physics-based unsupervised discovery of coherent structures in spatiotemporal systems;GradVis: visualization and second order analysis of optimization surfaces during the training of deep neural networks;metaoptimization on a distributed system for deep reinforcement learning;scheduling optimization of parallel linear algebra algorithms using supervised learning;parallel data-local training for optimizing Word2Vec embeddings for word and graph embeddings;and fine-grained exploitation of mixed precision for faster CNN training.

关键词：

来源：评论

学校读者我要写书评

暂无评论

parallel mechanism-based robots for single and dual extrusion 3D printing

Parallel mechanism-based robots for single and dual extrusio...

引用

2019 conference on advances in Robotics, AIR 2019

作者： Veerapur, Vinay Zemase, Shritej Tillu, Pranav Dwarakanath, T.A. Department of Mechanical Engineering Pillai College of Engineering New Panvel Navi Mumbai410206 India Division of Remote Handling and Robotics BARC Mumbai400085 India

ISBN: (纸本)9781450366502

This paper deals with the development of 3D printing machine using a parallel mechanism based robot. Discussed topics are the high motion resolution, high rigidity, high precision and workspace constraints of the parallel robot in 3D printing. The single extrusion is extended to dual extrusion 3D printing to accommodate very high adaptability in composite material 3D printing. This paper proposes intelligent algorithms based on mirror manipulation. Demonstration of prototype arrangement of dual extrusion 3D printing is done. © 2019 Association for computing Machinery.

关键词： 3D printers

来源：评论

学校读者我要写书评

暂无评论

Privacy-Protected Blockchain System 20

Privacy-Protected Blockchain System

引用

20th IEEE international conference on Mobile Data Management (IEEE MDM)

作者： Zhong, Ping Zhong, Qikai Mi, Haibo Zhang, Shigeng Xiang, Yang Cent S Univ Changsha Hunan Peoples R China Natl Lab Parallel & Distributed Proc Changsha Hunan Peoples R China

ISBN: (纸本)9781728133638

The blockchain uses a decentralized consensus mechanism to maintain the books in an immutable way, which ensures the blockchain smart contract system highly secure. In existing blockchain systems, all user information is disclosed in the blockchain. However, currently users begin to pay more and more attention to personal privacy, therefore the future blockchain smart contract system needs not only to keep immutability but also to protect user privacy. To achieve this goal, in this paper we propose a Privacy-Protected Blockchain System, where all data is encrypted within a controllable period of time. Although the data is visible from a historical perspective, our design can effectively protect user privacy and against deceivers, making the system more secure and healthy.

关键词： Blockchain Smart contracts Encryption Data privacy Privacy Peer-to-peer computing

来源：评论

学校读者我要写书评

暂无评论

Understanding Hadoop Framework Through Single-Node Cluster Installation

Understanding Hadoop Framework Through Single-Node Cluster I...

引用

international conference on Recent advances in Energy-efficient computing and Communication (ICRAECC)

作者： V. G. Anisha Gnana Vincy T. Karthija J. Sunil Assistant Professor Department of Computer Science and Engineering V V College of Engineeing Tisaiyanvilai India Assistant Professor Department of Mechanical Engineering V V College of Engineeing Tisaiyanvilai India

ISBN: (纸本)9781538694831

Hadoop is a Java-based open source programming model that becomes a pillar in recent distributed computing by providing massive storage and multiprocessing of data. Hadoop becomes a simple and easy to implement programming model through the usage of commodity hardware. Hadoop open-source became a foundation for massive parallel processing of big data which includes scientific analytics, e-commerce data and sales planning, and processing enormous volumes of sensor from various sensors. Since Hadoop plays vital role in distributed parallel processing of big data, it is good to know the technical details behind the hadoop framework. This paper focus on detailing the necessary steps for the successful implementation of a Hadoop single-node cluster in a individual computer which provide a foundation for the new hadoop users.

关键词： Big Data Java parallel processing public domain software storage management parallel PROCESSING (COMPUTERS) big data open source software Store management Java Java programming language Sensors

来源：评论

学校读者我要写书评

暂无评论

A distributed complex event processing system based on publish/subscribe

A distributed complex event processing system based on publi...

引用

international conference on Intelligent computing, Communication and Devices, ICCD 2017

作者： Wang, Qi Shang, Yanlei Beijing University of Posts and Telecommunications Beijing China

ISBN: (纸本)9789811089435

The advent of the Internet of Things (IoT) significantly stimulates the development of context-aware applications. Complex event processing (CEP) is a technology for real-time data processing. However, a single node of CEP engine cannot keep up with the demand of high performance facing on the growing volume of sensor data. Many researches have focused on distributed complex event processing. In this paper, we propose a solution of distributed CEP based on pub/sub mechanism;by leveraging the loose coupling characteristics of pub/sub, it is easy to scale the system. The persistence storage and master–slave structure of the message broker also provide high reliability. Furthermore, we develop a configuration module for users to describe a complex event processing flow by a directed acyclic graph (DAG). The performance evaluation experiment demonstrates that our approach works well with large data set. © Springer Nature Singapore Pte Ltd. 2019.

关键词： Flow graphs

来源：评论

学校读者我要写书评

暂无评论

Distributing Sparse Matrix/Graph Applications in Heterogeneous Clusters - an Experimental Study

Distributing Sparse Matrix/Graph Applications in Heterogeneo...

引用

international conference on High Performance computing

作者： Charilaos Tzovas Maria Predari Henning Meyerhenke Humboldt-Universität zu Berlin Berlin Germany

Many problems in scientific and engineering applications contain sparse matrices or graphs as main input objects, e.g., numerical simulations on meshes. Large inputs are abundant these days and require parallel processing for memory size and speed. To optimize the execution of such simulations on cluster systems, the input problem needs to be distributed suitably onto the processing units (PUs). More and more frequently, such clusters contain different CPUs or a combination of CPUs and GPUs. This heterogeneity makes the load distribution problem quite challenging. Our study is motivated by the observation that established partitioning tools do not handle such heterogeneous distribution problems as well as homogeneous ones. In this paper, we first formulate the problem of balanced load distribution for heterogeneous architectures as a multiobjective, single-constraint optimization problem. We then split the problem into two phases and propose a greedy approach to determine optimal block sizes for each PU. These block sizes are then fed into numerous existing graph partitioners, for us to examine how well they handle the above problem. One of the tools we consider is an extension of our own previous work (von Looz et al., ICPP'18) called Geographer. Our experiments on well-known benchmark meshes indicate that only two tools under consideration are able to yield good quality. These two are ParMetis (both the geometric and the combinatorial variant) and Geographer. While ParMetis is faster, Geographer yields better quality on average.

关键词： Greedy algorithms High performance computing Memory management Tools parallel processing Numerical simulation Numerical models

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500页 << < 480 481 482 483 484 485 486 487 488 489 > >>

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：