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

3,226 篇 会议
72 篇 期刊文献
54 册 图书

馆藏范围

3,352 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

2,174 篇 工学
- 1,931 篇 计算机科学与技术...
- 702 篇 软件工程
- 418 篇 电气工程
- 333 篇 信息与通信工程
- 181 篇 控制科学与工程
- 79 篇 仪器科学与技术
- 75 篇 生物医学工程（可授...
- 64 篇 生物工程
- 48 篇 机械工程
- 46 篇 航空宇航科学与技...
- 35 篇 电子科学与技术（可...
- 33 篇 化学工程与技术
- 30 篇 光学工程
- 30 篇 网络空间安全
- 28 篇 动力工程及工程热...
- 27 篇 交通运输工程
423 篇 管理学
- 285 篇 管理科学与工程(可...
- 139 篇 图书情报与档案管...
- 74 篇 工商管理
399 篇 理学
- 199 篇 数学
- 116 篇 物理学
- 87 篇 生物学
- 68 篇 统计学（可授理学、...
- 52 篇 系统科学
- 45 篇 化学
- 42 篇 地球物理学
77 篇 医学
- 63 篇 基础医学(可授医学...
- 57 篇 临床医学
- 36 篇 药学(可授医学、理...
56 篇 法学
- 51 篇 社会学
28 篇 教育学
26 篇 经济学
12 篇 农学
4 篇 文学
3 篇 艺术学
1 篇 军事学

主题

1,151 篇 data mining
336 篇 big data
212 篇 cloud computing
150 篇 data models
123 篇 feature extracti...
118 篇 algorithm design...
95 篇 databases
80 篇 computational mo...
74 篇 clustering algor...
72 篇 training
71 篇 semantics
71 篇 machine learning
65 篇 conferences
63 篇 clustering
63 篇 support vector m...
63 篇 servers
61 篇 classification a...
56 篇 classification
56 篇 sentiment analys...
52 篇 predictive model...

机构

41 篇 infn sezione di ...
41 篇 infn sezione di ...
41 篇 universidade de ...
41 篇 universidad de m...
41 篇 universidade de ...
41 篇 torino
41 篇 palacky universi...
41 篇 palermo
41 篇 infn sezione di ...
41 篇 institute for as...
41 篇 infn sezione di ...
41 篇 rwth aachen univ...
41 篇 institut für pro...
41 篇 centro federal d...
41 篇 university of ad...
41 篇 charles universi...
41 篇 universität hamb...
40 篇 infn sezione di ...
40 篇 sorbonne univers...
40 篇 cnrs in2p3 ijcla...

作者

42 篇 aloisio r.
41 篇 almeida cheminan...
41 篇 aglietta m.
41 篇 anastasi g.a.
41 篇 buscemi m.
41 篇 catalani f.
41 篇 de souza v.
40 篇 bismark k.
40 篇 fazzini n.
40 篇 avila g.
40 篇 emam m.
40 篇 de mitri i.
40 篇 covault c.e.
40 篇 deligny o.
40 篇 condorelli a.
40 篇 cataldi g.
40 篇 cobos cerutti a....
40 篇 brack j.
40 篇 conte m.
40 篇 di matteo a.

语言

3,297 篇 英文
33 篇 其他
18 篇 中文
2 篇 葡萄牙文
2 篇 俄文
1 篇 德文

检索条件"任意字段=2016 International Conference on Data Mining and Advanced Computing, SAPIENCE 2016"

共 3352 条记录，以下是621-630 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：

Application and Adoption of Big data Technologies in SMEs

Application and Adoption of Big Data Technologies in SMEs

引用

international conference on Computational Science and Computational Intelligence (CSCI)

作者： Lila Rajabion Department of Information Technology University of South Florida Sarasota U.S.A

Recent years have witnessed a phenomenal growth in Small and Medium-Sized Enterprises (SMEs) and entrepreneurs all over the world. SMEs have played an essential role in transforming the American economy. SMEs forms 99 percent of all firms in the country, employ more than 50 percent of private sector employees, and account for more than 50% of the country's nonfarm GDP (Brief, 2000). Despite its role in the economy, SMEs are facing challenges in using vast chunks of data available to build a competitive environment that is significant for economic growth (Blackburn, 2016). Much of the data produced can either have a direct or indirect effect on the sector if well processed. Some of the data produced can be used to make relevant policies and decisions regarding supply chain, customer management, and market changes. To make good use of these enormous volumes of data, firms have employed available big data analytics. Although data mining has been in existence for a while now, it is until recently that big data has found its application in business. This paper intends to outline the adoption rates of big data in SMEs in the US. However, concepts of Business Intelligence (BI) was later developed to emphasize the need for the collection, analysis, and interpretation of that data for business use. With the use of BI, much of the produced data have been analyzed to help businesses make data-driven decisions which have helped them understand market trends. SMEs have for a long time used data for recording and monitoring transactions. However, in the recent past, a new awareness of the importance of data analytics have been going around. Consequently, a large number of SMEs have demonstrated an interest in using business analytics.

关键词： Big data Organizations Tools Cloud computing Social networking (online) Market research

来源：评论

学校读者我要写书评

暂无评论

An Innovative Method to Mitigate DDoS Attacks for Cloud Environment Using Bagging and Stacking 1st

An Innovative Method to Mitigate DDoS Attacks for Cloud Envi...

引用

1st international conference on Computational Intelligence and Informatics (ICCII)

作者： Kiranmai, B. Damodaram, A. Keshav Mem Inst Technol Hyderabad Andhra Pradesh India Sri Venkateswara Univ Tirupati Andhra Pradesh India

ISBN: (纸本)9789811024719;9789811024702

This paper describes an approach for mitigating distributed denial-of-services attacks in Cloud. DDoS attacks are huge pitfall for Cloud, and still, this is not very well handled. We presented a survey of existing work to defend DDoS attacks and mechanisms. In Cloud, intruder detection systems can be deployed at various positions like front-end, back-end or at Virtual Machine. Most of the existing IDS have been deployed at Virtual Machine in cloud. We proposed a new frame work using ensemble classifiers, namely, Bagging and Stacking to detect intrusions of both insiders and outsiders, and our proposed frame work will deploy at back-end. We focused on defending DDoS attacks in cloud environment which are the bottle neck of a Cloud environment compared to other type of attacks.

关键词： Cloud computing Intrusion detection system data mining techniques Weka WireShark

来源：评论

学校读者我要写书评

暂无评论

Stereoscopic 3D Graph Visualization for Assisted data Exploration and Discovery 10th

引用

10th international on conference Multimedia and Network Information Systems (MISSI)

作者： Turek, Michal Palka, Dariusz Zachara, Marek AGH Univ Sci & Technol Krakow Poland

ISBN: (纸本)9783319439822;9783319439815

data structures and relations are becoming increasingly complex and difficult to assess and manage. Although automated rules and algorithms can be used for many data-mining tasks, there are still situations where human attention and insight is required to identify unexpected circumstances or unanticipated patterns. Presentation of large quantities of data has always been a challenging task. In this paper a method for representing large graph-based data sets is proposed to help users navigate through large clusters of data. The proposed method is based on a stereoscopic 3D visualization with special enhancements for a large multi node graph visualization. The stereoscopic projection allows for utilization of techniques that can draw users' attention to particular regions of the graph. The method uses specially established node-node relations to calculate attention drawing factor values for each graph node.

关键词： Stereoscopy Visualization Graphs data exploration

来源：评论

学校读者我要写书评

暂无评论

11th international conference on Ubiquitous Information Technologies and Applications, CUTE 2016

11th International Conference on Ubiquitous Information Tech...

引用

11th international conference on Ubiquitous Information Technologies and Applications, CUTE 2016

ISBN: (纸本)9789811030222

The proceedings contain 171 papers. The special focus in this conference is on Ubiquitous Information Technologies and Applications. The topics include: Design and development of a robotic arm for rehabilitation and training;intelligent food distribution monitoring system;real-time dynamic motion capture using multiple kinects;SOA based equipment data management system for smart factory;the problem analysis of specific personal information protection assessment in Japan case;using a fine-grained hybrid feature for malware similarity analysis;finding comfortable settings of snake game using game refinement measurement;initialization of software defined wireless bacteria-inspired network platform;an extension of QSL for E-voting systems;a clustered index structure for efficient sequential access;performance analysis of tree-based algorithms for incremental high utility pattern mining;EPD noticeboard for posting multiple information;resource pooling mechanism for mobile cloud computing service;a comparison of data mining methods in analyzing educational data;survey of MCC architectures for computing service;drone classification by available control distances;platform independent workflow mechanism for bigdata analytics;water surface simulation based on perlin noise and secondary distorted textures;restoration method for satellite image based on content-aware reciprocal cell pool;classification algorithms for privacy preserving in data mining: a survey;a secure system framework for an agricultural IoT application;localization technology in wireless sensor networks using RSSI and LQI;a user empirical context model for a smart home simulator and a study of malicious code classification system using minhash in network quarantine using SDN.

关键词：

来源：评论

学校读者我要写书评

暂无评论

data Acquisition Solutions For Electricity Consumers Connected To Smart Grids 18

Data Acquisition Solutions For Electricity Consumers Connect...

引用

18th international Carpathian Control conference (ICCC)

作者： Oprea, Simona Vasilica Bara, Adela Mircea, Marinela Bucharest Univ Econ Studies Dept Econ Informat & Cybernet Bucharest Romania

ISBN: (纸本)9781509048625

More and more devices are nowadays connected all over the world creating a complex grid that generates large volume of data. This is enhanced by various smart metering applications that collect, process, analyze heterogeneous data sets and extract valuable information to their owners. Apart from conventional energy meters that provides only monthly feedback regarding the total consumption, smart meters allow shorter time intervals readings, implementation of advanced tariff scheme, less effort regarding physical reading and other benefits for grid operators and electricity consumers. In this paper we propose an architecture that includes several acquisition data protocols, data integration in relational and NoSQL databases, business intelligence solution and cloud computing that offer more information regarding electricity consumption for individual appliances. Based on these features, consumers will be able to analyze the efficiency of particular appliances or group of appliances for cooling, illumination, ventilation and so and to identify obsolete appliances that should be replaced. They could also rapidly identify interruptions, spikes or other abnormal operation by notifications and alerts. This way smart meters activate the electricity consumers' behavior by stimulating energy awareness and savings. Cloud computing provides capabilities for smart grid platforms in storage, analysis, and applications (elastic resources, shared services, energy management), and addresses some challenges and opportunities of smart grid. We will also propose an alternative, cheaper and more flexible smart meter built on an Arduino platform that could bring more data and information than a smart meter.

关键词： Arduino platform smart metering electricity appliances database cloud computing

来源：评论

学校读者我要写书评

暂无评论

FitCNN: A Cloud-Assisted Lightweight Convolutional Neural Network Framework for Mobile Devices 23

FitCNN: A Cloud-Assisted Lightweight Convolutional Neural Ne...

引用

23rd IEEE international conference on Embedded and Real-Time computing Systems and Applications (RTCSA)

作者： Li, Shiming Liu, Duo Xiang, Chaoneng Liu, Jianfeng Ling, Yingjian Liao, Tianjun Liang, Liang Chongqing Univ Coll Comp Sci Chongqing Peoples R China Chongqing Univ Coll Commun Engn Chongqing Peoples R China

ISBN: (纸本)9781538618981

Recently convolutional neural networks (CNNs) have essentially reached the state-of-the-art accuracies in image classification and recognition. CNNs are usually deployed in server side or cloud to handle tasks collected from mobile devices, such as smartphones, wearable devices, unmanned systems and so on. However, significant data transmission overhead and privacy issues have made it necessary to use CNNs directly in device side. Nevertheless, the statically trained model deployed on mobile devices cannot effectively handle the unknown data and objects in new environments, which could lead to low accuracy and unsatisfied user experience. Hence, it would be crucial to retrain a better model via future unknown data. However, with tremendous computing cost and memory usage, training a CNN on mobile devices with limited hardware resources is intolerable in practical. To solve this issue, by using the power of cloud is a promising solution to assist mobile devices to train a deep neural network. Therefore, this paper proposes a cloud-assisted lightweight CNN framework, named FitCNN, with incremental learning and low data transmission, to deploy CNNs on mobile devices and make them smarter. To reduce the data transmission during incremental learning, we propose a strategy to selectively upload the data with high learning value, and develop an extracting strategy to choose light weights of the new CNN model trained on the cloud to update the old one on devices. Experimental results show that the selectively uploading strategy can reduce 39.4% uploading transmission based on a certain dataset, and the extracting weights strategy reduces by more than 60% updating transmission with multiple CNNs and datasets.

关键词： data models Mobile handsets data communication Neural networks Training Computational modeling data mining

来源：评论

学校读者我要写书评

暂无评论

Exploiting analytics techniques in CMS computing monitoring 22

Exploiting analytics techniques in CMS computing monitoring

引用

22nd international conference on computing in High Energy and Nuclear Physics, CHEP 2016

作者： Bonacorsi, D. Kuznetsov, V. Magini, N. Repečka, A. Vaandering, E. Universita di Bologna Bologna Italy Cornell University IthacaNY United States Fermi National Accelerator Laboratory BataviaIL United States University of Vilnius Vilnius Lithuania

The CMS experiment has collected an enormous volume of metadata about its computing operations in its monitoring systems, describing its experience in operating all of the CMS workflows on all of the Worldwide LHC computing Grid Tiers. data mining efforts into all these information have rarely been done, but are of crucial importance for a better understanding of how CMS did successful operations, and to reach an adequate and adaptive modelling of the CMS operations, in order to allow detailed optimizations and eventually a prediction of system behaviours. These data are now streamed into the CERN Hadoop data cluster for further analysis. Specific sets of information (e.g. data on how many replicas of datasets CMS wrote on disks at WLCG Tiers, data on which datasets were primarily requested for analysis, etc) were collected on Hadoop and processed with MapReduce applications profiting of the parallelization on the Hadoop cluster. We present the implementation of new monitoring applications on Hadoop, and discuss the new possibilities in CMS computing monitoring introduced with the ability to quickly process big data sets from mulltiple sources, looking forward to a predictive modeling of the system. © Published under licence by IOP Publishing Ltd.

关键词： data mining

来源：评论

学校读者我要写书评

暂无评论

FLAP: An End-to-End Event Log Analysis Platform for System Management 17

FLAP: An End-to-End Event Log Analysis Platform for System M...

引用

23rd ACM SIGKDD international conference on Knowledge Discovery and data mining (KDD)

作者： Li, Tao Jiang, Yexi Zeng, Chunqiu Xia, Bin Liu, Zheng Zhou, Wubai Zhu, Xiaolong Wang, Wentao Zhang, Liang Wu, Jun Xue, Li Bao, Dewei Florida Int Univ Nanjing Univ Posts & Telecommun Miami FL 33199 USA Florida Int Univ Comp & Informat Sci Miami FL 33199 USA Nanjing Univ Posts & Telecommun Comp Sci Nanjing Jiangsu Peoples R China Huawei Nanjing Res & Dev Ctr Nanjing Jiangsu Peoples R China

ISBN: (纸本)9781450348874

Many systems, such as distributed operating systems, complex networks, and high throughput web-based applications, are continuously generating large volume of event logs. These logs contain useful information to help system administrators to understand the system running status and to pinpoint the system failures. Generally, due to the scale and complexity of modern systems, the generated logs are beyond the analytic power of human beings. Therefore, it is imperative to develop a comprehensive log analysis system to support effective system management. Although a number of log mining techniques have been proposed to address specific log analysis use cases, few research and industrial efforts have been paid on providing integrated systems with an end-to-end solution to facilitate the log analysis routines. In this paper, we design and implement an integrated system, called FIU Log Analysis Platform (a.k.a. FLAP), that aims to facilitate the data analytics for system event logs. FLAP provides an end-to end solution that utilizes advanced data mining techniques to assist log analysts to conveniently, timely, and accurately conduct event log knowledge discovery, system status investigation, and system failure diagnosis. Specifically, in FLAP, state-of-the-art template learning techniques are used to extract useful information from unstructured raw logs;advanced data transformation techniques are proposed and leveraged for event transformation and storage;effective event pattern mining, event summarization, event querying, and failure prediction techniques are designed and integrated for log analytics;and user-friendly interfaces are utilized to present the informative analysis results intuitively and vividly. Since 2016, FLAP has been used by Huawei Technologies Co. Ltd for internal event log analysis, and has provided effective support in its system operation and workflow optimization.

关键词： data mining System Log Processing Event mining Event Summarization

来源：评论

学校读者我要写书评

暂无评论

Coflourish: An SDN-Assisted Coflow Scheduling Framework for Clouds 10

Coflourish: An SDN-Assisted Coflow Scheduling Framework for ...

引用

10th IEEE international conference on Cloud computing (CLOUD)

作者： Chiu, Chui-Hui Singh, Dipak Kumar Wang, Qingyang Park, Seung-Jong Louisiana State Univ Ctr Computat & Technol Div Comp Sci & Engn Baton Rouge LA 70803 USA

ISBN: (纸本)9781538619933

Existing coflow scheduling frameworks effectively shorten communication time and completion time of cluster applications. However, existing frameworks only consider available bandwidth on hosts and overlook congestion in the network when making scheduling decisions. Through extensive simulations using the realistic workload probability distribution from Facebook, we observe the performance degradation of the state-of-the-art coflow scheduling framework, Varys, in the cloud environment on a shared data center network (DCN) because of the lack of network congestion information. We propose Coflourish, the first coflow scheduling framework that exploits the congestion feedback assistances from the software-defined-networking(SDN)-enabled switches in the networks for available bandwidth estimation. Our simulation results demonstrate that Coflourish outperforms Varys by up to 75.5% in terms of average coflow completion time under various workload conditions. The proposed work also reveals the potentials of integration with traffic engineering mechanisms in lower levels for further performance optimization.

关键词： Application-aware Networks Coflow Scheduling data Center Networks Software-defined Networking Cloud computing

来源：评论

学校读者我要写书评

暂无评论

1st international conference on Intelligent computing and Communication, ICIC2 2016

1st International Conference on Intelligent Computing and Co...

引用

1st international conference on Intelligent computing and Communication, ICIC2 2016

ISBN: (纸本)9789811020346

The proceedings contain 70 papers. The special focus in this conference is on Biomedical Image Processing, Bioinformatics, Cloud computing, Communication Network, Device System, Modeling, Security and Cryptography. The topics include: Concentration of acetone levels in breath for monitoring blood glucose level;an insight into signal transduction for ophthalmology;common subcluster mining to explore molecular markers of lung cancer;intelligent storage management using cloud shared disk architecture;introspecting effect of packet size on end-to-end network delay;an ontology based context aware protocol in healthcare services;link based protection of light trail in WDM mesh networks;event detection over twitter social media;comparative study of parallelism on data mining;brief review on optimal suffix data structures;closure based integrated approach for associative classifier;a novel mapreduce based k-means clustering;cross-coupled dynamic CMOS latches;cross-coupled dynamic CMOS latches;design based new coupling metric for component based development environment;scientific workflow management system for community model in data fusion;a new implementation scheme in robotic vehicle propulsion using brushless DC motor;binary fuzzy goal programming for effective utilization of IT professionals;AVR microcontroller based conference presentation timer;a person identification system with biometrics using modified RBFN based multiple classifiers;automatic measurement and analysis of vessel width in retinal fundus image;an eigencharacter technique for offline-tamil handwritten character recognition;page-to-word extraction from unconstrained handwritten document images and a novel approach to E-Voting using multi-bit steganography.

关键词：

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336页 << < 59 60 61 62 63 64 65 66 67 68 > >>

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：