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

3,176 篇 会议
42 册 图书
25 篇 期刊文献

馆藏范围

3,243 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

2,217 篇 工学
- 2,037 篇 计算机科学与技术...
- 1,329 篇 软件工程
- 423 篇 信息与通信工程
- 339 篇 电气工程
- 307 篇 控制科学与工程
- 156 篇 机械工程
- 128 篇 生物工程
- 124 篇 交通运输工程
- 116 篇 动力工程及工程热...
- 110 篇 生物医学工程（可授...
- 102 篇 安全科学与工程
- 81 篇 环境科学与工程（可...
- 72 篇 仪器科学与技术
- 70 篇 建筑学
- 67 篇 电子科学与技术（可...
677 篇 管理学
- 514 篇 管理科学与工程(可...
- 313 篇 工商管理
- 251 篇 图书情报与档案管...
500 篇 理学
- 246 篇 数学
- 138 篇 生物学
- 96 篇 统计学（可授理学、...
- 73 篇 系统科学
- 64 篇 物理学
152 篇 医学
- 141 篇 临床医学
- 131 篇 基础医学(可授医学...
- 76 篇 药学(可授医学、理...
- 75 篇 公共卫生与预防医...
138 篇 法学
- 105 篇 社会学
115 篇 经济学
- 114 篇 应用经济学
67 篇 教育学
- 67 篇 教育学
63 篇 农学
2 篇 文学
2 篇 军事学

主题

376 篇 big data
257 篇 internet of thin...
228 篇 cloud computing
133 篇 machine learning
130 篇 edge computing
123 篇 real-time system...
103 篇 data analytics
99 篇 artificial intel...
95 篇 smart cities
93 篇 intelligent sens...
84 篇 monitoring
81 篇 data models
79 篇 smart city
78 篇 data mining
74 篇 blockchain
72 篇 predictive analy...
64 篇 deep learning
64 篇 sensors
60 篇 iot
58 篇 security

机构

14 篇 jilin engineerin...
9 篇 hubei province k...
8 篇 school of comput...
8 篇 fujian provincia...
7 篇 institute for in...
7 篇 chitkara univers...
7 篇 liaoning jianzhu...
7 篇 school of econom...
6 篇 college of compu...
6 篇 fuzhou universit...
6 篇 symbiosis instit...
5 篇 china electric p...
5 篇 school of big da...
5 篇 luoyang normal u...
5 篇 smart agricultur...
5 篇 comsats univ isl...
5 篇 college of mecha...
5 篇 guangzhou colleg...
5 篇 electrical and i...
5 篇 university of ma...

作者

18 篇 javaid nadeem
9 篇 xu hongsheng
8 篇 leung carson k.
7 篇 zeng zeng
7 篇 xu xiaolong
7 篇 chang kuo-chi
7 篇 ramakrishnan ram...
6 篇 tang you
6 篇 doukovska lyubka
6 篇 wang wei
6 篇 cuzzocrea alfred...
5 篇 liu yang
5 篇 silva jesús
5 篇 vikrant bhateja
5 篇 fan ganglong
5 篇 vale zita
5 篇 qiu meikang
5 篇 cristea valentin
5 篇 stoyanov stanimi...
5 篇 wang yong

语言

3,183 篇 英文
49 篇 其他
21 篇 中文

检索条件"任意字段=International Conference on Intelligent and Smart Computing in Data Analytics, ISCDA 2020"

共 3243 条记录，以下是251-260 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：

The Impact of data Quality on Neural Network Models

The Impact of Data Quality on Neural Network Models

引用

international conference on Cyber Security Intelligence and analytics (CSIA)

作者： Li, Chunmei Li, Zhao Jun, Xu Pi, Wei Qinghai Univ Dept Comp Technol & Applicat Xining Qinghai Peoples R China China Mobile Commun Grp Guangxi Co Ltd Guilin Peoples R China

ISBN: (纸本)9783030152352;9783030152345

This paper introduces the neural network evaluates Sanjiangyuan grassland degradation degree evaluation model from three aspects: data source, the neural network design and experimental process analysis. It focuses on analyzing the impact of training data quality on neural network quality and points out that the importance of data quality in big data era.

关键词： Grassland degradation Evaluation Neural network Big data

来源：评论

学校读者我要写书评

暂无评论

Spatial data Science of COVID-19 data 22

Spatial Data Science of COVID-19 Data

引用

22nd IEEE international conference on High Performance computing and Communications, 18th IEEE international conference on smart City and 6th IEEE international conference on data Science and Systems, HPCC-smartCity-DSS 2020

作者： Shang, Siyuan Leung, Carson K. Chen, Yubo Pazdor, Adam G.M. University of Manitoba Department of Computer Science WinnipegMB Canada

ISBN: (纸本)9781728176499

Huge amounts of big data can be generated and collected from a wide variety of rich data sources. Embedded in these big data are useful information and valuable knowledge. An example is healthcare and epidemiological data such as data related to patients who suffered from viral diseases like the coronavirus disease 2019 (COVID-19). Knowledge discovered from these epidemiological data via data science helps researchers, epidemiologists and policy makers to get a better understanding of the disease, which may inspire them to come up ways to detect, control and combat the disease. In this paper, we present a spatial data science system for analyzing big COVID-19 epidemiological data, with focus on the spatial data analytics among different geographic locations. The system helps users to get a better understanding of information about the confirmed cases of COVID-19. Evaluation results show the benefits of our system in spatial data analytics of big COVID-19 data. © 2020 IEEE.

关键词： Coronavirus

来源：评论

学校读者我要写书评

暂无评论

Autonomous network traffic control system based on intelligent edge computing 21

Autonomous network traffic control system based on intellige...

引用

21st international conference on Advanced Communication Technology (ICACT)

作者： Kim, Kwihoon Hong, Yong-Geun ETRI 218 Gajeong Ro Daejeon 34129 South Korea

ISBN: (纸本)9791188428021

This paper considers an intelligent network traffic control technology for high-reliability IoT services based on edge computing technology featuring modular micro-service computing technology, intelligent traffic analysis and predictive technologies for various applications. This paper proposes an autonomous network traffic control system that takes into account the recycling of edge technologies. intelligent internet live monitoring service that provides online display of noise, vibration, gas readings, and field images on site as quickly as possible in the event of a civil complaint and efficiently store to prevent on-site images. This intelligent IoT edge computing technology proposes the structure, procedures, configuration and behaviour of intelligent IoT edge computing technologies, including IoT Things, data collection, data analytics capabilities, and gateways for delivering processed information to cloud servers. It applied smart construction monitoring as a representative service example.

关键词： machine learning data generator deep learning network machine learning supervised learning

来源：评论

学校读者我要写书评

暂无评论

international conference on Machine Learning and Big data analytics for IoT Security and Privacy, SPIoT 2020

International Conference on Machine Learning and Big Data An...

引用

international conference on Machine Learning and Big data analytics for IoT Security and Privacy, SPIoT 2020

ISBN: (纸本)9783030627454

The proceedings contain 126 papers. The special focus in this conference is on Machine Learning and Big data analytics for IoT Security and Privacy. The topics include: Development of Industrial Chain of Internet of Things Based on 5G Communication Technique;path Choice of smart City Construction from the Perspective of Economic Growth;computer Audit Quality Control in Big data Era;MOOC System in the Era of Big data Improves the Effectiveness of College Physical Education;Risks and Prevention in the Application of AI;improvement of Microblog Recommendation System Based on Interaction Strategies of Agricultural E-Commerce Enterprise;exploration and Construction of "One Ring, Three Deductions" Innovation and Entrepreneurship Talent Cultivation Model for Higher Vocational Art Design Major Based on Information Technology;research Progress of Neuroimaging Techniques in Organizational Behavior Under the Background of smart City;recommendation Strategies for smart Tourism Scenic Spots Based on smart City;control Strategy of Environmental Control System in Power Transmission;design and Implementation of Self-service Tourism Management Information System Based on B/S Architecture;MATLAB Software in the Numerical Calculation of Civil Engineering;Low Latency V2X Application of MEC Architecture in Traffic Safety;cloud computing Technology for the Network Resource Allocation on the Research of Application;talent Evaluation Model of College Students Based on Big data Technology;application of Cloud Class in Comprehensive English Teaching in the Context of Internet Plus;the Application of 3D Printing Technology in Sculpture;the Development Strategy of Current Medical Scientific Research Information;on the Development of the Industry Trend of "Ai+Education".

关键词：

来源：评论

学校读者我要写书评

暂无评论

Sensors data collection architecture in the Internet of Mobile Things as a service (IoMTaaS) platform

Sensors data collection architecture in the Internet of Mobi...

引用

international conference on I-SMAC (IoT in Social, Mobile, analytics and Cloud) (I-SMAC)

作者： Maiti, Prasenjit Sahoo, Bibhudatta Turuk, Ashok Kumar Satpathy, Suchismita Natl Inst Technol Dept Comp Sci & Engn Rourkela Odisha India

ISBN: (纸本)9781509032433

smart object interconnected between each other and producing a large volume of information in Internet of Mobile Things (IoMT) is a huge challenge. The things that we expect to connect to the Internet will consist of sensors, actuators with information processing and communication capabilities that will make themselves intelligent. Sensors are collecting continuously environmental data (e.g. body area network, smart city, cars, smartphones, etc.). We used Arduino, XBee, Raspberry Pi 3 and open source software for framework design. This architecture process real-time data and maximize the delivery of raw data to the cloud for post processing. It also ensure efficient eventdriven data collection given the buffer space and communication bandwidth limitations of each sensor. An intelligent IoMT gateway and middleware used to support different message format of sensor data and efficient decision-making system. We also propose an Android data collection system where data collectors are smartphones. This paper defines a data collection architecture supporting the physical dimension of sensors to the storage of data in a cloud-based service. This class of architecture must tackle several challenges, e.g., buffer management, sensor message ordering, data alignment for multiple temporal data streams, data storage, sensor heterogeneity, high throughput and avoiding processing bottlenecks. For the issues of an extended advancement cycle, poor transportability and high-chance in the improvement procedure of ZigBee remote system, presents the Unified Modeling Language (UML) to institutionalize the advancement procedure, enhancing improvement productivity and guaranteeing item quality.

关键词： Architecture Cloud data collection Distributed computing Sensors UML

来源：评论

学校读者我要写书评

暂无评论

international conference on Machine Learning and Big data analytics for IoT Security and Privacy, SPIoT 2020

International Conference on Machine Learning and Big Data An...

引用

international conference on Machine Learning and Big data analytics for IoT Security and Privacy, SPIoT 2020

ISBN: (纸本)9783030627423

关键词：

来源：评论

学校读者我要写书评

暂无评论

Big data analytics Concepts, Technologies Challenges, and Opportunities 5th

Big Data Analytics Concepts, Technologies Challenges, and Op...

引用

5th international conference on Advanced intelligent Systems and Informatics (AISI)

作者： Shehab, Noha Badawy, Mahmoud Arafat, Hesham Mansoura Univ Fac Engn Comp Engn & Control Syst Dept Mansoura Egypt

ISBN: (纸本)9783030311292;9783030311285

The rapid observed increase in using the Internet led to the presence of huge amounts of data. Traditional data technologies, techniques, and even applications cannot cope with the new data's volume, structure, and types of styles. Big data concepts come to assimilate this non-stop flooding. Big data analysis process used to jewel the useful data and exclude the other one which provides better results with minimum resource utilization, time, and cost. Feature selection principle is a traditional data dimension reduction technique, and big data analytics provided modern technologies and frameworks that feature selection can be integrated with them to provide better performance for the principle itself and help in preprocessing of big data on the other hand. The main objective of this paper is to survey the most recent research challenges for big data analysis and preprocessing processes. The analysis is carried out via acquiring data from resources, storing them, then filtered to pick up the useful ones and dismissing the unwanted ones then extracting information. Before analyzing data, it needs preparation to remove noise, fix incomplete data and put it in a suitable pattern. This is done in the preprocessing step by various models like data reduction, cleaning, normalization, preparation, integration, and transformation.

关键词： Big data analytics Big data preprocessing Feature selection Flink

来源：评论

学校读者我要写书评

暂无评论

The Role of Cloud computing in Real-Time Big data analytics for smart Cities and Infrastructure Automation 15

The Role of Cloud Computing in Real-Time Big Data Analytics ...

引用

15th international conference on computing Communication and Networking Technologies, ICCCNT 2024

作者： Sarpal, Sumeet Singh Kumar, V. Mathan Pimplapure, Vivek Patil, Shrinivas Marathe, Vijay Henrietta, H. Mary Chitkara University Institute of Engineering and Technology Chitkara University Punjab India Karpagam Academy of Higher Education Department of Computer Science Coimbatore641021 India Dr. Ambedkar Institute of Management Studies And Research Department of Management Nagpur India School of Mangement - Pg Karnataka Bangalore India Prince Shri Vishwakarma Institute of Technology Department of Electrical Pune India Saveetha Engineering College Department of Mathematics Tamil Nadu Chennai602105 India

ISBN: (纸本)9798350370249

With the enhancement of Big data and smart Cities, Cloud computing has emerged as an advanced technology. Innovative city operations require real-time processing of vast volumes of data from various sources like sensors, IOT devices, or social media so that it can be analyzed and acted on in real-time with better automation for its infrastructure against different parameters. This article examines the potential of cloud computing to enable real-time big data analytics for smart cities and infrastructure automation. The cloud allows for real-time big data analytics, collecting input from disparate sources across a business ecosystem and analyzing it immediately for actionable insights. The need for large amounts of data combined with the nature of many Iota devices necessitates processing and storage at scale, a task uniquely suited to cloud computing due to its ability to provide scalability, flexibility, and lower cost essential qualities in building intelligent cities or automated infrastructure. Cloud computing offers a space for shared data and collaborative analysis, allowing the city government to open up its vast browser-based datasets so that other agencies (both within government and outside it), researchers, and even citizens can access this information, in turn driving innovation or assisting with strategic planning. Moreover, the evolution not just in cloud-based machine learning and artificial intelligence algorithms but also device-side AI/ML allows for predictive analytics, which can be helpful to preemptively discern potential failures to prevent them pro-actively, thus augmenting city operations efficacy as well as resource utilization besides operational efficiency of infrastructural management. Cloud computing is integral for real-time and big data analytics and innovates cities, organizations, and infrastructure. © 2024 IEEE.

关键词： Automation Infrastructure intelligent Organizations Parameters

来源：评论

学校读者我要写书评

暂无评论

Designing smart-Contract Based Auctions 2nd

Designing Smart-Contract Based Auctions

引用

2nd international conference on Security with intelligent computing and Big-data Services (SICBS)

作者： Braghin, Chiara Cimato, Stelvio Damiani, Ernesto Baronchelli, Michael Univ Milan Dipartimento Informat Milan Italy Khalifa Univ Ctr Cyber Phys Syst Abu Dhabi U Arab Emirates

ISBN: (纸本)9783030169466;9783030169459

In this paper, we developed an online auction system based on Ethereum smart contracts. A smart contract is executable code that runs on top of the blockchain to facilitate, execute and enforce an agreement between untrusted parties without the involvement of a trusted third party. A decentralised auction guarantees greater transparency and avoids cheating auctioneers. Since in Ethereum computation is expensive as transactions are executed and verified by all the nodes on Ethereum network, we analysed our implementation in terms of cost and time efficiency, obtaining promising results.

关键词： Auction Blockchain smart contract

来源：评论

学校读者我要写书评

暂无评论

Predictive analytics for Human Resource Management: Enhancing Talent Acquisition and Retention Using data analytics

Predictive Analytics for Human Resource Management: Enhancin...

引用

2024 international conference on Innovative computing, intelligent Communication and smart Electrical Systems, ICSES 2024

作者： Radhasri, D. Easwara Moorthy, R. Vinothini, K. Karthikeyan, S. Aswini, L. Dr.SNS Rajalakshmi College of Arts and Science Department of Commerce Tamilnadu India

ISBN: (纸本)9798331543617

HRM depends on the output of predictive analytics by which the input achieves accurate data on employee hiring and retention. For enhancing the decision-making in the HR domain, this research proposes a novel multi-modal logistic regression, XGBoost, and deep learning-based designated hybrid prediction model. Due to the integration of several more common and uncommon HR datasets and richer feature engineering techniques, the mentioned model eliminates the limitations of previous studies. These enhance the chances of applicant selection and consequently the chances of the applicants' retention. The proposed hybrid model achieved 91.4% accuracy for applicant selection and 89.7% for employee retention;the accuracy of the models developed in the years 2021, 2022 & 2023, was 82.3%, 84.9%, and 87.4% respectively. Its implementation using IBM Watson and Kafka will afford HR managers practical real-time information from the model. Lastly, the benefits of applying the model to enhance the HR procedures are highlighted and recommendations for further work to increase the model's applicability in other areas are made. © 2024 IEEE.

关键词： data accuracy

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325页 << < 22 23 24 25 26 27 28 29 30 31 > >>

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：