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

1,325 篇 会议
27 册 图书
7 篇 期刊文献

馆藏范围

1,359 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

973 篇 工学
- 918 篇 计算机科学与技术...
- 635 篇 软件工程
- 236 篇 信息与通信工程
- 131 篇 控制科学与工程
- 101 篇 生物工程
- 97 篇 电气工程
- 64 篇 安全科学与工程
- 60 篇 动力工程及工程热...
- 58 篇 交通运输工程
- 58 篇 网络空间安全
- 47 篇 机械工程
- 47 篇 生物医学工程（可授...
- 42 篇 仪器科学与技术
- 29 篇 建筑学
- 28 篇 环境科学与工程（可...
354 篇 理学
- 183 篇 数学
- 113 篇 生物学
- 74 篇 统计学（可授理学、...
- 58 篇 化学
- 41 篇 物理学
- 31 篇 系统科学
347 篇 管理学
- 237 篇 管理科学与工程(可...
- 213 篇 图书情报与档案管...
- 121 篇 工商管理
62 篇 法学
- 52 篇 社会学
61 篇 医学
- 54 篇 临床医学
- 50 篇 基础医学(可授医学...
- 32 篇 药学(可授医学、理...
47 篇 经济学
- 47 篇 应用经济学
28 篇 教育学
- 28 篇 教育学
14 篇 农学
7 篇 文学
2 篇 军事学

主题

256 篇 big data
79 篇 artificial intel...
67 篇 cloud computing
63 篇 machine learning
50 篇 computational mo...
49 篇 deep learning
42 篇 internet of thin...
41 篇 data models
35 篇 training
27 篇 data mining
25 篇 neural networks
24 篇 smart cities
23 篇 predictive model...
23 篇 edge computing
21 篇 computational in...
21 篇 feature extracti...
19 篇 industries
18 篇 object detection
17 篇 social networkin...
16 篇 data privacy

机构

14 篇 ajou univ dept a...
13 篇 school of big da...
12 篇 renmin univ chin...
11 篇 beijing key lab ...
9 篇 college of compu...
7 篇 university of ch...
7 篇 beijing universi...
6 篇 school of comput...
6 篇 key laboratory o...
6 篇 school of comput...
6 篇 key laboratory o...
6 篇 shandong fundame...
5 篇 college of big d...
5 篇 national enginee...
5 篇 shiga university...
5 篇 ajou univ dept i...
5 篇 riken center for...
5 篇 gaoling school o...
5 篇 chongqing univ s...
5 篇 college of intel...

作者

13 篇 shin hyunjung
10 篇 liu yong
7 篇 geng xin
6 篇 zhou xiaokang
6 篇 dai fei
6 篇 mariano vladimir...
6 篇 li shaojie
6 篇 wang jun
5 篇 xu ning
5 篇 wang xiaofei
5 篇 li xiuhua
5 篇 yang yang
5 篇 su bing
5 篇 kim myungjun
5 篇 zhao wei
5 篇 qi jinli
5 篇 wu yanmin
5 篇 jin hai
5 篇 gao yanxia
5 篇 liu yiwen

语言

1,331 篇 英文
21 篇 其他
9 篇 中文
1 篇 西班牙文

检索条件"任意字段=International Conference on Big Data Intelligence and Computing, DataCom 2022"

共 1359 条记录，以下是411-420 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：

Research of Hotspots and Emerging Trends in Swarm intelligence (2013-2022): A Visualization Analysis based on Citespace 8

Research of Hotspots and Emerging Trends in Swarm Intelligen...

引用

8th international conference on big data and Information Analytics, bigDIA 2022

作者： Zhang, Qian Yang, Aihua Qin, Lina College of Military and Political Basic Education National University of Defense Technology Changsha China

ISBN: (数字)9781665487962

ISBN: (纸本)9781665487962

Based on the theory of scientometrics and visual analysis, this paper uses Citespace to analyze the Publication Distribution, Geographical Distribution, Institutional Distribution, Hotspots, Emerging Trends in Swarm intelligence. The dataset includes 7370 records published in Web of Science core database from 2013 to 2022. The results show that the publication volume of Swarm intelligence has been increasing over the past decade. China has the largest number of publications in the world. The main research force is distributed in Europe and Australia. Research hotspots focus on the optimization of Particle Swarm Optimization, Genetic Algorithm, Evolutionary Algorithm, Ant Colony Optimization and other methods, as well as applications in Cloud computing, Unmanned Aerial Vehicle, Power System and other fields. The development trend will focus on the improvement of convergence, running speed and dynamic characteristics of basic theories such as Artificial Bee Colony, Grey Wolf Optimizer, and Memetic Algorithm. © 2022 IEEE.

关键词： Swarm intelligence

来源：评论

学校读者我要写书评

暂无评论

Internet of Things- Cloud Security Automation Technology Based on Artificial intelligence 1

Internet of Things- Cloud Security Automation Technology Bas...

引用

1st international conference on Applied Artificial intelligence and computing, ICAAIC 2022

作者： Hussain, Karrar Vanathi, D. Jose, Bibin K Kavitha, S. Rane, Bhuvaneshwari Yogesh Kaur, Harpreet Sandhya, C. Cvr College of Engineering Ibrahimpatnam Department of Ece Telangana India Nandha Engineering College Department of Artificial Intelligence and Data Science Erode India Department of Mathematics Kerala India Saveetha College of Liberal Arts and Science Saveetha Ins Titute of Medical and Technical Sciences Department of Computer Science Chennai India KYDSCT's College of Pharmacy Pharmaceutical Chemistry Department India Lovely Professional University School of Computer Science & Engineering Punjab Phagwara India S.A.Engineering College Management of Science Chennai India

ISBN: (纸本)9781665497107

The development of industrial robots, as a carrier of artificial intelligence, has played an important role in promoting the popularisation of artificial intelligence super automation technology. The paper introduces the system structure, hardware structure, and software system of the mobile robot climber based on computer big data technology, based on this research background. At the same time, the paper focuses on the climber robot's mechanism compound method and obstacle avoidance control algorithm. Smart home computing focuses on 'home' and brings together related peripheral industries to promote smart home services such as smart appliances, home entertainment, home health care, and security monitoring in order to create a safe, secure, energy-efficient, sustainable, and comfortable residential living environment. It's been twenty years. There is still no clear definition of 'intelligence at home,' according to Philips Inc., a leading consumer electronics manufacturer, which once stated that intelligence should comprise sensing, connectedness, learning, adaption, and ease of interaction. S mart applications and services are still in the early stages of development, and not all of them can yet exhibit these five intelligent traits. © 2022 IEEE.

关键词： Industrial robots

来源：评论

学校读者我要写书评

暂无评论

A Study on BNM-cBLSTM for Financial Sentiment Analysis in European Bond Markets Based on mpBC-ELMo

A Study on BNM-cBLSTM for Financial Sentiment Analysis in Eu...

引用

2022 international conference on data Analytics, computing and Artificial intelligence, ICDACAI 2022

作者： Wang, Qian You, Hanxing International College Krirk University Bangkok10220 Thailand

ISBN: (数字)9781665454704

ISBN: (纸本)9781665454704

Economic and fiscal policies devised by international organizations, governments, and central banks rely significantly on economic projections, particularly during times of economic instability such as the one we have recently seen with the COVID-19 virus spreading globally. However, the accuracy of economic forecasting and now casting models remains a challenge since modern economies are prone to multiple shocks that make forecasting and now casting activities extremely difficult, both in the short and medium range. The purpose of the paper is to identify the key aspects, which must be taken into account in big data sentiment analysis to solve the problem of forecasting and now casting tasks. The work has developed an mpBC-ELMo based BNM-cBLSTM for financial sentiment analysis in European Bond markets. The proposed framework is processed based on collection of big data that are formed into a corpus. Initially, the corpus data is subjected to preprocessing, which performs tokenization, Lemmatization, URL removal, punctuations removal, Dependency Parsing, Noun Phrases, Named Entity recognition, and Coreference Resolution in order to make the data healthier and to get a potential impact for analyzing the sentiments. Thereafter, the data is converted into a vector using mpBC-ELMo, which addresses the complex characteristics of the word as well as polarity and handles stock bond correlation invariant, behavioral biases. Finally, BNM-cBLSTM analyses the sentiments and provides an accurate as well as optimized improvisation. In comparison to existing state-of-the-art methods, experimental results show that the work tends to deliver a precise sentiment analysis and avoids erroneous prediction rate. © 2022 IEEE.

关键词： Sentiment analysis

来源：评论

学校读者我要写书评

暂无评论

Knowledge: Making a Quality Choice

Knowledge: Making a Quality Choice

引用

2022 international conference on Computational Science and Computational intelligence, CSCI 2022

作者： Sanchez, Antonio Texas Christian University Department of Computer Science United States

ISBN: (纸本)9798350320282

We discuss in this paper how we teach an intro to data science course. Knowledge is a matter of choice and choosing the best course of action is through computer programming this is the way which we consider how to teach this course. We begin with an introduction to big data, data mining, machine learning and data visualization. We use python as the language to clean big data files and to select the right attributes for classification when mining the data. We discuss the Bayes method for classification, then we move to java, specifically Weka, to show how to program the algorithms, some applications are also discussed specifically using Bayes for text processing, we then move to other supervised classification algorithm such as J4.8 and Random Forest trees. And then move to clustering, where we discuss both KMeans and EM algorithms. We discuss truth and knowledge and it is where we use cross validation as the most reasonable approach to find truth based on historical data. Later we discuss supervised and unsupervised Learning, briefly talking about Neural Networks collective and reinforced learning. Briefly talk about current deep learning using CNNs. We finish the course talking about Genetic Algorithms and soft computing. © 2022 IEEE.

关键词： big data

来源：评论

学校读者我要写书评

暂无评论

Robust Decentralized Federated Learning Using Collaborative Decisions 18

Robust Decentralized Federated Learning Using Collaborative ...

引用

18th IEEE international Wireless Communications and Mobile computing conference (IWCMC)

作者： Gouissem, A. Abualsaud, K. Yaacoub, E. Khattab, T. Guizani, M. Qatar Univ Comp Sci & Engn Doha Qatar Qatar Univ Elect Engn Doha Qatar Mohamed Bin Zayed Univ Artificial Intelligence Machine Learning Dept Abu Dhabi U Arab Emirates

ISBN: (纸本)9781665467490

Federated Learning (FL) has attracted a lot of attention in numerous applications due to recent data privacy regulations and increased awareness about data handling issues, combined with the ever-increasing big-data sizes. This paper proposes a server-less, robust FL training mechanism that allows any set of participating data-owners to train a neural network (NN) model collaboratively without the assistance of any central node and while being resilient to Byzantine attacks. The proposed approach makes use of a dual-way update mechanism to allow each node to take a model forwarding decision towards a global collaborative decision of isolating any malicious updates. The efficiency of the proposed approach in detecting cardiac irregularities is verified using simulation results conducted based on the Physikalisch-Technische Bundesanstalt database electrocardiogram (PTBDB ECG) dataset.

关键词： Federated Learning Distributed Learning Byzantine attacks Decentralized Networks E-health

来源：评论

学校读者我要写书评

暂无评论

Elastic Service Provisioning for Mobile Edge computing 7

Elastic Service Provisioning for Mobile Edge Computing

引用

7th IEEE international conference on big data intelligence and computing, datacom 2021

作者： Duan, Xuefei Lu, Hua Li, Sisi GuangDong Communications and Networks Institute Guangzhou China Beijing University of Posts and Telecommunications Beijing China

ISBN: (纸本)9781665420716

Major mobile edge computing service providers employ container-based virtualization so as to implement elastic service offerings. Prior works mainly dedicate to service deployment toward lower service latency and better edge resource utility. Due to the time-varying workloads at the edge, it is of critical importance to consider elastic service provisioning. In elastic service provisioning, container images need to be frequently fetched from remote cloud to edge servers, which may incur significant overhead in terms of latency and network resource consumption. Given the limited resources at the edge, we need to minimize such overhead. We exploit service migration in elastic service provisioning to reduce the overhead in terms of latency and core network resource consumption. Taking into account the dynamic of the workloads and the locations of current deployed service entities, we investigate to study the elastic service provisioning problem in this paper. We formulate the problem into an optimization problem and a greedy algorithm is designed to solve the problem. Extensive experiments validate the efficiency of our algorithm. © 2021 IEEE.

关键词： Mobile edge computing

来源：评论

学校读者我要写书评

暂无评论

Cloud-edge collaborative data processing architecture for state assessment of transmission equipments 7

Cloud-edge collaborative data processing architecture for st...

引用

7th international conference on Intelligent computing and Signal Processing, ICSP 2022

作者： Chen, Honghu Zhou, Te Yang, Chao Li, Qiang Peng, Bo Cheng, Qing Southwest University of Science and Technology School of Information Engineering Mianyang China Tsinghua University Sichuan Energy Internet Research Institute Chengdu China

ISBN: (纸本)9781665478571

In the process of asset status assessment, the power transmission intelligent Internet of Things (IoT) with smart towers as the core IoT nodes faces many problems such as large workload of physical information, poor data quality, large data processing delay and heavy cloud computing pressure. At the same time, traditional front-end sensing equipment is limited by the actual hardware computing power level and low power consumption requirements, which makes the front-end algorithm low in intelligence and consumes a lot of manual data verification. In view of the above problems, this paper proposes a cloud-edge collaborative data processing architecture suitable for transmission asset status assessment by combining big data framework, deep learning and edge computing technology. The architecture clearly divides the functions of the cloud, edge and data terminals based on the status assessment requirements of power transmission assets, and then divides a part of the data processing and analysis operations in the cloud to the edge, which reduces the computing pressure on the cloud and enhances resources utilization rate. © 2022 IEEE.

关键词： Edge computing

来源：评论

学校读者我要写书评

暂无评论

MLRNet: Towards Real-Time Crowd Counting With Mobile-Based Lightweight Framework 19

MLRNet: Towards Real-Time Crowd Counting With Mobile-Based L...

引用

2022 IEEE SmartWorld, 19th IEEE international conference on Ubiquitous intelligence and computing, 2022 IEEE international conference on Autonomous and Trusted Vehicles conference, 22nd IEEE international conference on Scalable computing and Communications, 2022 IEEE international conference on Digital Twin, 8th IEEE international conference on Privacy computing and 2022 IEEE international conference on Metaverse, SmartWorld/UIC/ATC/ScalCom/DigitalTwin/PriComp/Metaverse 2022

作者： Ji, Peirong Xia, Xiaofeng Wu, Zhiwei Wang, Fusen Liu, Xinyue Sang, Jun Chongqing University School of Big Data & Software Engineering Chongqing401331 China

ISBN: (纸本)9798350346558

The trade-off between efficiency and generalization has been a challenging problem in crowd counting. In this work, we are devoted to suggesting an application-oriented solution to practical device deployment for crowd counting in resource-constrained scenes. In order to optimize the application computation complexity, this paper proposes a counting architecture, called Mobile Lightweight Refine Net (MLRNet), which is targeted for the high-effectiveness of neural networks in real-time crowd counting tasks on light-scale servers or intelligent devices. In the proposed framework, MobileNetV3 is used as the front-end which enables the model of an efficient feature extraction ability with low resource use. Besides, the back-end introduces the design of Light-weight RefineNet, which maintains the overall counting accuracy while compressing the computing costs. Extensive experiments on four mainstream datasets have demonstrated the availability of our proposed network. Particularly, compared with the baseline method, MLRNet achieves higher accuracy while only using around 1/3 of the FLOPS and parameters on three public crowd counting datasets. © 2022 IEEE.

关键词： Economic and social effects

来源：评论

学校读者我要写书评

暂无评论

Research on Discrimination and Regulation of Artificial intelligence Algorithm 2

Research on Discrimination and Regulation of Artificial Inte...

引用

2nd international conference on Artificial intelligence, Automation, and High-Performance computing, AIAHPC 2022

作者： Tao, Xianghui Li, Lujia He, Jianjun Suzuki Law School China Jiliang University Hangzhou0571-87676425 China

ISBN: (纸本)9781510657717

The rapid development of artificial intelligence has given rise to a series of algorithmic problems that are thoughtprovoking, and algorithmic discrimination is a more prominent problem in the development of artificial intelligence algorithms. The main manifestations of algorithmic discrimination include feature-selective discrimination, associative discrimination, and big data-enabled price discrimination. The causes of algorithmic discrimination mainly include original bias, learning bias and external bias. The regulation of algorithmic discrimination should follow the principles of visualization and transparency, and at the same time, in the improvement of algorithmic technology, it is necessary to ensure the accuracy of algorithm operation while focusing on the inherent fairness of the algorithm. All in all, the regulation of algorithmic discrimination is a synergistic situation formed by the joint participation of multiple parties. © 2022 SPIE. All rights reserved.

关键词： Machine learning

来源：评论

学校读者我要写书评

暂无评论

Research on hardware assisted data cleaning algorithm for IoT Edge computing 3

Research on hardware assisted data cleaning algorithm for Io...

引用

3rd international conference on big data, Artificial intelligence and Internet of Things Engineering, ICBAIE 2022

作者： Jin, Hui Cao, Tiejun Nie, Yongjie Shen, Jun Yan, Hongfeng Wang, Hongyu Wiscom System Co. Ltd Nanjing China Chongqing University School of Electrical Engineering Chongqing China Yunnan Power Grid Co. Ltd Kunming China

ISBN: (数字)9781665451604

ISBN: (纸本)9781665451604

With the rapid development of Internet of Things(IoT) applications and edge computing, the data cleaning algorithm based on anomaly detection adopted by IoT terminals requires stream data processing, low power consumption and real-time performance. Based on the study of the core clustering feature (CF) tree data structure and processing window type of BIRCH stream clustering algorithm, this paper proposes an IoT terminal data cleaning algorithm supported by the IoT terminal Storage and Computation Integrated (SCI) architecture for the first time, and makes a low-power application design and comparative analysis on the Phase Change Random Access Memory (PCRAM) CF tree data storage and access. Prototype based experiments and results analysis shows that the proposed algorithm can meet the intermittent working mode requirements of IoT terminals, reduce power consumption, meet the real-time and online data cleaning performance requirements, and can be extended to support more complex machine learning enhanced data cleaning algorithms. © 2022 IEEE.

关键词： Internet of things

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136页 << < 38 39 40 41 42 43 44 45 46 47 > >>

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：