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

40,039 篇 会议
1,084 册 图书
455 篇 期刊文献
1 篇 学位论文

馆藏范围

41,579 篇 电子文献
4 种 纸本馆藏

日期分布

学科分类号

23,913 篇 工学
- 18,120 篇 计算机科学与技术...
- 14,370 篇 软件工程
- 6,139 篇 信息与通信工程
- 3,970 篇 控制科学与工程
- 3,142 篇 电气工程
- 2,550 篇 生物工程
- 2,431 篇 电子科学与技术（可...
- 2,201 篇 生物医学工程（可授...
- 2,086 篇 机械工程
- 1,649 篇 动力工程及工程热...
- 1,515 篇 光学工程
- 1,233 篇 仪器科学与技术
- 1,218 篇 化学工程与技术
- 1,119 篇 安全科学与工程
- 953 篇 建筑学
9,611 篇 理学
- 4,134 篇 数学
- 3,007 篇 物理学
- 2,735 篇 生物学
- 1,227 篇 统计学（可授理学、...
- 1,140 篇 化学
- 953 篇 系统科学
6,222 篇 管理学
- 4,399 篇 管理科学与工程(可...
- 2,263 篇 工商管理
- 2,197 篇 图书情报与档案管...
2,203 篇 医学
- 1,805 篇 临床医学
- 1,695 篇 基础医学(可授医学...
- 1,115 篇 公共卫生与预防医...
- 928 篇 药学(可授医学、理...
1,254 篇 法学
- 1,026 篇 社会学
920 篇 经济学
- 914 篇 应用经济学
803 篇 教育学
527 篇 农学
211 篇 文学
195 篇 军事学
38 篇 艺术学
2 篇 哲学
1 篇 历史学

主题

1,357 篇 internet of thin...
1,325 篇 computer archite...
1,066 篇 computational mo...
1,052 篇 accuracy
1,045 篇 real-time system...
845 篇 artificial intel...
819 篇 deep learning
819 篇 wireless sensor ...
686 篇 monitoring
683 篇 application soft...
677 篇 cloud computing
673 篇 training
668 篇 machine learning
641 篇 security
580 篇 computer science
577 篇 feature extracti...
574 篇 protocols
507 篇 software
469 篇 wireless communi...
456 篇 hardware

机构

106 篇 chitkara univers...
67 篇 school of comput...
57 篇 lovely professio...
45 篇 maharishi school...
44 篇 school of comput...
42 篇 department of el...
39 篇 centre of resear...
35 篇 computer science...
33 篇 school of comput...
31 篇 school of comput...
31 篇 centre of interd...
29 篇 school of comput...
29 篇 department of co...
28 篇 karnataka bangal...
28 篇 graphic era deem...
28 篇 department of co...
27 篇 department of co...
26 篇 computer technol...
25 篇 department of co...
25 篇 chitkara centre ...

作者

36 篇 bernady o. apduh...
33 篇 rakesh kumar
18 篇 amit kumar
16 篇 valeriy vyatkin
15 篇 weiming shen
15 篇 shiva mehta
15 篇 amit joshi
15 篇 muntather almusa...
13 篇 bibhuti bhusan d...
12 篇 gupta richa
12 篇 marina l. gavril...
11 篇 patti gaetano
11 篇 wang lei
11 篇 zhang lei
11 篇 sharma dilip kum...
11 篇 manika manwal
11 篇 alzubaidi laith ...
11 篇 rishabh sharma
10 篇 sharma vikrant
10 篇 anjali t.

语言

40,025 篇 英文
1,266 篇 其他
409 篇 中文
5 篇 法文
3 篇 土耳其文
1 篇 德文
1 篇 西班牙文
1 篇 葡萄牙文
1 篇 俄文
1 篇 乌克兰文

检索条件"任意字段=International Conference on Computer Technologies in Physical and Engineering Applications"

共 41579 条记录，以下是321-330 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：

Enhancing physical-Layer Security in Full-Duplex Cooperative Wireless Networks over α-μ Fading Channels 7

Enhancing Physical-Layer Security in Full-Duplex Cooperative...

引用

7th international conference on Advanced Communication technologies and Networking, CommNet 2024

作者： Saddouq, Ayam Al-Mistarihi, Mamoun F. Khoderi, Mahmoud A. Darabkh, Khalid A. Jordan University of Science and Technology Faculty of Engineering Electrical Engineering Department P.O. Box 3030 Irbid Jordan The University of Jordan School of Engineering Computer Engineering Department Amman11942 Jordan

ISBN: (纸本)9798350367027

Cooperative communication is an emerging method that allows devices with a single antenna to share their antennas and assist other nodes in transmitting signals. This leads to enhanced spatial diversity, lower power consumption, and increased reliability of signal reception. This study uses full-duplex mode and α-μ fading channels and derives the secrecy outage probability for a single relay to assess the system's secrecy performance and examine how utilizing jamming signals affects system security. Theoretical results for the derived expression are given. © 2024 IEEE.

关键词： Cooperative communication

来源：评论

学校读者我要写书评

暂无评论

Challenges and Opportunities in Healthcare and Industrial IoT: A Comparative Analysis 1

Challenges and Opportunities in Healthcare and Industrial Io...

引用

1st international conference on Emerging technologies for Dependable Internet of Things, ICETI 2024

作者： Berjis, Zaid Ameen, Siddeeq Y. Al-Jammas, Mohammed H. Electrical and Computer Engineering Department College of Engineering University of Duhok Duhok Iraq Energy Engineering Department College of Technical Engineering Duhok Polytechnic University Duhok Iraq Computer and Information Engineering Department College of Electronics Ninevah University Mosul Iraq

ISBN: (纸本)9798331533557

The Internet of Things (IoT) has changed many industries by enabling smart devices to transmit data, operate autonomously, and interact in real-time. Among its most prominent applications are in healthcare and industrial sectors, where IoT is classified into two classes: massive Machine-Type Communication (mMTC) and Ultra-Reliable Low Latency Communication (URLLC). While mMTC devices prioritize low energy consumption and can handle large-scale deployments with minimal data rates, URLLC devices are focused on mission-critical applications requiring ultra-low latency and high reliability. This paper examines the challenges and opportunities of IoT implementation in healthcare and industrial sectors, focusing on interoperability, data security, and scalability issues. The objective is to provide actionable solutions for the effective integration of IoT technologies. The investigation shows that in healthcare, mMTC is utilized for non-critical monitoring, while URLLC supports critical tasks like remote surgery. In industrial settings, mMTC improves processes like supply chain management, while URLLC enables automation and real-time control of machinery. Despite these opportunities, challenges such as data privacy, security, interoperability, and reliability remain. Addressing these issues is crucial for unlocking the full potential of IoT in healthcare and industrial sectors. © 2024 IEEE.

关键词： Data privacy

来源：评论

学校读者我要写书评

暂无评论

Exploring the Use of Machine Learning and the Internet of Things in Intelligent Agriculture: Short Survey 10

Exploring the Use of Machine Learning and the Internet of Th...

引用

10th international conference on Optimization and applications, ICOA 2024

作者： El Majdouby, Karima El Mohadab, Mohamed Daoud, Rachid Ait Abouelmehdi, Karim University of Chouaib Doukkali Elites laboratory Faculty of Sciences Computer Science department Eljadida Morocco Sultan Moulay Slimane University Systems Engineering Laboratory Computer Science department Beni Mellal Morocco

ISBN: (纸本)9798350387353

Agriculture is evolving towards more sustainable practices thanks to the integration of the machine learning and Internet of Things, which addresses many of the issues related to agricultural production and leads to increased yields with reduced input and labor costs. Smart farming has developed solutions to many conventional agricultural problems to automatically manage and monitor farmland. These technologies reduce the risk of field management in the event of bad weather, and also provide benefits to farmers in the event of labor shortages. The Internet of Things ensures the connection of physical objects that are equipped with sensors to the internet, enabling them to collect and exchange data and communicate with each other and with computer systems to gather information, perform analysis and take actions in real time that require rapid data analysis, and this task can be accomplished through machine learning algorithms with greater efficiency and high-quality decision-making. In addition, we carry out an in-depth state-of-the-art survey to identify very recent work that has implemented the Internet of Things and machine learning in smart agriculture, analyzing the development of practical solutions and discussing recent research trends and future prospects. © 2024 IEEE.

关键词： Internet of things Machine learning Smart Agriculture

来源：评论

学校读者我要写书评

暂无评论

A Survey on Alzheimer's Patient's Assistive Technology 1

A Survey on Alzheimer's Patient's Assistive Technology

引用

1st international conference on Trends in engineering Systems and technologies, ICTEST 2024

作者： Menon, Raghi R Varghese, Rosemary Sobha, T. Shaju, Anjaly Bhadran, Athira Sirosh, Fathima Adi Shankara Institute of Engineering and Technology Computer Science and Technology Kalady India

ISBN: (纸本)9798350307795

Assistive technologies for Alzheimer's patients are becoming increasingly important in today's world. This survey primarily explores advanced technological solutions specifically designed for Alzheimer's patients., with a focus on the integration of artificial intelligence (AI)., the Internet of Things (IoT)., robotics., and wearable computing. These technologies aim to support the unique needs of patients., making them well-suited for use in care facilities and at home. The survey delves into various applications and systems., examining their evolution and impact over time. The primary goal is to identify and assess the distinctive features of each technology. Additionally., the paper discusses the limitations and challenges of existing systems., offering insights into the progress and hurdles of assistive technologies tailored for Alzheimer's patients. © 2024 IEEE.

关键词： Assistive technology

来源：评论

学校读者我要写书评

暂无评论

Digital Twin and Cloud Based Remote Control of Vehicles 2

Digital Twin and Cloud Based Remote Control of Vehicles

引用

2nd IEEE international conference on Mobility, Operations, Services and technologies, MOST 2024

作者： Rovid, Andras Tihanyi, Viktor Cserni, Marton Csontho, Mihaly Domina, Adam Remeli, Viktor Vincze, Zsolt Szanto, Matyas Szalai, Matyas Nagy, Szabolcs Szalay, Zsolt Budapest University of Technology and Economics Faculty of Transportation Engineering and Vehicle Engineering Department of Automotive Technologies Hungary Budapest University of Technology and Economics Faculty of Electrical Engineering and Informatics Department of Control Engineering and Information Technology Hungary

ISBN: (纸本)9798350307733

Cloud-based, centralized control system architectures have been published in recent years, examining the applications, structure and validity of the idea of controlling a vehicle, or multiple vehicles directly from the cloud. The literature presents possible advantages and disadvantages of Control as a Service (CaaS), as well as multiple viable applications, however no real-car real-world implementation exists to the best of our knowledge. In our experiments, we demonstrate a real-life and real-time vehicle control method that runs in the cloud and reacts adaptively to the vehicle's surroundings. In the presented tests, acquisition of the vehicle and environment state is performed from a collective perception-based digital twin that is also produced in our cloud-based Central System using data streams from our distributed sensor network. We conduct real-world physical vehicle tests, and establish that cloud-based centralized control is a viable solution, and an interesting research direction. We test our vehicle control in one mixed reality, and two real-world scenarios on the ZalaZONE proving ground in Hungary, Zalaegerszeg. Our experiments prove that cloud-based low-level vehicle control is feasible. © 2024 IEEE.

关键词： Sensor networks

来源：评论

学校读者我要写书评

暂无评论

Deep Learning for Fraud Detection in Bitcoin Transactions: An AI Approach

Deep Learning for Fraud Detection in Bitcoin Transactions: A...

引用

2025 international conference on Pervasive Computational technologies, ICPCT 2025

作者： Shravan, M. Ajitha, E. Arnone, Gioia Renu, Nekkanti Tiwari, Mohit Chouhan, Kuldeep Sr University School of Business Telangana Warangal India St. Joseph's Institute of Technology Computer Science and Engineering India Vrije Universiteit Brussel Department of Private and Economic Law Bruxelles Belgium Department of Computer Science and Engineering Duvvada India Bharati Vidyapeeth's College of Engineering Department of Computer Science and Engineering Delhi Delhi India Sharda University Sharda School of Engineering and Technology Department of Computer Science and Applications Greater Noida201310 India

ISBN: (纸本)9798331508685

This research looks into how deep learning methods can be used to find fake Bitcoin transfers. It's mostly about the unique problems and chances that come with trading in cryptocurrencies and blockchain. Deep learning models are used to look at transaction trends and find oddities that could be signs of fraud. This is because Bitcoin's open structure makes it harder to use traditional methods of fraud detection. We offer a structure that connects CNNs (convolutional neural networks) and RNNs (recurrent neural networks) so that strange patterns can be found in big sets of blockchain transactions. An AI-driven method aims to improve detection accuracy while lowering false positives by taking on scammers' complicated and always-changing strategies. Experienced researchers have shown that the model is good at finding strange things, which means it can be used to safely stop theft in Bitcoin networks in real time. It looks like deep learning could make digital money safer and give us data that can be used in bigger blockchain-based money systems. © 2025 IEEE.

关键词： Adversarial machine learning

来源：评论

学校读者我要写书评

暂无评论

IoT-Enabled Asset Management and Tracking in Organizations 2

IoT-Enabled Asset Management and Tracking in Organizations

引用

2nd international conference Computational and Characterization Techniques in engineering and Sciences, IC3TES 2024

作者： Kumar, Brajesh Anjali, Y. Mudholkar, Megha Mudholkar, Pankaj Bharati, P. Vijaya Abdullayeva, Nilufar Dr. Apj Abdul Kalam Women's Institute of Technology Department of Computer Science & Engineering Bihar Darbhanga India Mlr Institute of Technology Department of Cybersecurity Hyderabad India Marwadi University Department of Computer Engineering Gujarat Rajkot360003 India Marwadi University Faculty of Computer Applications Gujarat Rajkot360003 India Vignans Institute of Engineering for Women Department of Cse Andhra Pradesh Visakhapatnam530049 India Tashkent State University of Economics The Department of Budget Accounting and Treasury Tashkent Uzbekistan

ISBN: (纸本)9798350364699

The manner in which assets are monitored, controlled, and utilized has been substantially altered by organizations that have implemented IoT-enabled asset management and monitoring technologies. Businesses can achieve improved operational efficiency and cost savings by perpetually monitoring the location, activities, and performance of their assets through the use of IoT technologies. Minimized periods of inactivity and enhanced asset lifecycle management are among the three benefits of this predictive maintenance approach. When it comes to resource allocation and strategic decision-making, the data insights provided by IoT-enabled devices are of paramount importance. Companies that implement these technologies should anticipate an increase in productivity, a decrease in losses, and an improvement in their ability to comply with regulatory standards. © 2024 IEEE.

关键词： Predictive maintenance

来源：评论

学校读者我要写书评

暂无评论

Block chain and Deep Learning Based Secure Communication using SAE-LSTM &salp Swarm Optimizer for Multivariate Industrial IoT-oriented Infrastructure 15

Block chain and Deep Learning Based Secure Communication usi...

引用

15th international conference on Computing Communication and Networking technologies, ICCCNT 2024

作者： MathalaiRaj, J. Sivaranjani, S. Rajalakshmi, J. Jayachandran, T. Maheswari, M. Kavin Kumar, K. Chandrasekaran, Gokul Nadar Saraswathi College of Engineering and Technology Department of Computer Science and Engineering Theni India Sethu Institute of Technology Department of Computer Science and Engineering Virudhnagar India Sethu Institute of Technology Department of Electronics and Communication Engineering Virudhunagar India Nandha Engineering College Department of Electronics and Communication Engineering Erode India Kongu Engineering College Department of Electronics and Communication Engineering Erode Perundurai638060 India Karpagam Institute of Technology Department of Electronics and Communication Engineering Coimbatore India

ISBN: (纸本)9798350370249

The rapid development of the Industrial Internet of Things (IIoT) imposes the needs for digitization of industrial procedures so as to enhance the efficiency of the network. Cyber-physical System (CPS) has important role in applications of industries and infrastructure towards IoT. There are several challenges in IIoT environment such as centralization, scalability, privacy, security and communication latency. To overcome these issues, Deep learning based Sparse Autoencoder-Long Short-Term Memory (SAE-LSTM) with Salp swarm optimizer SSA based IoT-oriented infrastructure is used to detect the attacks. The major objective of this work is to propose a deep learning and blockchain based smart contract technique for a secure communication in smart city using Salp Swarm Optimizer algorithm for determining data privacy and security for the IIoT's application service. Blockchain & data aggregation with Proof-of-Work (PoW) generates a distributed network for communication phase of CPS. The protocols to forward the data in the network is established by Software-Defined Networking (SDN). Smart contract is employed to execute the transaction. The suggested technique is implemented and the performance is carried out by estimating Accuracy, Precision, Recall and F1 Score. © 2024 IEEE.

关键词： Blockchain and data aggregation with Proof-of-Work (PoW) Decision Sparse Autoencoder-Long Short-Term Memory (DSAE-LSTM) Industrial IoT Salp swarm optimizer SSA Smart contract

来源：评论

学校读者我要写书评

暂无评论

Comprehensive Survey on Body Language Decoder 4

Comprehensive Survey on Body Language Decoder

引用

4th international conference on Expert Clouds and applications, ICOECA 2024

作者： Jyoti Moharkan, Muarij Javid Juveriyah Chandigarh University Department of Computer Science & Engineering Punjab Gharuan India

ISBN: (纸本)9798350385793

Human Body language and expressions reveal a person's thoughts and emotions. Nonverbal cues provide insight into an individual's emotions. It describes the person's emotion, such as happiness or sadness. Detection techniques, such as instrumented sensor technology and computer vision, are well- established in research articles. Expressions can be classified based on the person's motion, whether still or moving. This research explores the use of Artificial Intelligence, Media-pipe, computer vision and other various technologies to detect people's emotions. The proposed model recognizes three emotions: joyful, sad, and victorious based on detected gestures. Difference in locations and detection from a distance may be challenging due to varying coordinates. This study provides a comprehensive review of Body Language Decoder. © 2024 IEEE.

关键词： Human computer interaction

来源：评论

学校读者我要写书评

暂无评论

Sign Language Detection in Real-Time applications

Sign Language Detection in Real-Time Applications

引用

2024 international conference on Computing and Intelligent Reality technologies, ICCIRT 2024

作者： Milinda, Renata Rachael Sara Ramsiej, Barrister Yasmin, Reshma Ambeth Kumar, V.D. Sekar, K. Anna University India Dept. of Artificial Intelligence and Machine Learning Anna University India Dept. of Computer Engineering Mizoram University Aizawl India Department of AIML Rajalakshmi Engineering College Chennai India

ISBN: (纸本)9798331510299

Individuals with hearing and speech impairments often rely on gesture language for communication, but a lack of widespread understanding of this language among others creates significant barriers. A machine learning model that recognizes hand signals and converts them into English can help bridge this gap, facilitating communication between hearing and deaf individuals. Existing non-verbal communication identification systems, while leveraging computational learning and AI models for both single- and double-handed gestures, generally lack real-time capabilities. This research proposes a live symbolic language identification platform that uses a webcam to build a regional gesture communication dataset and TensorFlow for cross-domain learning. Despite a smaller dataset, the system targets high accuracy in recognition. Advanced technologies, including computer vision and deep learning, are applied to improve communication for deaf individuals by developing accessible technical applications and platforms. The proposed model, utilizing TensorFlow and OpenCV, aims to identify commonly used American Sign Language gestures in real time with accuracy and efficiency, including signs such as "hello, " "thanks, " "bye, " "yes, " "no, " "dad, " and "mom". © 2024 IEEE.

关键词： Adversarial machine learning

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 << < 29 30 31 32 33 34 35 36 37 38 > >>

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：