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

191,938 篇 会议
1,973 册 图书
1,433 篇 期刊文献
8 篇 学位论文
2 篇 科技报告

馆藏范围

195,355 篇 电子文献
4 种 纸本馆藏

日期分布

学科分类号

111,927 篇 工学
- 86,613 篇 计算机科学与技术...
- 63,779 篇 软件工程
- 30,642 篇 信息与通信工程
- 14,723 篇 控制科学与工程
- 12,639 篇 电气工程
- 10,398 篇 生物工程
- 8,351 篇 电子科学与技术（可...
- 7,746 篇 机械工程
- 7,401 篇 生物医学工程（可授...
- 5,717 篇 仪器科学与技术
- 5,138 篇 光学工程
- 4,751 篇 动力工程及工程热...
- 4,547 篇 安全科学与工程
- 4,430 篇 网络空间安全
- 3,909 篇 化学工程与技术
- 3,762 篇 交通运输工程
43,474 篇 理学
- 23,768 篇 数学
- 11,210 篇 生物学
- 9,444 篇 物理学
- 7,277 篇 统计学（可授理学、...
- 5,280 篇 系统科学
- 4,058 篇 化学
32,618 篇 管理学
- 19,840 篇 管理科学与工程(可...
- 15,303 篇 图书情报与档案管...
- 9,771 篇 工商管理
6,880 篇 医学
- 5,810 篇 临床医学
- 5,438 篇 基础医学(可授医学...
- 3,266 篇 药学(可授医学、理...
5,399 篇 法学
- 4,407 篇 社会学
3,675 篇 经济学
- 3,619 篇 应用经济学
3,255 篇 教育学
2,631 篇 农学
1,510 篇 文学
536 篇 军事学
385 篇 艺术学
16 篇 历史学
13 篇 哲学

主题

9,521 篇 cloud computing
6,203 篇 computational mo...
4,700 篇 information tech...
4,650 篇 feature extracti...
4,047 篇 accuracy
3,588 篇 training
3,537 篇 data mining
3,485 篇 computer archite...
3,413 篇 image coding
3,270 篇 internet of thin...
3,168 篇 security
2,982 篇 servers
2,953 篇 mobile computing
2,915 篇 computer science
2,890 篇 protocols
2,698 篇 machine learning
2,680 篇 deep learning
2,549 篇 real-time system...
2,532 篇 educational inst...
2,458 篇 wireless sensor ...

机构

630 篇 university of ch...
556 篇 institute of com...
382 篇 school of comput...
291 篇 chitkara univers...
244 篇 maharishi school...
224 篇 university of sc...
187 篇 department of co...
169 篇 faculty of infor...
152 篇 department of co...
150 篇 faculty of compu...
143 篇 school of comput...
143 篇 department of co...
142 篇 lovely professio...
134 篇 key laboratory o...
127 篇 shenyang institu...
118 篇 maharishi school...
105 篇 school of inform...
102 篇 state key labora...
100 篇 institute of inf...
99 篇 college of infor...

作者

108 篇 lei wang
98 篇 wang lei
98 篇 leonard barolli
76 篇 yang yang
75 篇 wang wei
73 篇 zhang tao
67 篇 jian wang
65 篇 china
60 篇 wei wang
59 篇 rui wang
53 篇 bin wang
51 篇 li wei
50 篇 liu yang
48 篇 li cheng
47 篇 feng liu
47 篇 zhang lin
46 篇 xiao liu
44 篇 bastieri d.
42 篇 yongdong zhang
42 篇 yang liu

语言

190,586 篇 英文
3,413 篇 其他
1,975 篇 中文
19 篇 俄文
10 篇 法文
5 篇 阿拉伯文
3 篇 西班牙文
3 篇 葡萄牙文
3 篇 乌克兰文
2 篇 德文

检索条件"任意字段=International Conference on Information Technology - Coding and Computing"

共 195356 条记录，以下是461-470 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 on the Application of Multi-Channel Display technology in Virtual Scene Image Generation 5

Research on the Application of Multi-Channel Display Technol...

引用

5th IEEE international conference on Power, Electronics and Computer Applications, ICPECA 2025

作者： Liu, Yuanlin Wang, Lingling Haikou University of Economics Haikou571127 China

ISBN: (纸本)9798331533694

This study proposes an innovative algorithm based on DCNN and multi-channel image fusion, aiming to improve the quality and efficiency of virtual scene image generation. The algorithm extracts depth information and texture features in virtual scenes through DCNN, and combines multi-channel image fusion technology to optimize and fuse the information of different image channels (such as color, depth, normal, etc.), thereby significantly improving the image rendering effect. Through adaptive weight adjustment and image fusion strategy, the image detail performance is optimized, especially in scenes with complex lighting and rich textures, the rendering quality is significantly improved. Experimental results show that the image generation system based on this algorithm improves image quality by 15%, rendering speed by 25%, and computing resource consumption by 20%. When processing highly complex virtual scenes, the system can achieve real-time rendering and meet the performance requirements of VR and AR applications. This study provides a new and efficient solution for image generation in virtual reality and augmented reality, and demonstrates the great potential of combining multi-channel display technology with deep learning in improving rendering effects. © 2025 IEEE.

关键词： Virtual environments

来源：评论

学校读者我要写书评

暂无评论

ASTGNN: Adaptive Spatio-Temporal Graph Neural Network for Motor Imagery Recognition

ASTGNN: Adaptive Spatio-Temporal Graph Neural Network for Mo...

引用

2024 international conference on Mechatronics and Intelligent Control, ICMIC 2024

作者： Zhao, Zheng Xue, Haixiao Huang, Yuwen Zhao, Qi Xie, Xin Dalian Maritime University Dalian China Northeastern University Shenyang China Hunan University of Information Technology Changsha China Hunan Province Higher Education Key Laboratory of Intelligent Sensing and Computing Changsha China

ISBN: (数字)9781510686847

ISBN: (纸本)9781510686830

Motor imagery electroencephalogram recognition is a key area in brain-computer interfaces, with applications in human-computer interaction, rehabilitation, and virtual reality. Traditional methods often overlook the brain's topological characteristics and the correlations between EEG channels, resulting in suboptimal decoding. To address this, we propose an adaptive spatio-temporal graph neural network (ASTGNN), which constructs a brain graph topology and adaptively learns the topological adjacency matrix, exploring both common and individual electrode connections. The spatial features are extracted using a graph convolutional network, while a gated position-aware self-attention mechanism captures movement information and global dependencies, enhancing temporal feature extraction. Experiments show that ASTGNN significantly improves recognition, achieving an average accuracy of 87.36%. © 2025 SPIE.

关键词： Electroencephalography

来源：评论

学校读者我要写书评

暂无评论

Medical Diagnosis through Machine Learning: Detecting Heart Disease, Lung and Breast Cancer 6

Medical Diagnosis through Machine Learning: Detecting Heart ...

引用

6th international conference on Mobile computing and Sustainable Informatics, ICMCSI 2025

作者： Satya Naga Deep, G. BalaKrishna, G. Sathya Bama krishna, R. School of Computing Sathyabama Institute of Science and Technology Chennai India

ISBN: (纸本)9798331522667

Medical diagnostics for heart disease, lung cancer, and breast cancer using ML algorithms. The ML algorithms used in medical research have received considerable attention, motivated by their potential to revolutionize early analysis and enhance patient care. The relevancy of machine learning techniques to medical research in three significant conditions—breast cancer, lung cancer, and heart disease—is examined in this paper. This approach can improve the prompt diagnosis with better patient outcomes. In this work, it has adopted several machine learning techniques like naive Bayes, decision tree classification, k-nearest neighbor, support vector machines, linear discriminant analysis, and logistic regression. For heart disease, lung cancer, and breast cancer datasets, we evaluate all algorithms regarding their unique characteristics. We carefully assess the effectiveness of these algorithms utilizing a wide range of experimental conditions and comparison analysis. The review analyzes the processes of data preprocessing, feature selection, and model validation. Additionally, it offers a thorough analysis of current studies, providing information on earlier machine learning research on medical subjects. © 2025 IEEE.

关键词： Lung cancer

来源：评论

学校读者我要写书评

暂无评论

Enhancing Summarization of Legal Text Documents using Pre-trained Models 5

Enhancing Summarization of Legal Text Documents using Pre-tr...

引用

5th international conference on Emerging Systems and Intelligent computing, ESIC 2025

作者： Kasar, Ashish Matade, Suyash Rasal, Durvankur Shinde, Swapnil Vishwakarma Institute of Information Technology Department of Artificial Intelligence and Data Science Pune India

ISBN: (纸本)9798331522100

A very relevant challenge of summarizing legal text documents often exceeds the length, therefore being complex, was addressed using pre-trained models such as BART and PEGASUS. In the paper, the issue is discussed-the challenge that these pre-trained models face while being effective in general text summarization tasks, which becomes difficult in legal contexts due to specialized vocabulary and structure of legal documents. The authors fine-tune these models using the BillSum dataset-provided US Congressional bills as a proxy for court documents. Evaluation on ROUGE metrics reveals that BART outperforms PEGASUS in summation of content structures of legal texts to the greatest extent intended. The results suggest that the pre-trained models significantly improve the process of summarizing legal documents, both for professionals in law and general readers who would otherwise have to wade through an extensive amount of legal information. © 2025 IEEE.

关键词： Natural language processing systems

来源：评论

学校读者我要写书评

暂无评论

A Scalable Framework for Multi-cloud IoT Data Synchronization 25

A Scalable Framework for Multi-cloud IoT Data Synchronizatio...

引用

26th international conference on Distributed computing and Networking, ICDCN 2025

作者： Mallick, Arnab Barnwal, Rajesh P. AI & IoT Lab Information Technology Group CSIR-Central Mechanical Engineering Research Institute West Bengal Durgapur India

ISBN: (纸本)9798400710629

The increasing deployment of Internet of Things (IoT) technologies in different societal infrastructures, like household water quality monitoring systems, necessitates the development of robust methods to synchronize vast datasets across multi-tiered cloud infrastructures. This paper introduces a comprehensive and highly scalable framework designed to facilitate the efficient synchronization of IoT-generated water quality and quantity data between heterogeneous cloud environments. The framework employs a hybrid data aggregation mechanism, optimizing both network bandwidth and computational resources while minimizing latency. Using a sender-receiver architecture, the proposed system ensures seamless data transfer by dynamically segmenting and processing large datasets in parallel, maintaining real-time data integrity and consistency across distributed systems. This approach addresses critical challenges inherent to large-scale IoT deployments, such as data duplication, transfer delays, and system overhead through concurrent data handling and fault-tolerant mechanisms. The framework is positioned to enhance scalability and reliability, making it well-suited for use in environments that require frequent, high-volume data synchronization, such as governmental water quality monitoring networks. © 2025 Copyright held by the owner/author(s).

关键词： Data integrity

来源：评论

学校读者我要写书评

暂无评论

Predictive Modeling of Cardiovascular Disease Using Machine Learning: A Comparative Analysis 5

Predictive Modeling of Cardiovascular Disease Using Machine ...

引用

5th international conference on Advanced Research in computing, ICARC 2025

作者： Tonni, Sadia Islam Alam, Md Ashraful Sohel, Amir Khan, Chonchal Onik, Md.Khaledur Rahman Pranto, Ismail Hossain Jahangirnagar University Institute of Information Technology Dhaka Bangladesh Colorado State University Department of Computer Science CO United States Project Management St. Francis College Department of Information Technology New York United States Daffodil International University Department of Computer Science and Engineering Dhaka Bangladesh American International University- Bangladesh Department of Computer Science and Engineering Dhaka Bangladesh

ISBN: (纸本)9798331530983

Cardiovascular disease remains one of the leading causes of death worldwide, necessitating the development of efficient diagnostic tools. This study presents a machine learning framework for predicting cardiovascular disease based on clinical and demographic data. We employ a comprehensive data preprocessing pipeline that includes handling missing values, normalizing data, and balancing the dataset to ensure robust model performance. Feature extraction and selection techniques are applied to identify the most relevant predictors of cardiovascular risk, optimizing model performance and reducing computational complexity. Eight machine learning algorithms were employed to predict cardiovascular disease outcomes, including logistic regression, decision trees, random forest, support vector machines, k-nearest neighbors, naïve Bayes, XGBoost, and AdaBoost model. Our approach achieved an accuracy of surpassing 98%, demonstrating the potential of ML techniques in aiding early diagnosis and improving patient outcomes. This comparative analysis highlights the strengths and limitations of each algorithm, providing insights into the most suitable models for clinical use. © 2025 IEEE.

关键词： Support vector machines

来源：评论

学校读者我要写书评

暂无评论

A comprehensive survey on client selections in federated learning

A comprehensive survey on client selections in federated lea...

引用

international conference on Innovation and Technological Advances for Sustainability, ITAS 2023

作者： Gouissem, A. Chkirbene, Z. Hamila, R. College of Computing and Information Technology University of Doha for Science and Technology Qatar Electrical Engineering Qatar University Qatar

ISBN: (纸本)9781032803722

Federated Learning (FL) is a rapidly growing field in machine learning that allows data to be trained across multiple decentralized devices. The selection of clients to participate in the training process is a critical factor for the performance of the overall system. In this survey, we provide a comprehensive overview of the state-of-the-art client selection techniques in FL, including their strengths and limitations, as well as the challenges and open issues that need to be addressed. We cover conventional selection techniques such as random selection where all or partial random of clients is used for the trained. We also cover performance-aware selections and as well as resource-aware selections for resource constrained networks and heterogeneous networks. We also discuss the usage of client selection in model security enhancement. Lastly, we discuss open issues and challenges related to clients selection in dynamic constrained, and heterogeneous networks. © 2025 The Author(s).

关键词： Federated learning

来源：评论

学校读者我要写书评

暂无评论

Enhancing Health Record Exchange with a Novel Cloud-Based Framework for Personalized Competence Evidence 12th

Enhancing Health Record Exchange with a Novel Cloud-Based Fr...

引用

12th international conference on Frontiers of Intelligent computing: Theory and Applications, FICTA 2024

作者： Saravanan, D. Kaushik, S. Sudha, C. Kalaivani, J. Hyderabad India ICFAI Foundation for Higher Education Hyderabad India Hyderabad India Department of Computing Technologies SRM Institute of Science and Technologies Kattankulathur Chennai India

ISBN: (纸本)9789819601424

Today, technology enables users to perform various operations using cloud-based services. With this approach, users do not need to create physical copies of documentation, and the same information can be accessed and shared through cloud-based operations. This not only eliminates the need to physically carry records but also secures information, preventing unauthorized access without the user’s permission. This concept extends into the fitness world as well. Patient details can be maintained in cloud-based Health Competence Evidence (HCR) services and shared globally for suggestions and investigations. This approach improves operational efficiency and facilitates the quick and easy exchange of data on a global scale. Health competence Evidence services empower users to build, sustain, and modify records using information technology, facilitating the extraction, storage, and exchange of information more rapidly and effectively. In this proposed work, an encoded file is created to securely retain information using key management techniques. This ensures the highly protected storage of information in multi-owner systems, guarding against eavesdropping. The outputs confirm that the proposed approach performs well in cloud-based environments. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Electronic health record

来源：评论

学校读者我要写书评

暂无评论

Source IP Hashing Algorithm for Load Balancing in Cloud Server 6

Source IP Hashing Algorithm for Load Balancing in Cloud Serv...

引用

6th international conference on Mobile computing and Sustainable Informatics, ICMCSI 2025

作者： Gokul, M. Rajkumar, N. Department of Computer Science and Engineering Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Institute of Science and Technology Chennai India

ISBN: (纸本)9798331522667

The high trend in the adoption of online banking makes complex load balancing highly crucial to maximize computing capacity in the cloud, data management, and security. This research focuses on analyzing the Source IP Hashing method of load balancing where client requests are evenly distributed depending on their source IP address to provide persistence of client sessions and protect against session hijacking among other risks. The proposed framework, captured in Java, follows a systematic procedure of directing the client requests to the most appropriate servers using hash values generated from the IP address of the clients reducing server resource consumption. The paper also yields numerical results comparing throughput and system responsiveness with pretested significant enhancement affirming that even under high traffic the system achieves high responsiveness and reliability. This analysis proves that Source IP Hashing helps deliver high success rates in request routing while maintaining a 99% retention of session persistence and improving server utility. Thus, the study also proves that Source IP Hashing algorithm enhances the safety and security of data even when distributing the practical load among different servers, which makes it a more innovative solution for easing the problems of cloud-based financial services of the present days. © 2025 IEEE.

关键词： information management

来源：评论

学校读者我要写书评

暂无评论

Efficient cloud-assisted revocable identity-based broadcast encryption in IoT 4

Efficient cloud-assisted revocable identity-based broadcast ...

引用

4th international conference on Network Communication and information Security, ICNCIS 2024

作者： Chen, Zhou Han, Lidong School of Information Science and Technology Hangzhou Normal University Hangzhou China

ISBN: (数字)9781510688261

ISBN: (纸本)9781510688254

While the Internet of Things (IoT) has greatly facilitated our daily lives, this trend has encountered numerous security challenges in data storing and sharing especially for sensitive personal data. Identity-Based Broadcast Encryption (IBBE) is an efficient cryptographic technique to securely share messages among multiple users. Nevertheless, to prevent access by users who were previously authorized but now lack permission, user revocation should be integrated into IBBE. Despite several previous Revocable Identity-Based Broadcast Encryption (RIBBE) schemes were proposed, they are not practical for resource-constrained IoT devices due to their high computational cost during encryption and decryption, as well as the significant storage needs for the revocation list. To tackle these issues, we propose an outsourced RIBBE scheme that is appropriate for resource-constrained IoT devices. It not only effectively implements user revocation but also leverages a cloud server to handle complex calculations. Additionally, our scheme is designed to resist collusion attacks, enhancing overall security. Performance evaluation describes the great practicality and efficiency of our scheme. © 2025 SPIE.

关键词： Internet of things Clouds Computer security Cloud computing Cryptography Network security Systems modeling

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 << < 43 44 45 46 47 48 49 50 51 52 > >>

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：