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

18,583 篇 会议
112 篇 期刊文献
16 册 图书

馆藏范围

18,711 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

12,027 篇 工学
- 9,579 篇 计算机科学与技术...
- 5,513 篇 软件工程
- 3,078 篇 电气工程
- 2,966 篇 控制科学与工程
- 2,549 篇 信息与通信工程
- 955 篇 仪器科学与技术
- 932 篇 交通运输工程
- 929 篇 机械工程
- 641 篇 生物工程
- 630 篇 电子科学与技术（可...
- 556 篇 动力工程及工程热...
- 539 篇 生物医学工程（可授...
- 484 篇 安全科学与工程
- 421 篇 石油与天然气工程
- 420 篇 网络空间安全
- 257 篇 光学工程
3,020 篇 管理学
- 2,252 篇 管理科学与工程(可...
- 1,158 篇 图书情报与档案管...
- 861 篇 工商管理
2,982 篇 理学
- 1,547 篇 数学
- 786 篇 生物学
- 504 篇 统计学（可授理学、...
- 485 篇 物理学
- 392 篇 系统科学
- 391 篇 化学
648 篇 医学
- 505 篇 临床医学
- 440 篇 基础医学(可授医学...
- 291 篇 公共卫生与预防医...
325 篇 法学
- 271 篇 社会学
279 篇 经济学
- 274 篇 应用经济学
172 篇 教育学
150 篇 农学
33 篇 文学
31 篇 军事学
12 篇 艺术学

主题

1,144 篇 data acquisition
763 篇 data mining
571 篇 real-time system...
567 篇 data models
444 篇 intelligent syst...
421 篇 big data
420 篇 conferences
409 篇 cloud computing
375 篇 internet of thin...
359 篇 computational mo...
345 篇 monitoring
321 篇 computer archite...
319 篇 sensor systems
315 篇 machine learning
308 篇 deep learning
306 篇 control systems
304 篇 training
298 篇 feature extracti...
287 篇 robot sensing sy...
284 篇 neural networks

机构

49 篇 university of ch...
42 篇 lviv polytechnic...
30 篇 hubei key labora...
25 篇 school of comput...
20 篇 west ukrainian n...
18 篇 beijing key labo...
17 篇 shenzhen institu...
17 篇 chitkara univers...
16 篇 university of el...
15 篇 school of comput...
15 篇 institute of aut...
14 篇 faculty of compu...
14 篇 school of artifi...
14 篇 shenzhen institu...
14 篇 peng cheng labor...
13 篇 ieee
13 篇 college of compu...
12 篇 key laboratory o...
12 篇 beijing univ pos...
12 篇 yeshwantrao chav...

作者

25 篇 anatoliy sachenk...
22 篇 wu xinyu
18 篇 anatoly sachenko
16 篇 a. sachenko
16 篇 liu yang
16 篇 xiong gang
15 篇 chen chen
14 篇 sachenko anatoli...
12 篇 xinyu wu
12 篇 li yang
12 篇 yang yang
11 篇 zhang tao
11 篇 wang lei
11 篇 li peng
11 篇 li li
11 篇 kurosh madani
11 篇 sachenko a.
11 篇 wu bin
11 篇 iryna turchenko
11 篇 golovko vladimir

语言

18,146 篇 英文
498 篇 其他
81 篇 中文
2 篇 西班牙文

检索条件"任意字段=IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems"

共 18711 条记录，以下是51-60 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：

Edge-Centric IoT Health Monitoring: Optimizing Real-Time Responsiveness, data Privacy, and Energy Efficiency 6

Edge-Centric IoT Health Monitoring: Optimizing Real-Time Res...

引用

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

作者： Swathi, B. Veerabomma, Supraja Archana, M. Bhadru, Dharavath Somu, Naga Lakshmi Bhavsingh, M. Dept of CSE G Pulla Reddy Engineering College A.P. Kurnool India Department of ECE G Pullaiah College of Engineering and Technology A.P. Kurnool India Department of Computer Science and Engineering CVR College of Engineering Vasthunagar Hyderabad India CSE Department NarSimha Reddy Engineering college Telangana Maisammaguda India Shri Jagdishprasad Jhabarmal Tibrewala University Rajasthan Jhunjhunu India Department of CSE Ashoka Women’s Engineering College Andhra Pradesh Kurnool India

ISBN: (纸本)9798331522667

The innovation of IoT and edge computing has significantly advanced real-time health monitoring systems by providing timely data processing, improved responsiveness, and enhanced data privacy. This study introduces the Edge-Centric IoT Health Monitoring System (EC-HMS), which overcomes limitations observed in cloud-based and hybrid models, including high latency, data privacy vulnerabilities, and excessive energy consumption. EC-HMS leverages localized edge processing to reduce latency, safeguard sensitive data, and optimize energy efficiency, thereby enabling real-time health interventions. The proposed architecture integrates data acquisition, filtering, and anomaly detection at the edge layer, facilitating immediate decision-making and secure data transmission. Experimental evaluations highlight that EC-HMS achieves a 50 ms average latency, consumes 40% less energy compared to cloud-based systems, and ensures robust privacy through localized data handling. This research contributes to the advancement of scalable, responsive, and secure healthcare monitoring frameworks suitable for remote and resource-constrained environments. Future enhancements aim to incorporate predictive analytics and synchronization mechanisms to improve performance and adaptability further. © 2025 ieee.

关键词： Electronic health record

来源：评论

学校读者我要写书评

暂无评论

VTU Question Classification System based on BERT and Bloom's Taxonomy Ring' 5

VTU Question Classification System based on BERT and Bloom's...

引用

5th international conference on Emerging systems and intelligent computing, ESIC 2025

作者： Punyatoya, Swastisudha Vidya, N. Pradhan, Chittaranjan Thejaswini, S. Sahoo, Abhaya Kumar Shaista Afrin, Z. Sandhya, S. Kalinga Institute of Industrial Technology School of Computer Engineering Bhubaneswar India Mvj College of Engineering Department of Cse Bangalore India

ISBN: (纸本)9798331522100

The "VTU Question Classification System Based on BERT and Bloom's Taxonomy"integrates advanced Natural Language Processing (NLP) techniques to automate the classification of questions related to education. Utilizing the BERT (Bidirectional Encoder Representations from Transformers) model, the system aims to categorize questions into respective cognitive levels as defined by Bloom's Taxonomy. This initiative addresses the challenges of manual question classification, which is often time-consuming and prone to errors. The application encompasses stages of data gathering, preprocessing, model fine-tuning, and developing an accessible user interface. The expected outcomes include an efficient NLP system capable of accurately classifying questions, thereby aiding in aligning educational assessments with specific learning objectives. This work contributes to the enhancement of educational assessment techniques and offers potential for future advancements in the application of NLP in education. © 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

Advancements in AI-Powered Robotic Cleaning systems: Autonomous Path Planning, Predictive Maintenance, and Cleanliness Assessment Frameworks 3

Advancements in AI-Powered Robotic Cleaning Systems: Autonom...

引用

3rd international conference on intelligent data Communication Technologies and Internet of Things, IDCIoT 2025

作者： Jones Sarah, A. Nandhakumar, D. Kumar, Atchitha Magesh Pavithra, S. Department of Computer Science and Engineering Chennai Institute of Technology Tamilnadu Chennai600069 India

ISBN: (纸本)9798331527549

Artificial Intelligence (AI) is transforming robotic cleaning systems to be more efficient, safe, and adapt in various environments, including public spaces and industrial facilities. The novelty of these systems is the use of advanced sensing and deep learning to identify areas that need cleaning, plan paths, and save resources all while meeting high cleanliness standards required in sensitive areas like hospitals and pharmaceutical facilities. The objective is how recent developments in path planning, dirt detection, and predictive maintenance improve these systems, which reduce costs and perform without human supervision. Though these systems work well, challenges remain in deciding on cleaning paths for complex spaces, correctly detecting various types of dirt, adapting to changing environments, and maintaining to prevent breakdowns. © 2025 ieee.

关键词： Predictive maintenance

来源：评论

学校读者我要写书评

暂无评论

Optimizing data Movement in Heterogeneous computing: A LASSA-based Approach for Efficient Nucleation List Precomputation 3

Optimizing Data Movement in Heterogeneous Computing: A LASSA...

引用

3rd international conference on intelligent systems, advanced computing, and Communication, ISACC 2025

作者： Bhowmik, Biswajit Girish, K.K. Pandey, Himanshu Prabhanjans, Piyus National Institute of Technology Karnataka BRICS Laboratory Dept. of Computer Science and Engineering Mangalore India National Institute of Technology Karnataka Ishwarchandra Vidyasagar AIT Lab BRICS Laboratory Dept. of Computer Science and Engineering Mangalore India National Institute of Technology Karnataka Maharshi Sushrut CAS Lab BRICS Laboratory Dept. of Computer Science and Engineering Mangalore India

ISBN: (纸本)9798331523893

In the rapidly evolving landscape of heterogeneous computing, the efficiency of data movement between CPUs and GPUs can make or break system performance. Despite advancements in parallel processing, existing methods for managing data transfers - particularly in GPU offloading scenarios - suffer from significant inefficiencies. These inefficiencies are particularly evident in nucleation list precomputation for non-equilibrium solidification models, where redundant data movements and complex dynamic work-sharing in OpenMP lead to significant performance overhead. To tackle this issue, this paper proposes a novel solution that integrates the Location-Aware Heap Static Single Assignment (LASSA) algorithm into the compilation process. This approach identifies and eliminates redundant memory copy operations, optimizing data transfers and reducing overhead. The findings reveal a dramatic performance boost, with up to a 9.6-fold increase in efficiency. By addressing the specific challenges of nucleation list precomputation, this work provides valuable insights into optimizing data movement in heterogeneous computing environments, paving the way for enhanced performance in parallel programming models. © 2025 ieee.

关键词： Cellular Automata Models Heterogeneous computing Nucleation List Precomputation OpenMP Performance Issues System Efficiency

来源：评论

学校读者我要写书评

暂无评论

Enhancing data Security and Privacy in Cloud computing: A Survey of Modern Techniques 3

Enhancing Data Security and Privacy in Cloud Computing: A Su...

引用

3rd international conference on intelligent data Communication Technologies and Internet of Things, IDCIoT 2025

作者： Suganya, N. Gouthami, P. Sathiya, R. Sivaranjani, S. Murugesan, M. Department of Computer Science and Business Systems Dr. N.G.P. Institute of Technology Coimbatore India Department of Information Technology Thangavelu Engineering College Chennai India Departement of Electrical and Electronics Engineering Sri Krishna College of Engineering and Technology Coimbatore India Departement of Electrical and Electronics Engineering Karpagam Institute of Technology Coimbatore India

ISBN: (纸本)9798331527549

A computing system that is based on the internet and offers users all resources as on-demand services. Servers, storage, databases, software, and networking are among these on-demand services. Usually, the user must pay for the use of the resources;they are not their property. The number of people using this technology is increasing dramatically as a result of these features. Although it has benefits, cloud computing poses certain security and privacy risks. The authorized user’s data can be stolen easily. This current research thoroughly investigates modern strategies to these problems, highlighting identity management protocols, effective encryption and blockchain-based solutions. The article identifies research gaps, focuses attention to the inadequacies of current approaches, and recommends the possible ways to improve the efficiency, scalability and trustworthiness. © 2025 ieee.

关键词： Cloud security

来源：评论

学校读者我要写书评

暂无评论

intelligent Control Mechanisms for Renewable Energy Integration Using Machine Learning Models

Intelligent Control Mechanisms for Renewable Energy Integrat...

引用

2025 international conference on Pervasive Computational Technologies, ICPCT 2025

作者： Chahar, Suman Kaur, Kawaljit Kaswan, Kuldeep Singh Malik, Kiran University Institute of Computing Chandigarh University Mohali India Galgotias University Department of Computer Science and Engineering Greater Noida India Gl Bajaj Institute of Technology and Management Department of Computer Science and Engineering-AIML Greater Noida India

ISBN: (纸本)9798331508685

The deployment of renewable energy sources (RES) in power systems used to be a major challenge owing to their intermittent and uncertain nature. Therefore, in this paper, the use of ML models as an intelligent control system to improve the operation of RES is studied. We survey different types of ML approaches, covering supervised learning for energy predic- tion, unsupervised learning for clustering demand, reinforcement learning for energy storage management, and deep learning for real time data processing. The intent of these advanced control strategies are to balance and stabilize the grid, harmonize demand response, and augment energy storage. We highlight the use-cases and impacts of ML from real-world cases across various geographies, showing operational gains and peak-demand savings. While these technologies hold great promise, they also face challenges like data privacy, interpretability of models, and availability of high-quality datasets. Moving forward, there is a need to improve transparency of algorithms and to strengthen the collaboration of different stakeholders. Our work paves the way for a systematic and automated approach to renewable energy integration, which can serve as a critical factor to build a reliable and efficient future modern power systems with machine learning. © 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

datashield: Developing and Implementing advanced Cloud Security Solutions

Datashield: Developing and Implementing Advanced Cloud Secur...

引用

2025 international conference on computing for Sustainability and intelligent Future, COMP-SIF 2025

作者： Swetha, M.S. Muneshwara, M.S. Yadav, Shreyas A. Naveen, Shresta Shreya, M.J. Bms Institute of Technology & Management Dept. of Ise Bengaluru India Bms Institute of Technology & Management Dept. of Cse Bengaluru India

ISBN: (纸本)9798331538538

Cloud security is an important aspect of protecting data and applications hosted in cloud environments from both external and insider threats. dataShield: Enhanced Cloud Security System, presents a robust mechanism to ensure the integrity, confidentiality, and security of sensitive data in cloud storage and transfer. The present work uses Elliptic Curve Cryptography (ECC) to encrypt files, and the present system doesn't provide Erasure method. The proposed system is introducing a secure and efficient framework for handling sensitive data in the cloud, including advanced cryptographic techniques and a wellstructured workflow. The research work focuses on providing a secure framework i.e. Elliptical cryptography method for security in combination with Erasure method for splitting them into three fragments stored across separate cloud locations. Unique cryptographic key is issued by the system to ensure detection and flagging of changes in stored files. A unique key is generated using random key generation. With this unique key generated randomly users can upload, edit and download files in the system which is secured with the ECC technology and the Erasure method. Files encrypted and fragmented give good protection against breaches in the data and resilience to hacking attacks. This contrasts from normal IT systems, which exist in self-controlled networks. Third- party infrastructure for cloud computing has given rise to additional vulnerabilities to data. dataShield protects against these risks through distributing file storage and combining such with advanced cryptographic techniques;thus, sensitive information will never be compromised while access to the files remains open to the original users. The response time of the system is comparatively faster than the existing ones and around 30% quicker than existing systems. The throughput has improved by a similar margin, processing approximately 120 requests per seconds for 50 concurrent users. © 2025 ieee.

关键词： Sensitive data

来源：评论

学校读者我要写书评

暂无评论

An intelligent SCADA System for Power Distribution Network Cable Fault Detection with Real-Time Monitoring and Autonomous Maintenance 4

An Intelligent SCADA System for Power Distribution Network C...

引用

4th international conference on Robotics, Electrical and Signal Processing Techniques, ICREST 2025

作者： Nahidul Islam, S.M. Ahmad, Shameem Prodhan, Md. Mahbub-E-Elahi Khan Chowdhury, Md. Shoaib Bin Mizan, Sakib Ahmed, Abir Jahan, Effat Hazari, Md. Rifat Hossain, Chowdhury Akram American International University-Bangladesh Faculty of Engineering Department of Electrical and Electronic Engineering Dhaka1229 Bangladesh American International University-Bangladesh Faculty of Engineering Department of Computer Engineering Dhaka1229 Bangladesh

ISBN: (纸本)9798331530938

Supervisory Control and data acquisition (SCADA) systems are significant for boosting industrial operations, but established systems often struggle with fault management and real-time monitoring. To address these issues, this paper proposes an advanced SCADA system that integrates IoT technologies, multi-agent systems, and predictive maintenance for seamless data collection, analysis, and decision-making. Machine learning enhances fault detection and cybersecurity, while a modular hardware design allows scalability and flexibility to various industrial environments. The system is highly sensitive to detecting faults, including open circuit faults, line-to-ground faults, line-to-line faults, double line to ground faults and three-phase faults. It improves operational safety and efficiency by accurately locating faults and notifying professionals in real time. Extensive simulations and hardware tests were conducted to validate its performance in different fault scenarios. The results show that the proposed SCADA system has successfully detected different types of faults, offering a unified approach for fault management, maintenance, and real-time monitoring. © 2025 ieee.

关键词： SCADA systems

来源：评论

学校读者我要写书评

暂无评论

Integrating Big data Analytics in Soil Quality Assessment: Techniques, Challenges, and Applications 3

Integrating Big Data Analytics in Soil Quality Assessment: T...

引用

3rd international conference on intelligent and Innovative Technologies in computing, Electrical and Electronics, IITCEE 2025

作者： Mohammed, Shehu Singh, Arun Hanif, Md Abu Lovely Professional University Department of Computer Applications Phagwara India Lovely Professional University Department of Computer Science and Engineering Phagwara India Department of Computer Science 365 5th Ave New YorkNY110016 United States

ISBN: (纸本)9798331515911

This review paper investigates the application of Big data analytics, focusing on soil quality assessment, with an emphasis on the innovative benefits offered by modern data-driven techniques for improved soil management. With world food demands rising, the importance for real-time and exact soil quality monitoring has increased. Although still useful, traditional approaches to modeling are limited in their ability to capture the spatial and temporal variability of soil properties. Big data analytics sits as the answer to the above by facilitating extensive and large volume data processing resulting in better, on-demand and scalable soil quality assessment. In the paper, we describe machine learning algorithms, remote sensing and geospatial analysis as key techniques to mine soil data at scales and resolutions unprecedented so far. We also critically evaluate the challenge of data integration (heterogeneity, scalability and multi-disciplinarity). These analytics are scalable for assessment and decision-making in precision agriculture, sustainable land management and environmental conservation. Thus, this paper synthesizes current research and practical implications in support of the need for Big data analytics within soils and soil sciences to cover also future challenges. Future research directions are also highlighted, including the importance of improved data acquisition and algorithmic advances as well greater synergy between Big data and conventional soil science practices.. © 2025 ieee.

关键词： data quality

来源：评论

学校读者我要写书评

暂无评论

Audit Risk Identification based on Mutual Information with Backpropagation Neural Network 1

Audit Risk Identification based on Mutual Information with B...

引用

1st international conference on intelligent systems and Computational Networks, ICISCN 2025

作者： Su, Di Tianjin Tianshi College Tianjin China

ISBN: (纸本)9798331529246

In recent years, identifying audit risk had become important for maintaining financial transparency and detecting fraud. Instead of focusing solely on risk valuation, there had been an increased demand for advanced audit systems. The existing methods suffer from irrelevant feature inclusion, slow convergence in audit risk classification. Therefore, this research proposes Mutual Information based Backpropagation Neural Network (MI-BPNN) for identifying audits risks. Initially, audit data dataset is taken which incorporated audit data information of various firms. The collected audit is preprocessed by utilizing data cleaning which removes errors and normalization for ensuring uniform. Then this audit data features are selected by employed MI method for selecting the most informative indicators. The selected relevant features are evaluated for detecting the fraudulent firms by utilizing BPNN method. The proposed MI-BPNN achieved better results which comprises accuracy of (98.58%), specificity of (97.95%), sensitivity of (96.69%), and recall of (97.20%) when compared with existing Long Short-Term Memory (LSTM). © 2025 ieee.

关键词： audit risk identification backpropagation neural network data cleaning fraudulentfirms mutual information

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 << < 2 3 4 5 6 7 8 9 10 11 > >>

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：