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

85,859 篇 会议
397 篇 期刊文献
68 册 图书
1 篇 学位论文

馆藏范围

86,325 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

53,946 篇 工学
- 43,083 篇 计算机科学与技术...
- 31,581 篇 软件工程
- 13,370 篇 信息与通信工程
- 9,673 篇 控制科学与工程
- 8,710 篇 电气工程
- 4,910 篇 生物工程
- 4,109 篇 生物医学工程（可授...
- 3,830 篇 电子科学与技术（可...
- 3,463 篇 机械工程
- 3,264 篇 仪器科学与技术
- 2,954 篇 动力工程及工程热...
- 2,870 篇 交通运输工程
- 2,742 篇 安全科学与工程
- 2,377 篇 网络空间安全
- 2,135 篇 光学工程
20,152 篇 理学
- 10,696 篇 数学
- 5,372 篇 生物学
- 4,193 篇 统计学（可授理学、...
- 3,564 篇 物理学
- 3,174 篇 系统科学
- 2,082 篇 化学
15,760 篇 管理学
- 10,187 篇 管理科学与工程(可...
- 7,507 篇 图书情报与档案管...
- 4,854 篇 工商管理
4,289 篇 医学
- 3,501 篇 临床医学
- 3,351 篇 基础医学(可授医学...
- 2,101 篇 公共卫生与预防医...
- 1,794 篇 药学(可授医学、理...
2,401 篇 法学
- 1,960 篇 社会学
1,776 篇 经济学
- 1,764 篇 应用经济学
1,212 篇 农学
736 篇 教育学
294 篇 文学
187 篇 军事学
66 篇 艺术学
3 篇 哲学
3 篇 历史学

主题

4,178 篇 data mining
3,606 篇 data models
3,409 篇 computer science
2,417 篇 real-time system...
2,378 篇 training
2,280 篇 computational mo...
2,203 篇 feature extracti...
2,066 篇 accuracy
1,984 篇 big data
1,791 篇 machine learning
1,766 篇 predictive model...
1,484 篇 deep learning
1,414 篇 cloud computing
1,243 篇 monitoring
1,242 篇 internet of thin...
1,147 篇 neural networks
1,112 篇 conferences
1,096 篇 computer archite...
995 篇 databases
984 篇 learning systems

机构

154 篇 university of sc...
98 篇 school of comput...
91 篇 school of automa...
83 篇 chitkara univers...
77 篇 institute of inf...
77 篇 college of compu...
73 篇 school of comput...
72 篇 huazhong univers...
69 篇 school of comput...
55 篇 department of co...
54 篇 school of comput...
53 篇 shandong provinc...
52 篇 academy of mathe...
52 篇 tsinghua univers...
50 篇 school of inform...
49 篇 college of compu...
49 篇 sathyabama insti...
43 篇 lovely professio...
42 篇 shanghai jiao to...
40 篇 graphic era hill...

作者

55 篇 wang lei
51 篇 zhang lei
50 篇 li yang
44 篇 li peng
41 篇 li xin
38 篇 wang jing
37 篇 gill kanwarparta...
37 篇 jun wang
36 篇 zhang tao
33 篇 lei wang
32 篇 rui wang
32 篇 yang bo
30 篇 yu wang
27 篇 xiao liu
23 篇 zhang lin
22 篇 zheng wei
22 篇 hui wang
21 篇 anjali t.
21 篇 pareek piyush ku...
21 篇 wang hui

语言

83,188 篇 英文
2,847 篇 其他
294 篇 中文
8 篇 俄文
7 篇 西班牙文
4 篇 土耳其文
2 篇 法文
2 篇 葡萄牙文

检索条件"任意字段=IEEE International Conference on Data Science and Data Intensive Systems"

共 86325 条记录，以下是191-200 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 Age-Related Robustness in Children Speaker Verification

Enhancing Age-Related Robustness in Children Speaker Verific...

引用

2025 ieee international conference on Acoustics, Speech, and Signal Processing, ICASSP 2025

作者： Shetty, Vishwas M. Zheng, Jiusi Lulich, Steven M. Alwan, Abeer Department of Electrical and Computer Engineering University of California Los Angeles United States Speech Language and Hearing Sciences Indiana University BloomingtonIN United States

ISBN: (纸本)9798350368741

One of the main challenges in children's speaker verification (C-SV) is the significant change in children's voices as they grow. In this paper, we propose two approaches to improve age-related robustness in C-SV. We first introduce a Feature Transform Adapter (FTA) module that integrates local patterns into higher-level global representations, reducing overfitting to specific local features and improving the inter-year SV performance of the system. We then employ Synthetic Audio Augmentation (SAA) to increase data diversity and size, thereby improving robustness against age-related changes. Since the lack of longitudinal speech datasets makes it difficult to measure age-related robustness of C-SV systems, we introduce a longitudinal dataset to assess inter-year verification robustness of C-SV systems. By integrating both of our proposed methods, the average equal error rate was reduced by 19.4%, 13.0%, and 6.1% in the one-year, two-year, and three-year gap inter-year evaluation sets, respectively, compared to the baseline. © 2025 ieee.

关键词： Children Speaker Verification data augmentation Domain adaptation Inter-Year Child Speaker Verification

来源：评论

学校读者我要写书评

暂无评论

Agricultural Water Conservation through AI-Enhanced Solar IoT Networks 3

Agricultural Water Conservation through AI-Enhanced Solar Io...

引用

3rd international conference on Electronics and Renewable systems, ICEARS 2025

作者： Maniraj, S.P. Monisha, J. Amutha, R. Kavitha, R. Shriidhar, P.J. Srinivasan, C. Srm Institute of Science and Technology School of Computing Department of Data Science and Business Systems Kattankulathur Tamilnadu Chennai India Tamil Nadu Chennai India Ultra College of Engineering and Technology Department of Electrical and Electronics Engineering Tamil Nadu Madurai India Chennai Institute of Technology Department of Computer Science and Engineering Tamil Nadu Chennai India Vinayaka Missions Kirupananda Variyar Engineering College Department of Computer Science and Engineering Tamil Nadu Salem India Saveetha Universityi Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Department of Computer Science and Engineering Tamil Nadu Chennai India

ISBN: (纸本)9798331509675

With the increasing water shortage and climatic uncertainty, creative strategies for effective water management in agriculture are necessary. This research investigates the integration of Artificial Intelligence (AI), particularly Artificial Neural Networks (ANN), with solar-powered Internet of Things (IoT) networks to enhance water utilization in agricultural activities. The proposed system facilitates accurate irrigation scheduling using real-time data from soil moisture sensors, meteorological stations, and crop health monitoring devices. The ANN model analyses this data to predict ideal irrigation schedules and volumes, minimizing water waste while improving crop yields. The solar-powered IoT framework provides sustainability and reduces dependence on traditional energy sources. Field trials indicate that the AI-enhanced system may promote water saving by as much as 30% relative to traditional irrigation techniques. Moreover, using AI enables adaptive learning, enabling the system to enhance its irrigation tactics using historical and real-time data. This novel method conserves water resources and fosters sustainable agriculture practices, coinciding with global initiatives to address water shortages and assure food security. The findings underscore the potential of technology-based solutions to revolutionize agricultural water management for a sustainable future. © 2025 ieee.

关键词： Smart agriculture

来源：评论

学校读者我要写书评

暂无评论

Fault Tolerant Quality of Service Provisioning in Internet of Things using One Class Support Vector Machine 1

Fault Tolerant Quality of Service Provisioning in Internet o...

引用

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

作者： Fallaah, Mohhamied Husaein Shanthi, T. Reddy, S. Balakrishna Rajavadhani, K. Sandhya, K. The Islamic University College of Technical Engineering Department of Computers Techniques Engineering Najaf Iraq Sona College of Technology Department of Electronics and Communication Engineering Salem India Hyderabad India Dhanalakshmi Srinivasan College of Engineering and Technology Department of Computer Science and Engineering Mamallapuram India Tirupati India

ISBN: (纸本)9798331529246

In recent years, the rapid development of the Internet of Things (IoT) has made fault tolerance is important for maintaining service quality and system availability. Fault tolerance Quality of Service (QoS) provisioning ensures IoT systems operate continuously, even in presence of failures or malfunctions. Traditional approaches for QoS provisioning had face several challenges which include data security risks, inconsistent updates. Therefore, this research proposes One Class Support Vector Machine (OCSVM) for fault tolerant QoS provisioning in IoT systems. Initially, data is collected from Message Queuing Telemetry Transport-IoT-Intrusion Detection System (MQTT-IoT-IDS 2020) and preprocessed by using Expectation Maximization (EM) which reduces noise in data and handles missing data. Finally, provisioning and fault detection is done by using proposed OCSVM which detected faults and communication errors. The proposed OCSVM achieved better results in Execution time (220.61), Execution Cost (793.02) and Energy Consumption (22J) when compared with existing Fault-Tolerant and data-Oriented Scientific Workflow Management and Scheduling System (FD-SWMS). © 2025 ieee.

关键词： Telemetering systems

来源：评论

学校读者我要写书评

暂无评论

FedRPN: An Efficient Framework for Optimizing System Heterogeneity in Federated Learning

FedRPN: An Efficient Framework for Optimizing System Heterog...

引用

2025 ieee international conference on Acoustics, Speech, and Signal Processing, ICASSP 2025

作者： Xue, Baolu Zheng, Hanyuan Zhang, Jiale Liu, Jiewen Chen, Bing Nanjing University of Aeronautics and Astronautics Nanjing China Yangzhou University Yangzhou China Collaborative Innovation Center of Novel Software Technology and Industrialization Nanjing China

ISBN: (纸本)9798350368741

Federated Learning (FL) enables machine learning tasks to be performed on distributed data in a privacy-preserving manner, but faces challenges related to the heterogeneity of device systems. This necessitates the customization of resource requirements to accommodate the diverse capacities of participating clients. However, existing approaches struggle to generate resource-customized, ready-to-use inference models while still incurring substantial resource consumption throughout the system workflow. In response, this paper introduces a novel framework, FedRPN, which incorporates Resource-customized Prototypical Networks. RPN leverages resource-customized pretrained models as the initial point and employs unbiased prototypical classification, enabling rapid convergence, resource efficiency, and robustness to non-IID data. Additionally, we propose a globally-aware training strategy that produces deployable inference models of varying capacities. Building on RPN, we propose a two-stage process comprising prototype construction followed by model fine-tuning, which further enhances performance. Experimental results demonstrate that FedRPN reduces computational and communication resource consumption by 48% and 43%, respectively, while delivering improved performance. © 2025 ieee.

关键词： Federated Learning non-IID data prototypical network system heterogeneity

来源：评论

学校读者我要写书评

暂无评论

Life Expectancy: Insights from data Analysis

Life Expectancy: Insights from Data Analysis

引用

2025 international conference on Multi-Agent systems for Collaborative Intelligence, ICMSCI 2025

作者： Maheswari, B. Uma Sindhuja, L.S. Rajarajeshwari, K. Sujithra, M. Shanmugapriyaa, D. Psg College of Arts & Science Department of Networking and Mobile Application Coimbatore India Coimbatore Institute of Technology Department of Computing Coimbatore India

ISBN: (纸本)9798331509828

This research examines the application of transfer learning techniques to improve the accuracy of land-use classification in metropolitan areas. Traditional remote sensing methods usually fail to accurately classify complex urban land cover patterns. The current study exploits pre-trained models and fine-tuning strategies to improve the performance of LSTM and DNNs for LAC. Utilizing transfer learning, the models can learn effectively from large datasets and adapt to the complexities of urban environments even with limited labeled data. The study demonstrates the effectiveness of this approach using the UC-Merced-LandUse dataset, with heatmap analysis providing insights into the models' classification decisions. This research contributes to the advancement of land-use classification techniques, enabling more accurate and informed urban planning and environmental management. © 2025 ieee.

关键词： data accuracy

来源：评论

学校读者我要写书评

暂无评论

Recommendation of Ideological and Political Course Resources using Proximal Policy Optimization 1

Recommendation of Ideological and Political Course Resources...

引用

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

作者： Zhao, Jiayi Guangdong University of Science and Technology Dongguan China

ISBN: (纸本)9798331529246

In recent days, the recommendation of ideological and political course resources has become essential in developing student's understanding of political theories and values. Even though, previous researchers suggested various traditional recommendation methods still they face issues in capturing student's dynamic learning, high-dimensional resource space and sparse feedback. Therefore, this research develops a robust system utilizing deep reinforcement learning namely Proximal Policy Optimization (PPO) which provides an effective solution by enabling an adaptive learning process through policy-based optimization. Firstly, the data is collected through Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) model which develops questionnaire based on required model preferences. Then, the collected data is validated through Structural Equation Modelling (SEM). Furthermore, the validated data is embedded into the pre-trained model Generative Pre-trained Transformer 2 (GPT-2) which has vast data resources. Finally, PPO is integrated with GPT-2 for effective course recommendation of ideological and political courses. From the results, it is depicted that the proposed PPO model has acquired greater precision of 95.70% and recall of 94.36% when compared to the existing Collaborative Filtering (CF) model. © 2025 ieee.

关键词： Deep reinforcement learning

来源：评论

学校读者我要写书评

暂无评论

Efficient Multilingual Bidirectional Encoder Representations for Transformers based English Translation System with Multi Head Attention 1

Efficient Multilingual Bidirectional Encoder Representations...

引用

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

作者： Tang, Liang Chengdu College University of Electronic Science and Technology of China School of Liberal Arts and Sciences Chengdu China

ISBN: (纸本)9798331529246

Over past few years, Machine Translation (MT) has revolutionized significantly, enabling automatic translation of text from one language to another language in remarkable manner. However, traditional translation approaches solely focused on training and optimizing English Language Translation thereby limiting its capability for generalizing across all other languages. Therefore, this study proposes Multilingual-Bidirectional Encoder Representations for Transformers (mBERT) to improve the English machine translation. Initially, data is collected from Wikipedia Question Answer (WiKiQA) dataset which is taken from internet having candidate questions and answers. Followed by data preprocessing which uses data cleaning for removing outliers and stop word removal for eliminating special characters present in textual data. After that, the pre-trained mBERT model is employed for learning text as well as word embeddings in various contexts. Next, the Multi Head Attention (MHA) network is applied for analyzing complex sentences and smooth processing of larger sentence having dependencies in translation process which helps in natural translation. The proposed mBERT model achieves better Bilingual Evaluation Understudy (BLEU) score of 65.83 when compared to existing X-transformer. © 2025 ieee.

关键词： Machine translation

来源：评论

学校读者我要写书评

暂无评论

Integrated Hydroponics Automation System Utilizing IoT for Enhanced Plant Growth 3

Integrated Hydroponics Automation System Utilizing IoT for E...

引用

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

作者： Nilahni, N. Sivasakthi, P. Kavitha, P. Madhumathi, S.M. Sakthi Lakshmi Priya, C. Saranyavaishalini, V.G. Department of Computer Science and Engineering PSR Engineering College Sivakasi India

ISBN: (纸本)9798331527549

Growing plants in nutrition solution with any growing medium or roots dipped in distilled water is Hydroponics. Hydroponics, the practice of growing plants in a nutrient-rich solution without soil, offers significant advantages such as higher yield, reduced water usage, and efficient resource management compared to traditional farming. However, existing hydroponic systems often require separate monitoring and control platforms for different setups, such as Wick and Drip systems, increasing complexity and cost. This paper proposes a Combined Hydroponics Automation System utilizing IoT, integrating both Wick and Drip systems into a single, unified platform. The system employs Nodemcu ESP8266 to monitor key parameters such as pH, humidity, moisture, and water levels, with data transmitted to a cloud platform for real-time access and control. The unified approach reduces development and operational costs while simplifying the monitoring process. The outcome demonstrates improved efficiency in plant management, with streamlined data visualization, remote control, and optimized resource allocation, making it a cost-effective solution for urban and resource-limited farming environments. © 2025 ieee.

关键词： Hydroponics

来源：评论

学校读者我要写书评

暂无评论

Hybrid Blockchain and IoT Driven Framework for Supply Chain Optimization by Enhancing Transparency, Efficiency and Cost Reduction 3

Hybrid Blockchain and IoT Driven Framework for Supply Chain ...

引用

3rd international conference on Electronics and Renewable systems, ICEARS 2025

作者： Pradeep Kumar, S. Basha, C.H. Hussaian Prasath, C. Arun Amirthayogam, G. Lathif, Syed Ismail Abdul Leelavathi, R. Rajalakshmi Engineering College Computer Science Design Department Thandalam Chennai602105 India Sr University Department of Electrical and Electronics Engineering Warangal506371 India Mahendra Engineering College Department of Ece Namakkal637503 India Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology School of Computing Department of Computer Science and Engineering Chennai600062 India Srm Institute of Science and Technology Department of Data Science and Business Systems Chennai603203 India Velalar College of Engineering and Technology Department of Biomedical Engineering Erode638012 India

ISBN: (纸本)9798331509675

Blockchain technology represents a modern supply chain management revolution which fixes operational challenges while providing enhanced transparency at reduced costs. The research develops HB-SCOF (Hybrid Blockchain-Enabled Supply Chain Optimization Framework) which combines blockchain self-verification databases with automatic smart contracts to maintain continuous supply chain observation and evaluate data credibility. The framework integrates tamper-proof transaction tracking mechanisms with unified supply chain network connectivity for securing data transmission as a trust delivery method through unbreakable shared databases. The retail-industry case study demonstrated a 25% decrease in expenses stemming from agency elimination alongside enhanced flow management and better stock distribution. The system demonstrates its effectiveness through assessments of key performance indicators including transaction speed and data accuracy together with business cost efficiency. This part looks at implementation methods through training stakeholders in addition to transforming organizational policies which produce successful outcomes. Blockchain technology labs verify its capability to enhance supply chain management efficiency while showing realistic deployment methods. © 2025 ieee.

关键词： Smart contract

来源：评论

学校读者我要写书评

暂无评论

Next-Gen IoT Battery and Cooling System for EV Safety and Efficiency 3

Next-Gen IoT Battery and Cooling System for EV Safety and Ef...

引用

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

作者： Selvanayagi, A. Kaleeswaran, T. Bhuvaneshwaran, M. Kavinraj, N. Logesh, C.N. Department of Computer Science and Engineering M.Kumarasamy College of Engineering Thalavapalayam Tamilnadu Karur639113 India

ISBN: (数字)9798331527549

ISBN: (纸本)9798331527549

The increasing adoption of EVs requires efficient battery management systems for optimal performance, safety, and increased battery life. An investigation of an IoT-based intelligent smart battery management system for EVs is presented. Here, real-time monitoring and analysis of important key parameters such as voltage, current, state of charge (SOC), and temperature are considered. It includes sensors, a microcontroller, and wireless communication transferring data to a cloud platform, hence allowing remote monitoring and control. It utilizes adaptive cooling to avoid overheating. It contains a display showing the status of the battery. The experimental results showed that the system had improved the performance of the battery, prevented thermal runaway for safety purposes, and made the lifespan of the battery longer. This is the nature of such methodology to create dependable, efficient, sustainable transportation using EV batteries. © 2025 ieee.

关键词： Battery management systems

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 << < 16 17 18 19 20 21 22 23 24 25 > >>

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：