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

15,262 篇 会议
109 册 图书
103 篇 期刊文献

馆藏范围

15,473 篇 电子文献
1 种 纸本馆藏

日期分布

学科分类号

9,010 篇 工学
- 5,113 篇 计算机科学与技术...
- 3,937 篇 软件工程
- 3,779 篇 控制科学与工程
- 2,615 篇 电气工程
- 1,531 篇 信息与通信工程
- 1,256 篇 机械工程
- 1,246 篇 电子科学与技术（可...
- 953 篇 动力工程及工程热...
- 747 篇 生物工程
- 703 篇 生物医学工程（可授...
- 623 篇 仪器科学与技术
- 536 篇 化学工程与技术
- 499 篇 交通运输工程
- 466 篇 光学工程
- 365 篇 安全科学与工程
- 346 篇 力学（可授工学、理...
- 302 篇 材料科学与工程（可...
- 296 篇 土木工程
4,125 篇 理学
- 2,094 篇 数学
- 1,193 篇 物理学
- 808 篇 生物学
- 720 篇 系统科学
- 520 篇 统计学（可授理学、...
- 484 篇 化学
1,711 篇 管理学
- 1,312 篇 管理科学与工程(可...
- 574 篇 工商管理
- 479 篇 图书情报与档案管...
497 篇 医学
- 459 篇 临床医学
- 410 篇 基础医学(可授医学...
- 302 篇 药学(可授医学、理...
235 篇 经济学
224 篇 法学
203 篇 农学
101 篇 教育学
51 篇 军事学
36 篇 文学
18 篇 艺术学

主题

817 篇 control systems
703 篇 automatic contro...
313 篇 computer science
305 篇 computational mo...
275 篇 mathematical mod...
254 篇 automation
225 篇 real-time system...
222 篇 computer archite...
204 篇 neural networks
194 篇 internet of thin...
156 篇 monitoring
149 篇 process control
146 篇 optimization
145 篇 switches
142 篇 stability analys...
141 篇 automatic voltag...
139 篇 cloud computing
138 篇 deep learning
137 篇 application soft...
129 篇 image segmentati...

机构

105 篇 school of automa...
85 篇 lovely professio...
34 篇 school of electr...
31 篇 department of co...
31 篇 department of el...
29 篇 department of el...
29 篇 mlr institute of...
26 篇 chitkara univers...
24 篇 college of medic...
24 篇 department of el...
23 篇 department of el...
21 篇 college of elect...
21 篇 radiology techni...
21 篇 galgotias univer...
19 篇 centro de invest...
19 篇 school of optica...
19 篇 college of elect...
18 篇 new horizon coll...
18 篇 beijing aerospac...
17 篇 department of au...

作者

25 篇 singh bhim
22 篇 g. silva-navarro
20 篇 mengchu zhou
19 篇 k.g. shin
19 篇 wang wei
17 篇 loukianov alexan...
16 篇 wang jing
15 篇 kang hee-jun
15 篇 yang yang
15 篇 m. a. reyes-barr...
14 篇 silva-navarro g.
14 篇 j.a. moreno-cade...
14 篇 valeriy vyatkin
14 篇 l. leija
13 篇 alexander g. lou...
13 篇 liu yang
12 篇 leija l.
12 篇 liu jun
12 篇 manish gupta
10 篇 flores-nava l.m.

语言

14,961 篇 英文
403 篇 其他
154 篇 中文
3 篇 西班牙文
1 篇 土耳其文

检索条件"任意字段=International Conference on Electrical Engineering Computing Science and Automatic Control"

共 15474 条记录，以下是201-210 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：

A UAV Target State Estimation Method by Fusing Game Reasoning to Eliminate Negative Particles 3rd

A UAV Target State Estimation Method by Fusing Game Reasonin...

引用

3rd international conference on Machine Learning, Cloud computing and Intelligent Mining, MLCCIM 2024

作者： Han, Wei Yang, Guang Luo, Ling Dong, Jingwei Xu, Peng Sun, Xuefei Command and Control Engineering College Army Engineering University of PLA Nanjing210007 China

ISBN: (纸本)9789819624676

Aiming at Unmanned Aerial Vehicle (UAV) target state estimation, a dynamic space model between the electro-optical platform and the target is established, and a target state estimation method by fusing game reasoning is proposed. The payoff matrix is defined according to the game concept. Then, the proposed density distribution function of particle swarm is established, and the particle filter method is improved by fusing the game reasoning. The state of the moving target can be accurately estimated by the retained effective particles. Through simulation experiments, the validity of state estimation results of moving target under different moving trajectories is analyzed and verified. The research in this paper can meet the requirements of the current UAV velocity measurement of maneuvering targets in terms of real-time and reliability. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Unmanned aerial vehicles (UAV)

来源：评论

学校读者我要写书评

暂无评论

Computer Vision Based Quality control for Molding Injection Machines 19th

Computer Vision Based Quality Control for Molding Injection...

引用

19th international conference on Soft computing Models in Industrial and Environmental Applications, SOCO 2024

作者： Moreno, Ramón García, Oscar Del Río Cristobal, Miguel Shankar Muthuselvam, Revanth María Sanjuan, José Vallejo, Andrés Wang, Ting Department of Advanced Manufacturing 4.0 Antolin Engineering Burgos Spain Instituto Tecnológico Catilla y Leon Burgos Spain College of Electrical Engineering and Control Science Nanjing Tech University and Southeast University Nanjing China

ISBN: (纸本)9783031750090

This paper presents a comprehensive study on the application of computer vision, specifically Convolutional Neural Networks (CNNs), for quality control in automotive interior manufacturing using Injection Molding Machines (IMMs). Despite the high precision and productivity of IMMs, a small percentage of defects persist. Addressing this, the paper compares four popular CNN algorithms—ResNet-50, SegNet, FCN, and PSPNet—on their ability to detect and analyze defects in post-manufacturing. The study outlines the advantages of IMMs, the challenges in defect management, and the potential of CNNs to revolutionize quality control processes. Experimental results demonstrate the efficacy of these algorithms, paving the way for enhanced quality management and reduced defect rates in the automotive sector. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

Emotion Decoding of Speech Using NLP Analysis Approach

Emotion Decoding of Speech Using NLP Analysis Approach

引用

2025 international conference on Intelligent control, computing and Communications, IC3 2025

作者： Bobbili, Charitha Dhushetti, Sri Varsha Harshith, Y. Shanmugapriyan, J. Hariharan, Shanmugasundaram Vaishnavi, Bandar Vardhaman College of Engineering Department of Artificial Intelligence and Data Science India Nsn College of Engineering and Technology Dept of Electrical and Electorics Engineering India Vardhaman College of Engineering Department of Artificial Intelligence and Data Science Hyderabad India

ISBN: (纸本)9798331527495

Emotion decoding of speech using NLP provides an integrated solution for emotion-driven applications. This project creates a comprehensive system for speech-to-text conversion, sentiment analysis, transcription accuracy evaluation, and senti- ment visualization. The system converts spoken audio into text using the SpeechRecognition library and the Google Web Speech API. To ensure reliability, transcription accuracy is assessed using the Levenshtein distance algorithm, which calculates the smallest number of edits necessary to determine the similarity between the transcribed text and the reference text. VADER (Valence Aware Dictionary and Sentiment Reasoner) from the NLTK library is used by the system for emotion analysis. It is a potent tool for assessing sentiment intensity and assigning sentiment scores to associated emotional states like positive, negative, or neutral. Actionable insights into the speech's emotional content are offered by this analysis. The system creates pie charts using Matplotlib to show sentiment distribution in order to improve interpretability. Users can quickly and naturally understand the emotion landscape thanks to this functionality. This system is well-suited for real-world uses like psychological analysis, where emotional states offer vital diagnostic information, and customer service, where comprehending client emotions is essential. It does this by integrating speech processing, transcription evaluation, sentiment analysis, and visualization into a coherent framework. © 2025 IEEE.

关键词： Emotion Recognition

来源：评论

学校读者我要写书评

暂无评论

Probabilistic Modeling and Uncertainty Quantification of Harmonic Distortions in Grid-Integrated Inverters Through Bayesian Neural Networks

Probabilistic Modeling and Uncertainty Quantification of Har...

引用

2025 international conference on Intelligent control, computing and Communications, IC3 2025

作者： Rao, Srinivasa Awasthy, Neeta Asha, V. Nijhawan, Ginni Singh, Gurmeet Albawi, Ali Annapoorna, E. Mlr Institute of Technology Department of Computer Science and Engineering Telangana Hyderabad India Gl Bajaj Group of Institutions Department of Computer Science and Engineering U.P. Mathura India New Horizon College of Engineering Bangalore India Lovely Professional University Phagwara India Galgotias university Department of Electrical Electronics & Communication Engineering Uttar Pradesh Gerater Noida203201 India College of Medical Technology The Islamic University Radiology Techniques Department Najaf Iraq Department of Aimle Griet Telangana Hyderabad India

ISBN: (纸本)9798331527495

Harmonic distortion in grid connected inverters Thus, impacts on power quality and system stability are high, and more especially for systems that use renewable energy sources. This research presents a new stochastic predictive modelling approach based on Bayesian Neural Networks for forecasting of harmonic distortions with prediction uncertainty. The proposed methodology uses data from the National Renewable Energy Laboratory (NREL) database that consists of detailed grid voltage, current under various REMs. Harmonics components derived via sophisticated signal processing algorithms then yields the desired data base for training and testing. The uncertainty of grid conditions can be modelled by means of probabilities due to the utilization of BNNs for improving the reliability of predictions. The combination of stochastic modelling and harmonic analysis in this work creates a complex approach to enhancing grid stability and power quality. As applied to renewable energy challenges, the common method enhances the proposed approach as a scalable and adaptive solution for the mitigation of harmonic impacts for future power systems. © 2025 IEEE.

关键词： Stochastic models

来源：评论

学校读者我要写书评

暂无评论

Attitude Stabilization control for Unmanned Aerial Vehicle with Robotic Arm Based on Fixed-Time Observer Active Disturbance Rejection control 3rd

Attitude Stabilization Control for Unmanned Aerial Vehicle w...

引用

3rd international conference on Machine Learning, Cloud computing and Intelligent Mining, MLCCIM 2024

作者： Mo, Fan Gu, Chaochen Wang, Kunkun Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai China

ISBN: (纸本)9789819616930

To address the periodic disturbances introduced by the manipulator mounted on the drone, as well as the overall system parameter variations caused by the robotic arm carried by the Unmanned Aerial Vehicle (UAV), the fixed-time convergence observer (FTCO) is introduced to ADRC to enhance the dynamic characteristics, including overshoot and convergence speed. The Active Disturbance Rejection controller (ADRC) is employed as the fundamental controller for UAV systems while the FTCO is used to rapidly observe disturbances and compensate them to the controller, aiming to counteract interference. The UAV system is established to verify the effect of Fixed-Time Convergence Observer-Active Disturbance Rejection controller (FTCO-ADRC) when it is compared to conventional ADRC and PID controller. The simulation outcome reveals that the FTCO-ADRC perform better in convergence speed, overshoot and robustness. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Disturbance rejection

来源：评论

学校读者我要写书评

暂无评论

Optimizing the Allocation of Dynamic Workloads in Cloud Infrastructure through the Use of Machine Learning for Cost-Effective Cloud Resource Management

Optimizing the Allocation of Dynamic Workloads in Cloud Infr...

引用

2025 international conference on Intelligent control, computing and Communications, IC3 2025

作者： Sivamuni, Kalaimagal Pugalendhi, G.S. Pandi, V. Samuthira Shobana, D. Lakshmi Priya, J. Archana, V. Panimalar Engineering College Department of Ai & Ds Varadharaj apuram Poonamallee Tamilnadu Chennai India Sri Krishna College of Engineering and Technology Department of Artificial Intelligence and Data Science Kuniamuthur Tamil Nadu Coimbatore India Chennai Institute of Technology Centre for Advanced Wireless Integrated Technology Tamil Nadu Chennai India Rajalakshmi Engineering College Department of Mechatronics Engineering Chennai India Saveetha Engineering College Department of Ece Chennai India Jeppiaar Institute of Technology Department of Aids Tamil Nadu Chennai India

ISBN: (纸本)9798331527495

The effective administration of dynamic workloads has emerged as a major obstacle for enterprises moving their operations to cloud computing. Intelligent allocation algorithms that guarantee optimal performance while minimizing operational expenses are necessary due to the fluctuation in demand for cloud resources. In order to achieve efficient and economical management of cloud resources, this study explores the use of machine learning (ML) methods to improve the distribution of dynamic workloads inside cloud infrastructure. In order to examine past workload data and forecast future resource needs, we present a thorough system that employs multiple ML algorithms, including supervised and unsupervised learning approaches. Our framework's goal is to automatically adjust to changing workload patterns and avoid under- or overprovisioning of resources by using data-driven insights to improve resource allocation in real-time. The platform relies on predictive analytics to foretell changes in workload, automatic resource scaling according to demand forecasts, and reinforcement learning to enhance allocation tactics in real-time. Extensive simulations and case studies are conducted across various cloud settings to test the efficiency of the proposed framework. In comparison to more conventional allocation strategies, the results show markedly higher rates of resource usage and lower costs. The flexibility of the framework to handle different types of workloads also highlights its wide range of possible uses in cloud computing. This research adds to the existing literature on cloud resource management and provides a solid method for improving the overall efficiency of cloud infrastructure and maximizing the distribution of workloads. Results highlight machine learning's revolutionary effect in propelling affordable cloud-based solutions for dynamic workload control. © 2025 IEEE.

关键词： Resource allocation

来源：评论

学校读者我要写书评

暂无评论

Dynamic Knowledge Graph Construction for Real-Time Natural Language Understanding in Autonomous Systems

Dynamic Knowledge Graph Construction for Real-Time Natural L...

引用

2025 international conference on Intelligent control, computing and Communications, IC3 2025

作者： Subhashini, P. Veeresh, G. Lakhanpal, Sorabh Sharma, Nidhi Saeed, Hazim Y. Soujanya, Rajireddy Mlr Institute of Technology Department of Computer Science and Engineering Telangana Hyderabad India New Horizon College of Engineering Bangalore India Lovely Professional University Phagwara India Galgotias university Department of Electrical Electronics & Communication Engineering Uttar Pradesh Gerater Noida203201 India College of Medical Technology The Islamic University Radiology Techniques Department Najaf Iraq Griet Department of Cse Bachupally Telangana Hyderabad India

ISBN: (纸本)9798331527495

This work presents Real- Time Semantic Mapping (RTSM), a new idea for improving the language comprehension in autonomous systems using the knowledge graph. RTSM solely relies on ConceptNet as its dataset and incorporate Spacy to parse and synchronize commends and signals from natural language appropriately. However, through the continuous updating of the knowledge graph, RTSM allows an autonomous system to provide accurate responding to real-time contextual changes with relatively low computational cost. Constant learning and semantic enhancement in this model make RTSM light and easily scalable, putting it at a higher ground as a natural language processing technique for use in autonomous systems. Due to a simple framework that makes it easy to incorporate all the knowledge, the RTSM is ideal in environments that are challenged for time and resources, but need to provide real time interaction capabilities. © 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 Survey on Application of Computational Technique for Two Area Interconnected automatic Generation control in Power System Using PSO-PID

A Survey on Application of Computational Technique for Two A...

引用

IEEE Students' conference on electrical, Electronics and Computer science (SCEECS)

作者： Arpit Yadav Lal Bahadur Prasad Rajan Kumar Department of Electrical Engineering Central Institute of Technology Kokrajhar Kokrajhar Assam India Department of Electrical Engineering Madan Mohan Malaviya University of Technology Gorakhpur U.P. India

ISBN: (数字)9798331529833

ISBN: (纸本)9798331529840

In this paper the various computational approaches for automatic generation control (AGC) of power systems is covers, with the goal of improving the automatic voltage regulator (AVR) and load frequency control (LFC) that are utilized with proportional integrative and derivatives (PID) controllers. PID tuning has long been a main area of current study, and PID controllers, sometimes known as proportional integrative and derivatives, are utilized in industry. The techniques being reviewed are conventional methods designed for PID based PSO optimization strategies that fit tuning requirements. Power engineering research and development now places a strong emphasis on optimization due to the growing requirement for energy. This paper deals on the electric power system applications of two area interconnected PSO based PID computational techniques to inspires power sector to uncover fresh information about the ideal rate of energy provision because of its creative application.

关键词： Surveys Industries Power engineering Regulators Reviews automatic generation control Power systems Optimization Tuning Research and development

来源：评论

学校读者我要写书评

暂无评论

Recurrent Mutual Attention Network with Transformer and LSTM Integration for Radiology Report Generation

Recurrent Mutual Attention Network with Transformer and LSTM...

引用

international conference on Applied Nonlinear Dynamics, Vibration and control, ICANDVC 2024

作者： Li, Zhenhao Wang, Chao Zhang, Yi Lin, Shen Yang, Xiaohui Geng, Haokun College of Information Science and Engineering University of Jinan Jinan250024 China Shandong Provincial Maternal and Child Health Care Hospital Jinan250014 China Jinan Authority Hospital Jinan250001 China Jinan Key Laboratory of Intelligent Medical Frontier Applications in Artificial Intelligence and Automation Jinan250001 China

ISBN: (纸本)9789819633166

Generating radiology reports by analyzing medical imaging data is becoming increasingly important not only in the research field but also in clinical practice. The automatic generation of accurate and coherent reports is of paramount importance to enhancing the efficiency and quality of medical diagnosis. Due to the rapid development of deep learning, automatic radiology report generation has evolved from simple feature transformation to cross-modal interactions between images and text. However, the correspondence between image regions and words remains unclear. Therefore, this paper proposes a recurrent mutual attention network that queries image features through text and then queries corresponding text features through image features. These features are then input into the report generation module. To enrich the semantic information, the long short-term memory (LSTM) is connected with the Transformer through gate control, enabling the automatic generation of radiology reports. The experimental results show that, compared with the other published methods, our proposed method has significantly improved the diagnostic report generation in quality, accuracy, and natural language fluency. Although our method has only been tested in radiology, it has shown potential usability in a wider range of different types of medical imaging analysis, due to its design principles and versatility. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Mammography

来源：评论

学校读者我要写书评

暂无评论

AI-Powered 6G Networks: Transforming Wireless Communication with Intelligence and Terahertz Waves

AI-Powered 6G Networks: Transforming Wireless Communication ...

引用

2025 international conference on Intelligent control, computing and Communications, IC3 2025

作者： Singh, Navdeep Devi, Runumi Singh, Jay Rajalakshmi, B. Mohammed, Mohammed Wael Thandra, Nagarjuna Vidyadhari, Chalasanvi Lovely Professional University Phagwara India Galgotias university Department of Electrical Electronics & Communication Engineering Uttar Pradesh Gerater Noida203201 India Gl Bajaj Institute of Technology and Management Dept. of Eee U.P. Gr. Noida India New Horizon College of Engineering Department of Computer Science Engineering Bangalore India College of Medical Technology The Islamic University Radiology Techniques Department Najaf Iraq Mlr Institute of Technology Department of Computer Science and Engineering Telangana Hyderabad India Griet Department of Information Technology Bachupally Telangana Hyderabad India

ISBN: (纸本)9798331527495

From 2027 to 2030, Sixth Generation (6G) wireless communication systems are expected to be launched to revolutionize human and machine interaction with ultra fast data transmission speeds and low, or virtually zero latency communication. In this paper, we investigate the transformative potential of 6G networks enabled by AI, and describe key 6G network technologies, including artificial intelligence (AI), machine learning (ML), and sub miiitter wave technology. In addition to being able to exceed 5G Maximum Throughput (MT), 6G is forecast to enable advanced applications including holographic communications, XR (extended reality), and ubiquitous M2M (machine to machine) interaction. Although significant obstacles remain with respect to security, energy efficiency, and spectrum management. In this paper, 5G development existing gaps are identified, and a comprehensive AI driven framework for resource allocation, latency reduction, and spectrum utilization optimization is proposed for 6G systems. This study further explores the position of edge computing, IoT integration, and AI powered network security protocols. Finally, we demonstrate real world applications, such as smart healthcare, autonomous vehicles, and space communications, discussing privacy and sustainability aspects of 6G technology. © 2025 IEEE.

关键词： Resource allocation

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 << < 17 18 19 20 21 22 23 24 25 26 > >>

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：