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

2,256 篇 会议
481 篇 期刊文献
23 册 图书

馆藏范围

2,760 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

1,614 篇 工学
- 1,097 篇 计算机科学与技术...
- 919 篇 软件工程
- 423 篇 控制科学与工程
- 361 篇 信息与通信工程
- 204 篇 电气工程
- 159 篇 机械工程
- 147 篇 电子科学与技术（可...
- 136 篇 生物工程
- 115 篇 动力工程及工程热...
- 99 篇 生物医学工程（可授...
- 78 篇 建筑学
- 77 篇 安全科学与工程
- 76 篇 仪器科学与技术
- 74 篇 光学工程
- 74 篇 交通运输工程
- 63 篇 化学工程与技术
- 61 篇 土木工程
823 篇 理学
- 454 篇 数学
- 214 篇 物理学
- 146 篇 统计学（可授理学、...
- 140 篇 生物学
- 140 篇 系统科学
- 58 篇 化学
447 篇 管理学
- 319 篇 管理科学与工程(可...
- 181 篇 工商管理
- 156 篇 图书情报与档案管...
116 篇 医学
- 91 篇 临床医学
- 75 篇 基础医学(可授医学...
84 篇 法学
- 73 篇 社会学
62 篇 经济学
- 62 篇 应用经济学
56 篇 农学
43 篇 教育学
8 篇 军事学
7 篇 文学

主题

73 篇 accuracy
64 篇 computational mo...
63 篇 real-time system...
55 篇 predictive model...
51 篇 feature extracti...
49 篇 training
48 篇 machine learning
46 篇 data mining
46 篇 data models
45 篇 deep learning
44 篇 optimization
37 篇 internet of thin...
37 篇 technological in...
36 篇 neural networks
36 篇 monitoring
35 篇 control systems
33 篇 artificial intel...
33 篇 testing
32 篇 support vector m...
31 篇 analytical model...

机构

20 篇 lovely professio...
17 篇 dept. of compute...
16 篇 dept. of compute...
16 篇 dept. of control...
14 篇 dept. of compute...
12 篇 graphic era deem...
12 篇 dept. of compute...
11 篇 graphic era hill...
10 篇 dept. of control...
9 篇 dept. of electro...
9 篇 dept. of informa...
8 篇 dept. of systems...
8 篇 dept. of compute...
8 篇 kalinga universi...
8 篇 dept. of automat...
8 篇 dept. of control...
8 篇 dept. of softwar...
8 篇 dept. of compute...
8 篇 dept. of softwar...
8 篇 sapienza univers...

作者

14 篇 lo hoi-kwong
14 篇 yang chao-tung
13 篇 reiner lisa
13 篇 deepak upadhyay
13 篇 chang chih-hung
12 篇 upadhyay deepak
12 篇 li kuan-ching
12 篇 bavarian behzad
10 篇 mridul gupta
10 篇 lu chih-wei
10 篇 chu william c.
10 篇 enrico macii
10 篇 he jianping
10 篇 olaf stursberg
9 篇 l. astolfi
9 篇 upadhyay abhay
9 篇 andrea acquaviva
9 篇 abhay upadhyay
9 篇 edoardo patti
9 篇 krejcar ondrej

语言

2,606 篇 英文
123 篇 其他
26 篇 中文
3 篇 朝鲜文
2 篇 日文

检索条件"机构=Dept. of Computer Control and Management Engineering"

共 2760 条记录，以下是661-670 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：

The Study of Online Appointment System - A Case Study 1

The Study of Online Appointment System - A Case Study

引用

1st International Conference on Computational Intelligence and Sustainable engineering Solution, CISES 2022

作者： Pankaj, Sabale Tomar, Ashwin Poojashree, Yadav Saurabh, Jadhav Bhatambrekar, Shubhangi Awasthi, Shashank Modern College of Arts Science and Commerce-gk Computer Science Department Pune India G.L. Bajaj Institute of Technology and Management Dept. of Comp. Science Engineering Noida India

The Online Appointment applicationprovides security which is a smart web application where doctors register themselves and finalize appointment of *** project developed is considered as Case study to find the efficacy... 详细信息

ISBN: (数字)9781665480048

ISBN: (纸本)9781665480048

关键词： Hospitals Data science Cameras Mobile handsets Registers Blockchains Security

来源：评论

学校读者我要写书评

暂无评论

Development of a OTA with DFVF for a 50nm VLSI Technology Application

Development of a OTA with DFVF for a 50nm VLSI Technology Ap...

引用

IEEE India Conference (INDICON)

作者： T.C. Manjunath Hareesh Kumar Rajani Rai B. S. Krishna Narayanan Padmavathi M. Pavithra G. Swapnil S. Ninawe Department of Electronics & Communication Engineering Dean (Research - R & D) Rajarajeswari College of Engineering Bangalore Karnataka Dept. of Electronics & Communication Engineering RV Institute of Technology & Management Bangalore Karnataka Dept. of Electronics & Communication Engineering Vivekananda College of Engineering and Technology Puttur South Kanara Karnataka Dept. of Computer Science & Engineering MVJ College of Engineering Bangalore Karnataka Department of Electronics & Communication Engineering Dayananda Sagar College of Engineering Bangalore Karnataka India

ISBN: (数字)9798350391282

ISBN: (纸本)9798350391299

This research paper presents the design and simulation of Multiple Path Fully Operational Transconductance Amplifiers (OTAs) with Dual Flipped Voltage Follower, targeted for VLSI-based signal processing applications. Leveraging 50nm CMOS technology and Cadence tools, the proposed OTA architecture offers enhanced performance and versatility in signal processing tasks. The design incorporates multiple paths for signal processing, enabling improved bandwidth, gain, and linearity while minimizing common-mode noise. The inclusion of Dual Flipped Voltage Follower enhances the OTA's stability and dynamic range, ensuring reliable operation in high-speed VLSI systems. Through extensive simulation studies, the paper demonstrates the effectiveness of the proposed OTA design in meeting the stringent requirements of modern signal processing applications. This research contributes to the advancement of VLSI design methodologies, offering a promising solution for high-performance signal processing tasks in nanoscale CMOS technologies. The simulation results from the cadence tool shows the effectiveness of the methodology that is being presented in this research article.

关键词： Simulation Noise Linearity Voltage Very large scale integration CMOS technology Stability analysis Nanoscale devices Reliability Transconductance

来源：评论

学校读者我要写书评

暂无评论

Remaining Useful Life Prediction of Multi-Component System Clustering with Time-Varying Kernel Density

Remaining Useful Life Prediction of Multi-Component System C...

引用

Chinese Automation Congress (CAC)

作者： Ke Li Xingle Fan Hui Shi Xiaohong Zhang Chaoli Sun Jianan Wang Dept. of Electronic and Information engineering Shanxi Key Laboratory of Advanced Control and Equipment Intelligence Taiyuan University of Science and Technology Taiyuan China Dept. of Economics and Management Shanxi Key Laboratory of Advanced Control and Equipment Intelligence Taiyuan University of Science and Technology Taiyuan China Dept. of Computer Science and Technology Shanxi Key Laboratory of Advanced Control and Equipment Intelligence Taiyuan University of Science and Technology Taiyuan China

Aiming at the uncertainty of the degradation procedure of a complex multi-component system in a time-varying environment and the influence of the random dependence between different components, a remaining useful life prediction model for time-varying adaptive kernel density estimation based on the dependence between multiple components is established. First, the random dependence between multi-component systems is clustered. Considering that different components in the same cluster are affected by the random dependence, the components between different clusters do not affect each other. Judge the dependence characteristics between components, and use the dependence characteristics of different components to conduct clustering degradation modelling. Secondly, the parameters of the system change with time. Considering that monitoring data near the current time has a greater impact on the remaining useful life prediction compared with historical data, data in the vicinity of the current time is accorded a more significant weight, and a time-varying kernel density estimation prediction method is designed, in which the nearest-neighbour adaptive window-width selection method is used. Finally, give an example to demonstrate the effectiveness by the proposed method.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Enhanced Handover management in 5G Networks using Machine Learning in Fading Scenarios 2

Enhanced Handover Management in 5G Networks using Machine Le...

引用

2nd International Conference on Computational Intelligence, Communication Technology and Networking, CICTN 2025

作者： Upadhyay, Deepak Rallapalli, Sreekanth Hussain, Zakir Venu, Nookala Sharma, Rashmi Shukla, Shipra Dept. of Computer Science and Engineering Graphic Era Hill University Dehradun India Department of MCA Nitte Meenakshi Institute of Technology Bengaluru India Centre for Internet of Things Madhav Institute of Technology & Science Deemed University Gwalior India Nagpur Campus Pune India G. L. Bajaj Institute of Technology and Management Greater Noida India

ISBN: (纸本)9798331530389

This study explores the use of machine learning (ML) to improve initial handover performance for 5G networks by analysing fading-affected scenarios. In this study, we assess the ability of ML models to predict optimal handover decisions compared with conventional methods. In this study, simulation results show that our ML-based methods can reduce the handover inaccuracy by 50%, decrease latency up to 10 times and stabilize network performance. We accompany our assessment with a series of graphical analyses to show how ML algorithms change their behaviour dynamically in response to deteriorating link intensity due user mobility and increasing h/o frequency, thereby degrading the network performance. The results clearly illustrate that ML enabled handover optimization is significantly more effective than traditional methods in accommodating fading-channel dynamics, thereby improving both the network performance and user experience of future generation wireless networks. © 2025 IEEE.

关键词： 5G mobile communication systems

来源：评论

学校读者我要写书评

暂无评论

A Framework Leveraging Robotics and Machine Learning Technologies for Early Disease and Pest Detection in Greenhouse Tomato Crops

A Framework Leveraging Robotics and Machine Learning Technol...

引用

International Conference on control, Artificial Intelligence, Robotics & Optimization (ICCAIRO)

作者： Nikolaos Kounalakis Emmanouil Kalykakis Dimitrios Kosmopoulos John Fasoulas Michael Sfakiotakis Control Systems and Robotics Laboratory (CSRL) School of Engineering Hellenic Mediterranean University Heraklion Greece Dept. of Computer Engineering and Informatics University of Patras Patras Greece

We present an integrated framework for intelligent automated plant monitoring, towards early disease and pest detection in greenhouse tomato crops. The framework combines the use of a robotic mobile platform to autonomously collect multi-spectral images of the plants, with a tool that utilizes Faster R-CNN to detect regions that signify the presence of a disease or pest. The robot is based on a modified mobile vertical mast lift platform, and integrates a 6-dof robotic arm that is used to position the plant imaging multi-spectral camera. The robot can navigate autonomously inside the greenhouse via a magnetic guidance sensor. Results from a series of experiments demonstrate the validity and effectiveness of the implemented framework.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Stacking Ensemble of Disproportionality Indicators for Adverse Vaccine Reactions Detection—An Empirical Study on Predicting Adverse Reactions of COVID-19 Vaccines

Stacking Ensemble of Disproportionality Indicators for Adver...

引用

Annual International Conference of the IEEE engineering in Medicine and Biology Society (EMBC)

作者： Bo-Xun Zhang Wen-Yang Lin Tsai-Kuei Huang Dept. of Computer Science and Information Engineering National University of Kaohsiung Taiwan Information Management Office Kaohsiung Veterans General Hospital Kaohsiung Taiwan Dept. of Computer Science and Information Engineering National University of Kaohsiung Kaohsiung Taiwan Dept. of Pharmacy Kaohsiung Veterans General Hospital Kaohsiung Taiwan

Vaccine safety is a critical issue for public health, which has recently become more crucial than ever since COVID-19 started to spread worldwide in 2020. Many COVID-19 vaccines have been developed and used without following the traditional three clinical trial stages. Instead, most COVID-19 vaccines were approved through emergency use approval (EUA) within one year, significantly raising the risk of rare and severe adverse events. Reporting systems like the Vaccine Adverse Event Reporting System (VAERS) have been established worldwide to detect unknown and severe adverse reactions as early as possible. Although experts and researchers have been working hard to find ways to detect adverse vaccine event (AVE) signals from VAERS data, most of the contemporary methods are statistical methods based on measuring the disproportionality between vaccine-induced events and non-vaccine-induced events. This paper proposes a novel ensemble AVE detection method, which adopts a stacking ensemble of various disproportionality indicators, fusing dual-scale contingency values measured in single and cumulative yearly duration, and embraces the concept of feature concatenation. Experiments conducted on US VAERS data to predict AVE caused by COVID-19 vaccines show that our proposed method is effective. We observed that: (1) Stacking ensemble of various disproportionality indicators is superior to any single disproportionality indicator and voting ensemble method; (2) Fusing dual-scale contingency values and feature concatenation brings synergy to our proposed stacking ensemble AVE detection. Compared to the best disproportionality metric in this study, our top-performing ensemble version exhibited a 34% improvement in accuracy, 71% in precision, 29% in recall, and 77% in F-measure, with a slight decrease (8%) in specificity.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Improvement of Protection Factor for a controlled Laboratory computer Network Using Artificial Intelligence

Improvement of Protection Factor for a Controlled Laboratory...

引用

engineering, Science and Advanced Technology (ICESAT), International Conference on

作者： Raid W. Daoud Enas F. Aziz Zaki M. Abdullah Ziyaad H. Saleh Electrical Tech. Dept. Northern Technical University Kirkuk Iraq Computer Systems Dept. Northern Technical University Kirkuk Iraq Petroleum Systems and Control Dept. College of Petroleum Processes Engineering Tikrit Iraq

computer networks provide exceptional privacy, primarily for testing and other educational activities. However, the security of computer networks is an exceptionally touchy subject, mainly when applied in labs and tests for educational purposes. Any software system created on a server typically requires a username and password to access a collection of computers on a particular network. The proposed work devised and implemented a neural network feedback network with four inputs (I.P. address, MAC address, user number, and time) and an output that represents the user's acceptance or rejection. A few instances of the data and numbers needed to train the neural network include the lab's address, the student's name, the academic stage's address, etc. Good results were obtained through the company's training and education, which was tested on more than 200 models, and the response aligned with the data. No user can access the network without first being recognized by the proposed network by comparing the pre-trained data to ensure they are authorized to take the exam or enter for any other reason.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Ethical Considerations in Data Mining and Analytics

Ethical Considerations in Data Mining and Analytics

引用

Advances in Computing, Communication and Networking (ICAC2N), International Conference on

作者： Priyanka Kaushik Khushboo Sharma Mukesh Kumar Mahawar Javed Wasim Gunadhar Dey S. Anto Nibiya Dept. of Com. Science Engineering Chandigarh University Chandigarh India Dept. of Commerce & Management Madhav University Pindwara India Dept. of Computer Eng. & Applications Mangalayatan University Aligarh India Dept. of Computing & IT Usha Martin University Jharkhand India Dept. of Mathematics Meenakshi A.H. Edu. & Research Chennai India

ISBN: (数字)9798350356816

ISBN: (纸本)9798350356823

As data mining & analytics technologies advance, they offer unprecedented opportunities for extracting valuable insights from vast datasets. However, these advancements bring forth a complex array of ethical considerations that must be addressed to ensure responsible practices in the field. This paper explores the ethical dimensions of data mining & analytics, focusing on key issues such as privacy, consent, & bias. Privacy concerns arise from the extensive collection & potential misuse of personal data, necessitating stringent measures to protect individuals’ information. Consent, a fundamental ethical principle, requires transparent practices where data subjects are informed & agree to the use of their data. Additionally, the challenge of algorithmic bias highlights how data-driven models can perpetuate or exacerbate existing inequalities if not carefully managed. The paper also examines the ethical implications of data ownership & the responsibilities of organizations in managing & communicating data effectively. Through a review of current practices, case studies, & regulatory frameworks, this study aims to provide a comprehensive overview of the ethical landscape in data mining & analytics. It proposes a set of best practices for professionals to navigate these challenges, emphasizing the need for ethical guidelines, ongoing education, & robust oversight mechanisms. By addressing these concerns, the paper seeks to foster a more responsible & equitable approach to data mining & analytics that balances innovation with the protection of individual rights & societal values.

关键词： Training Ethics Data privacy Adaptation models Technological innovation Reviews Navigation Data science Data models Complexity theory

来源：评论

学校读者我要写书评

暂无评论

A Machine Learning Model for Effective Consumer Behaviour Prediction 5

A Machine Learning Model for Effective Consumer Behaviour Pr...

引用

5th International Conference on Information Systems and computer Networks, ISCON 2021

作者： Anshu, Kalpana Singh, Sunil Kumar Kumari, Reenu Mahatma Gandhi Central University Dept. of Computer Science IT Bihar Motihari India Meerut Institute of Engineering Technology Dept. of Business and Management Studies Meerut India

ISBN: (纸本)9781665403412

Effective consumer behavior prediction can play a crucial role in online marketing, especially in the COVID19 scenario. In this work, we have analyzed consumer behavior to understand consumer needs and predict future requirements. For the same, we have applied the machine learning models on an amazon dataset collected from Kaggle. The dataset consists of reviewers' comments, ratings, many other parameters for the product. The model's outcome indicates that the proposed Random Forest model performs exceptionally well, and its Accuracy is approx. 98.73%. A comparative study has been done to show the efficacy of the work, and it has been observed that the performance of the proposed model is quite remarkable, and it can be a competent model for effective consumer behavior prediction. © 2021 IEEE.

关键词： Data visualization

来源：评论

学校读者我要写书评

暂无评论

AI-Driven Semiconductor Manufacturing via IC Failure Prediction: Cost-Effective Strategies for Process Improvement

AI-Driven Semiconductor Manufacturing via IC Failure Predict...

引用

Distributed Systems, computer Networks and Cybersecurity (ICDSCNC), International Conference on

作者： P. Shailaja K. Kranthi Kumar K. Sirnivas V. Bharath Simha Reddy Kesana Mohana Lakshmi D. Rajani Department of Computer Science Engineering Vaagdevi College of Engineering (UGC - Autonomous) Warangal India Dept. of EEE Kommuri Pratap Reddy Institute of Technology Hyderabad India Dept. Of CSE (AI & ML) St. Martin’s Engineering College Dhulapally Secunderabad India Department of Mechanical Engineering Malla Reddy Engineering College and Management Sciences India Dept. of ECE CMR Technical Campus Hyderabad India Dept. of ECE Sree Venkateswara College of Engineering Nellore India

ISBN: (数字)9798350375442

ISBN: (纸本)9798350375459

Integrated circuits (ICs) are fundamental components in a wide range of applications, including consumer electronics, automotive systems, telecommunications, and medical devices, where their reliable performance is crucial. However, identifying failures in ICs presents several challenges due to the complex nature of the circuits, variability in manufacturing processes, and the subtleties of faults that may not be easily detectable with traditional methods. To address these issues, a robust methodology incorporating data preprocessing, Synthetic Minority Over-sampling Technique (SMOTE) for data balancing, Principal Component Analysis (PCA) for feature extraction, and Random Forest classification is proposed. Data preprocessing involves cleaning and normalizing the dataset to ensure quality and consistency. SMOTE is then applied to address the imbalance in the dataset, enhancing the detection of minority class failures. PCA is used to reduce the dimensionality of the dataset, retaining essential features that capture the most variance, which improves the efficiency and accuracy of the model. Finally, Random Forest classification is employed due to its robustness and ability to handle large datasets with high dimensionality, providing a reliable prediction of IC failures.

关键词： Semiconductor device modeling Accuracy Data preprocessing Semiconductor device manufacture Feature extraction Telecommunications Telecommunication network reliability Integrated circuit modeling Random forests Principal component analysis

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276页 << < 63 64 65 66 67 68 69 70 71 72 > >>

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：