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

50,731 篇 会议
13,918 篇 期刊文献
280 册 图书
12 篇 科技报告

馆藏范围

64,941 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

42,715 篇 工学
- 18,323 篇 计算机科学与技术...
- 15,124 篇 软件工程
- 9,509 篇 电气工程
- 8,749 篇 电子科学与技术（可...
- 8,514 篇 信息与通信工程
- 7,384 篇 控制科学与工程
- 6,073 篇 化学工程与技术
- 5,177 篇 机械工程
- 4,878 篇 材料科学与工程（可...
- 4,854 篇 动力工程及工程热...
- 3,813 篇 力学（可授工学、理...
- 3,592 篇 土木工程
- 3,333 篇 建筑学
- 3,299 篇 仪器科学与技术
- 3,028 篇 生物医学工程（可授...
- 3,006 篇 光学工程
- 2,982 篇 生物工程
- 2,605 篇 冶金工程
- 1,843 篇 安全科学与工程
25,906 篇 理学
- 11,340 篇 数学
- 10,947 篇 物理学
- 5,558 篇 化学
- 3,459 篇 生物学
- 3,049 篇 统计学（可授理学、...
- 2,060 篇 系统科学
7,744 篇 管理学
- 5,731 篇 管理科学与工程(可...
- 2,883 篇 工商管理
- 2,318 篇 图书情报与档案管...
2,308 篇 医学
- 1,936 篇 临床医学
- 1,757 篇 基础医学(可授医学...
1,335 篇 经济学
1,214 篇 法学
875 篇 农学
664 篇 教育学
192 篇 军事学
180 篇 文学
77 篇 艺术学
9 篇 哲学
8 篇 历史学

主题

1,197 篇 accuracy
914 篇 feature extracti...
728 篇 computational mo...
728 篇 training
644 篇 real-time system...
565 篇 optimization
554 篇 deep learning
553 篇 mathematical mod...
511 篇 predictive model...
497 篇 switches
469 篇 internet of thin...
463 篇 support vector m...
461 篇 machine learning
451 篇 reliability
388 篇 monitoring
374 篇 neural networks
368 篇 wireless communi...
354 篇 convolutional ne...
326 篇 simulation
313 篇 testing

机构

364 篇 department of ph...
364 篇 dept. of astrono...
363 篇 dept. of physics...
361 篇 dept. of physics...
333 篇 iii. physikalisc...
243 篇 lawrence berkele...
242 篇 université libre...
240 篇 dept. of physics...
240 篇 institut für phy...
240 篇 dept. of physics...
240 篇 fakultät für phy...
239 篇 erlangen centre ...
239 篇 département de p...
239 篇 dept. of physics...
239 篇 niels bohr insti...
239 篇 dept. of physics...
238 篇 department of ph...
238 篇 dept. of physics...
238 篇 dienst elem brus...
238 篇 dept. of physics...

作者

361 篇 haungs a.
333 篇 fürst p.
283 篇 hoshina k.
276 篇 fan k.l.
244 篇 halve l.
238 篇 ahlers m.
237 篇 besson d.z.
237 篇 desiati p.
236 篇 botner o.
236 篇 aguilar j.a.
234 篇 ashida y.
233 篇 böttcher j.
233 篇 delaunay j.j.
233 篇 berley d.
233 篇 gerhardt l.
232 篇 bellenghi c.
232 篇 chirkin d.
232 篇 argüelles c.
231 篇 günther c.
231 篇 ehrhardt t.

语言

60,335 篇 英文
1,612 篇 其他
1,478 篇 日文
1,002 篇 中文
505 篇 朝鲜文
17 篇 德文
4 篇 泰文
3 篇 阿拉伯文
3 篇 西班牙文
3 篇 法文
2 篇 荷兰文
2 篇 土耳其文
1 篇 捷克文
1 篇 芬兰文
1 篇 意大利文
1 篇 立陶宛文
1 篇 葡萄牙文
1 篇 斯洛文尼亚文
1 篇 瑞典文

检索条件"机构=Dept. of System Engineering of Engineering Technology"

共 64941 条记录，以下是4741-4750 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 Hybrid Deep Learning Architecture Using Dense Neural Network and Gated Recurrent Unit for Cloud Intrusion Detection

A Hybrid Deep Learning Architecture Using Dense Neural Netwo...

引用

International Conference on Electrical, Computer and Communication engineering (ECCE)

作者： Iffath Tanjim Moon Md. Nazrul Islam Mondal Dept. of Computer Science & Engineering Rajshahi University of Engineering & Technology Rajshahi Bangladesh

ISBN: (数字)9798350357509

ISBN: (纸本)9798350357516

In this paper, we have used a hybrid deep-learning architecture to detect cloud intrusion. The cloud plays an important role in modern data management, accessibility, and storage. It enables organizations to store vast amounts of data remotely. Due to frequent data sharing between platforms and remote access, the cloud environment is more vulnerable to cyber threats. An intruder can access confidential data due to vulnerabilities including inadequate encryption, absence of authentication, poor access control, and so on. We can efficiently use deep learning approaches to enhance cloud security. In this research, we have developed a hybrid dense neural network (DNN) and gated recurrent unit (GRU)-based architecture to detect cloud intrusion. We have also developed individual DNN and GRU-based architectures. In our proposed model, the DNN layers can capture the nonlinear complex pattern, while GRU can identify the temporal dependencies of network traffic data. In this research work, we have utilized the network portion of the ToN-IoT dataset. For multiclass classification, the hybrid DNN-GRU model has achieved the highest performance, obtaining an accuracy of 98.66%, precision of 98.70%, recall of 98.66%, f1 score of 98.67%, and AUC of 99.98%. Moreover, the performance for detecting nine different attacks has also been evaluated. This case shows the hybrid DNN-GRU model performs well, identifying backdoor and ransomware attacks with 100% accuracy. Thus, this hybrid architecture works more robustly and efficiently to detect cloud intrusion by combining the strengths of both DNN and GRU, thereby strengthening cloud security.

关键词： Deep learning Access control Accuracy Cloud computing security Neural networks Intrusion detection Telecommunication traffic Organizations Encryption Ransomware

来源：评论

学校读者我要写书评

暂无评论

Arabic Sentiment Analysis of Mobile Banking Services Reviews 10

Arabic Sentiment Analysis of Mobile Banking Services Reviews

引用

10th International Conference on Social Networks Analysis, Management and Security, SNAMS 2023

作者： Khabour, Safaa M. Mustafa, Dheya Althebyan, Qutaibah Yarmouk University Faculty of Information Technology and Computer Sciences Dept. of Information Systems Irbid21163 Jordan The Hashemite University Faculty of Engineering Dept. of Computer Engineering Zarqa13133 Jordan Al Ain University Dept. of Cybersecurity Al Ain United Arab Emirates Jordan University of Science and Technology Irbid Jordan

ISBN: (纸本)9798350318906

Online customer reviews have developed into a significant source of information about a business's performance. Due to shifting consumer expectations and growing internet penetration, the Middle East, especially Jordan, is seeing an increase in the usage of online banking. This propensity toward digital transition has been accelerated by the COVID-19 pandemic. Mobile banking service companies aim to effectively use customers' feedback to identify areas for improvement in customer satisfaction. Although Arabic is becoming one of the most widely used languages on the Internet, only a few studies have focused on Arabic sentiment analysis to date. The present study conducts an extensive emotion mining and sentiment analysis on mobile banking reviews in Arabic, exploiting machine learning, natural language processing, and resampling methods to obtain subjective feedback, determine polarity, and identify customers' feelings in the banking domain. This work walks the reader through detailed steps of cleaning and preprocessing a manually annotated dataset of online banking reviews in Arabic, followed by features extraction and modeling, dataset splitting, and balancing training data. Finally, we examined classification algorithms including Decision Tree (DT), Support Vector Machine (SVM), Logistic Regression (LR), Naïve Bayes (NB), K-Nearest Neighbors (KNN), and Random Forest (RF). Ensemble hard and soft voting ML methods were also evaluated. We achieved a maximum accuracy of about 94% using the LR classifier and a maximum precision of 94% using the LR and hard voting methods. Our methodology will enable banks to acquire insights on how to develop their online presence and meet the demands of customers and stakeholders. © 2023 IEEE.

关键词： Sentiment analysis

来源：评论

学校读者我要写书评

暂无评论

Partial Discharge Localization Model in Power Transformer with Fingerprinting Technique 9

Partial Discharge Localization Model in Power Transformer wi...

引用

9th International Conference on engineering, Applied Sciences, and technology, ICEAST 2023

作者： Chaisang, Aditep Tiengthong, Thanadol Maw, Myo Myint Promwong, Sathaporn Rambhai Barni Rajabhat University Faculty of Industrial Technology Chanthaburi22000 Thailand School of Engineering King Mongkut's Institute of Technology Ladkrabang Bangkok10520 Thailand Mandalay Technological University Faculty of Engineering Dept. Computer Engineering and Information Technology Mandalay Myanmar

ISBN: (纸本)9798350322040

Partial discharge localization in power transformers is of utmost importance, requiring an effective evaluation method to identify the location of such events precisely. Antenna placement poses challenges within power transformers, as improper positioning can significantly affect localization precision. This paper introduces an evaluation of the fingerprinting method for ultra-high frequency partial discharge localization. The fingerprinting method, commonly employed in wireless localization systems, is utilized to assess the accuracy of partial discharge localization. The proposed method leverages fingerprinting analysis and received signal strength to evaluate partial discharge events in power transformers. Experimental partial discharge measurements are conducted on a power transformer model provided by Tesla Power Company. The results include the average received signal strength at each measurement position and the distance error of the partial discharge location determined using the fingerprinting method. This research contributes to assessing partial discharge in power transformers, offering valuable insights for enhancing their health and performance evaluation. © 2023 IEEE.

关键词： Partial discharges

来源：评论

学校读者我要写书评

暂无评论

Conjunctive Optimal Operation of Power and Water Networks

Conjunctive Optimal Operation of Power and Water Networks

引用

World Environmental and Water Resources Congress 2023: Adaptive Planning and Design in an Age of Risk and Uncertainty

作者： Shmaya, Tomer Housh, Mashor Pecci, Filippo Baker, Kyri Kasprzyk, Joseph Ostfeld, Avi Faculty of Civil and Environmental Engineering Technion-Israel Institute of Technology Haifa Israel Dept. of Natural Resources and Environmental Management Univ. of Haifa Haifa Israel Andlinger Center for Energy and the Environment Princeton Univ United States Dept. of Civil and Environmental Engineering Univ. of Colorado Boulder United States Dept. of Civil and Environmental Engineering Technion-Israel Institute of Technology Haifa Israel

ISBN: (数字)9780784484852

ISBN: (纸本)9780784484852

Power and water networks are massive critical infrastructure systems that are strongly coupled through the power transmitted from the power network to the water network, yet they are commonly operated independently. The resemblance between the two systems is high: a power network comprises a system of power stations, power transmission, and power distribution to individual customers, while a water network likely consists of water sources, regional pipelines, and a distribution system for supplying its end users. The physics of both systems are governed by Kirchhoff's laws of continuity of flow/current at nodes and energy pressure/voltage along paths. Smart joint operation of water and power networks has the potential of saving water, saving energy, and reducing environmental impact. Several studies have dealt with the problem. However, modeling can still be significantly improved, and many different research directions can be explored. The complexity of managing both systems independently differs according to the adopted assumptions and can be as easy as solving a linear programming (LP) problem or can end up as a challenging large-scale mixed integer nonlinear problem (MINLP). The objective of this study is to formulate and solve a conjunctive water-power flow (OWPF) problem for optimizing both systems simultaneously. The formulation and solution scheme will be demonstrated on a small yet general layout of a coupled power-water network. © World Environmental and Water Resources Congress *** rights reserved

关键词： Environmental impact

来源：评论

学校读者我要写书评

暂无评论

Multi-Class Cyberbullying Detection of Bengali Social Media Texts Using A Hybrid Model

Multi-Class Cyberbullying Detection of Bengali Social Media ...

引用

International Conference on Electrical, Computer and Communication engineering (ECCE)

作者： Pranti Debnath Md Saiful Islam Dept. Electronics and Telecommunication Engineering Chittagong University of Engineering and Technology Chattogram Bangladesh

ISBN: (数字)9798350357509

ISBN: (纸本)9798350357516

Cyberbullying is the act of a person by employing technology to shame or harass other people. Because bullying on online platforms spreads quickly to larger viewers, it can sometimes get more awful and studies reveal that this kind of activity happens a lot on social media platforms like Facebook and Twitter. Furthermore, generating an improved result is tough because of the unique nature of the Bengali language, a shortage of reliable records, and limited preliminary processing techniques. This study presents a deep learning-based hybrid method with an attention mechanism to identify bully expression in Bangla text by employing a multi-class dataset containing four classes such as political, religious, sexual, and non-bullying feelings. The proposed framework architecture combines Convolutional Neural Network(CNN) and bidirectional LSTM layers, resulting in a remarkable testing performance on the multi-class dataset. The research attempts to maximize performance and compare the suggested model with the initial approaches. Our recommended CNN-BiLSTM with additive attention framework improves cyberbullying identification with 0.86 F1 scores and 85.18% accuracy on a labeled dataset of 42,036 Facebook comments. This study enhances our comprehension of bully expression in the Bangla language, facilitating the development of more sophisticated natural language processing applications in languages with limited resources.

关键词： Fault diagnosis Emotion recognition Additives Accuracy Mood Computational modeling Cyberbullying Predictive models Natural language processing Testing

来源：评论

学校读者我要写书评

暂无评论

In-dept. Analysis of Information Overflows and its Role in Shaping Future Knowledge Structures 3

In-depth Analysis of Information Overflows and its Role in S...

引用

3rd IEEE International Conference on ICT in Business Industry and Government, ICTBIG 2023

作者： Paranthaman, V. Kamal, M.D. Raj Balaji, V. Sunil, G. Adhi College of Engineering and Technology Dept. of Mechanical Engineering TN Chennai India Velammal Institute of Technology Department of Mechanical Engineering TN Chennai India Loyola Institute of Technology Department of Mechanical Engineering TN Chennai India School of Computer Science and Artificial Intelligence Sr University Telangana Warangal India

ISBN: (纸本)9798350343274

This study provides a thorough evaluation of data deluges and how they will play a significant role in the development of future knowledge architectures. The suggested methodology is adaptable and interdisciplinary since it combines cutting-edge data mining, NLP, and network analysis methods. Data mining, NLP, network analysis, content analysis, big data analytics, cognitive mapping, SNA, MNA, QR, and IV are all compared to the proposed method, as are machine learning algorithms, qualitative research methods, and data visualization. Accuracy, relevance, dept. of analysis, innovation, practical consequences, and clarity are only a few of the areas where the suggested technique shines. Its greater analytical skills are shown by its persistent outperformance of conventional approaches. Additionally, the suggested approach better accords with ethical norms and responsible research procedures, thus they are all considered as well. In summary, this study demonstrates the value of looking at information floods from several angles of study. The suggested technique not only provides cutting-edge analytic instruments for negotiating the intricacies of the digital information ecosystem, but also gives a forward-looking viewpoint by anticipating new patterns and developments. It demonstrates how crucial it is to use cutting-edge methods and evolve with the information age. © 2023 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 Novel Design of Secured BlockChain Assisted Land Registration Mechanism by using Enhanced Verification Principles

A Novel Design of Secured BlockChain Assisted Land Registrat...

引用

2023 IEEE International Conference on Research Methodologies in Knowledge Management, Artificial Intelligence and Telecommunication engineering, RMKMATE 2023

作者： Prabu, R.T. Hemalatha, R. Madhini, M. Diwakaran, S. Senthilkumar, V. Thiyaneswaran, B. Dept. Electronics and Communication Saveetha School of Engineering Chennai India Dept. Computer Science Engineering St.Joseph College of Engineering Chennai India Dept. Electronics and Communication S.A.Engineering College Chennai India Dept. Master of Comp. Applns Kalasalingam Academy of Res. & Edn. Srivilliputhur India Department of Data Science VelTech Multitech Engg. College Chennai India Dept. Electronics & Communication Sona College of Technology Salem India

ISBN: (纸本)9798350305708

In the contemporary world, safeguarding data has assumed paramount importance, prompting numerous industrial sectors to fortify their defenses against potential hackers. In this landscape, blockchain has emerged as a cutting-edge technology that empowers peers to securely exchange various assets, including currency, financial documents, and land properties. Operating as an open-source public network, blockchain eliminates the need for a central authority. Instead, it facilitates peer-to-peer interactions, ensuring that transactions, value transfers, and data sharing are authenticated by all interconnected nodes within the network. The conventional process of land registration, characterized by its sluggishness and complexity, involves multiple intermediaries and is susceptible to instances of fraudulent and counterfeit land transfers. To address these challenges, the paper introduces a conceptual framework for blockchain-based land registry systems. By analyzing existing frameworks and scrutinizing the robust strategies and concepts they employ, the paper establishes connections that culminate in the creation of this conceptual framework. The proposed solution in the paper revolves around the secure transfer of land ownership through blockchain technology. This solution circumvents the need for intermediaries, allowing buyers and sellers to conduct land ownership transactions seamlessly using the Ethereum network. By leveraging the power of blockchain, this solution aims to mitigate the vulnerabilities and inefficiencies inherent in traditional land registration processes, ushering in a more secure, efficient, and transparent approach to managing land ownership transactions. © 2023 IEEE.

关键词： Blockchain Land Registration land registry systems

来源：评论

学校读者我要写书评

暂无评论

Inside the Energy Source: Exploring the Electrical Characteristics of Lithium-ion Battery

Inside the Energy Source: Exploring the Electrical Character...

引用

International Conference on Electrical, Computer and Communication engineering (ECCE)

作者： Asir Intisar Saurav Datta N. K. Das Dept. of Electrical and Electronic Engineering Chittagong University of Engineering and Technology Chattogram Bangladesh

ISBN: (数字)9798350357509

ISBN: (纸本)9798350357516

Lithium-ion batteries have revolutionized the energy storage landscape since their commercialization in the early 1990s. The continuous advancements in lithium-ion technology are driven by the pressing need for sustainable energy solutions and the growing demand for high-performance batteries. This paper explores the electrical characteristics of lithium-ion batteries, including current, voltage, capacity, energy density, voltage loss, and internal resistance, through simulations conducted using COMSOL Multiphysics software. The study highlights how these characteristics change under different discharge rates, providing insights into the ideal time frame for the effective use of a designed battery cell. Furthermore, the paper identifies potential pathways for enhancing battery performance by benchmarking against advancements in alternative battery technologies.

关键词： Lithium-ion batteries Resistance Hands Electric potential Voltage Pressing Fault location Discharges (electric) Software Commercialization

来源：评论

学校读者我要写书评

暂无评论

An Effective Prediction of Rainfall Using Machine Learning Technique 5

An Effective Prediction of Rainfall Using Machine Learning T...

引用

5th IEEE International Conference on Electrical, Computer and Communication Technologies, ICECCT 2023

作者： Rana, Nisha Guru Prasad, M. Sharma, Ashutosh Pratap, M.S. Anand Kumar, M. Aditya Pai, H. Dept. of Computer Science and Engineering Rishikesh India Graphic Era Deemed University Dept. Computer Science and Engineering Dehradun India Rishikesh India School of Computing and Information Technology Reva University Bengaluru India Dept. of Computer Application Dehradun India Dept. of Computer Science and Engg. Dehradun India

ISBN: (纸本)9781665493604

Climatic information such as temperature, humidity, and precipitation are useful for agriculturists, businesses, researchers, and the government. Estimating precipitation is a major factor that affects the environment and is one of the most important aspects of meteorological science. In this study, factual approaches and machine learning methods are used to estimate and forecast meteorological parameters for the government. Estimating precipitation is a major factor that affects the environment and is one of the most important aspects of meteorological science. Approaches are used to forecast and estimate precipitation. Daily observations were used as part of the experiment. Validation of results using real-world data is used to check the accuracy of forecasting model experimentation. The experimental results show that distribution, correlation, line-plots, and neural networks perform well for forecasting meteorological characteristics and have the best classification accuracy when compared to other types of machine learning methods for precipitation forecasting. © 2023 IEEE.

关键词： Machine learning

来源：评论

学校读者我要写书评

暂无评论

FPGA-based Hardware Acceleration of Scalable Convolutional Layers for Deep Learning Inference

FPGA-based Hardware Acceleration of Scalable Convolutional L...

引用

International Conference on Electrical, Computer and Communication engineering (ECCE)

作者： Nahin Ul Sadad Md. Nazrul Islam Mondal Dept. of Computer Science & Engineering Rajshahi University of Engineering & Technology Rajshahi Bangladesh

ISBN: (数字)9798350357509

ISBN: (纸本)9798350357516

Deep learning inference demands high computational efficiency and scalability, which traditional architectures struggle to provide. To address this, we propose an FPGA-accelerated scalable convolutional neural network (CNN) architecture optimized for inference. The design leverages FPGA’s parallelism and reconfigurability, integrating convolution, activation, and reshaping operations. It sequentially processes input data, synchronizing layers via control signals. The convolutional layer extracts spatial features, reshapes the feature map, and passes it to fully connected layers, with the output layer generating class probabilities. Our FPGA implementation achieves a remarkable 63000x speedup over CPU-based inference and a 6000x improvement compared to GPU-based inference with significantly reduced resource (except IO) requirements.

关键词： Deep learning Neural network hardware Convolution Scalability Process control Computer architecture Parallel processing Feature extraction Convolutional neural networks Hardware acceleration

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 << < 471 472 473 474 475 476 477 478 479 480 > >>

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：