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

2,175 篇 期刊文献
2,039 篇 会议
77 册 图书

馆藏范围

4,291 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

2,359 篇 工学
- 1,559 篇 计算机科学与技术...
- 1,259 篇 软件工程
- 636 篇 生物医学工程（可授...
- 516 篇 信息与通信工程
- 465 篇 生物工程
- 377 篇 光学工程
- 331 篇 控制科学与工程
- 310 篇 电气工程
- 256 篇 电子科学与技术（可...
- 154 篇 机械工程
- 142 篇 仪器科学与技术
- 134 篇 化学工程与技术
- 120 篇 安全科学与工程
- 104 篇 网络空间安全
- 103 篇 动力工程及工程热...
- 85 篇 交通运输工程
1,684 篇 理学
- 695 篇 物理学
- 596 篇 生物学
- 526 篇 数学
- 189 篇 统计学（可授理学、...
- 180 篇 化学
- 120 篇 系统科学
769 篇 医学
- 636 篇 临床医学
- 533 篇 基础医学(可授医学...
- 322 篇 药学(可授医学、理...
- 265 篇 公共卫生与预防医...
650 篇 管理学
- 400 篇 管理科学与工程(可...
- 258 篇 图书情报与档案管...
- 195 篇 工商管理
107 篇 法学
- 90 篇 社会学
99 篇 农学
75 篇 经济学
63 篇 教育学
9 篇 文学
9 篇 军事学
6 篇 艺术学
1 篇 哲学
1 篇 历史学

主题

157 篇 accuracy
155 篇 deep learning
117 篇 machine learning
95 篇 artificial intel...
87 篇 real-time system...
79 篇 computational mo...
78 篇 training
75 篇 internet of thin...
75 篇 feature extracti...
74 篇 predictive model...
73 篇 convolutional ne...
69 篇 medical services
68 篇 cloud computing
66 篇 image segmentati...
51 篇 security
50 篇 support vector m...
49 篇 data models
48 篇 wireless sensor ...
47 篇 proton-proton in...
46 篇 optimization

机构

287 篇 department for p...
286 篇 faculty of scien...
285 篇 department of ph...
281 篇 departamento de ...
277 篇 department of ph...
272 篇 kirchhoff-instit...
269 篇 department of ph...
269 篇 institute of phy...
264 篇 department of ph...
260 篇 faculté des scie...
257 篇 institute of phy...
252 篇 fakultät für phy...
239 篇 institut für ast...
231 篇 yerevan physics ...
223 篇 department of ph...
222 篇 department of ph...
219 篇 instituto de fís...
218 篇 physics division...
214 篇 department of ph...
212 篇 department of ph...

作者

267 篇 c. alexa
267 篇 j. m. izen
267 篇 g. bella
267 篇 j. strandberg
267 篇 d. calvet
267 篇 c. amelung
267 篇 g. spigo
267 篇 a. c. könig
266 篇 f. siegert
265 篇 m. klein
264 篇 r. ströhmer
264 篇 m. rijssenbeek
264 篇 s. jin
264 篇 g. gaudio
264 篇 s. mohapatra
262 篇 y. nagasaka
262 篇 s. guindon
261 篇 h. a. gordon
261 篇 h. sakamoto
257 篇 a. kaczmarska

语言

3,425 篇 英文
832 篇 其他
40 篇 中文
9 篇 德文
7 篇 日文
2 篇 法文
1 篇 斯洛文尼亚文

检索条件"机构=Institute of Computer Science and Information Engineering and Institute of Medical Informatics"

共 4291 条记录，以下是421-430 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：

Learning from Multi-Omics Networks to Enhance Disease Prediction: An Optimized Network Embedding and Fusion Approach

Learning from Multi-Omics Networks to Enhance Disease Predic...

引用

2024 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2024

作者： Hussein, Sundous Ramos, Vicente Liu, Weixuan Kechris, Katerina J. Lange, Leslie Bowler, Russell P. Banaei-Kashani, Farnoush University of Colorado Denver Department of Computer Science and Engineering DenverCO United States University of Colorado Anschutz Medical Campus Department of Biostatistics and Informatics AuroraCO United States University of Colorado Anschutz Medical Campus Division of Biomedical Informatics and Personalized Medicine AuroraCO United States Cleveland Clinic Main Campus Genomic Medicine Institute ClevelandOH United States

ISBN: (纸本)9798350386226

Understanding complex diseases hinges on a profound understanding of intricate biomolecular interactions unfolding within a complex, multidimensional landscape, challenging traditional methods to extract meaningful insights. While multi-omics networks capture the richness of biological data, providing a basis for predicting relationships between biomolecules and various phenotypic traits of complex diseases, their inherent complexity limits their predictive power. To address this challenge, we introduce a novel pipeline that leverages the power of Graph Neural Networks (GNNs) to extract and integrate meaningful information from multi-omics networks. By generating informative node embeddings and seamlessly incorporating them into the original subject-level data, our approach captures both local and global network dependencies, leading to substantial improvements in disease prediction accuracy. The proposed pipeline optimizes the embedding generation process for the specific prediction task, enabling the model to learn task-relevant representations. Through rigorous experimentation, we demonstrate the superior performance of our approach, surpassing existing methods by a substantial margin on nine real-world multi-omics datasets. With remarkable increases in accuracy ranging approximately from 8% to 10% over the best-performing baseline, particularly when the multi-omics networks are moderately dense, striking a balance between capturing complex relationships and avoiding excessive noise. Our findings underscore the potential of GNNs to significantly improve disease prediction by effectively extracting and representing knowledge embedded within multi-omics networks. © 2024 IEEE.

关键词： Graph neural networks

来源：评论

学校读者我要写书评

暂无评论

Enabling Protection for Critical Infrastructure through Security and Privacy in the Industrial Internet of Things 9

Enabling Protection for Critical Infrastructure through Secu...

引用

9th International Conference on Communication and Electronics Systems, ICCES 2024

作者： Yasotha, B. Vijayanandh, T. Thirumoorthy, P. Priya, M.Sangeetha Sasidaran, S. Prakalya, S.B. Srmist Department of Data Science and Business Systems Kattankulathur India School of Computing Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology Department of Computer Science & Engineering Avadi Tamil Nadu Chennai India Dhanalakshmi College of Engineering Department of Electrical and Electronics Engineering Chennai India Chennai India Panimalar Engineering College Department of Information Technology Chennai600123 India Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Department of Electronics and Communication Engineering Chennai India

ISBN: (纸本)9798350377972

Industrial Internet of Things can improve critical infrastructure in energy, transportation, and manufacturing. However, IIoT device and system integration opened security weaknesses that bad actors may exploit, causing huge disruptions and financial losses. IoT network security and privacy must be prioritized to protect key infrastructure. IIoT security issues and solutions are examined in this research. First, we take a look at the state of security and the unique risks that industrial IoT devices are up against, including hacking, illegal access, and cyber-physical assaults. Then, to lessen the impact of these dangers, we investigate cutting-edge security solutions, such as authentication, encryption, and access control systems. Building a robust security architecture specifically for IIoT applications is one of the main goals of the project. To improve safety and anonymity, this system uses cutting-edge innovation like blockchain, AI, and edge computing. We also talk about how privacy-preserving methods like differential privacy and anonymization are important for keeping sensitive information safe while allowing data sharing for analysis and operations. We assess the efficacy of the suggested security protocols and procedures using a battery of case studies and simulations. Reducing the attack surface and improving the resilience of IIoT systems can be achieved by a multi-layered security approach that includes effective privacy protections. We conclude by outlining our research's larger implications, which include the importance of standardization, regulatory compliance, and stakeholder collaboration in ensuring the safe and privacy-protecting deployment of IIoT technologies in vital infrastructure. Protecting vital infrastructure from cyber threats is our ultimate goal, and our work helps build IIoT systems that are more secure and dependable. © 2024 IEEE.

关键词： Industrial internet of things (IIoT)

来源：评论

学校读者我要写书评

暂无评论

Analysis of Banking and Financial Sector Services Using Artificial Intelligence (AI) 1

引用

8th International Conference on information System Design and Intelligent Applications, ISDIA 2024

作者： Isavnin, Alexey Kosorukova, Irina Madaminov, Inomjon Laxmi Lydia, E. Satapathy, Suresh Department of Business-Informatics and Mathematical Methods in Economics Naberezhnye Chelny Institute KFU Kazan Federal University Naberezhnye Chelny Russia Department of Corporate Finance and Corporate Governance Financial University under the Government of the Russian Federation Moscow Russia Department of Accounting and Auditing Urgench State University Urgench Uzbekistan Department of Computer Science and Engineering Vignan’s Institute of Information Technology Visakhapatnam530049 India School of Computer Engineering KIIT Deemed to be University Bhubaneswar India

ISBN: (数字)9789819748921

ISBN: (纸本)9789819748914

This research proposes the assessment of banking and financial services using AI to monitor how banks apply AI approaches and the feedback they receive from customers. In order to better track, anticipate, and react to customer behavior, the financial information generated by the growing utilization of digital pay and banking can be mined by banks and other financial institutions. Based on research, secondary sources are reviewed to ascertain the data used in banking and financial services. A methodical survey is designed to gather the main information clients have regarding AI applications. The study is that private banks and other financial institutions use a variety of artificial intelligence (AI) services to better serve their clients and ensure that they are happy with their financial services, as some clients are not happy with banking services. Additionally, the results indicated that clients would be more committed to banking and financial services representatives by providing creative preparation for the advancement of AI practices in the workplace. © The Author(s).

关键词： Decentralized finance

来源：评论

学校读者我要写书评

暂无评论

Digital Twins and Intelligent IoT for a Better World (Panel Discussion Report-I of IEEE AIoTSys2023)

Digital Twins and Intelligent IoT for a Better World (Panel ...

引用

2023 International Conference on Artificial Intelligence of Things and Systems, AIoTSys 2023

作者： Huang, Runhe Zhang, Daqing Yu, Zhiwen Nugent, Chris Jia, Weijia Yang, Kun Zhang, Yan Sekimoto, Yoshihide Guo, Bin Faculty of Computer and Information Sciences Hosei University Tokyo Japan Peking University Ip Paris France Harbin Engineering University Northwestern Polytechnical University China School of Computing Ulster University Ireland BNU-UIC Joint Ai Research Institute Beijing Normal University China School of Computer Science and Electronic Engineering University of Essex United Kingdom Department of Informatics University of Oslo Norway Institute of Industrial Science University of Tokyo Japan School of Computer Science Northwestern Polytechnical University China

ISBN: (纸本)9798350312270

This position paper provides a summary report of the panel discussion on "Digital Twins and Intelligent IoT for a Better World"at the International Conference on Artificial Intelligence of Things and Systems (AIoTSys'23). The panel featured seven distinguished invited panelists, including four IEEE Fellows from Peking University, Beijing Normal University, University of Essex, and the University of Oslo. Additionally, there was one vice president from Harbin engineering University, one school head from Ulster University, and one center vice director from the University of Tokyo. The panel covered seven topics: (1) The cost-effectiveness of IoTenabled digital twin design, (2) Ubiquitous crowd computing systems, (3) The vision for the fusion of the Intelligent IoT with the Digital Twin, (4) Intelligent networking in relation to Chinese culture and education, (5) Data-driven digital twin wireless networks, (6) Digital twins edge networking, and (7) The automatic generation of urban digital twins from local government s open data. The panel generated lively and comprehensive discussions, and this report represents the enriched outcome of our panelists insights, visions, and the interactive discussions with the audience. © 2023 IEEE.

关键词： Internet of things

来源：评论

学校读者我要写书评

暂无评论

Logistic Regression for Personalized Hypertension Risk Profiling in Cloud-Integrated Healthcare Systems

Logistic Regression for Personalized Hypertension Risk Profi...

引用

2024 Asian Conference on Intelligent Technologies, ACOIT 2024

作者： Saravanan, S. Ramya, S. Monikapreethi, S.K. Kavididevi, Venkatesh Kovarasan, Rajesh Kambattan Sujatha, S. Department of Electrical and Electronics Engineering Muthayammal Engineering College Tamil Nadu Namakkal India Department of Cyber Security Paavai Engineering College Tamil Nadu Namakkal India Department of Electronics and Communication Engineering Rajalakshmi Institute of Technology Tamil Nadu Chennai India Department of Information Technology Vardhaman College of Engineering Telangana Hyderabad India Department of Computer Science and Engineering Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Tamil Nadu Chennai India Department of Biomedical Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Tamil Nadu Chennai India

ISBN: (纸本)9798350374933

Advanced analytics for personalized chronic disease risk profiles are becoming possible as healthcare systems combine cloud-based technology. This work applies logistic regression (LR) models to cloud-integrated healthcare systems for personalized hypertension risk profiling. A large dataset of heterogeneous patient records was used to train and evaluate the LR model, including clinical characteristics and lifestyle variables. To assess the LR model's predictive accuracy in identifying high-risk hypertension patients and to provide a framework for personalized risk stratification that can be seamlessly integrated into cloud-based healthcare systems. The model's performance was rigorously cross-validated and compared to risk assessment methods. The LR approach predicted hypertension risk better than older techniques. Healthcare professionals and patients found the cloud integration of the personalized risk profiling system convenient, scalable, and accessible. It shows that cloud-based analytics may improve preventive healthcare by personalizing treatments to risk profiles. LR techniques can optimize personalized hypertension risk management in cloud-integrated systems, advancing data-driven healthcare. © 2024 IEEE.

关键词： Cloud Integration Healthcare Systems Hypertension Risk Personalized Medicine Predictive Modeling

来源：评论

学校读者我要写书评

暂无评论

Identity-Based Authentication Technique for IoT Devices

Identity-Based Authentication Technique for IoT Devices

引用

2022 IEEE International Conference on Consumer Electronics, ICCE 2022

作者： Gupta, Brij B. Gaurav, Akshat Chui, Kwok Tai Hsu, Ching-Hsien National Institute of Technology Haryana Kurukshetra India Ronin Institute MontclairNJ07043 United States Hong Kong Hong Kong Asia University Department of Computer Science and Information Engineering Taiwan Department of Computer Science and Information Engineering National Chung Cheng University Taiwan Department of Medical Research China Medical University Hospital China Medical University Taiwan

ISBN: (纸本)9781665441544

The Internet of Things (IoT) is a broad term used to describe many types of linked equipment that are both intelligent and interconnected through a network. These Internet of Things devices have become an essential part of our everyday lives. These devices, however, are still in the development stage. Because of their low computing capacity, they are susceptible to various cyberattacks like distributed denial of service (DDoS) attacks and denial of service (DoS) attacks. They disrupt the normal functioning of IoT devices and expose sensitive data;therefore, identifying and mitigating cyber-attacks on IoT devices is a critical area of study. In this regard, we proposed an IoT device-specific unique identity-based authentication method in this pa-per. Our proposed approach employs lightweight authentication procedures that use the unique IDs of IoT devices to provide identity - based encryption. © 2022 IEEE.

关键词： Denial-of-service attack

来源：评论

学校读者我要写书评

暂无评论

Adaptive Thermal Clothing with IoT and Random Forest Regression for Dynamic Outdoor Comfort

Adaptive Thermal Clothing with IoT and Random Forest Regress...

引用

2024 International Conference on Advances in Modern Age Technologies for Health and engineering science, AMATHE 2024

作者： Srinivasan, S. Sridevi, V. Saravanan, K. Murugan, S. Srinivasan, C. Muthulekshmi, M. Saveetha School Of Engineering Saveetha Institute Of Medical And Technical Sciences Saveetha University Department Of Biomedical Engineering Tamil Nadu Chennai India Academy Of Maritime Education And Training Deemed To Be University Department Of Electrical And Electronics Engineering Tamil Nadu Chennai India R.M.D. Engineering College Department Of Information Technology Tamil Nadu Chennai India Saveetha School Of Engineering Saveetha Institute Of Medical And Technical Sciences Saveetha University Department Of Computer Science And Engineering Tamil Nadu Chennai India

ISBN: (纸本)9798350371567

This research presents a novel method for improving outdoor comfort by combining adaptive thermal apparel with Internet of Things (IoT) and Random Forest Regression. Wearing inflexible traditional outdoor gear may be a real pain for those living in different parts of the world. As a solution, we present an intelligent garment system that can adapt its thermal insulation in real-time using data gathered from IoT sensors. A Random Forest Regression model is used to ascertain the most appropriate thermal settings for the garments based on the gathered data, which encompasses environmental factors such as humidity, temperature, and wind speed. By taking each user's tastes and physiological needs into account, the adaptive system strives to provide individualized comfort. The suggested technique successfully maintains the target comfort levels throughout varied outside situations, according to the experimental findings. In an age of rising climatic fluctuation, our study offers a potential answer for dynamic outdoor comfort to the expanding area of smart fabrics and wearable technologies. © 2024 IEEE.

关键词： Energy efficiency

来源：评论

学校读者我要写书评

暂无评论

An Advanced and Ideal Method for Tumor Detection and Classification from MRI Image Using Gaussian Mixture and RCNN

An Advanced and Ideal Method for Tumor Detection and Classif...

引用

2024 International Conference on Artificial Intelligence and Emerging Technology, Global AI Summit 2024

作者： Ray, Samrat Ramkumar, K. Anupama, Ch.V. Marybai, P. Misba Anguraju, K. Preethi, P. Iims Pune India Rajalakshmi Institute of Technology Department of Computer Science and Engineering Tamilnadu Chennai India Malla Reddy Engineering College Department: Information Technology Telengana Hyderabad India Panimalar Engineering College Artificial Intelligence and Data Science department Bangalore trunk road Varadharajapuram Poonamalee Chennai 600123 India Kongunadu College of Engineering and Technology Department of Computer Science and Engineering Trichy India Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Department of Computer Science and Engineering Tamilnadu Chennai 602105 India

ISBN: (纸本)9798350379716

Extensive research and methodological improvements over time attest to the necessity of brain tumour detection and analysis for any indication system. Accurate tumour detection is essential for this study;hence an efficient automated method must be implemented Numerous segmentation algorithms have been developed to classify brain tumors with greater precision. medical image processing experts agree that brain picture segmentation presents unique difficulties. A novel automatic detection and classification system is proposed in this work. The suggested method is broken down into several stages, including preprocessing of MRI images, segmentation of those images, extraction of features, and classification of those features. The noise in the MRI picture is reduced during the preprocessing stage by applying an adaptive filter. The grey level co-occurrence matrix (GLCM) is used for feature extraction, while the improved Means clustering (IMC) technique is used for image segmentation. To categorize MRI scans, we used a deep learning algorithm scan after features were extracted from the scans them as benign lesions, gliomas, meningiomas, or pituitary tumours. In order to accomplish the classification task, recurrent convolutional neural networks (RCNN) were utilised. For a given input dataset containing photographs of the brain, the proposed technique yields superior classification results. The investigations made use of MRI pictures from Kaggle's data sets, which included 464 testing sets and 3264 training sets. The outcomes show that the proposed strategy outperforms its predecessors. The suggested RCNN method is then compared to BP, VG-Net, and RCNN, three of the most popular classification techniques currently in use. The suggested classifier successfully identified 96.21 percent of brain tumour tissues in magnetic resonance imaging scans. © 2024 IEEE.

关键词： clinical data Deep Learning functional magnetic resonance imaging positron emission tomography Recurrent convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

Revolutionizing Carotid Pulse Analysis: A Novel Approach with Custom Designed Neck Band 7

Revolutionizing Carotid Pulse Analysis: A Novel Approach wit...

引用

7th IET Smart Cities Symposium, SCS 2023

作者： Dadi, Pradeep Surya Deepa, R. Johnpaul, S. Sadish Sendil, M. Surendran, R. Department of Mechatronics Engineering Chennai Institute of Technology Chennai India Department of Computing Technologies School of Computing College of Engineering and Technology SRM Institute of Science and Technology Kattankulathur Chennai India Department of Information Technology Vel Tech Multi Tech Dr.Rangarajan Dr.Sakunthala Engineering College Chennai India Department of Emerging Technologies Guru Nanak Institute of Technology Telegana India Department of Computer Science and Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Chennai India

ISBN: (纸本)9781839539831

Healthcare could undergo a major transformation with the incorporation of non-invasive sensors into wearable technology. This is due to these sensors' ability to provide instant monitoring of vital signs. Could be rewritten as Photoplethysmography (PPG) is a non-invasive technique that uses a small LED and photo sensor to detect the carotid pulse. Transcranial Doppler (TCD) is another noninvasive technique that measures the velocity of blood flow in the carotid artery using high frequency sound waves. This pulse is an essential indicator of blood pressure and heart rate. The primary goal of our research is to create a neck band equipped with both PPG and TCD sensors to enable comprehensive and precise carotid pulse monitoring. This paper will detail the designing, developing, and testing stages of the neck band, as well as the integration of sensors. Additionally, we will present data acquisition, data processing, and analysis. Lastly, the demonstration of the neck band's effectiveness in a controlled environment will be discussed. © The Institution of engineering & Technology 2023.

关键词： Blood pressure

来源：评论

学校读者我要写书评

暂无评论

Optical Evanescent Field for Direct Observation of Sub-100nm Particle Motion on Glass Surface 1

Optical Evanescent Field for Direct Observation of Sub-100nm...

引用

1st International Conference on Robotics, engineering, science, and Technology, RESTCON 2024

作者： Khajornrungruang, Panart Permpatdechakul, Thitipat Suzuki, Keisuke Blattler, Aran Terayama, Yutaka Goto, Daiki Phaisalpanumas, Pipat Bun-Athuek, Natthaphon Phunopas, Amornphun Kyushu Institute of Technology Iizuka-Shi Mechanical Science and Technology Division Dept. of Intelligent and Control System Faculty of Computer Science and Systems Engineering Fukuoka Japan Kyushu Institute of Technology Iizuka-Shi Mechanical Information Science and Technology Division Dept. of Interdisciplinary Informatics Graduate School of Computer Science and Systems Engineering Fukuoka Japan King Mongkut's University of Technology North Bangkok Bangsue Faculty of Engineering Dept. of Production and Robotics Engineering Bangkok Thailand Kyushu Institute of Technology Iizuka-Shi Mechanical Science and Technology Course Dept. of Intelligent and Control System Graduate School of Computer Science and Systems Engineering Fukuoka Japan King Mongkut's University of Technology North Bangkok Bangsue Faculty of Engineering Dept. of Industiral Engineering Bangkok Thailand King Mongkut's University of Technology North Bangkok Bangsue College of Industrial Technology Dept. of Mechanical Engineering Technology Bangkok Thailand

ISBN: (纸本)9798350348842

To directly investigate the dynamic nanoscale phenomenon on the surface being processed in wet conditions such as precision polishing, and cleaning in semiconductor industrial, an optical method for visualization and observation of each sub-100 nm sized particle that is moving on an interface such as a silica glass surface by applying an evanescent field have been proposing. Subsequently, we developed an experimental apparatus equipped with an optical microscopy system for verifying the moving particle observation method in a laboratory scale. This article introduces some experimentally direct observation results of duplicated wet processes. © 2024 IEEE.

关键词： Visualization

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430页 << < 39 40 41 42 43 44 45 46 47 48 > >>

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：