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

3,214 篇 会议
19 册 图书
10 篇 期刊文献

馆藏范围

3,243 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

1,942 篇 工学
- 1,740 篇 计算机科学与技术...
- 1,594 篇 软件工程
- 423 篇 信息与通信工程
- 329 篇 控制科学与工程
- 318 篇 生物工程
- 185 篇 生物医学工程（可授...
- 176 篇 电气工程
- 145 篇 机械工程
- 116 篇 电子科学与技术（可...
- 101 篇 光学工程
- 99 篇 安全科学与工程
- 93 篇 化学工程与技术
- 92 篇 动力工程及工程热...
- 79 篇 网络空间安全
893 篇 理学
- 499 篇 数学
- 336 篇 生物学
- 210 篇 统计学（可授理学、...
- 158 篇 物理学
- 154 篇 系统科学
- 84 篇 化学
505 篇 管理学
- 266 篇 管理科学与工程(可...
- 258 篇 图书情报与档案管...
- 160 篇 工商管理
185 篇 医学
- 158 篇 临床医学
- 156 篇 基础医学(可授医学...
- 110 篇 药学(可授医学、理...
- 83 篇 公共卫生与预防医...
134 篇 法学
- 91 篇 社会学
82 篇 经济学
- 82 篇 应用经济学
78 篇 农学
- 75 篇 作物学
66 篇 教育学
4 篇 文学
1 篇 军事学

主题

499 篇 machine learning
104 篇 deep learning
86 篇 software
62 篇 machine learning...
59 篇 support vector m...
52 篇 internet of thin...
52 篇 artificial intel...
49 篇 decision trees
47 篇 forecasting
44 篇 software enginee...
40 篇 training
39 篇 predictive model...
36 篇 feature extracti...
35 篇 neural networks
33 篇 software testing
31 篇 software algorit...
26 篇 reinforcement le...
26 篇 adversarial mach...
25 篇 covid-19
25 篇 object detection

机构

31 篇 college of compu...
31 篇 chitkara univers...
12 篇 karnataka bangal...
12 篇 school of inform...
11 篇 software enginee...
11 篇 department of so...
10 篇 department of so...
10 篇 school of comput...
9 篇 maharishi school...
8 篇 maharishi school...
7 篇 maharishi school...
7 篇 school of comput...
7 篇 daffodil interna...
7 篇 department of co...
7 篇 school of inform...
6 篇 school of comput...
6 篇 school of comput...
6 篇 software enginee...
6 篇 department of co...
6 篇 department of so...

作者

8 篇 patidar sanjay
7 篇 liu han
7 篇 han liu
6 篇 alfurhood badria...
6 篇 ishu sharma
6 篇 sharma ishu
6 篇 badria sulaiman ...
5 篇 bitto abu kowshi...
5 篇 dharshana kasthu...
5 篇 ali raja hashim
5 篇 yibeltal assefa
5 篇 assefa yibeltal
5 篇 ajmeera kiran
5 篇 raja hashim ali
5 篇 sethia divyashik...
4 篇 heyn hans-martin
4 篇 krishna aneesh
4 篇 william p.
4 篇 iqbal muhammad w...
4 篇 liu xin

语言

1,802 篇 英文
1,440 篇 其他
69 篇 中文
1 篇 德文

检索条件"任意字段=2023 International Conference on Software Engineering and Machine Learning, CONF-SEML 2023"

共 3243 条记录，以下是3121-3130 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：

Research on Online Monitoring of Wind Turbine Blade Damage Based on Working Mode Analysis

Research on Online Monitoring of Wind Turbine Blade Damage B...

引用

Power Energy Systems and Applications (ICoPESA), international conference on

作者： Yu Wang Hui Liu Feng Gao Yangfan Zhang Yaohan Wang Kai Liang Department of Smart Grid and New Energy Electric Power Research Institute of State Grid Jibei Eletric Power Co. Ltd Beijing Electric Power Research Institute of State Grid Jibei Eletric Power Co. Ltd Beijing School of Control and Computer Engineering North China Electirc Power University Beijing

To solve the problem that the blade damage of wind turbine is difficult to be directly monitored on-line, the blade vibration signal is used to realize the on-line monitoring of the blade damage fault. Firstly, based on the working mode analysis theory, an on-line identification method of wind turbine blade modal parameters based on the transmission rate is constructed, and a blade vibration physical experiment platform is built for the experimental verification of this method. Through the comparison with the experimental results of the traditional force hammer excitation method, the accuracy of the working mode parameter identification method is verified; Then, taking the 5MW offshore wind turbine in fast simulation software as an example, the multi condition operation simulation of blade damage is carried out, and the influence law of blade damage on the normal operation parameters and blade modal parameters of the unit is obtained through data analysis; Finally, using different combinations of blade monitoring data, the accuracy of machine learning algorithm (MLA) applied to blade damage fault diagnosis is tested. The results show that the accuracy of blade damage fault diagnosis can be significantly improved by incorporating online identification of blade modal parameters into the unit operation data.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Virtual Assistant with Facial Expession Recognition

Virtual Assistant with Facial Expession Recognition

引用

Advances in Computing, Communication Control and Networking (ICAC3N), international conference on

作者： Kanish Saxena S Janarthanan Himanshi Goyal School of Computing Science and Engineering Galgotias University India

ISBN: (数字)9798350330861

ISBN: (纸本)9798350330878

In Today’s world, Intelligent Virtual Assistants are used everywhere, and their base working principle is voice commands. And there are numerous technologies available for reading human facial expressions. So, in this paper, we will learn what happens if we combine both technologies. Does it better or create chaos? Artificial intelligence is gaining strength in the modern world. Every industry will soon use AI technology. AI has made great progress in recent years in identifying human emotions through voice, body language, facial expressions, etc. I’s significance stems from the fact that traditional human capabilities can now be studied inexpensively and at scale in the software. Every sector can use me to provide new possibilities and efficiencies. It is significant because it successfully overcomes a well-defined set of technological challenges. The technology enables us to complete competitive tasks with basic controls quickly. Every new voice-interactive technology we adopt deepens our reliance on artificial intelligence (AI) and machine learning from our smartphones, computers, televisions, and refrigerators. The connection between machines and humans that we had been seeing and dreaming about a few decades ago has been real thanks to voice assistants like Amazon Echo, Siri, Google Home, and Amazon Lexa. But today, the fact is undeniable and real. Voice search technology is the upcoming digital trend on the market; in certain cases, touch screens have already been replaced.

关键词： TV Military computing Prototypes Personal voice assistants machine learning Touch sensitive screens Motion pictures

来源：评论

学校读者我要写书评

暂无评论

Analysis of Techniques for Detection and Removal of Zero-Day Attacks (ZDA) 2nd

Analysis of Techniques for Detection and Removal of Zero-Day...

引用

2nd international conference on Ubiquitous Security, UbiSec 2022

作者： Hamid, Khalid Iqbal, Muhammad Waseem Aqeel, Muhammad Liu, Xiangyong Arif, Muhammad Department of Software Engineering The Superior University Lahore54000 Pakistan Department of Computer Science The Superior University Lahore54000 Pakistan School of Computer Science and Cyber Engineering Guangzhou University Guangzhou510006 China

ISBN: (纸本)9789819902712

Zero-day attacks (ZDAs) are previously unknown flaws and errors in operating systems, networks, and general-purpose software. ZDAs are the cause to open security breach holes for external users or hackers for illegal operations before patches. ZDAs are different from viruses, worms and Trojans. They are very difficult to detect and remove because they are unknown to users and even programmers. Conventional defense systems are useless against such types of attacks. This paper investigates the zero-day attacks, their vulnerabilities, the intensity of these attacks and the reasons in a real-time environment. Different techniques are compared to investigate ZDAs. The hybrid technique has been used to check the behavior of data traffic coming from outside the world in the virtual environment for zero-day attacks. Static check tools (MD5 Checksum, AV-Suite, and SOPHOS) and behavioral check tools (SANDBOX) have been used for the verification and validation of results. The second comparatively best technique is machine learning-Based Technique which showed the best results. The results show how to choose the best solution against zero-day attacks in the real-time environment of the software. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Zero-day attack

来源：评论

学校读者我要写书评

暂无评论

Visual Gesture-Based Home Automation

Visual Gesture-Based Home Automation

引用

Advances in Computing, Communication, Embedded and Secure Systems (ACCESS), international conference on

作者： Biya Kurian Jerom Regi Dennis John Hari P Therese Yamuna Mahesh Dept. of Electronics and Communication Engineering Amal Jyothi College of Engineering Kanjirappally India

In recent years, there has been an increase in the use of IoT devices for home automation, shopping malls, and other public places. However, for individuals who are mute or bedridden, accessing these devices can be difficult, especially when they are voice-activated. To address this issue, hand gesture recognition technology has been developed to allow individuals to control these devices through simple hand movements. Image processing and pattern recognition are crucial for accurately detecting these hand gestures, and platforms such as Open CV, Python, PyCharm, and Media Pipe are commonly used in software development to achieve this. This technology has the potential to help people with physical, sensory, or intellectual disabilities to participate fully in all activities in society and enjoy equal opportunities. By using hand gestures to communicate with IoT devices, individuals who are deaf can also benefit from this technology. Ultimately, this technology has the potential to create a human-computer interaction that is accessible to all, making it a valuable addition to the field of assistive technology. Furthermore, hand gesture recognition technology is an excellent example of the potential of IoT devices to facilitate a more connected and automated world. However, it is important to note that with any new technology, there are also concerns around data privacy and security. As such, it is essential that developers prioritize ethical considerations and robust security protocols when designing these systems. Moreover, hand gesture recognition technology can be further improved through the use of artificial intelligence and machine learning. These technologies can help improve the accuracy of the recognition system and provide a more personalized experience for users. This system is highly reliable and user-friendly, and does not require any physical contact, which makes it highly suitable for disabled people. Furthermore, the development of new sensor technolo

关键词：

来源：评论

学校读者我要写书评

暂无评论

Estimating Chlorophyll Content from Hyperspectral Data Using Gradient Features 23rd

Estimating Chlorophyll Content from Hyperspectral Data Usin...

引用

23rd international conference on Computational Science, ICCS 2023

作者： Ruszczak, Bogdan Wijata, Agata M. Nalepa, Jakub Faculty of Electrical Engineering Automatic Control and Informatics Department of Informatics Opole University of Technology Opole Poland Faculty of Biomedical Engineering Silesian University of Technology Zabrze Poland Faculty of Automatic Control Electronics and Computer Science Department of Algorithmics and Software Silesian University of Technology Gliwice Poland KP Labs Gliwice Poland

ISBN: (纸本)9783031360206

Non-invasive estimation of chlorophyll content in plants plays an important role in precision agriculture. This task may be tackled using hyperspectral imaging that acquires numerous narrow bands of the electromagnetic spectrum, which may reflect subtle features of the plant, and inherently offers spatial scalability. Such imagery is, however, high-dimensional, therefore it is challenging to transfer from the imaging device, store and investigate. We propose a machine learning pipeline for estimating chlorophyll content from hyperspectral data. It benefits from the Savitzky-Golay filtering to smooth the (potentially noisy) spectral curves, and from gradient-based features extracted from such a smoothed signal. The experiments revealed that our approach significantly outperforms the state of the art according to the widely-established estimation quality metrics obtained for four chlorophyll-related parameters. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： machine learning

来源：评论

学校读者我要写书评

暂无评论

Fine-Tuning Vision Transformer for Arabic Sign Language Video Recognition on Augmented Small-Scale Dataset

Fine-Tuning Vision Transformer for Arabic Sign Language Vide...

引用

IEEE international conference on Systems, Man and Cybernetics

作者： Munkhjargal Gochoo Ganzorig Batnasan Ahmed Abdelhadi Ahmed Munkh-Erdene Otgonbold Fady Alnajjar Timothy K. Shih Tan-Hsu Tan Lai Khin Wee Dept. of Computer Science and Software Engineering United Arab Emirates University Al Ain United Arab Emirates College of EECS National Central University Taoyuan Taiwan Dept. of Electrical Engineering National Taipei University of Technology Taipei Taiwan Dept. of Biomedical Engineering University of Malaya Kuala Lumpur Malaysia

With the rise of AI, the recognition of Sign Language (SL) through sign-to-text has gained significance in the field of computer vision and deep machine learning. However, there are only a few medium to large open datasets available for this task, as it requires a vast dataset of thousands of signs for words/phrases in different environments, which is a time-consuming and tedious process. Furthermore, there has been very little effort towards Arabic Sign Language Recognition (ArSLR). This research paper presents the results of fine-tuning the Vision Transformer (ViT) model on a small-scale in-house dataset of ArSL. The main goal is to attain satisfactory results by utilizing minimal computing power and a small dataset involving less than 10 individuals, with only one recording made for each sign in every environment. The dataset comprises 49 classes/signs, all of which were made with two hands and belong to the Level I category in terms of popularity. To enhance the dataset, three types of augmentations - translation, shear, and rotation were employed. The ViT model, pre-trained on the Kinetics dataset, was trained on the variation of augmented datasets with 2 to 40 times samples for each original video, where the training set includes original and augmented videos of 8 volunteers and the test set includes only original videos of one particular volunteer. Experimental results reveal that the combination of rotation and shear outperformed the others, achieving an accuracy of 93% on the 20 times augmented samples per class per signer dataset. We believe this study sheds light on small-scale dataset-based SLR tasks and video/action recognition in general.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Ensemble Deep learning Approach for Identification of DDOS Attack 1st

Ensemble Deep Learning Approach for Identification of DDOS A...

引用

1st international conference on Advances in Artificial Intelligence and machine learning in Big Data Processing, AAIMB 2023

作者： Balakrishnan, C. kumar, V. S. Prassana Department of Computer Science and Engineering S.A.Engineering College Chennai India

ISBN: (纸本)9783031730641

Numerous IoT web apps have been hindered by multiple safety hazards and network intrusions as a result of the home control dataset's on going enhancement. Automating your home has always been centred on safety and the recognition of DDOS Threats. It is essentially possible to make use of numerous IoT web-based resources through input of a set of data for the home's automation or by tapping on a hyperlink in the application itself. The cloud manages the aforementioned difficulties in the concept of the Edge of Things. An attacker can create various web strikes. By embedding executable instructions or injecting illicit software inside a DDOS threat, many simultaneous intricate models are employed to improve system reliability and the ease of maintaining data disclosure. By accurately recognising malicious automated homes information set, it is crucial to enhance the steadfast reliability and integrity of IOT web apps. The site of harmful home automation information set detection according to character-centered material categorization emphasises will be investigated using an artificial learning algorithm system in this work. The fact that hazardous buzz phrases are exceptional home automation information set, it is possible to divide the equipment in an ordinary intelligent home setting into four classes: Class 1 is very high traffic reliability, Class 2 is high traffic certainty, Class 3 is medium traffic accuracy, and Class 4 is low traffic stability. According on the test outcomes, our suggested neural network identification algorithm is actually appropriate for high-accuracy tasks such as categorization. When compared to different categorization designs, the model's accuracy rate is over %. Considerable speculative and empirical advantages for web safety studies can be derived from the use of deep learning to aggregate home automation information to identify Web visitor's goals, which opens up novel possibilities for clever safety studies. © The Author(s), under ex

关键词： Deep learning

来源：评论

学校读者我要写书评

暂无评论

An Intelligent software Tool for Audio Signal-based Hinglish to English Language Translation

An Intelligent Software Tool for Audio Signal-based Hinglish...

引用

IEEE Punecon

作者： Aditi Vikrant Dhavale Amit Vikrant Dhavale Sunita Vikrant Dhavale Department of Artificial Intelligence & Machine Learning Symbiosis Institute of Technology Pune India Department of Mechanical Engineering Indian Institute of Technology Indore India SoCE & MS Defence Institute of Advanced Technology Pune India

Most of the current Indian generation speaks/writes using Hinglish on various social media platforms. It is difficult to understand and interpret Hinglish using existing computational linguistic tools mainly based on English. Hence, there is a need to provide automated Hinglish to English Language Translation tools to integrate with existing NLP-based applications like hate speech detection. Currently, such complex language translations are manually intensive and require domain experts. Also, there is a scarcity of standard datasets in this domain for carrying out helpful research. In this research, we propose an intelligent AI-based translator for translating audio data signals from Hinglish to English, which can be integrated into various NLP-based applications in the Indian Context. We also created a large-scale customized annotated Hinglish to English dataset containing 27135 entries of size 4.121MB. After extensive experimentation, we received the highest BLEU (Bi-Lingual Evaluation Understudy) score of 92.20 on our customized Hinglish to English dataset, while on the original PHINC dataset, we found a BLEU score of 70 approx. We also developed a Python TKinter-based user-friendly GUI application that takes audio signal/voice as input and provides English-translated text as output.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Boosting Spectrum-Based Fault Localization for Spreadsheets with Product Metrics in a learning Approach 22

Boosting Spectrum-Based Fault Localization for Spreadsheets ...

引用

Proceedings of the 37th IEEE/ACM international conference on Automated software engineering

作者： Adil Mukhtar Birgit Hofer Dietmar Jannach Franz Wotawa Konstantin Schekotihin Graz University of Technology Austria University of Klagenfurt Austria

ISBN: (纸本)9781450394758

Faults in spreadsheets are not uncommon and they can have significant negative consequences in practice. Various approaches for fault localization were proposed in recent years, among them techniques that transferred ideas from spectrum-based fault localization (SFL) to the spreadsheet domain. Applying SFL to spreadsheets proved to be effective, but has certain limitations. Specifically, the constrained computational structures of spreadsheets may lead to large sets of cells that have the same assumed fault probability according to SFL and thus have to be inspected manually. In this work, we propose to combine SFL with a fault prediction method based on spreadsheet metrics in a machine learning (ML) approach. In particular, we train supervised ML models using two orthogonal types of features: (i) variables that are used to compute similarity coefficients in SFL and (ii) spreadsheet metrics that have shown to be good predictors for faulty formulas in previous work. Experiments with a widely-used corpus of faulty spreadsheets indicate that the combined model helps to significantly improve fault localization performance in terms of wasted effort and accuracy.

关键词： Artificial Intelligence Spreadsheets Spectrum-based Fault Localization machine learning

来源：评论

学校读者我要写书评

暂无评论

A Drift Handling Approach for Self-Adaptive ML software in Scalable Industrial Processes 22

A Drift Handling Approach for Self-Adaptive ML Software in S...

引用

Proceedings of the 37th IEEE/ACM international conference on Automated software engineering

作者： Firas Bayram Bestoun S. Ahmed Erik Hallin Anton Engman Department of Mathematics and Computer Science Karlstad University Sweden Sweden Uddeholms AB Uvedsvägen Hagfors 683 33 Värmlands län Sweden Sweden

ISBN: (纸本)9781450394758

Most industrial processes in real-world manufacturing applications are characterized by the scalability property, which requires an automated strategy to self-adapt machine learning (ML) software systems to the new conditions. In this paper, we investigate an Electroslag Remelting (ESR) use case process from the Uddeholms AB steel company. The use case involves predicting the minimum pressure value for a vacuum pumping event. Taking into account the long time required to collect new records and efficiently integrate the new machines with the built ML software system. Additionally, to accommodate the changes and satisfy the non-functional requirement of the software system, namely adaptability, we propose an automated and adaptive approach based on a drift handling technique called importance weighting. The aim is to address the problem of adding a new furnace to production and enable the adaptability attribute of the ML software. The overall results demonstrate the improvements in ML software performance achieved by implementing the proposed approach over the classical non-adaptive approach.

关键词： concept drift changing environments automated industrial process ML software adaptability Electroslag Remelting (ESR)

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325页 << < 309 310 311 312 313 314 315 316 317 318 > >>

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：