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

4,140 篇 会议
38 册 图书
6 篇 期刊文献

馆藏范围

4,184 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

2,738 篇 工学
- 2,466 篇 计算机科学与技术...
- 2,041 篇 软件工程
- 615 篇 生物工程
- 587 篇 信息与通信工程
- 364 篇 生物医学工程（可授...
- 266 篇 控制科学与工程
- 216 篇 电气工程
- 211 篇 光学工程
- 148 篇 安全科学与工程
- 136 篇 机械工程
- 124 篇 电子科学与技术（可...
- 118 篇 化学工程与技术
- 107 篇 交通运输工程
- 91 篇 动力工程及工程热...
1,367 篇 理学
- 673 篇 数学
- 645 篇 生物学
- 331 篇 统计学（可授理学、...
- 307 篇 物理学
- 197 篇 系统科学
- 127 篇 化学
720 篇 管理学
- 393 篇 管理科学与工程(可...
- 388 篇 图书情报与档案管...
- 237 篇 工商管理
342 篇 医学
- 315 篇 临床医学
- 308 篇 基础医学(可授医学...
- 221 篇 药学(可授医学、理...
- 125 篇 公共卫生与预防医...
159 篇 法学
- 138 篇 社会学
157 篇 教育学
- 155 篇 教育学
141 篇 农学
- 140 篇 作物学
89 篇 经济学
9 篇 军事学
5 篇 文学

主题

528 篇 machine learning
245 篇 deep learning
117 篇 support vector m...
99 篇 adversarial mach...
93 篇 accuracy
93 篇 machine learning...
83 篇 forecasting
76 篇 convolutional ne...
70 篇 predictive model...
70 篇 feature extracti...
59 篇 artificial intel...
53 篇 students
51 篇 learning systems
48 篇 decision trees
48 篇 training
47 篇 reinforcement le...
47 篇 computational mo...
47 篇 computer vision
46 篇 internet of thin...
41 篇 neural networks

机构

46 篇 chitkara univers...
15 篇 graphic era hill...
10 篇 college of manag...
9 篇 graphic era deem...
8 篇 computer science...
8 篇 beijing universi...
7 篇 school of comput...
7 篇 school of comput...
7 篇 school of comput...
7 篇 department of in...
6 篇 università di ca...
6 篇 infn sezione di ...
6 篇 north-west unive...
6 篇 computer science...
6 篇 lovely professio...
6 篇 in2p3 lpc campus...
6 篇 kkr and ksr inst...
6 篇 institut univers...
6 篇 national centre ...
6 篇 greater bay area...

作者

18 篇 kukreja vinay
15 篇 mehta shiva
10 篇 william p.
8 篇 sharma vikrant
7 篇 mahamudul hasan
7 篇 shiva mehta
6 篇 chen a.
6 篇 benoit d.m.
6 篇 ferrara g.
6 篇 ardid m.
6 篇 calvo d.
6 篇 gagliardini s.
6 篇 eddymaoui a.
6 篇 kulikovskiy v.
6 篇 labalme m.
6 篇 gal t.
6 篇 bozza c.
6 篇 khatun a.
6 篇 kalekin o.
6 篇 huang f.

语言

2,638 篇 英文
1,545 篇 其他
112 篇 中文

检索条件"任意字段=Proceedings of the 2023 4th International Conference on Machine Learning and Computer Application"

共 4184 条记录，以下是1731-1740 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：

MUCS@DravidianLangTech2023: Malayalam Fake News Detection Using machine learning Approach 3

MUCS@DravidianLangTech2023: Malayalam Fake News Detection Us...

引用

3rd Workshop on Speech and Language Technologies for Dravidian Languages, DravidianLangTech 2023

作者： Coelho, Sharal Hegde, Asha Kavya, G. Shashirekha, Hosahalli Lakshmaiah Department of Computer Science Mangalore University Mangalore India

ISBN: (纸本)9789544520854

Social media is widely used to spread fake news which can lead to individuals or group making wrong judgments based on fake news. the fake news can even create confusion, panic, anxiety, etc., leading to taking inappropriate actions by the individuals. Fake news creators with their tactics may use legitimate sources and mimic the style of reputed publications to create fake news, making it difficult and challenging to identify such content. To address the challenges of detecting fake news in this paper, we - team MUCS, describe the machine learning (ML) models submitted to"Fake News Detection in Dravidian Languages" at DravidianLangTech@RANLP 2023 shared task. three different models, namely: Multinomial Naive Bayes (MNB), Logistic Regression (LR), and an Ensemble model (MNB, LR, and Support Vector machine (SVM)) with hard voting, are trained using Term Frequency - Inverse Document Frequency (TF-IDF) of word unigrams, to detect fake news in code-mixed Malayalam text. Among the three models ensemble model performed better with a macro F1-score of 0.831 and placed 3rd rank in the shared task. © DravidianLangTech 2023 - 3rd Workshop on Speech and Language Technologies for Dravidian Languages, associated with 14th international conference on Recent Advances in Natural Language Processing, RANLP 2023 - proceedings.

关键词： Support vector machines

来源：评论

学校读者我要写书评

暂无评论

Research and application of the Primary Harmonic Eliminator for the thermal Resistor 4

Research and Application of the Primary Harmonic Eliminator ...

引用

4th international conference on Advances in Electrical Engineering and computer applications, AEECA 2023

作者： Wei, Ying Niu, Bo Wang, Xiaokang Power Research Institute of State Grid Ningxia Power Co. Yinchuan China Wuzhong Power Company of State Grid Ningxia Power Co. Wuzhong China

ISBN: (纸本)9798350308082

In the neutral non-effective grounding system, the ferromagnetic resonance overvoltage of the electromagnetic voltage transformer appears the most frequently. the study shows that the SiC harmonic eliminator is connected between the primary neutral point of the electromagnetic voltage transformer and the ground, and the ferromagnetic resonance suppression through the voltage state applied to the two ends of the device during the resonance process is easy to fuse and burst during the resonance process. this paper presents a PTC harmonic eliminator, based on the correlation between temperature and electrical properties of thermistors, and the test shows that the PTC harmonic eliminator can suppress the excitation surge current below 0.2A in a short harmonic suppression time, and the surge suppression ability is better than the SiC harmonic eliminator, which can solve the problem of electromagnetic voltage transformer burst caused by the intermittent grounding of the system. the application of PTC harmonic eliminator in distribution network systems will effectively improve the operational stability of ungrounded neutral systems. © 2023 IEEE.

关键词： Ferromagnetic materials

来源：评论

学校读者我要写书评

暂无评论

Explainable AI-Driven machine learning Approach for Prediction of Acoustic-Based Fire Extinction 4

Explainable AI-Driven Machine Learning Approach for Predicti...

引用

4th international conference on Data Analytics for Business and Industry, ICDABI 2023

作者： Sarker, Baneswar Gupta, Suraj Singh, Gajendra Kumar, Piyush Maiti, J. Indian Institute of Technology Kharagpur Department of Industrial and Systems Engineering Kharagpur India Indian Institute of Technology Kharagpur Ranbir & Chitra Gupta School of Infrastructure Design & Mgmt. Kharagpur India Indian Institute of Technology Kharagpur Centre of Excellence in Safety Engineering and Analytics India Indian Institute of Technology Kharagpur Centre of Excellence in Safety Engineering and Analytics Department of Industrial and Systems Engineering Kharagpur India

ISBN: (纸本)9798350369786

Acoustic fire-extinguishing system is an alternative system for the safe handling and control of fire accidents by extinguishing different classes of fires. It is necessary to accurately identify and predict the extinction and non-extinction states of the flames based on certain characteristic features. It is also important to identify the most important features governing the classification of the states of the flame. Both of these can be achieved by the combination of deep learning techniques and explainable artificial intelligence (XAI). In this study, models like artificial neural networks (ANN) and convolution neural networks (CNN) were deployed on an experimental dataset to classify the extinction states of the flame based on features, namely, flame sizes, fuel type, airflow, decibel, frequencies, and distance range. On the implementation of ANN, 95% and 92% accuracy were obtained, while 97% and 98% accuracy were obtained on a CNN model, for the liquid and LPG fuels respectively. the application of XAI in this study indicates that distance range has the maximum impact among all features of the model. © 2023 IEEE.

关键词： Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

Protecting the IoT Devices from DDoS Attack Using Blockchain-Based Multi-code-Driven Trust Mechanism 1

引用

4th international conference on computer Vision, High-Performance Computing, Smart Devices, and Networks, CHSN 2023

作者： Jayanarayana Reddy, D. Jahnavi, Addula Indhu, Pothula Latha, Mekala Hema Department of CSE G. Pullaiah College of Engineering and Technology Kurnool India Kurnool India

ISBN: (数字)9789819777945

ISBN: (纸本)9789819777938

the Internet of things (IoT) offers a promising platform for developing mission-critical programs. However, these programs often depend on a centralised storage architecture, which poses significant challenges such as security, privacy, and a single point of failure. Recently, blockchain technology has emerged as a key component in IoT application development. Blockchain can address issues related to data privacy, security, and third-party dependence in IoT applications. Both individuals and communities can benefit from integrating blockchain with IoT. Nonetheless, a DDoS attack on a mining pool in 2017 exposed significant vulnerabilities in blockchain-enabled IoT systems. Additionally, the data generated by these programs is vast. machine learning (ML) is an effective analytical tool that facilitates fully autonomous analysis and decision-making with large datasets. this research proposes a novel distributed intrusion detection system (IDS) utilising fog computing to detect DDoS attacks on mining pools in blockchain-enabled IoT networks, addressing the aforementioned challenges. It introduces an energy-efficient, decentralised, blockchain-based multi-mobile code-driven method for detecting internal threats in sensor node-powered IoT. the results indicate that the proposed approach outperforms existing alternatives. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Blockchain-based multi-mobile code driven solution Distributed Denial of Service Internet of things machine learning

来源：评论

学校读者我要写书评

暂无评论

Reward based Collaborative learning Platform with Integrated AI based Monitoring 4

Reward based Collaborative Learning Platform with Integrated...

引用

4th international conference on Inventive Research in Computing applications, ICIRCA 2022

作者： Prasanthan, Abijith Anand, K.S. Nair, Bharath Prathap Gautham Santhosh, K. Manoj, Rahan Anjali, T. Amrita Vishwa Vidhyapeetham Department of Computer Science and Engineering Amritapuri India

ISBN: (数字)9781665497077

ISBN: (纸本)9781665497077

this paper focuses on a Reward based Collaborative learning Platform that has an integrated AI-based Monitoring. the objective of this application is to provide a platform for students within an institution to study online in a collaborative manner and to monitor the productivity of a student by tracking the duration the student studied and hence calculate the student's attention span. Based on the calculated attention span, the student will be rewarded points by which the student will be able to redeem the points for de-stressing activities within the application. © 2022 IEEE.

关键词： Students

来源：评论

学校读者我要写书评

暂无评论

Determination of Fatigue Strength of Steel Using Deep learning Techniques 4th

Determination of Fatigue Strength of Steel Using Deep Learni...

引用

4th international conference on Advanced Engineering Optimization through Intelligent Techniques

作者： Kumar, Punit Anand, Ayush Kavitha, B. Natl Inst Technol Warangal Dept Civil Engn Hanamkonda Telangana India Natl Inst Technol Warangal Fac Civil Engn Hanamkonda Telangana India

ISBN: (纸本)9789819796618;9789819746545;9789819746538

Steel is one of the primary components of a structure from a strength perspective. Since the load applied to some structures is cyclic, fatigue strength becomes a crucial factor for durability. However, due to the complex nature of fatigue strength formation in steel, it is not yet completely understood. Fortunately, the evolution of new technologies like artificial intelligence and machine learning has led to the development of regression models that can accurately predict the fatigue strength of steel. Although machine learning models have a defined structure, their performance improvement is limited after reaching a certain threshold. However, this limitation can be overcome with neural networks (NN), which are highly customizable and improve with the addition of data. In this study, seven different NN models were constructed with successive enhancements to predict the fatigue strength of steel with high accuracy. Various performance metrics were utilized to evaluate the models. the dataset used in this project is the fatigue dataset for steel from Japan NIMS (National Institute for Materials Science), which is an open-source and the world's largest dataset on steel fatigue strength. It comprises 437 instances with 25 different factors influencing the property, such as chemical composition (9), heat treatment conditions (12), and upstream processing details (4). these instances include 371 carbon and low-alloy steels, 48 carburizing steels, and 18 spring steels. the data covers various heats of each steel grade and different processing conditions. After testing various neural networks and determining the best train-test split, a maximum accuracy of 99.7% was achieved on the test data. Furthermore, the model was deployed as a web application, making it accessible to everyone.

关键词： Fatigue strength of steel Material science Deep learning Artificial neural network Model deployment

来源：评论

学校读者我要写书评

暂无评论

ColCompNeT: Deep learning-Based Colorization-Based Coding Network 1

引用

4th international conference on machine Intelligence and Signal Processing, MISP 2022

作者： Mishra, Dipti Singh, Satish Kumar Mahindra University Hyderabad500043 India Indian Institute of Information Technology Allahabad Allahabad211012 India

ISBN: (数字)9789819900855

ISBN: (纸本)9789819900848

Converting a grayscale image to a visually plausible and perceptually meaningful color image is an exciting research topic in computer vision and graphics. However, predicting the chrominance channels from a grayscale image is an ill-posed problem, especially when the objective is to produce the same color as in the ground truth image, like for the application of compression using colorization or video/image restoration. Compression using colorization efficiently reduces the storage space and transmission bandwidth by two-thirds and maintains the image’s visual quality. However, colorizing decompressed gray images exactly as ground truth with maximum accuracy is a challenging task. In this paper, learning-based CNN network ColCompNeT has been proposed in which concept of parallel training of colorization and compression network is utilized. With the proposed algorithm, a maximum bit saving of 36.45% is achieved with the improved objective and subjective performance when compared with the state-of-the-art methods. © 2023, the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Network coding

来源：评论

学校读者我要写书评

暂无评论

On Comparing Mutation Testing Tools through learning-based Mutant Selection 4

On Comparing Mutation Testing Tools through Learning-based M...

引用

4th IEEE/ACM international conference on Automation of Software Test (AST)

作者： Ojdanic, Milos Khanfir, Ahmed Garg, Aayush Degiovanni, Renzo Papadakis, Mike Le Traon, Yves Univ Luxembourg Luxembourg Luxembourg

ISBN: (纸本)9798350324020

Recently many mutation testing tools have been proposed that rely on bug-fix patterns and natural language models trained on large code corpus. As these tools operate fundamentally differently from the grammar-based traditional approaches, a question arises of how these tools compare in terms of 1) fault detection and 2) cost-effectiveness. Simultaneously, mutation testing research proposes mutant selection approaches based on machine learning to mitigate its application cost. this raises another question: How do the existing mutation testing tools compare when guided by mutant selection approaches? To answer these questions, we compare four existing tools mu BERT (uses pre-trained language model for fault seeding), IBIR (relies on inverted fix-patterns), DeepMutation (generates mutants by employing Neural machine Translation) and PIT (applies standard grammar-based rules) in terms of fault detection capability and cost-effectiveness, in conjunction with standard and deep learning based mutant selection strategies. Our results show that IBIR has the highest fault detection capability among the four tools;however, it is not the most cost-effective when considering different selection strategies. On the other hand, mu BERT having a relatively lower fault detection capability, is the most cost-effective among the four tools. Our results also indicate that comparing mutation testing tools when using deep learning-based mutant selection strategies can lead to different conclusions than the standard mutant selection. For instance, our results demonstrate that combining mu BERT with deep learningbased mutant selection yields 12% higher fault detection than the considered tools.

关键词： Fault Seeding, Mutation Testing, Empirical Study, Empirical Comparison

来源：评论

学校读者我要写书评

暂无评论

Diabetic Condition Classification using Supervised and Unsupervised machine learning Techniques: A Use Case for HealthTech Industry 4

Diabetic Condition Classification using Supervised and Unsup...

引用

4th IEEE international conference on Smart Technologies in Computing, Electrical and Electronics, ICSTCEE 2023

作者： Bongale, Anupkumar M. Biradar, Santoshkumar Pise, Priya Suke, Amita Priyadarshan Uke, Nilesh Dharrao, Deepak S. Symbiosis Institute Of Technology Department Of Aiml Pune Campus Pune India G H Raisoni College Of Engineering And Management Department Of Cyber Security And Data Science Pune Wagholi India Indira College Of Engineering And Management Department Of Ai And Ds Pune India Trinity Academy Of Engineering Pune India Symbiosis Institute Of Technology Department Of Cse Pune Campus Pune India

ISBN: (纸本)9798350384628

Diabetes is a very underestimated and, in many cases, an ignored disease. People do not understand the seriousness of diabetes. Many people think diabetes is just something because of which one cannot consume sweets. this, however, is not true. Diabetes is a very serious problem where symptoms can range from being very thirsty all the time to even death. there are many cases where diabetic people had to get their leg, or some other limb amputated because of it. thus, people have to be made cognizant of diabetes' seriousness. this article dives deep into this disease and lists the different types of diabetes, and the way people can know if they are diabetic. Also, there is an in-depth literature review of research papers ranging from 2002-2020. Furthermore, a deep dive in the project of diabetes prediction is present. the techniques used to classify into 'diabetic' or 'non-diabetic' are Random Forest, Logistic Regression and K Nearest Neighbor algorithms which all belong to the supervised machine learning algorithms. Logistic Regression uses sigmoid function to classify into different classes, Random Forest approach uses multiple Decision Trees and the majority decision of them all for the final output. Moreover, K Nearest Neighbor technique uses the concept of Euclidean Distance to decide which class is suitable for any new coming datapoint. © 2023 IEEE.

关键词： Decision trees

来源：评论

学校读者我要写书评

暂无评论

application research of hyperspectral remote sensing in the identification of stratigraphic boundaries alongside growing tunnels 4

Application research of hyperspectral remote sensing in the ...

引用

4th international conference on Telecommunications, Optics, and computer Science, TOCS 2023

作者： Bi, Xiaojia Jiang, Liangwen Dong, Qing He, Lei Wang, Dong China Railway ErYuan Engineering Group Co. Ltd Sichuan Chengdu China Beijing China School of Software Engineering Chengdu University of Information Technology Sichuan Chengdu China

ISBN: (数字)9781510679849

ISBN: (纸本)9781510679832

the geological survey along the large railway in China is difficult, the boundaries of many regional geological maps are unclear, and the geological mapping is very different. the use of hyperspectral remote sensing can greatly improve the survey accuracy in complex mountainous areas. In the identification of lithology and structure, hyperspectral remote sensing has certain advantages compared with multi-spectral satellite images. In this paper, the hyperspectral data of Gaofen-5 satellite is interpreted by a series of technical methods, such as data preprocessing, radiometric calibration, atmospheric correction, orthographic correction, image information enhancement, radiation homogenization processing, etc. According to different geological conditions, lithologic structure information by hyperspectral information enhancement technology in different regions and layers. Different geological units are effectively divided, the distribution characteristics of geological structure space are identified, and some stratigraphic boundaries of the original geological map are adjusted. this paper solves the problems that the survey personnel of long and large tunnels cannot reach, and the conventional survey methods cannot verify the stratigraphic boundaries and lithological characteristics. It also provides an important auxiliary reference value for the identification of surrounding rock of hyperspectral remote sensing. © 2024 SPIE.

关键词： Image enhancement

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419页 << < 170 171 172 173 174 175 176 177 178 179 > >>

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：