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

8,230 篇 会议
121 篇 期刊文献
79 册 图书
1 篇 学位论文

馆藏范围

8,431 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

6,179 篇 工学
- 5,350 篇 计算机科学与技术...
- 3,854 篇 软件工程
- 1,260 篇 信息与通信工程
- 1,258 篇 生物工程
- 904 篇 控制科学与工程
- 898 篇 电气工程
- 762 篇 生物医学工程（可授...
- 408 篇 机械工程
- 332 篇 交通运输工程
- 310 篇 光学工程
- 301 篇 化学工程与技术
- 275 篇 安全科学与工程
- 259 篇 动力工程及工程热...
- 225 篇 电子科学与技术（可...
- 166 篇 材料科学与工程（可...
2,921 篇 理学
- 1,535 篇 数学
- 1,328 篇 生物学
- 624 篇 系统科学
- 592 篇 统计学（可授理学、...
- 513 篇 物理学
- 284 篇 化学
1,577 篇 管理学
- 851 篇 管理科学与工程(可...
- 826 篇 图书情报与档案管...
- 441 篇 工商管理
655 篇 医学
- 606 篇 临床医学
- 576 篇 基础医学(可授医学...
- 421 篇 药学(可授医学、理...
- 196 篇 公共卫生与预防医...
363 篇 教育学
- 362 篇 教育学
246 篇 法学
- 218 篇 社会学
160 篇 农学
138 篇 经济学
21 篇 文学
16 篇 军事学
3 篇 艺术学
1 篇 哲学
1 篇 历史学

主题

1,688 篇 machine learning
660 篇 deep learning
411 篇 machine learning...
323 篇 support vector m...
294 篇 training
264 篇 feature extracti...
245 篇 real-time system...
238 篇 predictive model...
237 篇 reinforcement le...
217 篇 neural networks
192 篇 computational mo...
151 篇 learning systems
145 篇 conferences
140 篇 artificial intel...
139 篇 data models
128 篇 covid-19
128 篇 decision trees
128 篇 forecasting
126 篇 internet of thin...
106 篇 prediction algor...

机构

21 篇 max planck inst ...
19 篇 chitkara univers...
16 篇 school of intell...
16 篇 school of inform...
15 篇 sri krishna coll...
14 篇 univ tubingen tu...
14 篇 university of ch...
11 篇 school of intell...
10 篇 school of artifi...
10 篇 machine learning...
10 篇 college of syste...
9 篇 shanghai jiao to...
9 篇 school of comput...
9 篇 shandong provinc...
9 篇 school of scienc...
9 篇 kazan natl res t...
9 篇 school of comput...
8 篇 carnegie mellon ...
8 篇 institute of inf...
8 篇 peking universit...

作者

16 篇 xiong gang
15 篇 wu xinyu
11 篇 wang jing
11 篇 hennig philipp
10 篇 zhang tao
10 篇 sattar abdus
9 篇 li yang
9 篇 li hao
8 篇 li rui
8 篇 shen zhen
8 篇 yang yang
8 篇 jitpattanakul an...
8 篇 salloum said a.
7 篇 wang lei
7 篇 ishii t.
7 篇 liu xin
7 篇 elamvazuthi irra...
7 篇 heryadi yaya
7 篇 wang hao
7 篇 mishra debahuti

语言

8,342 篇 英文
76 篇 其他
10 篇 中文
4 篇 葡萄牙文
1 篇 西班牙文
1 篇 土耳其文

检索条件"任意字段=2021 International Conference on Machine Learning and Intelligent Systems Engineering, MLISE 2021"

共 8431 条记录，以下是31-40 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：

Adaptive Differentially Private Robust Federated learning Against Backdoor Attacks 1

Adaptive Differentially Private Robust Federated Learning Ag...

引用

1st international conference on intelligent Manufacturing and Cloud Computing, ICIMCC 2024

作者： Yao, Ruixiang Wen, Hong Hou, Wenjing Ma, Wendi Sun, Fan Zhao, Ziang School of Aeronautics and Astronautics University of Elec.Science and Tech. of China Chengdu611731 China Aircraft Swarm Intelligent Sensing and Cooperative Control Key Lab. of Sichuan Province UESTC 611731 China Intelligent IoT Communication Technology Engineering Research Center of Sichuan Province UESTC 611731 China

ISBN: (纸本)9781643685779

In federated learning systems, malicious attackers can manipulate training datasets by injecting backdoor triggers to achieve data poisoning. Addressing this vulnerability, this paper proposes a new defense method, the adaptive differential privacy stochastic gradient descent (ADP-SGD) algorithm, which increases the Euclidean distance between malicious and benign updates to enhance aggregation efficiency. Experiments were conducted on typical datasets, and the results show that combining ADP-SGD with the m-Krum aggregation algorithm can effectively defend against backdoor attacks in complex attack environments. While ensuring the accuracy of the main task, it significantly reduces the success rate of backdoor attacks, especially under the condition of unknown proportions of malicious participants, proving to be effective and robust. © 2025 The Authors.

关键词： Federated learning

来源：评论

学校读者我要写书评

暂无评论

Why a Bot is Undetectable? An Explainability-Based Study of Misclassified Automated Accounts in Social Networks 20th

Why a Bot is Undetectable? An Explainability-Based Study of ...

引用

20th international conference on Information Processing and Management of Uncertainty in Knowledge-Based systems

作者： Lopez-Joya, Salvador Diaz-Garcia, Jose Angel Ruiz, Maria Dolores Martin-Bautista, Maria Jose Res Ctr Informat & Communicat Technol CITIC UGR Granada 18014 Spain Univ Granada Dept Comp Sci & Artificial Intelligence Granada 18014 Spain

ISBN: (纸本)9783031739965;9783031739972

Detecting bots on social media platforms is a major challenge, as these automated entities are constantly evolving to evade detection. In this study, we investigate the main features that contribute to the difficulty of bot detection. Leveraging the TwiBot-20 dataset, we analyze the characteristics of misclassified accounts and explore the reasons behind their erroneous classification. Our approach combines feature engineering, machine learning with Random Forest, and the interpretation of model predictions using SHAP (SHapley Additive exPlanations) values. We employ clustering techniques to identify patterns in feature contributions and provide insights into the complexities of distinguishing between human and automated accounts. Our findings highlight the nature of bot detection and the need for advanced methods to address the problem of social media manipulation.

关键词： Bot detection Social media machine learning Explainability SHAP values Clustering Data mining

来源：评论

学校读者我要写书评

暂无评论

Analysing User Engagement in e-learning Platforms: A machine learning Approach to Web Analytics 27th

Analysing User Engagement in e-Learning Platforms: A Machine...

引用

27th international conference on Interactive Collaborative learning, ICL 2024

作者： Christina, Gouvatsou Pantazatos, Dimitris Grammatikou, Mary Maglaris, Vasilis Stefaneas, Petros School of Applied Mathematics and Physical Sciences National Technical University of Athens Athens15780 Greece School of Electrical and Computer Engineering National Technical University of Athens Athens15780 Greece

ISBN: (纸本)9783031856518

The scope of this paper is to analyze the web analytics of a Next Generation Digital learning Environment (NGDLE), which was part of a European initiative, specifically focusing on how platform engagement was affected by the COVID-19 pandemic waves and the mandatory e-schooling in Europe. Emphasis was given to the Bounce Rate (%) variable, a metric to estimate the platform’s effectiveness in retaining its users. This was achieved by applying a classification problem, comparing different machine learning models, and identifying the most contributing features. The study revealed patterns in the data, providing an overview of user engagement in the e-service while unfolding the complex relationships among the features and the need for robust analysis. Finally, it highlighted features contributing to the target variable Bounce Rate (%) that could be further explored to enhance the VLE. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Adversarial machine learning

来源：评论

学校读者我要写书评

暂无评论

machine learning Methods for Phenotype Prediction from High-Dimensional, Low Population Aquaculture Data

Machine Learning Methods for Phenotype Prediction from High-...

引用

18th international Joint conference on Biomedical engineering systems and Technologies, BIOSTEC 2025

作者： Faldani, Giovanni Rossignolo, Enrico Signor, Eleonora Longo, Alessio Faggion, Sara Bargelloni, Luca Comin, Matteo Pizzi, Cinzia Department of Information Engineering University of Padova Padova35131 Italy Department of Comparative Biomedicine and Food Science University of Padova PD Legnaro35020 Italy

Recent research has increasingly focused on classification rules within the big data framework, yet many bioin formatics applications still address prediction problems that involve small-sample, high-dimensional data. In phenotype prediction, especially with the rise of large-scale genomic data, a central challenge arises from han dling high-dimensional datasets where the number of genetic features (such as SNPs) far exceeds the sample size. A significant example of such high-dimensional, low-sample datasets is found in aquaculture, a rapidly growing sector within global food production and a crucial source of high-quality protein. This study uses data from an experiment performed on European seabass as a test case, focusing on predicting resistance to Viral Nervous Necrosis (VNN) as a specific phenotype of interest. We explore a range of machine learning tech niques to address the complexities of high-dimensional data, from established methods like gradient boosting, SVM, and deep learning to newer approaches. This paper evaluates various methods for associating SNPs with phenotypic traits, benchmarking their performance on challenging aquaculture genomic data to provide insight into the effectiveness of these techniques. © 2025 by SCITEPRESS– Science and Technology Publications, Lda.

关键词： Adversarial machine learning

来源：评论

学校读者我要写书评

暂无评论

Models of intelligent Tutoring systems Based on Autonomous Agents for Virtual learning Environments: A Systematic Literature Review 22nd

Models of Intelligent Tutoring Systems Based on Autonomous A...

引用

22nd international conference on Practical Applications of Agents and Multi-Agent systems, PAAMS 2024

作者： López-Goyez, Juan P. González-Briones, Alfonso Chamorro, Andrea F. Grupo de Investigación BISITE Departamento de Informática y Automática Facultad de Ciencias University of Salamanca Instituto de Investigación Biomédica de Salamanca Calle Espejo 2 24.2 Salamanca37007 Spain Universidad Politécnica Estatal del Carchi Antisana S/N Tulcán040101 Ecuador

ISBN: (纸本)9783031704147

Virtual education combines didactic strategies with information and communication technologies to facilitate student access, interaction, and active participation. Academic monitoring and tutoring should be conducted within virtual learning environments (VLE) with the support of a virtual tutor to provide personalized advice and feedback. The review integrates theories, didactic strategies, learning styles, and computational models. This research presents a systematic review of literature on tutoring models in virtual education. The objective is to identify intelligent tutoring systems (ITS) models that use autonomous agents and expert systems in virtual learning environments. Additionally, strategies for implementing ITS in VLEs are presented. The identified models focus on adaptive learning, learning styles, and student skills for developing a specific course. It is proposed to design an architecture in the Moodle platform for academic monitoring of students in the online modality using autonomous agents. A holistic approach is considered, combining the efficiency of AI with didactic strategies that personalize learning through friendly human-machine interaction. The research on ITS models focuses on adaptive learning, considering new technological trends, while also considering the interaction between the student and the virtual tutor. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Virtual environments

来源：评论

学校读者我要写书评

暂无评论

machine learning-Based Prediction of Flue-Cured Tobacco Quality Using Chemical Composition Analysis: A Case Study in Sichuan Province, China 1

Machine Learning-Based Prediction of Flue-Cured Tobacco Qual...

引用

1st international conference on intelligent Manufacturing and Cloud Computing, ICIMCC 2024

作者： Qiu, Jun Bie, Rui Wang, Zhiying Sun, Jingxian Li, Xiaojie Jin, Dongmei Cao, Jianmin Tobacco Research Institute of CAAS Qingdao266101 China Graduate School of CAAS Beijing100081 China China Tobacco Shandong Industry Co. Ltd. Jinan250013 China Sichuan Tobacco Quality Supervision and Testing Station Chengdu610041 China HONG TA Liaoning Tobacco Co. LTD Shenyang110003 China

ISBN: (纸本)9781643685779

Background: In this study, we aimed to establish an efficient and accurate machine -learning model for evaluating tobacco quality based on its chemical composition. To achieve this, we gathered a dataset comprising 188 tobacco samples taken from the production area of Sichuan, China in 2021. Four machine learning algorithms—Random Forest (RF), Support Vector machine (SVM), K-Nearest Neighbors (KNN), and Gradient Boosting Classifier (GBC)—were used to establish a predictive model for assessing tobacco quality. The study focused on comparing the predictive performance of these models and exploring the upper limit of prediction accuracy using genetic algorithm (GA) hyperparameter optimization. Additionally, the SHAP value model interpretation framework was introduced to provide a comprehensive global interpretation and conduct feature dependency analysis. Results: The results showed that model accuracy ranked as RF>GBC> KNN>SVM, with the GA-RF machine learning model achieving a prediction accuracy of 86.8%. SHAP values identified seven important characteristic indexes affecting Sichuan tobacco leaf quality, highlighting RF as the optimal classifier for predicting flue-cured tobacco quality in Sichuan Province. Conclusions: The GA-RF model constructed in this study effectively identifies Sichuan tobacco leaf quality. These findings offer novel insights and data support for the application of machine learning algorithms in tobacco fields and tobacco leaf quality evaluation. © 2025 The Authors.

关键词： Adversarial machine learning

来源：评论

学校读者我要写书评

暂无评论

Integrating Temporal Analysis with Hybrid machine learning and Deep learning Models for Enhanced Air Quality Prediction 19

Integrating Temporal Analysis with Hybrid Machine Learning a...

引用

19th international conference on Ubiquitous Information Management and Communication, IMCOM 2025

作者： Omer, Muhammad Ali, Sardar Jaffar Raza, Syed M. Le, Duc-Tai Choo, Hyunseung Dept. of Computer Science and Engineering Sungkyunkwan University Suwon Korea Republic of Dept. of AI Systems Engineering Sungkyunkwan University Suwon Korea Republic of James Watt School of Engineering University of Glasgow Glasgow United Kingdom Dept. of Electrical and Computer Engineering Sungkyunkwan University Suwon Korea Republic of

ISBN: (纸本)9798331507817

Air pollution remains a critical issue, adversely affecting public health and the environment. In this study, we utilize the Air Quality index dataset from Kaggle to analyze temporal and seasonal variations of key pollutants, specifically Carbon Monoxide (CO), Nitrogen Oxides (NOx), and Benzene (C6H6 ). Building upon this analysis, we predict Absolute Humidity (AH), a vital meteorological factor influencing pollutant dispersion, using machine learning (ML) and Deep learning (DL) techniques. Three ML techniques, Linear Regression (LR), Random Forest (RF), and Support Vector Regression (SVR), and three DL techniques, Artificial Neural Network (ANN), Convolutional Neural Network (CNN), and Long Short-Term Memory (LSTM), are employed for predicting AH. The results indicate that while the RF model achieved the lowest Mean Absolute Error (MAE) among ML methods (0.02), the CNN model, despite having an MAE of 0.04, demonstrated statistical superiority through paired t-tests and Wilcoxon signed-rank tests (p © 2025 IEEE.

关键词： Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

IHILLM-RAG: A safe and private medical large language model based on intelligent hardware interaction and retrieval-augmented generation(RAG) 4

IHILLM-RAG: A safe and private medical large language model ...

引用

4th international Computational Imaging conference, CITA 2024

作者： Zhou, Zibo Yang, Yi Ren, Tianling School of Integrated Circuit Tsinghua University Beijing100084 China Tsinghua University Beijing100084 China

ISBN: (纸本)9781510688834

Large language models (LLMs) have shown great potential in medical question answering and health management in the rapidly evolving healthcare landscape these ***, even with domain-specific pretraining, LLMs may potentially hallucinate and produce factually inaccurate outcomes. In addition, in the field of healthcare, due to the different habits, backgrounds, and physical conditions of patients, it is necessary to strengthen user-oriented medical assistants, but there is relatively little exploration of personalized medical assistants based on LLM. In this study, we propose a medical assistant LLM that combines external medical knowledge base and intelligent monitoring hardware interaction, which is called IHILLM-RAG. On the one hand, we build RAG system through external medical knowledge base to improve the security and accuracy of medical assistant and reduce the phenomenon of hallucination. On the other hand, we design the human physiological signal monitoring chip as a"human-machine interface" and carry out physical interaction with the human body and data interaction with LLM, so as to enhance the LLM's learning and memory of the user's own habits and improve the degree of personalization. We evaluated IHILLM-RAG on the important medical question-answering datasets, our experimental results demonstrate that IHILLM-RAG compares to the state-of-the-art open source models, the accuracy of the three datasets was improved by an average of 62.4%, 50.4%and 48.6%. Through this work, we provide a safer and more personalized method for healthcare which achieves a new paradigm of medical consultation with"Private AI-doctor" at any time and anywhere. © 2025 SPIE.

关键词： Digital storage

来源：评论

学校读者我要写书评

暂无评论

Qualitative analysis of caffeine in beverages based on Raman spectroscopy 17

Qualitative analysis of caffeine in beverages based on Raman...

引用

17th international conference on Photonics and Imaging in Biology and Medicine, PIBM 2024

作者： Yang, Yuhang Zhao, Zexian Pu, Wenjun Wu, Huikang Wang, Nan Zeng, Qi Chen, Xueli Center for Biomedical-photonics and Molecular Imaging Advanced Diagnostic-Therapy Technology and Equipment Key Laboratory of Higher Education Institutions in Shaanxi Province School of Life Science and Technology Xidian University Shaanxi Xi'an710126 China Engineering Research Center of Molecular and Neuro Imaging Ministry of Education Xi'an Key Laboratory of Intelligent Sensing and Regulation of Trans-Scale Life Information School of Life Science and Technology Xidian University Shaanxi Xi'an710126 China Inovation Center for Advanced Medical Imaging and Intelligent Medicine Guangzhou Institute of Technology Xidian University Guangdong Guangzhou510555 China

ISBN: (数字)9781510688070

ISBN: (纸本)9781510688063

Caffeine is an alkaloidal stimulant prevalently in food additives. The widespread presence of caffeine in a wide range of beverages has led to increased consumption, commonly exceeding safe levels. In this study, about 30 beverages available in the Chinese market, were analyzed using a 785 nm Raman spectrometer. The raw spectral data were preprocessed by noise reduction and baseline correction. The qualitative model was established using principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA), and the classification discrimination was carried out using K-nearest neighbor algorithm (KNN) and support vector machine algorithms (SVM). Especially, the two models could identify "Spirte" (without caffeine) from other beverages. It was demonstrated that Raman spectroscopy combined with machine learning can provide non-destructive, fast and efficient qualitative detection of caffeine in liquid beverages. © 2025 SPIE.

关键词： Noise abatement

来源：评论

学校读者我要写书评

暂无评论

Research on false news detection based on BERT model and attention mechanism 2

Research on false news detection based on BERT model and att...

引用

2nd international conference on Big Data, Computational Intelligence, and Applications, BDCIA 2024

作者： Fang, Jiamin Xi'an Eurasia University Xi'an710000 China

ISBN: (纸本)9781510689053

Artificial intelligence and intelligent algorithms have made remarkable progress in information processing. However, driven by the rapid development of the Internet, fake news interferes with people's access to accurate information. Aiming at the problem of false news detection, a multimodal false news detection model is proposed on the basis of the attention mechanism optimization bidirectional converter model. The designed model has an average accuracy of 98.61% in identifying news and an average response time of 1.74 seconds. It has a high recognition accuracy on various types of news data, especially on plain text news, with an accuracy of 99.82% and a response time of 1.15s. This shows that the new model can accurately and quickly determine the authenticity of news. This study provides an effective fake news identification tool that helps reduce the false information spread and improve the authenticity of network information. © 2025 SPIE.

关键词： Performance modeling Data modeling Mathematical optimization Image processing Feature extraction Image enhancement Image fusion Internet machine learning Semantics

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 << < 1 2 3 4 5 6 7 8 9 10 > >>

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：