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

107,183 篇 会议
678 篇 期刊文献
565 册 图书
2 篇 学位论文

馆藏范围

108,427 篇 电子文献
1 种 纸本馆藏

日期分布

学科分类号

60,908 篇 工学
- 49,897 篇 计算机科学与技术...
- 39,812 篇 软件工程
- 13,426 篇 信息与通信工程
- 11,482 篇 生物工程
- 8,512 篇 控制科学与工程
- 6,739 篇 电气工程
- 6,349 篇 生物医学工程（可授...
- 3,866 篇 光学工程
- 3,332 篇 机械工程
- 2,984 篇 电子科学与技术（可...
- 2,763 篇 网络空间安全
- 2,719 篇 安全科学与工程
- 2,516 篇 动力工程及工程热...
- 2,319 篇 化学工程与技术
- 2,188 篇 仪器科学与技术
25,996 篇 理学
- 12,113 篇 生物学
- 12,065 篇 数学
- 5,172 篇 物理学
- 4,919 篇 统计学（可授理学、...
- 3,515 篇 系统科学
- 2,330 篇 化学
17,450 篇 管理学
- 11,016 篇 管理科学与工程(可...
- 7,614 篇 图书情报与档案管...
- 5,174 篇 工商管理
13,621 篇 教育学
- 13,420 篇 教育学
6,408 篇 医学
- 5,469 篇 临床医学
- 5,220 篇 基础医学(可授医学...
- 3,406 篇 药学(可授医学、理...
- 2,887 篇 公共卫生与预防医...
3,377 篇 法学
- 2,923 篇 社会学
1,965 篇 文学
1,766 篇 农学
1,661 篇 经济学
267 篇 艺术学
106 篇 军事学
11 篇 历史学
10 篇 哲学

主题

7,214 篇 machine learning
7,071 篇 deep learning
5,537 篇 accuracy
5,104 篇 training
4,929 篇 computational mo...
4,222 篇 education
3,838 篇 students
3,623 篇 feature extracti...
3,070 篇 support vector m...
3,068 篇 predictive model...
3,061 篇 machine learning...
3,029 篇 convolutional ne...
2,594 篇 real-time system...
2,397 篇 data models
2,245 篇 neural networks
2,010 篇 cloud computing
1,840 篇 teaching
1,497 篇 reinforcement le...
1,472 篇 artificial intel...
1,412 篇 internet of thin...

机构

826 篇 chitkara univers...
145 篇 lovely professio...
105 篇 computer science...
98 篇 karnataka bangal...
94 篇 college of compu...
89 篇 school of comput...
79 篇 chitkara univers...
76 篇 school of comput...
72 篇 department of co...
70 篇 department of co...
67 篇 department of co...
63 篇 department of co...
58 篇 school of comput...
58 篇 department of co...
52 篇 department of in...
49 篇 chitkara univers...
43 篇 department of me...
42 篇 school of automa...
41 篇 chennai
40 篇 vellore institut...

作者

70 篇 shiva mehta
70 篇 anjali t.
53 篇 li yang
42 篇 sharma vikrant
40 篇 wang lei
40 篇 kukreja vinay
39 篇 rakesh kumar
36 篇 gill kanwarparta...
35 篇 sharma neha
33 篇 wang jing
32 篇 vinay kukreja
31 篇 lei wang
31 篇 zhang lei
30 篇 huang yueh-min
29 篇 yu wang
28 篇 liu bo
27 篇 li xin
26 篇 amandeep nagpal
25 篇 vinay gautam
25 篇 shang wang

语言

91,086 篇 英文
16,987 篇 其他
949 篇 中文
23 篇 西班牙文
12 篇 葡萄牙文
5 篇 阿拉伯文
3 篇 法文
3 篇 土耳其文
2 篇 俄文
1 篇 捷克文

检索条件"任意字段=International Conference on Teaching and Learning in Computing and Engineering"

共 108428 条记录，以下是4171-4180 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：

Android Malware Categorization and Characterization Using Machine learning

Android Malware Categorization and Characterization Using Ma...

引用

2024 international conference on Advances in computing, Communication, Electrical, and Smart Systems, iCACCESS 2024

作者： Nabi, Nurun Khan, Mozammel H. A. East West University Department of Computer Science and Engineering Dhaka Bangladesh

ISBN: (纸本)9798350350289

Among all the current mobile operating systems, Android has the most market share with more than three billion active users. As android is open-source, it possesses many challenges of malicious cyberattacks. Most of the android applications are now online or somehow connected to internet and for this availability of connectivity with internet, hackers can push malware into the system easily without any concern of the user, although the application was safe and secure while installing for the first time. As a result, it is becoming difficult to identify their behavior and categorize to implement protection inside android operating system. In this research, we proposed a system to categorize and characterize various types of malware based on their network traffic pattern using K-means and Decision Tree algorithm, and also proposed a diagram demonstrating how android developers can implement this system in android OS. © 2024 IEEE.

关键词： Machine learning

来源：评论

学校读者我要写书评

暂无评论

A Novel Approach for Retinal Vessel Extraction Using Multi-Scale Deep learning and Morphological Techniques

A Novel Approach for Retinal Vessel Extraction Using Multi-S...

引用

2024 international conference on computing and Intelligent Reality Technologies, ICCIRT 2024

作者： Kavya, G.S. Kumarganesh, S. Department of BME Paavai College of Engineering Tamil Nadu Namakal India Department of ECE Knowledge Institute of Technology Tamil Nadu Salem India

ISBN: (数字)9798331510299

ISBN: (纸本)9798331510299

Retinal vessel extraction is pivotal in diagnosing and managing various ophthalmic and systemic diseases. This study introduces a novel approach that combines multi-scale deep learning with advanced morphological techniques to achieve accurate and efficient retinal vessel extraction. Our multi-scale convolutional neural network (CNN) captures both global and local vessel structures, while morphological operations refine the segmentation. Evaluations on publicly available datasets, including DRIVE and STARE, show that our method outperforms existing techniques with a vessel segmentation accuracy of 95.8%, sensitivity of 88.4%, specificity of 97.2%, and a Dice coefficient of 92.1%. The proposed approach demonstrates significant potential for clinical applications in early disease detection and monitoring, promising enhanced performance in retinal imaging tasks. © 2024 IEEE.

关键词： Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

An SGX and Blockchain-Based System for Federated learning in Classifying COVID-19 Images 21

An SGX and Blockchain-Based System for Federated Learning in...

引用

21st IEEE international Symposium on Parallel and Distributed Processing with Applications, 13th IEEE international conference on Big Data and Cloud computing, 16th IEEE international conference on Social computing and Networking and 13th international conference on Sustainable computing and Communications, ISPA/BDCloud/SocialCom/SustainCom 2023

作者： Qin, Sihang Gu, Xianjun Jun, Xing Li, Haitao Huang, Mengqi Dai, Weiqi Huazhong University of Science and Technology Hubei Key Laboratory of Distributed System Security Hubei Engineering Research Center on Big Data Security School of Cyber Science and Engineering Wuhan430074 China State Grid Wuhan Power Supply Company China

ISBN: (纸本)9798350329223

Federated learning, an emerging distributed learning framework, has gained prominence recently. However, two challenges arise when applying federated learning to medical data. The first challenge stems from the inability of model-generating nodes to ensure computational fairness. The second challenge involves the potential leakage of private information through gradient differences. This paper introduces a federated learning system that leverages Software Guard Extensions (SGX) and blockchain technology to enhance the fairness and security of federated learning for analyzing chest imaging data. The modeling of imaging factors for chest radiography data can effectively regulate the data quality of semi-trusted nodes. A blockchain smart contract is employed for data quality-aware proof, and the quality-aware block undergoes a two-stage rewriting process across distinct nodes. A notary membership model achieves notarized cluster consensus for imaging informatics data. The multi-channel layer model quantifies the distribution of computational workload across participating nodes within the medical consortium. Upon successful verification of the enclave command in the aggregation cycle, traceable and packaged signatures are generated to support computational fairness. To ensure robust information security, SGX remote authentication is used between downstream and upstream nodes. The federated learning system, built upon SGX and blockchain, has been implemented using the Fabric federated chain platform. The ResNet model underwent training through cross-sectional federated learning to effectively classify novel coronavirus lung medical image data. Following this, multiple experimental control and security analyses were conducted, revealing that the time loss incurred due to crossing channels is approximately 21.31%, while the time overhead of SGX remains within 5.2%, as allowed by the number of nodes. © 2023 IEEE.

关键词： Blockchain

来源：评论

学校读者我要写书评

暂无评论

Student performance prediction in e-learning system and evaluating effectiveness of online courses

Student performance prediction in e-learning system and eval...

引用

2023 international conference on Advances in Intelligent computing and Applications, AICAPS 2023

作者： Blessy Paul, P. Kurian, Cini Mg University School of Computer Sciences Kerala Kottayam India Al-Ameen College Kerala Edathala India

ISBN: (纸本)9798350333817

In recent years, the number of online courses in India has skyrocketed especially due to the Covid pandemic. The most significant increments have happened in degree colleges, where 85% concur that internet based courses are important for their drawn-out procedure when contrasted with 60% in 2015. The distribution of online courses has evolved dramatically as technology has advanced. Web-based platform provides new challenges for both teachers and students. Teachers should be clear about the effectiveness of online learning in teaching students. For that, the possibilities of online learning should be compared with traditional learning. Students are evaluated based on their focus on online learning. This study aims to determine the efficacy of online courses by predicting student performance in an e-learning system. These research findings evaluate modern learning methods, highlight students' potential and help teachers understand how to assess and lead students on online platforms. © 2023 IEEE.

关键词： Decision trees

来源：评论

学校读者我要写书评

暂无评论

Review of Databases used for Text Based Emotion Detection

Review of Databases used for Text Based Emotion Detection

引用

2024 MIT Art, Design and Technology School of computing international conference, MITADTSoCiCon 2024

作者： Deshmukh, Shrikala Amity University Mumbai India College of Engineering Department of Information Technology Pune India

ISBN: (纸本)9798350362879

Currently most all the information sharing takes place in the form of Text-based input. Diverse information sources, encompassing speech, text, and visual elements, offer opportunities for analyzing emotions. Presently, written content manifests in various formats like micro-blogs, news articles and social media posts. This content proves to be an asset for the practice of text mining, enabling the exploration and revelation of multifaceted aspects, including emotions. People share their emotions about a topic or any subject through text. Emotion recognition falls within the realm of sentiment analysis, focusing on the identification and examination of emotions. This paper is a review of advancements in Text-based emotion detection and state-of-The-Art techniques and methodologies employed in text-based emotion recognition previously used deep learning, and the machine learning approach. © 2024 IEEE.

关键词： Emotion Recognition

来源：评论

学校读者我要写书评

暂无评论

DDPG Algorithm with Elastic Replay Buffer Assisting in the Optimization of the NOMA System 5

DDPG Algorithm with Elastic Replay Buffer Assisting in the O...

引用

5th international conference on Intelligent computing and Human-Computer Interaction, ICHCI 2024

作者： Zheng, Wenjing Wang, Jinghan Fu, Wenwen Li, Jun Lin, Fei Zheng, Xuehan Gao, He Jinan China School of Information and Electrical Engineering Shandong Jianzhu University Jinan China Shandong Zhengchen Technology Co. LTD Jinan China

ISBN: (纸本)9798350368284

Non-orthogonal multiple access networks inspired by cognitive radio technology can enhance energy efficiency and address the issue of spectrum resource scarcity. However, resource allocation strategies are still needed for optimization. This paper applies deep reinforcement learning (DRL) algorithms to optimize transmission strategies. We propose a DDPG algorithm integrated with elastic experience replay, which helps the agent strike a better balance between exploring new strategies and utilizing existing experiences. Simulation results demonstrate that the proposed algorithm achieves a higher transmission rate compared to the standard DDPG algorithm, random algorithm and greedy algorithm. © 2024 IEEE.

关键词： Deep reinforcement learning

来源：评论

学校读者我要写书评

暂无评论

Evaluating Teachers' Performance through Aspect-Based Sentiment Analysis 9

Evaluating Teachers' Performance through Aspect-Based Sentim...

引用

9th IEEE international conference for Convergence in Technology, I2CT 2024

作者： Bhowmik, Abhijit Noor, Noorhuzaimi Mohd Mazid-Ul-Haque, Md. Miah, Md Saef Ullah Karmaker, Debajyoti Universiti Malaysia Pahang Al-Sultan Abdullah Faculty of Computing Pekan Malaysia American International Univeristy-Bangladesh Department of Computer Science Dhaka Bangladesh

ISBN: (纸本)9798350394474

This research demonstrates a novel approach for evaluating teacher performance by conducting aspect-based sentiment analysis (ABSA) on student feedback. A large dataset of over 2 million student comments about teachers is analyzed using cutting-edge natural language processing and customized deep learning techniques. The methodology involves identifying positive, negative and neutral aspects of teaching using a BiLSTM model. Rigorous preprocessing, domain adaptation, and performance metrics ensure a robust and objective evaluation. The granular, nuanced insights obtained through this aspect-level sentiment analysis enable educational institutions to provide targeted and unbiased feedback to teachers on their strengths and areas needing improvement. Moreover, this work lays the foundation for detecting potentially fraudulent reviews in academic settings - a crucial capability for safeguarding assessment integrity. The detailed aspect-based analysis methodology presented here significantly advances subjective and holistic evaluation practices. This research has far-reaching implications for enriching teacher development while upholding the credibility of performance assessments through sentiment analysis innovations. © 2024 IEEE.

关键词： Sentiment analysis

来源：评论

学校读者我要写书评

暂无评论

Construction and Application of Digital College English teaching Resources on the Basis of Data Mining 3rd

Construction and Application of Digital College English Teac...

引用

3rd EAI international conference on Application of Big Data, Blockchain, and Internet of Things for Education Informatization, BigIoT-EDU 2023

作者： Yang, Xiaomin Guilin University School of Language and Literature Guangxi541002 China

ISBN: (纸本)9783031631290

The arrival of the digital era has brought many challenges and changes to traditional teaching models, teaching methods, and teaching resources in higher education. Among them, the construction and application of digital educational resources has also become an important trend in the future development of higher education. This article mainly introduces the construction and application of digital college English teaching resources based on data mining. In terms of the construction of teaching resources, this paper uses the method based on data mining technology to analyze and process a large number of student learning data and teacher teaching data within a certain period of time, mine the patterns and rules of student learning, and establish knowledge expressions, Knowledge graph and curriculum knowledge trees related to the curriculum;In terms of application, online teaching platforms are used to provide students with rich and diverse digital teaching resources, allowing them to achieve targeted learning through various social learning methods such as independent learning, autonomous dialogue, and group discussions. Practice has proven that digital college English teaching resources based on data mining can better serve the teaching practice of higher education. On the one hand, this teaching resource makes students’ learning more targeted and personalized, which is not only conducive to interaction between teachers and students, but also helps to improve students’ English learning efficiency;On the other hand, this teaching resource can provide data support and reference for teachers’ teaching practice, so as to better grasp students’ learning situation and teaching progress, and achieve optimization and improvement of the teaching process. In summary, the digital college English teaching resources proposed in this article based on data mining are a feasible and effective teaching model teaching. Based on this model, we can continuously optimize teaching content,

关键词： Students

来源：评论

学校读者我要写书评

暂无评论

Exploiting Bytecode Analysis for Reentrancy Vulnerability Detection in Ethereum Smart Contracts

Exploiting Bytecode Analysis for Reentrancy Vulnerability De...

引用

2023 IEEE international conference on Dependable, Autonomic and Secure computing, 2023 international conference on Pervasive Intelligence and computing, 2023 international conference on Cloud and Big Data computing, 2023 international conference on Cyber Science and Technology Congress, DASC/PiCom/CBDCom/CyberSciTech 2023

作者： Tahir, Usman Siyal, Fiza Ianni, Michele Guzzo, Antonella Fortino, Giancarlo University of Camerino Italy Modeling Electronics and Systems University of Calabria Department of Computer Engineering Italy

ISBN: (纸本)9798350304602

Reentrancy is a type of attack that can occur in smart contracts, enabling untrusted external code execution within the contract. This method exploits a vulnerability that allows an attacker to repeatedly invoke a function in the contract, resulting in an infinite loop and potentially leading to fund theft. Therefore, the reentrancy attack represents a critical concern in blockchain security, prompting the development of various methods for analyzing and detecting reentrancy vulnerabilities over the last decade. Among these methods, the most recent ones leverage the advantages of AI and deep learning techniques. Nonetheless, several limitations persist in existing approaches. Many current methods rely on complex code analysis rules, resulting in a high number of false positives and false negatives. Additionally, the feature engineering process involving word embedding techniques can lead to the loss of critical information. Lastly, the majority of proposed methods necessitate access to the actual source code of the smart contracts for analysis. In this study, we introduce a straightforward and lightweight approach to address these limitations in reentrancy detection. Our approach employs an image-based detection method utilizing deep learning. The pipeline of our method involves disassembling the smart contracts into opcodes and transforming them into RGB images. These images are then used to train a VGG16 CNN model to detect similarities between images labeled as either 'Vulnerable' or 'Not Vulnerable'. To address class imbalance, we implement image augmentation techniques to expand the training dataset. Experimental results conducted on a publicly available dataset demonstrate that our model achieves a significantly high accuracy rate of 99.07%. © 2023 IEEE.

关键词： Smart contract

来源：评论

学校读者我要写书评

暂无评论

A Proactive Method Using Machine learning Models to Detect Phishing Attacks in Thread Sharing Network 10

A Proactive Method Using Machine Learning Models to Detect P...

引用

10th international conference on Advanced computing and Communication Systems, ICACCS 2024

作者： Ajay Kumar, K.V. Deepalakshmi, R. Balasubramaniyamoorthy, P.S. Murugan, K.R. Senthil Velammal College of Engineering and Technology Department of Computer Science and Engineering Tamil Nadu Madurai India

ISBN: (纸本)9798350384369

Phishing attacks present an enduring and pervasive threat in the digital realm, with cybercriminals continuously devising innovative techniques to deceive users and compromise sensitive information. This paper focuses on the crucial task of detecting phishing using advanced machine learning techniques. Recognized as a critical challenge in the digital landscape, phishing detection is imperative due to its potential to undermine trust, compromise security, and inflict financial and reputational damage. The paper employs feature extraction from diverse datasets as a pivotal step in the process, ensuring that relevant attributes are identified and utilized effectively. Moreover, it highlights the system's capability for real-time interpretation of websites, enhancing its responsiveness and efficacy in detecting phishing attempts promptly. The approach integrates machine learning models to enhance accuracy and robustness, achieving a notable accuracy of 97.5% through the utilization of the Gradient Boosting algorithm. This paper contributes to ongoing cybersecurity efforts by offering a multifaceted approach to phishing detection, leveraging the capabilities of machine learning. The findings underscore the importance of continuous research in adapting to evolving phishing tactics and improving the overall security posture of digital environments. Moving forward, the integration of real-time interpretation and adaptive machine learning models promises to further strengthen cybersecurity measures, ensuring a safer digital environment for users worldwide. © 2024 IEEE.

关键词： Phishing

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 << < 414 415 416 417 418 419 420 421 422 423 > >>

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：