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

30,125 篇 会议
4,639 篇 期刊文献
236 册 图书

馆藏范围

35,000 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

21,708 篇 工学
- 15,708 篇 计算机科学与技术...
- 13,221 篇 软件工程
- 5,803 篇 信息与通信工程
- 3,413 篇 控制科学与工程
- 2,672 篇 电子科学与技术（可...
- 2,616 篇 电气工程
- 2,351 篇 生物工程
- 1,887 篇 生物医学工程（可授...
- 1,528 篇 光学工程
- 1,339 篇 机械工程
- 1,214 篇 动力工程及工程热...
- 1,200 篇 仪器科学与技术
- 1,017 篇 化学工程与技术
- 850 篇 安全科学与工程
- 718 篇 交通运输工程
11,131 篇 理学
- 6,029 篇 数学
- 3,039 篇 物理学
- 2,567 篇 生物学
- 1,987 篇 统计学（可授理学、...
- 1,337 篇 系统科学
- 1,088 篇 化学
5,602 篇 管理学
- 3,272 篇 管理科学与工程(可...
- 2,608 篇 图书情报与档案管...
- 1,819 篇 工商管理
1,590 篇 医学
- 1,379 篇 临床医学
- 1,292 篇 基础医学(可授医学...
- 852 篇 药学(可授医学、理...
- 671 篇 公共卫生与预防医...
1,024 篇 法学
- 820 篇 社会学
643 篇 经济学
- 643 篇 应用经济学
487 篇 农学
430 篇 教育学
157 篇 文学
77 篇 军事学
39 篇 艺术学
1 篇 哲学

主题

1,046 篇 accuracy
852 篇 feature extracti...
815 篇 computational mo...
699 篇 deep learning
678 篇 computer science
668 篇 training
509 篇 support vector m...
501 篇 real-time system...
494 篇 machine learning
433 篇 predictive model...
419 篇 internet of thin...
350 篇 computer archite...
347 篇 convolutional ne...
342 篇 data models
320 篇 reliability
303 篇 optimization
287 篇 data mining
281 篇 routing
263 篇 wireless sensor ...
253 篇 conferences

机构

83 篇 institut univers...
82 篇 north-west unive...
81 篇 national centre ...
79 篇 infn sezione di ...
77 篇 institute of inf...
76 篇 infn sezione di ...
76 篇 tno technical sc...
67 篇 université de st...
66 篇 università di ca...
66 篇 dept. of informa...
64 篇 nikhef national ...
59 篇 dept. of compute...
58 篇 dept. of informa...
56 篇 dept. of compute...
53 篇 leiden universit...
52 篇 school of automa...
51 篇 dept. of compute...
49 篇 dept. of compute...
45 篇 dept. of electri...
45 篇 university würzb...

作者

85 篇 ferrara g.
85 篇 ardid m.
85 篇 gal t.
85 篇 bozza c.
84 篇 calvo d.
82 篇 kalekin o.
81 篇 chen a.
80 篇 díaz a.f.
80 篇 boumaaza j.
78 篇 coleiro a.
77 篇 gozzini s.r.
70 篇 huang f.
70 篇 dallier r.
61 篇 anguita m.
52 篇 kulikovskiy v.
44 篇 del burgo r.
41 篇 benoit d.m.
41 篇 eddymaoui a.
40 篇 gagliardini s.
40 篇 labalme m.

语言

33,762 篇 英文
827 篇 其他
310 篇 中文
54 篇 日文
45 篇 朝鲜文
2 篇 德文
1 篇 法文
1 篇 葡萄牙文
1 篇 斯洛文尼亚文

检索条件"机构=Computer Applications in Science and Engineering dept."

共 35000 条记录，以下是131-140 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：

Fine-Tuning of Large Language Models for Solving DSA Problems Using QLoRA

Fine-Tuning of Large Language Models for Solving DSA Problem...

引用

2025 International Conference on Computing for Sustainability and Intelligent Future, COMP-SIF 2025

作者： Pavan Kalyan, S. Arun Kumar, B.R. Satish Kumar, T. Prem Raj, S. Patil, Pratik B. Harshini, Pothireddy Bms Institute of Technology and Management Dept. Computer Science and Engineering Karnataka Bangalore5600119 India

ISBN: (纸本)9798331538538

Fine-tuning large language models (LLMs) for domain specific tasks is often an expensive resource intensive procedure requiring large computing and memory resources. In this paper, We introduce finetuned-leetcode-CodeLlama-7b, a version of CodeLlama that was fine tuned for solving LeetCode problems, specifically. Using QLoRA (Quantized Low Rank Adaptation) techniques, we show that smaller models achieve high performance when solving Data Structure and Algorithm (DSA) problems, providing a cost effective alternative to larger models. The proposed incremental approach reduces memory and computational needs, keeping high accuracy while providing advanced problem-solving in resource constrained environments. © 2025 IEEE.

关键词： Digital differential analyzers

来源：评论

学校读者我要写书评

暂无评论

Predicting Customer Purchase Intent Using Logistic Regression: A Data-Driven Approach 2

Predicting Customer Purchase Intent Using Logistic Regressio...

引用

2nd International Conference on Machine Learning and Autonomous Systems, ICMLAS 2025

作者： Rajarajachozhan, C. Karthika, G. Rajakrishnammal, A. Mano, M. Kumar, P. Nithish Jayahari, E. Saveetha Engineering College Dept. of Electronics and Communication Engineering Tamil Nadu Chennai India Saveetha Engineering College Dept. of Artificial Intelligence and Data Science Tamil Nadu Chennai India Saveetha Engineering College Dept. of Computer Science and Engineering Tamil Nadu Chennai India

ISBN: (纸本)9798331505745

Predicting customer purchase intent is crucial for modern businesses in order to improve engagement, refine marketing strategies, and increase revenue. Conventional rule-based systems encounter difficulties with dynamic and extensive customer data, limiting their flexibility and precision. This project employs a machine learning methodology utilizing logistic regression to forecast customer intent based on demographic, transactional, and behavioral data. The proposed model analyses input features including age, browsing history, and previous purchases, employing sophisticated data preprocessing methods such as One-Hot Encoding and feature scaling to guarantee data integrity. Through hyperparameter tuning and the assessment of critical metrics including accuracy, precision, recall, and Fl-score, the system provides dependable and actionable insights. Real-time predictive capabilities enable businesses to customize customer interactions, facilitating targeted marketing and enhancing customer experience. This project underscores the capacity of predictive analytics to tackle real-world issues, facilitating data-driven decision-making and sustainable business development. © 2025 IEEE.

关键词： Logistic regression

来源：评论

学校读者我要写书评

暂无评论

Understanding the Student Confidence in Viva Responses Through Audio Analysis 3

Understanding the Student Confidence in Viva Responses Throu...

引用

3rd International Conference on Integrated Circuits and Communication Systems, ICICACS 2025

作者： Reddy, Kunuthuru Navya Keerthi, Medikonda Sree, R. Nithya Pati, Peeta Basa Amrita School of Computing Amrita Vishwa Vidyapeetham Dept. of Computer Science and Engineering Bengaluru India

ISBN: (纸本)9798331508456

Assessment of student responses during viva examinations presents challenges in terms of consistency, objectivity, and efficiency. Traditional methods rely on manual evaluation, which can be lengthy and prone to human bias. To address this, machine learning techniques are applied to automatically evaluate student confidence levels based on their oral responses. Student answers are transformed into numerical features using word embeddings such as TF-IDF, RoBERTa, BERT, GloVe, T5, GPT-2, FastText, and SBERT. A variety of machine learning classifiers, including MLP, AdaBoost, and Logistic Regression, were used to classify answers into confidence levels: weak, moderate, and strong. Among these, MLP with GloVe embedding models yielded the best results, achieving a test accuracy of 76%, an F1-score of 76%, and minimal overfitting with a training-test performance gap of 4%. These results demonstrate the strong potential of ML-based systems in improving automated grading and ensuring reliability and scalability in evaluating student responses. © 2025 IEEE.

关键词： Semi-supervised learning

来源：评论

学校读者我要写书评

暂无评论

Unmasking the Reality: A Comprehensive Study of Deepfake Identification Techniques and Their Expanding Terrain 2

Unmasking the Reality: A Comprehensive Study of Deepfake Ide...

引用

2nd International Conference on Computational Intelligence, Communication Technology and Networking, CICTN 2025

作者： Sharma, Shubh Pathak, Disha Mohini Jain, Dhyanendra Srivastava, Somya Vats, Prashant Upadhyay, Govind Murari Department of Computer Science ABES Engineering College U.P. Ghaziabad India Department of Computer Science Engineering-AIML ABES Engineering College U.P. Ghaziabad India Dept. of CSE School of CSE Manipal University Jaipur Rajasthan Jaipur India Dept. of Computer Application Manipal University Jaipur Rajasthan Jaipur India

ISBN: (纸本)9798331530389

The swift progression of deepfake-generating technologies has elicited much apprehension about their potential misuse in digital media, necessitating the development of efficient detection methods. This research aims to improve the precision of deepfake detection by the application of spatial-temporal feature engineering methods. A comparative comparison of advanced preprocessing techniques is performed to enhance the extraction of spatial and temporal indicators essential for detecting deepfake abnormalities. The study investigates the amalgamation of sophisticated machine learning and deep learning models with designed characteristics to get enhanced detection efficacy. Experimental assessments are conducted on benchmark datasets to verify the effectiveness of the suggested methodologies. The findings highlight the importance of effective preprocessing strategies in enhancing model generalizability and dependability, hence supporting the overarching goal of preserving digital authenticity. © 2025 IEEE.

关键词： Contrastive Learning

来源：评论

学校读者我要写书评

暂无评论

An Analysis of Various Classification Algorithms for Fake News Detection 2

An Analysis of Various Classification Algorithms for Fake Ne...

引用

2nd International Conference on Computational Intelligence, Communication Technology and Networking, CICTN 2025

作者： Khare, Sakshi Singh, Pushpa Kumar, Pankaj Dept. of Computer Science and Engineering G. L. Bajaj Institute of Technology & Management Greater Noida India

ISBN: (纸本)9798331530389

With the expansion of social media and advanced stages, the spread of fake news has ended up a noteworthy societal issue. This paper presents a comprehensive outline of machine learning strategies utilized for the detection of fake news. We talk about different approaches such as Natural Language Processing (NLP), unsupervised learning calculations, and machine learning models utilized within the recognizable proof of fake news. We dive into highlight designing, opinion investigation, and organize examination as key components of fake news detection frameworks. Moreover, we look at datasets, assessment measurements, and challenges related with detection of fake news. Through this analysis, we point to supply bits of knowledge into the current state-of-the-art techniques and headings for future investigate in combating fake news dispersal. This paper mainly used K-Nearest Neighbor, Jaccard similarity, LSTM, Decision Tree, and Logistic regression Classifiers for the classification. Main objective of this paper to verify the accuracy of models by performing the pre-processing the data and handle the unbalanced data more appropriately. The results of this papers show comparison of all classifiers with accuracy. Our results shows that KNN achieves 83%, 84% for Logistic Regression, 84% for Decision Tree, 85% for Jaccard Similarity & Random Forest is 85% and 98% for LSTM in our experiment. © 2025 IEEE.

关键词： Adversarial machine learning

来源：评论

学校读者我要写书评

暂无评论

Deep Learning-Based Spectrum Sharing for Dynamic Resource Allocation in 6G Cognitive Radio Networks 4

Deep Learning-Based Spectrum Sharing for Dynamic Resource Al...

引用

4th International Conference on Power, Control and Computing Technologies, ICPC2T 2025

作者： Upadhyay, Deepak Upadhyay, Abhay Venu, Nookala Kukreti, Kamlesh Dept. of Computer Science and Engineering Graphic Era Hill University Dehradun India Dept. of Computer Science and Engineering Graphic Era Deemed to Be University Dehradun India Centre for Internet of Things Madhav Institute of Technology & Science Deemed University Gwalior India Dept. of Electronics and Communication Engineering Graphic Era Deemed to be University Dehradun India

ISBN: (纸本)9798331530402

We conduct an extensive study on deep learning-based spectrum sharing to resolve dynamic resource allocation in 6G cognitive radio networks in this paper. The approach uses modern machine learning models to optimize spectrum usage, increase prediction accuracy of spectrum availability, and reduce interference among the primary and secondary users. We need to evaluate the performance of deep learning algorithms against the traditional spectrum allocation methods in simulation. In the paper, regular quality of service metrics such as throughput distribution and fairness among users are demonstrated to be much improved with these results, where both latency and energy consumption have been cut down dramatically. This work demonstrates the paradigm-shifting role of deep learning in spectrum management for 6G networks, pointing towards intelligent and effective resource allocation mechanisms in tomorrow's communications. © 2025 IEEE.

关键词： Cognitive radio

来源：评论

学校读者我要写书评

暂无评论

Image-Driven Face Presentation Attack Detection in Biometric Systems

Image-Driven Face Presentation Attack Detection in Biometric...

引用

2025 International Conference on Emerging Technologies for Intelligent Systems, ETIS 2025

作者： Vijayan, Rini Salim, A. College of Engineering Trivandrum Affliated to Apj Abdul Kalam Technological University Dept. of Computer Science and Engineering Kerala India

ISBN: (纸本)9798331507541

As biometric systems become increasingly relied on secure authentication, concerns about their susceptibility to Face Presentation Attacks (FPAs) have intensified. This paper introduces a framework for detection of image-driven FPAs in biometric systems, focusing on enhancing the security of face recognition technologies. We propose a methodology that integrates Histogram of Oriented Gradients (HOG) with deep learning techniques. This approach utilizes pretrained models and custom layers to effectively differentiate between legitimate user images and various forms of presentation attacks, including those generated by GANs, morphing techniques, and photoshop manipulations. Through extensive experimentation, we analyzed the performance of each model, offering detailed comparisons concerning accuracy, precision, and F1 score across various categories as well as overall performance of each model. Our findings imply that fusion of HOG with a fine-tuned VGG16 model can achieve significantly higher overall accuracy. © 2025 IEEE.

关键词： Face recognition

来源：评论

学校读者我要写书评

暂无评论

2D Numerical Modeling of Pavements on Expansive Soil in Extreme Climates

2D Numerical Modeling of Pavements on Expansive Soil in Extr...

引用

Geotechnical Frontiers 2025: Geotechnics of Natural Hazards

作者： Agarwal, Ekansh Zhang, Xiong Luo, Ning Dept. of Engineering College of Engineering and Computer Science Texas A&M Univ.–Corpus Christi Corpus ChristiTX United States Dept. of Civil Architectural and Environmental Engineering Missouri Univ. of Science and Technology RollaMO United States

ISBN: (数字)9780784485996

This study focuses on modeling a rigid pavement slab on expansive soil in extreme climates to understand the interaction between weather, pavement, and soil. Lightweight superstructures such as pavements are particularly prone to damage due to the differential settlement of expansive soils. In the context of climate change, the occurrence of severe droughts followed by intense rainfall has risen, causing severe impacts on crack initiation and development, and thus infiltration patterns in the structures built on expansive soils. Pavements are typically designed for a limited lifespan, and early failure may occur if climate change is not considered during design. This is especially important in coastal areas when coastal flooding becomes more frequent. The interplay between climates, soils, and pavements leads to a spatial and temporal change in soil moisture and even soil structure, causing significant variations of volume change. Despite the dominant impact of expansive soils on pavement systems, a deep understanding of their role in pavement structural behavior remains challenging to both the researchers and the practitioners. This paper addresses this gap through a comprehensive numerical study using two-dimensional (2D) finite element modeling. We adopted the unsaturated soil constitutive relationship to understand the stress changes during the expansion and shrinkage of expansive soil. We employed four user-defined subroutines in ABAQUS to perform a coupled hydro-mechanical stress analysis. The study uses historical climate events as a reference to assess the impact of climate events on pavements. Mechanical, hydraulic, and soil-vegetation-atmosphere (SVA) boundary conditions are considered. The numerical findings highlight the vulnerability of pavements founded on expansive soils to climate change-induced events and indicate that a coupled hydro-climate-geotechnical analysis is necessary. Unprecedented climatic events lead to more uneven settling of pavements

关键词： Subroutines

来源：评论

学校读者我要写书评

暂无评论

Advancing Phishing Detection with Random Forest: A Machine Learning Approach for Enhanced Cybersecurity 3

Advancing Phishing Detection with Random Forest: A Machine L...

引用

3rd International Conference on Intelligent Systems, Advanced Computing, and Communication, ISACC 2025

作者： Chandra, Sucheta Das, Priyanka Mandal, Ankita Chakroborty, Sriparno Chowdhury, Ishika Ghosh, Kathamrita University of Engineering & Management Institute of Engineering & Management Dept. of Computer Application and Science Kolkata India

ISBN: (纸本)9798331523893

Phishing attacks remain a critical threat to cybersecurity, leveraging deception to steal sensitive information from individuals and organizations. Traditional detection methods often fail to keep up with evolving phishing tactics, highlighting the need for advanced solutions. This paper investigates the use of the Random Forest algorithm, a powerful machine learning technique, to enhance phishing detection systems. By leveraging the ensemble learning approach of Random Forest, we improve accuracy and efficiency in classifying phishing attempts, while reducing false positives. The methodology includes data preprocessing, feature extraction, and model implementation, showcasing its effectiveness in real-time detection. The study also emphasizes the importance of continuous learning, allowing the model to adapt to new phishing strategies, thereby offering a robust defense against emerging threats. This research contributes to advancing cybersecurity by providing a dynamic, scalable approach to phishing detection. © 2025 IEEE.

关键词： Random forests

来源：评论

学校读者我要写书评

暂无评论

Edge Node Load Balancing Using Game Theoretic Approaches 5

Edge Node Load Balancing Using Game Theoretic Approaches

引用

5th International Conference on Emerging Systems and Intelligent Computing, ESIC 2025

作者： Haldar, Rajdeep Rooj, Saptadip Sharma, Neeraj Das, Ritambhar Mandal, Arnab Bandyopadhyay, Anjan Dept. of Information Technology Bhubaneswar India Lovely Professional University School of Computer Science and Engineering Jalandhar India School of Computer Engineering Bhubaneswar India

ISBN: (纸本)9798331522100

This paper explores the application of game theoretic approaches to load balancing across edge nodes within distributed computing systems. Focusing on a non-cooperative game model, we aim to enhance system efficiency by strategically optimizing resource allocation and load distribution among autonomous edge nodes. Initial simulations demonstrate that our approach not only addresses the inherent complexities of edge environments but also outperforms traditional load balancing mechanisms in terms of both operational efficiency and system responsiveness. © 2025 IEEE.

关键词： Edge computing

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 << < 10 11 12 13 14 15 16 17 18 19 > >>

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：