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

34,825 篇 会议
5,749 篇 期刊文献
296 册 图书

馆藏范围

40,870 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

25,549 篇 工学
- 17,910 篇 计算机科学与技术...
- 15,005 篇 软件工程
- 6,564 篇 信息与通信工程
- 4,222 篇 控制科学与工程
- 3,253 篇 电子科学与技术（可...
- 3,205 篇 电气工程
- 2,620 篇 生物工程
- 2,155 篇 生物医学工程（可授...
- 1,793 篇 光学工程
- 1,689 篇 机械工程
- 1,448 篇 动力工程及工程热...
- 1,421 篇 仪器科学与技术
- 1,253 篇 化学工程与技术
- 954 篇 安全科学与工程
- 850 篇 交通运输工程
- 781 篇 建筑学
13,171 篇 理学
- 7,160 篇 数学
- 3,666 篇 物理学
- 2,884 篇 生物学
- 2,315 篇 统计学（可授理学、...
- 1,598 篇 系统科学
- 1,294 篇 化学
6,464 篇 管理学
- 3,838 篇 管理科学与工程(可...
- 2,940 篇 图书情报与档案管...
- 2,180 篇 工商管理
1,792 篇 医学
- 1,541 篇 临床医学
- 1,438 篇 基础医学(可授医学...
- 942 篇 药学(可授医学、理...
1,175 篇 法学
- 965 篇 社会学
778 篇 经济学
- 777 篇 应用经济学
556 篇 农学
547 篇 教育学
169 篇 文学
93 篇 军事学
46 篇 艺术学
3 篇 哲学
2 篇 历史学

主题

1,173 篇 accuracy
917 篇 computational mo...
886 篇 feature extracti...
745 篇 training
735 篇 deep learning
734 篇 computer science
579 篇 machine learning
549 篇 real-time system...
534 篇 support vector m...
516 篇 predictive model...
441 篇 internet of thin...
413 篇 data models
379 篇 convolutional ne...
371 篇 optimization
354 篇 reliability
353 篇 computer archite...
316 篇 data mining
315 篇 artificial intel...
299 篇 routing
296 篇 visualization

机构

83 篇 institut univers...
82 篇 north-west unive...
81 篇 national centre ...
79 篇 infn sezione di ...
76 篇 infn sezione di ...
76 篇 institute of inf...
67 篇 tno technical sc...
66 篇 università di ca...
59 篇 université de st...
58 篇 dept. of informa...
56 篇 dept. of compute...
53 篇 leiden universit...
52 篇 school of automa...
46 篇 dept. of compute...
44 篇 dept. of compute...
44 篇 dept. of electri...
44 篇 nikhef national ...
44 篇 dept. of compute...
42 篇 infn lnf via enr...
42 篇 in2p3 lpc campus...

作者

85 篇 ferrara g.
85 篇 ardid m.
85 篇 gal t.
85 篇 bozza c.
84 篇 calvo d.
81 篇 chen a.
78 篇 kalekin o.
78 篇 díaz a.f.
75 篇 boumaaza j.
72 篇 coleiro a.
67 篇 huang f.
64 篇 gozzini s.r.
52 篇 kulikovskiy v.
50 篇 dallier r.
42 篇 anguita m.
41 篇 benoit d.m.
41 篇 eddymaoui a.
41 篇 del burgo r.
40 篇 gagliardini s.
40 篇 labalme m.

语言

38,671 篇 英文
1,663 篇 其他
370 篇 中文
116 篇 日文
47 篇 朝鲜文
5 篇 德文
3 篇 法文
2 篇 斯洛文尼亚文
1 篇 葡萄牙文
1 篇 俄文
1 篇 土耳其文

检索条件"机构=Dept. of Computer Engineering and Systems Science"

共 40870 条记录，以下是801-810 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：

Microstrip Patch Antenna for Single Resonant Frequency Using Various Types of Slots

Microstrip Patch Antenna for Single Resonant Frequency Using...

引用

2023 International Conference on Electrical, computer, Communications and Mechatronics engineering, ICECCME 2023

作者： Islam, Md Amirul Stea, Giovanni Uddin, Md Ashraf Mahmud, Sultan Rahma, Kh. Mustafizur University of Pisa Dept. of Information Engineering Pisa Italy Jagannath University Dept. of Computer Science & Engineering Dhaka Bangladesh World University of Bangladesh Dept. of Computer Science & Engineering Dhaka Bangladesh

ISBN: (纸本)9798350322972

Microstrip patch antennas are widely utilized in WLAN applications, and body-centric wireless communication relies on multiple network links to get messages through. But the existing antenna size is big with less bandwidth, which increases the cost. This paper has taken a rigorous approach to design an antenna that will provide a single resonant frequency at the targeted bandwidth (2.45GHz). The patch size in the proposed antenna is 28mm by 27mm and energized by a 50 ohm microstrip feed line with dimensions 3.137mm by 18.35mm. The dielectric substrate of permittivity Er = 4.3 is used in the fabrication process. The optimal size and other antenna characteristics are found by finite difference time domain method based CST Studio Suite. Other parameters like return loss, input impedance, and bandwidth of the microstrip patch antennas are calculated using VNA and WATS software to verify the proposed work. Finally, the proposed slot-loaded antenna attains an improved bandwidth and gain while providing a single resonant frequency. © 2023 IEEE.

关键词： Bandwidth

来源：评论

学校读者我要写书评

暂无评论

Electricity Generation From Food Waste Using IOT 3

Electricity Generation From Food Waste Using IOT

引用

3rd International Conference on Artificial Intelligence For Internet of Things, AIIoT 2024

作者： Arunkumar, M. Agalya, S. Bhuvanaeshwari, M. IFET College of Engineering Dept. of Information Technology Villupuram India Surya Group of Institutions Dept. of Computer Science and Engineering Villupuram India

ISBN: (纸本)9798350372120

One inventive solution is to turn food waste into power using the Internet of Things (IoT) to meet the growing need for sustainable energy sources. It turns thermal energy from trash into electricity by utilizing thermoelectric devices and the Seebeck effect. Real-time monitoring and control are made possible with IoT integration. By improving the extraction of energy from liquid or semi-solid waste, this technique reduces waste and promotes a circular energy economy. The system makes use of hardware components such as transformers and voltage regulators. The outcomes of experiments demonstrate its efficacy and possible role in renewable energy. This creative idea, which provides a sustainable route ahead for the production of power from food waste, highlights the importance of IoT in improving waste-to-energy systems. © 2024 IEEE.

关键词： Internet of things

来源：评论

学校读者我要写书评

暂无评论

Detecting adversarial examples using constraint-based learning

Detecting adversarial examples using constraint-based learni...

引用

2024 International Conference on Smart Devices, ICSD 2024

作者： Kumar, Vivek Kumar, Kamal Singh, Maheep National Institute of Technology Dept. of Computer Science -and Engineering Uttarakhand Pauri India IGDTUW Department of Information Technology New Delhi India Doon University Dept. of Computer Science and Engineering Dehradun India

ISBN: (纸本)9798350394412

Deep learning models have been applied in various fields and continue producing exceptional results. However, these models are vulnerable to adversarial attacks, which are modified data samples maliciously crafted to cause misclassification by a target model. Fields like Network intrusion detection systems (NIDS) are security-critical;therefore, adversarial attacks pose a high risk in such applications. The attacker not only aims for evasion but also tries to launch an attack once the adversarial example has evaded detection by a NIDS. This paper presents a novel technique for detecting adversarial examples targeted towards a NIDS by learning the dependencies between features known as domain constraints. Our proposed method detects adversarial examples that violate these constraints learned during training. Compared with prevalent detection techniques, our method does not require generating adversarial examples for training, which reduces its computational requirement. We assume a grey-box threat model where the attacker can access the training data. We perform experiments on the CICIDS2017 dataset against five state-of-the-art adversarial attacks: FGSM, BIM, PGD, Deep fool and BIM. The results show that our method can detect up to 100% adversarial attacks, outperforming the contemporary schemes. © 2024 IEEE.

关键词： Adversarial machine learning

来源：评论

学校读者我要写书评

暂无评论

Supervised Learning Approaches for Vibration Analysis and Anomaly Detection in Rotating Machines 3

Supervised Learning Approaches for Vibration Analysis and An...

引用

3rd International Conference on Emerging Trends in Electrical, Control, and Telecommunication engineering, ETECTE 2024

作者： Ali, Syed Zulfiqar Ali, Syed Hasnat Javeed, Anees Ullah, Ihsan Memon, Sufyan Ali Manzoor, Sajjad Dept. of Electrical and Computer Engineering CUI Abbottabad Campus Abbottabad Pakistan Dept. of Defence Systems Engineering Sejong University Seoul Korea Republic of Dept. of Electrical Engineering MUST AJK Mirpur Pakistan

ISBN: (纸本)9798331504861

Safety and reliability are crucial for modern systems and technologies. This paper presents an approach for real-time anomaly detection in rotating machines using vibration analysis and machine learning algorithms for predictive maintenance. Rotating machines such as motors, engines, gearboxes and turbines are widely used systems and faults in these systems can result in complete shutdowns. Preventing unexpected downtime while ensuring equipment reliability and safety is essential. In this context, anomaly detection plays a vital role in monitoring the healthy operation of rotating machines. A test-bed was designed to generate datasets for both balanced (healthy) and unbalanced (faulty) motor conditions. The experimental setup consists of a three-phase induction motor, a signal acquisition system (Raspberry Pi), a vibration sensor (MPU6050) and a coupling system capable of adjusting motor balance. Supervised machine learning algorithms, Support Vector Machine (SVM) and Random Forest (RF) were applied to classify and detect anomalies in the collected datasets. A grid search algorithm was employed for hyperparameter tuning of the SVM and RF models. The proposed technique achieved a maximum accuracy of approximately 98% using SVM and 100% using the RF algorithm leveraging nine optimally selected temporal features. ©2024 IEEE.

关键词： Rotating machinery

来源：评论

学校读者我要写书评

暂无评论

An ensemble learning-based machine learning with voting mechanism for chronic disease prediction

An ensemble learning-based machine learning with voting mech...

引用

2024 International Conference on Artificial Intelligence, computer, Data sciences, and Applications, ACDSA 2024

作者： Soualihou, Soualihou Ngnamsie Kim, Jeong-Dong Zonyfar, Candra Lee, Hyun Lee, Taek Lee, Jung-Been Sun Moon University Dept. of Computer Science and Electronic Convergence Asan Korea Republic of Sun Moon University Dept. of Computer Science and Engineering Asan Korea Republic of Sun Moon University Division of Computer Science and Engineering Asan Korea Republic of

ISBN: (纸本)9798350394528

Chronic diseases present a significant challenge in healthcare, often requiring ongoing medical attention and posing limitations on patients' daily activities. Diagnosis of such diseases is hindered by the absence of specific symptoms making them hard to detect and or prevent. Addressing this issue, researchers have turned to computational approaches, analyzing patients' medical records to predict the presence or absence of chronic diseases with promising results. However, there is potential for further improvement. This paper introduces an ensemble classifier, ELVot-CroDiP, designed to enhance chronic disease prediction. ELVot-CroDiP harnesses the collective strengths of various machine learning algorithms through a majority voting mechanism, thereby boosting predictive accuracy. The model's performance was evaluated using precision, recall, f1-score, and accuracy across five medical datasets, including heart disease, chronic kidney disease, diabetes, and heart stroke. Comparative analysis shows that ELVot-CroDiP offers superior performance in predicting chronic diseases compared to existing models, as evidenced by its higher scores in the mentioned evaluation metrics for each dataset tested. © 2024 IEEE.

关键词： Forecasting

来源：评论

学校读者我要写书评

暂无评论

Enhanced Rainfall Prediction: Leveraging Ensembling Models for Maximum Forecasting Performance 1

Enhanced Rainfall Prediction: Leveraging Ensembling Models f...

引用

1st International Conference on Advanced Computing and Emerging Technologies, ACET 2024

作者： Dasari, Krishna Kumar Nuthanakanti, Bhaskar Raju, K.Srujan Madhusudhan, Mudimela Nazare, Sanjana S Raji Reddy, Avala Cmr Technical Campus Dept. Computer Science and Engineering Telangana Hyderabad India Cmr Dept. of Mechanical Engineering Telangana Hyderabad India

ISBN: (纸本)9798350367720

Many important fields rely on accurate rainfall predictions, including agriculture, water resource management, and emergency preparation. The many nonlinear interactions included in weather data are notoriously difficult for traditional approaches to grasp. Agriculture, water resource management, and disaster preparation are just a few of the many sectors that might benefit greatly from accurate rainfall predictions. Because meteorological data is both complicated and dynamic, traditional methods often get it wrong. Recent years have seen encouraging results in the use of machine learning (ML) approaches, especially ensemble models, to enhance the precision and consistency of precipitation forecasts. This research provides a new method for predicting precipitation using an ensemble of ML models. The ensemble model EERP algorithm combines the predictions of numerous base learners to create a more reliable and accurate forecast. Decision trees, random forests, gradient boosting machines, neural networks, and other ML approaches serve as the ensemble's base learners. Assess the effectiveness of the proposed approach and then compare it with some existing classifiers in which the proposed classifier gave the best accuracy when compared with the other i.e., 96 %. © 2024 IEEE.

关键词： Prediction models

来源：评论

学校读者我要写书评

暂无评论

Using Machine Learning Algorithms in Edge Intelligence for Ultra-Reliable and Low-Latency Communications in the Industrial Metaverse 29

Using Machine Learning Algorithms in Edge Intelligence for U...

引用

29th International computer Conference, computer Society of Iran, CSICC 2025

作者： Mohammadvand, Reza Mozayani, Naser Dept. Computer Engineering Iran University of Science and Technology Tehran Iran

ISBN: (纸本)9798331523114

Given the rapid advancements in technologies such as the metaverse and digital twins, the need for effective integration of communication, computation, and storage in complex systems and edge computing environments is becoming increasingly apparent. This paper proposes an architecture to support an industrial metaverse based on digital twins that optimizes resources by leveraging mobile edge computing and ultra-reliable low-latency communication. This architecture reduces latency by employing task offloading and storage methods on nearby edge servers, meeting the precise requirements of future metaverses in terms of reliability and latency minimization. The proposed model, utilizing reinforcement learning algorithms such as Deep Q-Network (DQN), Double Deep Q-Network (DDQN), and Dueling Double Deep Q-Network (Dueling DDQN), is capable of achieving adaptability in dynamic conditions and making intelligent decisions. The simulation results demonstrate that the proposed method reduces by more than 10% on average compared to the best method available in the literature and improves resource utilization efficiency. © 2025 IEEE.

关键词： Reinforcement learning

来源：评论

学校读者我要写书评

暂无评论

BanglaGPT: A Generative Pretrained Transformer-Based Model for Bangla Language 2

BanglaGPT: A Generative Pretrained Transformer-Based Model f...

引用

2nd International Conference on Information and Communication Technology for Sustainable Development, ICICT4SD 2023

作者： Salim, Md. Shahidul Murad, Hasan Das, Dola Ahmed, Faisal Khulna University of Engineering Technology Dept. of Computer Science and Engineering Khulna9203 Bangladesh Chattogram University of Engineering Technology Dept. of Computer Science and Engineering Chattogram4349 Bangladesh

ISBN: (纸本)9798350358667

Natural Language Processing (NLP) has entered a new era with the advent of pre-trained language models, paving the way for constructing robust language models. Pretrained transformer-based models such as GPT-2 have become prevalent due to their cutting-edge efficiency. However, these approaches rely heavily on resource-intensive languages, forcing other languages to adopt multilingual frameworks (mGPT). The mGPT model could perform better for low-resource languages such as Bangla because the model has been trained on a diverse dataset spanning multiple languages. Recent studies show that the language-specific GPT model outperforms the multilingual mGPT model. In this research, we have proposed a pretrained monolingual GPT model called BanglaGPT using the objective of causal language modeling (CLM). Due to the lack of available large datasets for NLP tasks in Bangla, we have created a Bangla language model dataset called BanglaCLM using a 26.24 GB Bangla corpus scraped from several public websites. We have used a subword-based tokenization algorithm named Byte-Pair Encoding (BPE) for Bangla and finally trained the Bangla-GPT2 model from scratch using the BanglaCLM dataset. Our pretrained BanglaGPT provides state-of-the-art performance for Bangla text generation with a perplexity score of 2.86 and a loss score of 0.45 on the test set. © 2023 IEEE.

关键词： Large dataset

来源：评论

学校读者我要写书评

暂无评论

Stress Level Analysis Using EEG Signals: A Comparative Study of EEGNET and CNN Deep Learning Models 5

Stress Level Analysis Using EEG Signals: A Comparative Study...

引用

5th IEEE Global Conference for Advancement in Technology, GCAT 2024

作者： Khanaganni, Anulaxmi S. Monisha, H.M. Kumar, R. Ashok Bms College of Engineering Dept Information Science and Engineering Bangalore India Bms College of Engineering Dept Computer Science and Business Systems Bangalore India

ISBN: (纸本)9798350376685

Understanding the brain's response to stress is pivotal for advancing mental health monitoring technologies. In this research paper, we leverage deep learning techniques to predict stress levels using electroencephalography (EEG) data from 10 students. This data captures brain activity during both rest and stress-induced conditions, with the stress induced through a visually demanding Stroop test. We focus on categorizing stress levels into four distinct categories: no stress, low stress, medium stress, and high stress. For analysis, we employ two advanced deep learning models, EEGNet and Convolutional Neural Network (CNN), which have demonstrated significant potential in managing the complexities of EEG data and identifying intricate patterns related to different stress *** methodology in this study includes rigorous data preprocessing, segmentation, and labeling to ensure the reliability and accuracy of the model training process. The EEG data from the 10 students are combined into a single dataset, with 70% allocated for training and 30% for testing. This approach ensures a robust evaluation of the models' predictive capabilities. We systematically compare EEGNet and CNN based on accuracy, precision, recall, and other relevant metrics. Our goal is to determine which model more effectively predicts stress levels and to understand their respective strengths and limitations. This comparative analysis provides valuable insights and paves the way for future applications in real-time stress monitoring. © 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

Embracing the Future: Unveiling the Revolution of Human-AI Interaction in the Digital Education Era 13

Embracing the Future: Unveiling the Revolution of Human-AI I...

引用

13th International Conference on Virtual Campus, JICV 2023

作者： Cotino Arbelo, Andrea E. Gonzalez-Gonzalez, Carina S. Molina Gil, Jezabel M. University of La Laguna Dept. of Computer Engineering and Systems Tenerife Spain

ISBN: (纸本)9798350343441

The recent and emerging introduction of generative AI in all areas of society poses new challenges to be overcome, particularly in the educational setting. The intimate and affective relationship that may develop between students and generative AI devices raises critical questions about the psychological and emotional impact of such interactions. This issue becomes particularly significant when the interactions with AI-based systems begin at an early age, and these systems assume roles as digital tutors, digital secretaries, motivator agents, and/or mentors. The aim of this work in progress was to address a recent challenge within the digital educational context: the psychological and emotional impact that the introduction of AI-based systems in digital education may have on students. However, we have faced limitations in terms of data availability and resources, particularly when addressing the issue from early ages, where there is a notable lack of studies. Although the results may not have been significant, the research has provided a general overview and a solid theoretical foundation for future studies in this field. Therefore, we suggest conducting more rigorous studies with representative samples and complete data, alongside developing reliable and validated methodologies and assessment tools to address the issues involved. © 2023 IEEE.

关键词： Human computer interaction

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 << < 77 78 79 80 81 82 83 84 85 86 > >>

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：