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

30,047 篇 会议
4,659 篇 期刊文献
235 册 图书

馆藏范围

34,941 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

21,687 篇 工学
- 15,657 篇 计算机科学与技术...
- 13,159 篇 软件工程
- 5,775 篇 信息与通信工程
- 3,434 篇 控制科学与工程
- 2,675 篇 电子科学与技术（可...
- 2,626 篇 电气工程
- 2,332 篇 生物工程
- 1,880 篇 生物医学工程（可授...
- 1,525 篇 光学工程
- 1,345 篇 机械工程
- 1,216 篇 动力工程及工程热...
- 1,199 篇 仪器科学与技术
- 1,014 篇 化学工程与技术
- 848 篇 安全科学与工程
- 712 篇 交通运输工程
11,140 篇 理学
- 6,033 篇 数学
- 3,053 篇 物理学
- 2,562 篇 生物学
- 2,003 篇 统计学（可授理学、...
- 1,317 篇 系统科学
- 1,088 篇 化学
5,582 篇 管理学
- 3,263 篇 管理科学与工程(可...
- 2,591 篇 图书情报与档案管...
- 1,804 篇 工商管理
1,587 篇 医学
- 1,371 篇 临床医学
- 1,278 篇 基础医学(可授医学...
- 835 篇 药学(可授医学、理...
- 663 篇 公共卫生与预防医...
1,027 篇 法学
- 824 篇 社会学
636 篇 经济学
- 636 篇 应用经济学
481 篇 农学
439 篇 教育学
154 篇 文学
76 篇 军事学
39 篇 艺术学
1 篇 哲学

主题

1,077 篇 accuracy
832 篇 feature extracti...
829 篇 computational mo...
709 篇 deep learning
680 篇 computer science
671 篇 training
508 篇 support vector m...
508 篇 real-time system...
502 篇 machine learning
430 篇 predictive model...
407 篇 internet of thin...
350 篇 convolutional ne...
347 篇 computer archite...
344 篇 data models
327 篇 reliability
307 篇 optimization
287 篇 data mining
274 篇 routing
256 篇 wireless sensor ...
246 篇 image segmentati...

机构

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

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.
79 篇 coleiro a.
78 篇 gozzini s.r.
70 篇 huang f.
70 篇 dallier r.
64 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

33,053 篇 英文
1,478 篇 其他
308 篇 中文
54 篇 日文
48 篇 朝鲜文
2 篇 德文
2 篇 斯洛文尼亚文
1 篇 法文
1 篇 葡萄牙文

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

共 34941 条记录，以下是4811-4820 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：

Air Pollution Forecasting Using Machine Learning with Temporal Fusion Transformer and Graph Neural Networks

Air Pollution Forecasting Using Machine Learning with Tempor...

引用

Intelligent Data Communication Technologies and Internet of Things (IDCIoT), International Conference on

作者： Subhashree Rath Maneesha P dept. of Computer Science and Engineering New Horizon College Of Engineering Autonomous College Affiliated to VTU Bengaluru

ISBN: (数字)9798331527549

ISBN: (纸本)9798331527556

Air pollution is a significant obstacle to achieving urban sustainability and public health, particularly in rapidly developing regions. Accurate air quality prediction is essential for proactive pollution management and policy formulation. In this study, we employ sophisticated machine learning frameworks, such as Temporal Fusion Transformer (TFT) and Graph Neural Networks (GNNs), to predict air quality levels. TFT is designed to capture temporal dependencies, making it ideal for time-series forecasting, while GNNs model spatial relationships, enabling the analysis of pollutant dispersion across monitoring stations. A synthetic dataset comprising 50 rows was generated, simulating pollutant concentrations (PM2.5, PM10, CO, NO2, SO2) and meteorological variables (temperature, humidity, wind speed). The models were assessed using criteria like $R^{2}$ , RMSE, and MAE. TFT achieved an $R^{2}$ of 0.97 and an RMSE of $4.2 \mu ~\mathrm{g} / \mathrm{m}^3$ , significantly outperforming traditional models like Random Forest and XGBoost. GNN provided spatial insights, identifying pollutant hotspots and their dispersion patterns. This research highlights the superior accuracy and scalability of TFT and GNN for air quality prediction. The results underline their potential for real-time monitoring, smart city integration, and proactive environmental management, offering a robust solution for addressing urban air pollution challenges.

关键词： Accuracy Atmospheric modeling Predictive models Transformers Air pollution Graph neural networks Real-time systems Thin film transistors Forecasting Dispersion

来源：评论

学校读者我要写书评

暂无评论

A 10ps-Order Flexible Resolution Time-to-Digital Converter with Linearity Calibration and Legacy FPGA

A 10ps-Order Flexible Resolution Time-to-Digital Converter w...

引用

2025 Design, Automation and Test in Europe Conference, DATE 2025

作者： Katoh, Kentaroh Nakura, Toru Kobayashi, Haruo Faculty of Engineering Fukuoka University Dept. of Electronics Engineering and Computer Science Japan Gunma Univesity Japan

ISBN: (纸本)9783982674100

This paper presents a 10ps-order flexible resolution time-to-digital converter (TDC) consisting of only Lookup Tables and Flip-Flops that can be applied to legacy FPGAs, which is industry friendly. The proposed TDC is a Vernier delay-line based TDC. By using MUX chains as the delay adjustable buffers, it realizes flexible and high resolution 10ps-order TDC. By controlling the control values of each MUX chain independently, the nonlinearity of TDC is compensated. In the evaluation using the AMD Artix-7 FPGA, the DNL and INL were [-0.26 LSB, 0.91 LSB] and [-0.84 LSB, 2.27 LSB], respectively, at a resolution of 8.92 ps. © 2025 EDAA.

关键词： Table lookup

来源：评论

学校读者我要写书评

暂无评论

Predicting the Likelihood of a Recurrent Febrile Seizure Using Thermographic Images and Deep Learning with Rules Generation

Predicting the Likelihood of a Recurrent Febrile Seizure Usi...

引用

AIML-Applications for engineering & Technology (ICAET), International Conference on

作者： Pratima Patil Deepa S Deshpande Dept. of Computer Science and Engineering Jawaharlal Nehru Engineering College MGM University Chhatrapati Sambhajinagar India

ISBN: (数字)9798350355611

ISBN: (纸本)9798350355628

Recurrent febrile seizures are a common concern in children, often triggered by rapid changes in body temperature during fever episodes. For rapid action and care, early and accurate seizure recurrence prediction is crucial. Limited techniques were developed for predicting the likelihood of a Recurrent Febrile Seizure using a Thermographic image. Several drawbacks were considered for recurrent febrile seizure prediction such as lower performance, high time consumption, and error rate. Hence, the proposed technique is introduced to provide an efficient Deep Learning (DL)-based technique. Initially, the data is gathered from datasets, and the Intra-Attentional Convolutional ResNet (InAtt-CRNet) with the Yolov5-Face model detects the face and reduces the processing time by tacking the face with a bounding box. The patient's forehead or nose temperature is monitored using the Region of Interest (ROI) finding approach following face detection and tracking in each frame. Then, the temperature is predicted using the Enhanced Convolutional Capsule Network (EC2Net). The body temperature, age, duration of fever, and family history are used to construct the clinical decision rule. The Twin-directional Gated Long Short-term memory (TdG-LSTM) is used to predict the likelihood of a subsequent febrile seizure. The proposed technique achieves 98.16% accuracy, 98.45% precision, 0.12 RMSE, and 29 seconds as processing time.

关键词： Deep learning YOLO Temperature sensors Accuracy Forehead Nose Face detection History Long short term memory Faces

来源：评论

学校读者我要写书评

暂无评论

Transformer-Based Self-Supervised Imputation for Medical Data

Transformer-Based Self-Supervised Imputation for Medical Dat...

引用

Electrical, computer, Communications and Mechatronics engineering (ICECCME), International Conference on

作者： Aryan Kumar Singh Arpit Saikia Pranita Baro Malaya Dutta Borah Dept. of Computer Science and Engineering National Institute of Technology Silchar Cachar India

ISBN: (数字)9798350391183

ISBN: (纸本)9798350391190

Dealing with missing data is necessary to develop a solid predictive medical research model. This work presents a hybrid dynamic imputation method devoted to addressing the challenge of missing data, specifically focusing on medical datasets. In this work, we investigate the incompleteness of the dataset using a sophisticated measure called the Incompleteness Factor. This metric is used to guide a hybrid dynamic approach. A novel Transformer-based Self-Supervised imputation method is employed to learn complex data dependencies to impute missing data. This paper introduces one potential solution to obtain model-level accuracy increase for tasks like disease prediction, patient prognosis, etc., over medical datasets. The proposed method aims to remove the measurement biases caused by incompleteness and preprocess the data to enhance the credibility and clinical relevance of the experimental results.

关键词： Measurement Solid modeling Mechatronics Focusing Predictive models Transformers Solids Imputation Prognostics and health management Diseases

来源：评论

学校读者我要写书评

暂无评论

SiCBit-PUF: Strong in-Cache Bitflip PUF Computation for Trusted SoCs

SiCBit-PUF: Strong in-Cache Bitflip PUF Computation for Trus...

引用

IEEE European Test Symposium (ETS)

作者： Athanasios Xynos Vasileios Tenentes Yiorgos Tsiatouhas Dept. of Computer Science & Engineering University of Ioannina Greece

Secure computing necessitates hardware root of trust (RoT) integrated in Systems-on-Chips (SoCs) for cryptographic keys generation, authentication and identification. In this paper, we observe that bitflips in SRAM cells that appear while accessing multiple cells from the same bitline, are not stochastic, as previously considered, but systematic. Based on this observation, a novel strong in-memory Physical Unclonable Function (PUF) computation is proposed for harvesting static entropy from SRAM arrays. The proposed design is compatible with existing in-SRAM computing architectures. To verify our PUF operation, we implement a 6T SRAM array model that performs in-memory computing using a 32 nm CMOS Technology, and, through SPICE simulation, we evaluate the proposed PUF performance. The proposed PUF operation achieves uniqueness and uniformity of 49.99%, and 49.74%, respectively, and reliability higher than 97.4% when the temperature is varied from 0°C to 100°C, and higher than 95.2% when the nominal voltage supply is varied by 10%. Furthermore, we explore the scaling of the number of Challenge Response Pairs (CRPs) of the proposed PUF, and we compare it against the state-of-the-art. Our PUF offers orders of magnitude higher number of CRPs, therefore it is suitable for integrated mechanisms that assure secure computing in SoCs.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Design and Implementation of 2-DOF Arm Manipulator Robot as Robotic Kinematic Learning Platform 6

Design and Implementation of 2-DOF Arm Manipulator Robot as ...

引用

6th International Conference on Vocational Education and Electrical engineering, ICVEE 2023

作者： Widayaka, Parama Diptya Puspitaningayu, Pradini Alamsyah, Sayyidul Aulia Muktiadji, Rifqi Firmansyah Widodo, Arif Abdillah, Rifqi Universitas Negeri Surabaya Dept. of Electrical Engineering Surabaya Indonesia King Abdulaziz University Dept. of Electrical and Computer Engineering Jeddah Saudi Arabia Okayama University Graduate School of Interdisciplinary Science and Engineering in Health Systems Okayamas Japan Institut Teknologi Sepuluh Nopember Surabaya Dept. of Informatics Surabaya Indonesia

ISBN: (纸本)9798350326642

Technological developments have impacts and challenges in human life. Technological advances have made human life easier. The impact of technological developments is the industrial manufacturing process getting faster with the help of robotics technology. Robots can shorten manufacturing process time and efficient. On the other hand, challenges with technological developments force us to keep learning and adaptive to every changes around us, especially in the education sector. In education sector, formal educational institutions or campuses must be able to facilitate students to be able to learn comprehensively in the field of technology, especially robotics, where we can make an innovative learning platform based on robotics technology. In this study, we discussed a 2-DOF arm manipulator robot as kinematics learning platform of industrial robot to increase student competencies in preparation for facing the industrial environment in century. Inverse kinematics equation has been applied in the robot by providing input coordinates on the x-Axis and y-Axis where the accuracy value on the x-Axis is 77% and the accuracy on the y-Axis is 83.1%. © 2023 IEEE.

关键词： Machine design

来源：评论

学校读者我要写书评

暂无评论

A Dynamic Study on Energy Forecasts and The Potential of Renewable Energy Sources

A Dynamic Study on Energy Forecasts and The Potential of Ren...

引用

2022 IEEE Delhi Section Conference, DELCON 2022

作者： Noman, S.M. Salehin, Imrus Hasan, Mohammad Mahedy Baki-Ul-Islam Haque, Obaidul Haque, Ifranul Daffodil International University Dept. of Electrical and Electronic Engineering Dhaka Bangladesh Daffodil International University Dept. of Computer Science and Engineering Dhaka Bangladesh Pabna University of Science and Technology Dept. of Electrical and Electronic Engineering Pabna Bangladesh

ISBN: (纸本)9781665458832

With developing countries, energy demand has been rapid over the years. Bangladesh contributes just 5% of the entire energy ratio in a proportion of renewable energy, and desire to 10% of the year 2025. Bangladesh is based on imported fossil fuel, which is quite expensive and uses natural gas for about 65% of energy production. Bangladesh is fortunate to have a small amount of fossil fuel, i.e., natural gas assets, but these are not adequate to meet the desired robust growth for glorious achievements in the government and non-government sectors. The sustainable power source is a key segment for improvement and has just made significant track in succeeding the greater part of the nation's power request;both in Urban and Rural territories. The motivation behind this study is to analyse energy forecasting for upcoming days and the potential of alternative renewable energy sources to assimilate a comparison in the general diagram of the power utilization of Bangladesh from a global perspective. Anticipating the future demand and looking at the competent outcomes of renewable energy may make urgency among the developing countries to satisfy the high future need for clean energy. In this article, we have focused our attention on the examination of sustainable power sources and the potential outcomes for future energy. © 2022 IEEE.

关键词： Forecasting

来源：评论

学校读者我要写书评

暂无评论

Forecasting EV Market Trends in India: A Deep Learning Approach for Two/Three-Wheelers 12

Forecasting EV Market Trends in India: A Deep Learning Appro...

引用

12th International Electrical engineering Congress, iEECON 2024

作者： Mishra, Rishav Dev Kumar Dash, Santanu Chudjuarjeen, Saichol Korkua, Suratsavadee School Of Computer Science And Engineering Vellore Institute Of Technology Vellore India Vellore Institute Of Technology TIFAC-CORE Vellore India Rajamangala University Of Technology Krungthep Faculty Of Engineering Dept. Electrical Engineering Bangkok Thailand School Of Engineering And Technology Walailak University Thailand

ISBN: (纸本)9798350383591

This research paper presents a comprehensive analysis of machine learning models for predicting future sales of electric vehicles (EVs) in the Indian Market. With a specific focus on 2 and 3 wheeler sales. The study compares different machine learning approaches, including Linear Regression, Support Vector Regression (SVR), Long Short-Term Memory (LSTM) Neural Network, Through an evaluation of their respective errors, LSTM Neural Network method demonstrates superior prediction accuracy, making it the preferred model for forecasting EV sales, specifically 2 wheeler and 3 wheeler sales over the next five years. The paper aims to present the forecasted sales figures, in hopes of providing valuable insights into the future trajectory of EV sales and serving as a vital resource for stakeholders in the electric vehicle industry. © 2024 IEEE.

关键词： Long short-term memory

来源：评论

学校读者我要写书评

暂无评论

CamTran: An Intelligent Automatic System for the Pest Infestation Assessment 1

CamTran: An Intelligent Automatic System for the Pest Infest...

引用

1st IEEE International Conference on Emerging Research in Computational science, ICERCS 2023

作者： Saravana Kumar, G. Parthasarathy, V. Santhosh, R. Roy, Somnath Kanrar, Bappaditya Karpagam College of Engineering Dept. of Electronics and Telecommunications Engineering Coimbatore India Dept. of Computer Science and Engineering Coimbatore India Tocklai Tea Research Institute Entomology Department Assam India Tea Research Association Scientist and Quality Manager TLabs Kolkata India

ISBN: (纸本)9798350359756

In the vast expanse of the tea industry, addressing pest infestations on tealeaves and improving vegetation indices has long been a challenge. While these issues may seem minor on the surface, in reality, they can lead to substantial financial strain. Beyond the immediate, monetary implications, the ripple effect of these challenges can profoundly impact local economies, disrupt trade, and jeopardize the livelihoods of those deeply entrenched in the world of tea cultivation. Convolutional Neural Networks (CNNs) are widely acknowledged for their capability to accurately identify and classify complex characteristics in images, especially those depicting disease or pest-afflicted tea leaves. The technology's premise lies in autonomously extracting features from imagery, allowing for accurate and timely identification, which can potentially lead to early interventions. The process of capturing images of tealeaves in their natural habitat is fraught with complexities. Factors like fluctuating lighting conditions, owing to the time of day or changing weather patterns, can significantly alter an image's clarity. Cultivating tea in the plantation, it has been observed that the holistic life cycle stages of several pests on tea leaves have been detrimentally affecting both the yield and quality of the tea leaves, demanding a comprehensive automated assessment strategy. Recognizing these shortcomings, the paper adopts a fundamental shift in approach and implements CamTran. The architecture, rooted in the Vision Transformer model, adopts a specialized attention mechanism to discern and prioritize salient features within localized image segments, ensuring efficient and relevant feature extraction. The Non-local Blocks, on the other hand, serve a strategic purpose by capturing and integrating long-range dependencies and spatial relationships in the image, providing a holistic understanding of the context. Additionally, the Atrous Spatial Pyramid Pooling (ASPP) module is integrat

关键词： Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

LiDAR Spoofing Attack Detection in Autonomous Vehicles

LiDAR Spoofing Attack Detection in Autonomous Vehicles

引用

2022 IEEE International Conference on Consumer Electronics, ICCE 2022

作者： Alheeti, Khattab M. Ali Alzahrani, Abdulkareem Al Dosary, Duaa College of Computer and Information Technology University of Anbar Computer Networking Systems Dept. Ramadi Iraq Albaha University Faculty of Computer Science and Information Technology Computer Engineering and Science Department Albaha Saudi Arabia College of Computer Sciences and Information Technology University of Anbar Ramadi Iraq

ISBN: (纸本)9781665441544

Detecting 3D objects is a core task for autonomous vehicles (AVs), as it allows them to drive safely and responsibly. To detect objects quickly and accurately, AVs have LiDAR sensors, which can capture 3D data from 360° in various conditions, including harsh weather. However, LiDAR sensors may face a spoofing attack via laser satirizing. This type of attack does not require physical contact with the sensors nor does it need to change them. It can mislead AVs by providing them with false information, which can then put passengers, pedestrians, and other vehicles in danger. Therefore, this paper proposes a model utilizing machine learning (i.e., decision trees) to protect AVs from such attacks. The performance of the proposed model indicates that it can detect LiDAR spoofing attacks. © 2022 IEEE.

关键词： Autonomous vehicles

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 << < 478 479 480 481 482 483 484 485 486 487 > >>

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：