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

7,090 篇 会议
48 篇 期刊文献
39 册 图书

馆藏范围

7,177 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

4,913 篇 工学
- 4,098 篇 计算机科学与技术...
- 2,520 篇 软件工程
- 1,048 篇 信息与通信工程
- 789 篇 控制科学与工程
- 663 篇 生物工程
- 643 篇 电气工程
- 424 篇 生物医学工程（可授...
- 285 篇 交通运输工程
- 281 篇 机械工程
- 226 篇 仪器科学与技术
- 226 篇 安全科学与工程
- 206 篇 建筑学
- 197 篇 动力工程及工程热...
- 185 篇 光学工程
- 166 篇 化学工程与技术
- 154 篇 土木工程
1,899 篇 理学
- 1,065 篇 数学
- 717 篇 生物学
- 442 篇 统计学（可授理学、...
- 285 篇 物理学
- 252 篇 系统科学
- 140 篇 化学
1,151 篇 管理学
- 655 篇 管理科学与工程(可...
- 582 篇 图书情报与档案管...
- 315 篇 工商管理
407 篇 医学
- 353 篇 临床医学
- 297 篇 基础医学(可授医学...
- 188 篇 药学(可授医学、理...
244 篇 教育学
- 243 篇 教育学
211 篇 法学
- 197 篇 社会学
119 篇 农学
111 篇 经济学
50 篇 文学
7 篇 艺术学
5 篇 军事学

主题

558 篇 machine learning
456 篇 deep learning
267 篇 training
253 篇 data mining
245 篇 data models
220 篇 feature extracti...
211 篇 accuracy
184 篇 support vector m...
178 篇 predictive model...
138 篇 neural networks
133 篇 computational mo...
131 篇 reinforcement le...
129 篇 machine learning...
110 篇 convolutional ne...
103 篇 real-time system...
92 篇 artificial intel...
89 篇 learning systems
88 篇 transfer learnin...
87 篇 forecasting
86 篇 big data

机构

69 篇 chitkara univers...
17 篇 school of electr...
15 篇 computer science...
14 篇 harbin engineeri...
13 篇 graphic era hill...
12 篇 building civil a...
12 篇 uttaranchal inst...
12 篇 computer science...
11 篇 university of ch...
10 篇 school of electr...
10 篇 school of comput...
10 篇 graphic era deem...
10 篇 school of electr...
10 篇 yonsei univ dept...
9 篇 wuhan university...
9 篇 univ chinese aca...
9 篇 school of inform...
8 篇 school of remote...
7 篇 university of sa...
7 篇 microsoft resear...

作者

17 篇 kukreja vinay
15 篇 vinay kukreja
13 篇 yin hujun
12 篇 liu yang
12 篇 corchado emilio
12 篇 cho sung-bae
10 篇 shiva mehta
10 篇 hujun yin
10 篇 mehta shiva
9 篇 notsu akira
9 篇 silva catarina
9 篇 alhajj reda
7 篇 ksieniewicz pawe...
7 篇 hammer barbara
7 篇 zhang byoung-tak
7 篇 wozniak michal
7 篇 hussain abir
7 篇 huang de-shuang
6 篇 héctor quintián
6 篇 tang ke

语言

6,195 篇 英文
971 篇 其他
31 篇 中文
1 篇 西班牙文
1 篇 俄文

检索条件"任意字段=11th International Conference on Intelligent Data Engineering and Automated Learning"

共 7177 条记录，以下是1061-1070 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：

11th international conference on E-Health and Bioengineering, EHB 2023

11th International Conference on E-Health and Bioengineering...

引用

11th international conference on E-Health and Bioengineering, EHB 2023

ISBN: (纸本)9783031625015

the proceedings contain 168 papers. the special focus in this conference is on E-Health and Bioengineering. the topics include: Cost and Effects of Treatment of Biceps Long Head Tendon Injury;health Technology Assessment: Current State of Access to Medical Device Outcomes;early Stage Health Technology Assessment: Still Unknown Helper of Medical Device Manufacturers;Identifying Hidden Patterns from Health Administrative Claims by Means of "HAC2Vec" Embedding;tracing Real-World Patient Pathway by Harnessing Healthcare Administrative Claims;nation-Wide Benchmarking of Healthcare Indicators: From Inferential Statistics to Dashboard Cards;cost-Effectiveness Analysis of Multiple Sclerosis Treatment Approaches;legal and Procedural Health data Anonymization Framework of the Faculty of Biomedical engineering, Czech Technical University;A Burden of Disease Model for Assessing the Economic and Outcomes Impact of Diseases Associated with HPV Infection;Mean Membrane Potential Estimation for Neural Mass Models in EEG Recordings Using a Linear State Observer;gait Analysis of Electromyographic Spectral Differences in Stroke Survivors and Healthy Controls;cardiac Arrhythmia Identification Using Feature Selection and Rule-Based Classifiers;automatic Detection of High-Quality Fibrillatory Waves Segments from Atrial Fibrillation Electrocardiographic Recordings;murmur Separation and Classification from Heart Sound;Bio-Signal Based Detection of Hyperarousal as Onset of Post-Traumatic Stress Disorder (PTSD) Episodes;heart Rate Variability Machine learning Models to Facilitate Elevated Blood Pressure Detection;improved Hypertension Detection Models Utilizing Pulse Rate Variability and Asymmetry;application of Meta learning in Quality Assessment of Wearable Electrocardiogram Recordings;heart Rate Variability Analysis on Forcecardiography Signals: A Preliminary Study;Accurate ECG-Free Heartbeats Localization in Long-Lasting SCG Recordings;resilience in Adults.

关键词：

来源：评论

学校读者我要写书评

暂无评论

An Experimental Study on the Railway Track Surface Fault Detection with Automation 17

An Experimental Study on the Railway Track Surface Fault Det...

引用

17th international conference on engineering of Modern Electric Systems, EMES 2023

作者： Mukhtiar, Noorain Khuwaja, Komal Tocut, Danut Pavel Tarca, Ion Mehran University of Engineering & Technology Department of Electronic Engineering Jamshoro Pakistan University of Oradea Department of Mechatronics Oradea Romania University of Oradea Department of Mechanics Oradea Romania

ISBN: (纸本)9798350310634

Railway networks serve as a pivotal component of the transportation industry, exerting a substantial impact on the conveyance of both passengers and cargo. However, these tracks are susceptible to damage and Impairment due to various factors including increased traffic, heavier axles, faster speeds, and harsh environmental conditions. Such damage, if not addressed promptly and effectively, can ultimately result in the deterioration and failure of the railway network, potentially leading to derailments and other safety hazards. this research proposes an automated approach for real-time surface fault identification of railway tracks by employing intelligent Micro-electromechanical sensors for data acquisition and advanced machine learning algorithms. Moreover, the proposed approach effectively exploits the vast potential of the Internet of things (IoT) paradigm by utilizing a Wi-Fi module for subsequent transmission of the processed data to the thingSpeak cloud for centralized storage and further analysis. the presented methodology involves the comparative analysis between two machine learning algorithms namely Density-Based Spatial Clustering of Applications with Noise (DBSCAN) and K-means Clustering, to categorize faulty and non-faulty data. K-means clustering was found to be the most effective with an accuracy exceeding 95%. this integrated approach enables remote monitoring and automated control of railway tracks, enhancing the overall efficiency and efficacy of the system. Additionally, the location of faulty points was calculated using GPS NEO 6m. the proposed approach offers a promising solution for the fault detection and maintenance of railway networks with its low computational complexity, real-time data processing capabilities, and compatibility with existing railway systems paving the way for safer and more resilient transportation infrastructure. the model was validated via visual inspection of the identified faulty areas, confirming the accuracy and effe

关键词： Fault detection

来源：评论

学校读者我要写书评

暂无评论

Development of an automated Damage Detection System for Modular Buildings 11

Development of an Automated Damage Detection System for Modu...

引用

11th international conference on Structural Health Monitoring of intelligent Infrastructure, SHMII 2022

作者： Valinejadshoubi, Mojtaba Bagchi, Ashutosh Moselhi, Osama Building Civil and Environmental Engineering Department Gina Cody School of Engineering and Computer Science Concordia University MontrealQCH3G 1M8 Canada Pomerleau Inc. Montreal Canada

Transportation is a very significant part of the process for construction of buildings with prefabricated modules. the purpose of our research is to develop a novel data-driven structural health monitoring (SHM) system to assess the structural condition of individual prefabricated building modules during transportation. the developed system consists of a sensor-based data acquisition (DAQ) module and a storage module, along with automated data analysis module. the system was applied to a wooden prefabricated building module. We attached 8 vibration sensors to the walls and floors of that building module when it left the factory and monitored its structural condition during its transportation to the site. After detailed analysis, using performance measurement techniques: confusion matrix and accuracy score, we found that the DBSCAN algorithm yielded the full accuracy score in the case of more than one level of damage compared with k-means, mean shift, and agglomerative clustering with accuracy scores of 0.81, 0.79, and 0.78 respectively. the system can allow for timely replacement of damaged parts of the prefabricated modules before installation and provide evidence to support manufacturers insurance claims on repair and modification costs. © 2022 international conference on Structural Health Monitoring of intelligent Infrastructure: Transferring Research into Practice, SHMII. All rights reserved.

关键词： Structural health monitoring

来源：评论

学校读者我要写书评

暂无评论

RAG for Question-Answering for Vocal Training Based on Domain Knowledge Base 11

RAG for Question-Answering for Vocal Training Based on Domai...

引用

11th IEEE international conference on Behavioural and Social Computing, BESC 2024

作者： Leung, Chun-Hung Jonas Yi, Yicheng Kuai, Le Li, Zongxi Yeung, Siu-Kei Au Lee, Kwok-Wah John Ho, Ka-Him Kelvin Hung, Kevin School of Science and Technology Hong Kong Metropolitan University Hong Kong Hong Kong School of Data Science Lingnan University Hong Kong Hong Kong Sing Sharp Ltd. Hong Kong Hong Kong

ISBN: (纸本)9798331531904

Although Large language models (LLMs) are well-known due to their superior capacity for text generation and logical inference, they are found to be inaccurate in domain-specific question-answering tasks. the powerful generator still tends to generate content even when the LLM does not have sufficient knowledge at all, which is known as the hallucination problem. We find there is a research void in applying LLMs in the vocal training industry, which requires intensive expert knowledge in any chatbot or intelligent tutor services. this paper details employing Retrieval-Augmented Generation (RAG) technology to develop a domain-specific language model, addressing inherent challenges such as hallucination, where large models generate plausible but inaccurate content, and lack of domain specificity. By segmenting the knowledge base and establishing semantic similarities between user queries and knowledge data, the project lays a solid foundation for integrating RAG, significantly improving response accuracy and contextual relevance. the report highlights the successful implementation of RAG, enhancing system intelligence and personalization for user-specific needs, discusses challenges and solutions during the implementation process, and outlines future directions to expand RAG capabilities and improve user experiences. © 2024 IEEE.

关键词： Question answering

来源：评论

学校读者我要写书评

暂无评论

Human Posture Identification and Recognition Using Deep learning Techniques 11th

Human Posture Identification and Recognition Using Deep Lear...

引用

11th international conference on intelligent Computing and Applications, ICRTC 2023

作者： Grover, Anuj Arora, Deepak Grover, Anant Department of Computer Science and Engineering Amity School of Engineering and Technology Amity University Lucknow Campus Lucknow India

ISBN: (纸本)9789819717231

Human Pose Estimation is the task of estimating the human joints in a 2D or 3D coordinate plane from an input RGB image. the 2D HPE are of two types: top-down and bottom-up. the 3D Human Pose Estimation gives better understanding of the relative position of the joints of the person and is helpful to understand the positions of close joints. the evaluation metrics and the architectures for 2D HPE are discussed in brief in the paper. the paper focuses on 3D Human Pose Estimation because it provides more information about the depth of the joint and gives better spatial understanding of the joint’s position. the evaluation metrics and various 3D HPE architectures: Simple Baseline, Lifting from the Deep, Camera Distance Aware approach, and BlazePose. A custom in-the-wild dataset was built and was used for evaluating the 3D Human Pose Estimation architectures. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Computer vision

来源：评论

学校读者我要写书评

暂无评论

On Improving Malaria Parasite Detection from Microscopic Images: A Comparative Analytics of Hybrid Deep learning Models 11

On Improving Malaria Parasite Detection from Microscopic Ima...

引用

11th international conference on Information and Communication Technology, ICoICT 2023

作者： Dev, Antora Fouda, Mostafa M. Kerby, Leslie Fadlullah, Zubair Md Idaho State University Department of Electrical and Computer Engineering PocatelloID United States Idaho State University Department of Computer Science PocatelloID United States Western University Department of Computer Science LondonON Canada

ISBN: (纸本)9798350321982

Malaria, a life-threatening mosquito-borne disease, contributes to a significantly high number of fatalities in tropical/sub-tropical regions due to inadequate detection technology, lack of laboratory experience, and other barriers. From the design perspective of a general-purpose point-of-care solution for detecting malaria along with other tropical diseases, malaria parasite detection from blood work needs to integrate accurate and fast detection capabilities. In this vein, in this paper, we develop three hybrid data-driven models in this paper that combine a convolutional neural network (CNN) with long short-term memory (LSTM), bi-directional LSTM (BiLSTM), and gated recurrent unit (GRU), respectively. CNN is employed in all three proposed models to extract the relevant features that are passed to two cascaded layers of Recurrent Neural Networks (RNNs) in each model that acts as a classifier. Based on the experiments conducted with a public dataset, we demonstrate that our designed CNN-GRU-GRU hybrid model outperformed the other models in terms of accuracy (96.01%), less type-I error rate (1.81%), and type-II error rate (2.18%). On the other hand, the CNN-LSTM-LSTM model was attributed to a low computing (training) time of just 4 minutes and 46 seconds. Our findings clearly elucidate the potential of combining classifiers in biomedical analytics research and pave the way for portable point-of-care devices with reasonable accuracy and fast computation times, enabling them to be used for collaborative learning for large-scale, real-time disease modeling. © 2023 IEEE.

关键词： Image recognition

来源：评论

学校读者我要写书评

暂无评论

Digital Twin and Resources Analytics Integration Framework for Indonesia New Capital City Construction 5th

Digital Twin and Resources Analytics Integration Framework f...

引用

5th international conference on Structural engineering and Construction Management

作者： Yogi, Muhammad Rilly Aka Berawi, Mohammed Ali Latief, Yusuf Sucahyo, Yudho Giri Univ Indonesia Depok 16424 Indonesia Univ Riau Pekanbaru 28293 Indonesia

ISBN: (纸本)9783031704338;9783031704314;9783031704307

this article presents an approach to integrate digital twin and resource analytics for resource utilization in Indonesia New Capital City (Nusantara) construction. the digital twin is used in construction projects as a systematic representation of physical objects into virtual models of construction. While the analytical system is used as an intelligent function for optimizing resource utilization. the integration of these two requires a data-centric construction system followed by a high maturity level of platform ecosystem to control the project. the state-of-the-art literature review is used through various studies related to the research objectives along with the digital transformation vision of Nusantara development. the result shows that the integration of BIM, GIS, data architecture, scheduling, and machine learning is needed to develop a model for controlling resource utilization on the project. Performing resource leveling from resource allocation through an ecosystem is required to effectively distribute construction resources and to obtain efficient project cost and duration. the study contributes to the construction digital twin for aerial development.

关键词： Digital twin Resources analytics data centric Construction project Nusantara

来源：评论

学校读者我要写书评

暂无评论

automated sleep staging based on multi-module neural network using simpler signal: Respiratory signal 7

Automated sleep staging based on multi-module neural network...

引用

7th international conference on Mechatronics and intelligent Robotics, ICMIR 2023

作者： Que, Yinqing Jiang, Pengyi Zhang, Tianyi Cheng, Yunzhang School of Health Science and Engineering University of Shanghai for Science and Technology Shanghai200093 China School of Information Science and Engineering East China University of Science and Technology Shanghai200237 China

ISBN: (数字)9781510668089

ISBN: (纸本)9781510668072

Sleeping is a vital biological state which help maintaining the homeostasis of organisms of all biological lives. A full sleep can be divided into different repeating stages, rapid eye movement sleep (REM) stage, non-rapid eye movement sleep (NREM) stage 1-4. An effective sleep staging system can help patients improving their sleep quality. In the past, patients are required to wear polysomnogram (PSG) for the whole night to collect signals like electroencephalogram (EEG), electrooculogram (EOG), electromyogram (EMG) for diagnosis. And the traditional sleep staging system use one or more signals above to predict a sleep stage. In this paper, we introduce a new sleep staging algorithm based on machine learning. Our model has two main inputs: patients respiratory signal and their physical data, like age, gender, and weight. the strategy is to use two CNNs to extract features from raw respiratory signal in time domain and frequency domain, several Word2vec layers are built to extract features from patients meta data and a transformer encoder to collect all the features. Using the MIT-BIH Polysomnographic database, our model achieves a result of 81.96% accuracy. this shows that it is completely feasible to classify patients sleep stage with their respiratory signal and meta information. © 2023 SPIE. All rights reserved.

关键词： Machine learning

来源：评论

学校读者我要写书评

暂无评论

Cooperative and Dynamic UAV-Based Mobile Sink Deployment using Deep Reinforcement learning 11

Cooperative and Dynamic UAV-Based Mobile Sink Deployment usi...

引用

11th international conference on Advanced Cloud and Big data, CBD 2023

作者： Shao, Mingyue Luo, Hanjiang Ruby, Rukhsana Dong, Pengyan Tao, Hang Shandong University of Science and Technology College of Computer Science and Engineering Qingdao China Shenzhen University College of Computer Science and Software Engineering Shenzhen China

ISBN: (纸本)9798350345346

In maritime emergency response operations, autonomous underwater vehicles (AUVs) can perform underwater search and transmit emergency data in real-time. To collect the sensed data from AUVs across the water-air interface, the traditional method is to deploy surface relays. However, the deployment of surface relays has some disadvantages, such as poor and imbalanced communication coverage of real-time connections with AUVs. Since the deployment of static relays may limit the dynamic search area of AUVs, whereas the deployment of free surface drifting relays may disrupt the connections while the relays are drifting away with the ocean current. To address these challenges, in this paper, we propose a novel method by leveraging the flexibility of multiple unmanned aerial vehicles (UAVs) equipped with underwater hydrophones and design a dynamic deployment scheme based on a multi-agent deep deterministic policy gradient (MADDPG) approach. By this scheme, multiple UAVs are able to deploy in a cooperative manner to deal with the coverage imbalance issue and provide maximum coverage service. the numerical simulations demonstrate that the proposed scheme is effective in terms of communication coverage, fairness, and energy consumption. © 2023 IEEE.

关键词： Autonomous underwater vehicles

来源：评论

学校读者我要写书评

暂无评论

Classification of Autism Spectrum Disorder Based on Brain Image data Using Deep Neural Networks 1

引用

11th international conference on Frontiers of intelligent Computing: theory and Applications, FICTA 2023

作者： Lakshmi, Polavarapu Bhagya Reddy, V. Dinesh Ghosh, Shantanu Sengar, Sandeep Singh School of Engineering and Sciences SRM University AP Amaravati India School of Liberal Arts and Social Sciences SRM University AP Amaravati India Department of Computer Science Cardiff Metropolitan University Llandaff Campus Cardiff United Kingdom

ISBN: (数字)9789819967025

ISBN: (纸本)9789819967018

Autism spectrum disorder (ASD) is a neuro-developmental disorder that affects 1% of children and has a lifetime effect on communication and interaction. Early prediction can address this problem by decreasing the severity. this paper presents a deep learning-based transfer learning applied to resting state fMRI images for predicting the autism disorder features. We worked with CNN and different transfer learning models such as Inception-V3, Resnet, Densenet, VGG16, and Mobilenet. We performed extensive experiments and provided a comparative study for different transfer learning models to predict the classification of ASD. Results demonstrated that VGG16 achieves high classification accuracy of 95.8% and outperforms the rest of the transfer learning models proposed in this paper and has an average improvement of 4.96% in terms of accuracy. © 2023, the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Forecasting

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 << < 103 104 105 106 107 108 109 110 111 112 > >>

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：