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

890 篇 会议
6 册 图书
5 篇 期刊文献

馆藏范围

901 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

611 篇 工学
- 514 篇 计算机科学与技术...
- 320 篇 软件工程
- 102 篇 信息与通信工程
- 94 篇 电气工程
- 78 篇 生物工程
- 72 篇 控制科学与工程
- 47 篇 环境科学与工程（可...
- 35 篇 机械工程
- 35 篇 安全科学与工程
- 30 篇 交通运输工程
- 29 篇 生物医学工程（可授...
- 28 篇 动力工程及工程热...
- 24 篇 建筑学
- 23 篇 光学工程
- 18 篇 电子科学与技术（可...
186 篇 理学
- 87 篇 数学
- 81 篇 生物学
- 30 篇 统计学（可授理学、...
- 29 篇 物理学
- 22 篇 系统科学
132 篇 管理学
- 99 篇 管理科学与工程(可...
- 50 篇 图书情报与档案管...
- 48 篇 工商管理
112 篇 教育学
- 111 篇 教育学
49 篇 法学
- 40 篇 社会学
36 篇 医学
- 35 篇 临床医学
- 34 篇 基础医学(可授医学...
- 25 篇 公共卫生与预防医...
21 篇 经济学
- 21 篇 应用经济学
19 篇 农学
- 19 篇 作物学
6 篇 军事学
4 篇 文学

主题

81 篇 machine learning
60 篇 deep learning
43 篇 internet of thin...
39 篇 accuracy
38 篇 ecosystems
25 篇 predictive model...
23 篇 reinforcement le...
23 篇 convolutional ne...
22 篇 training
19 篇 real-time system...
19 篇 feature extracti...
19 篇 security
19 篇 artificial intel...
18 篇 big data
18 篇 technological in...
17 篇 computational mo...
17 篇 students
17 篇 machine learning...
16 篇 sustainable deve...
16 篇 e-learning

机构

11 篇 chitkara centre ...
9 篇 department of in...
8 篇 chitkara univers...
8 篇 aslerd rome
7 篇 chitkara univers...
6 篇 centre of resear...
5 篇 department of co...
4 篇 texas a&m univer...
4 篇 czech tech univ ...
4 篇 bina nusantara u...
4 篇 lloyd institute ...
4 篇 the islamic univ...
4 篇 univ politehn bu...
4 篇 acad romanian sc...
4 篇 lloyd law colleg...
4 篇 univ innsbruck i...
3 篇 yunnan key labor...
3 篇 kkr and ksr inst...
3 篇 vishwakarma inst...
3 篇 universidad tecn...

作者

7 篇 giovannella carl...
6 篇 urban josef
5 篇 dascalu mihai
4 篇 bakken jeffrey p...
4 篇 uskov vladimir l...
4 篇 rachakonda rama
3 篇 heinemann collee...
3 篇 maranan ramya
3 篇 p. william
3 篇 refaat shady s.
3 篇 kaliszyk cezary
3 篇 olsak miroslav
3 篇 setiawan karli e...
3 篇 santos fernando ...
3 篇 leoste janika
3 篇 trausan-matu ste...
2 篇 m. vigenesh
2 篇 zhao huijuan
2 篇 toma irina
2 篇 a l n rao

语言

854 篇 英文
45 篇 其他
5 篇 中文
1 篇 法文

检索条件"任意字段=4th International Conference on Smart Learning Ecosystems and Regional Development"

共 901 条记录，以下是71-80 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：

Analyzing the Impact of ChatGPT on Enhancing Academic Skills and learning Concepts Among University Students in Jakarta 4

Analyzing the Impact of ChatGPT on Enhancing Academic Skills...

引用

4th international conference of Science and Information Technology in smart Administration, ICSINTESA 2024

作者： Lucas, Jerry Madyatmadja, Evaristus Didik Syahchari, Dicky Hida Bina Nusantara University School of Information Systems Jakarta Indonesia Bina Nusantara University Binus Business School Jakarta Indonesia

ISBN: (纸本)9798350376111

there has been a noticeable change in the way that academic skill development and learning work with the introduction of ChatGPT as a key educational technology tool, especially for Jakarta university students. this study aims to clarify how ChatGPT helps students get a deeper knowledge and improve their academic performance, as artificial intelligence (AI) becomes more and more integrated into educational environments. With a quantitative approach, we investigated the usefulness, interaction, flexibility, and possible drawbacks of ChatGPT in educational contexts using questionnaires. the results of 331 university students who participated in a snowball sampling process indicated a strong preference for ChatGPT as a tool to improve studying. the model is effective at enhancing learning experiences, according to preliminary results, but it also raises questions about the critical thinking abilities that may be compromised by an overreliance on artificial intelligence. therefore, this study contributes and give insights into the application of ChatGPT in education, offering educational institutions, teacher, or student a comprehensive strategy for leveraging AI technology to improve the academic skill and learning concepts. © 2024 IEEE.

关键词： Contrastive learning

来源：评论

学校读者我要写书评

暂无评论

User-Centered Design and Implementation of an Intelligent Wearable Device for Real-Time Health Monitoring in IoT ecosystems 4

User-Centered Design and Implementation of an Intelligent We...

引用

4th international conference on Electronic Information Engineering and Computer Communication, EIECC 2024

作者： Li, Zhengdong Wuhan University Bioengineering Art College Wuhan China

ISBN: (纸本)9798331534622

this paper focuses on the user-centered design and development of an intelligent wearable device for real-time health monitoring, within an IoT ecosystem. Emphasizing ergonomics, aesthetic appeal, and ease of use, the product design process incorporates human factors engineering and material selection to ensure a comfortable and durable device. the wearable integrates advanced biosensors for continuous monitoring of key health metrics and employs wireless communication for seamless data transmission. A key innovation lies in the integration of machine learning algorithms that enhance the device's predictive capabilities, offering users valuable health insights. this paper outlines the design iterations, prototyping process, and usability testing that led to a market-ready product, ensuring the device meets both functional and user experience goals. © 2024 IEEE.

关键词： Electronic health record

来源：评论

学校读者我要写书评

暂无评论

Optimizing Self-learning Forwarding Strategies in Vehicular Named Data Network through Protocol Simplification 4

Optimizing Self-Learning Forwarding Strategies in Vehicular ...

引用

4th international conference of Science and Information Technology in smart Administration, ICSINTESA 2024

作者： Hanif, Fitra Nur Yovita, Leanna Vidya Istikmal Telkom University Bandung Indonesia

ISBN: (纸本)9798350376111

the Information Centric Network (ICN) concept gave rise to the Named Data Network (NDN), a content-centric computer network architecture. Vehicular ad-hoc Networks (VANETs), characterized by high mobility, have embraced NDN, employing broadcast-based forwarding strategies. this self-learning approach enables adaptive path adjustments without relying on explicit routing instructions, a valuable trait in dynamic wireless environments. However, node movements are interpreted as link failures, prompting nodes to issue Negative Acknowledgments (NACKs) to consumers. Yet, due to changes in node positions, NACKs might lose their way back to the intended consumers, leading to increased transmission overhead. To address these issues, this paper proposes a streamlined communication protocol for self-learning forwarding strategies. the suggested approach mitigates the overhead associated with negative acknowledgments, thereby reducing the delay in re-transmitting failed packets. Simulations conducted in ndnSIM 2.8 compare the performance of this scheme against existing strategies (such as multicast, multicast VANET, and self-learning) across scenarios with varying numbers of nodes. Results indicate that the proposed scheme achieves a lower round-trip time (approximately 1 2. 8 9%) and a higher throughput (around 1 6. 0 2%) compared to the default self-learning approach as the number of nodes increases. this improvement stems from the reduction in negative acknowledgment protocol overhead within the self-learning forwarding strategy, enabling more efficient retrieval of successful packets. © 2024 IEEE.

关键词： Vehicular ad hoc networks

来源：评论

学校读者我要写书评

暂无评论

Indoor Pedestrian Location Estimation with HAR Assistance 4

Indoor Pedestrian Location Estimation with HAR Assistance

引用

4th international conference on Computer Communication and Artificial Intelligence (CCAI)

作者： Guo, Sheng Li, Minmin Li, You Guangdong Lab Artificial Intelligence & Digital E Shenzhen Peoples R China Guangdong Hong Kong Macau Joint Lab Smart Cities Shenzhen Peoples R China Shenzhen Univ Sch Architecture & Urban Planning Smart Cities Shenzhen Peoples R China

ISBN: (纸本)9798350362770;9798350362763

Human activity recognition (HAR) technology plays a crucial role in inferring indoor environmental information through the analysis of pedestrian activity data within indoor environments. However, traditional methods that utilize recognized environmental information as landmarks for indoor localization face limitations in map dependency and timeliness issues. To overcome these challenges, we propose a novel approach that leverages deep learning techniques to estimate both position and activity recognition in real time directly from raw inertial sensor data. In contrast to the traditional approach of relying on indoor maps for location correction, our method directly utilizes the results of HAR identification for real-time position estimation, eliminating the need for pre-existing maps and ensuring optimal performance of the positioning system. To support our research, we constructed an indoor activity dataset consisting of six common activities: standing, walking, running, escalator up, escalator down, upstairs, downstairs. the experimental results indicate that the proposed method not only reduces errors but also ensures stable indoor positioning.

关键词： HAR indoor positioning deep learning

来源：评论

学校读者我要写书评

暂无评论

HRBwSD: Hybrid radial based with standard deviation 4

HRBwSD: Hybrid radial based with standard deviation

引用

4th IEEE international conference on smart Information Systems and Technologies, SIST 2024

作者： Imanbek, Rustem Buribayev, Zholdas Yerkos, Ainur Shaikalamova, Saida Abdirazak, Zemfira Dauletiya, Daniyar Department of Computer Science Al-Farabi KazNU Almaty Kazakhstan Information Systems Development Department Al-Farabi KazNU Almaty Kazakhstan Research and Innovation Laboratory FabLab Astana IT University Astana Kazakhstan

ISBN: (纸本)9798350374865

the problem of class imbalance has become a relevant topic in the field of machine learning, and there are several ways to solve this problem, including oversampling, undersampling, and hybrid algorithms. the HRBwSD algorithm proposed in the research belongs to the category of hybrid algorithms. the algorithm was created based on the RBU (Radial-Based Undersampling) and RBO (Radial-Based Oversampling) algorithms, which take into account the exclusion of duplicates and the preservation of the original class distribution. the results show that the model estimates obtained using the proposed algorithm were comparable to the estimates obtained using other class balancing algorithms. this confirms the importance of adapting algorithms to the specifics of the data to obtain more accurate and fair results. © 2024 IEEE.

关键词： Consensus algorithm

来源：评论

学校读者我要写书评

暂无评论

smart Microgrid Optimization using Deep Reinforcement learning by utilizing the Energy Storage Systems 4

Smart Microgrid Optimization using Deep Reinforcement Learni...

引用

4th international conference on smart Grid and Renewable Energy, SGRE 2024

作者： Ahmed, Ibrahim Pedersen, Andreas Mihet-Popa, Lucian Ostfold University College Engineering Department Fredrikstad Norway

ISBN: (纸本)9798350306262

the need for power is expanding quickly, and as fossil fuels are depleted, alternatives based on renewable energy are emerging. In recent years, microgrids, which are based on distributed generation and storage systems, have been on an increasing trend. this generates various new opportunities, one of which is the capacity to monitor, control, and regulate the energy flow inside and outside of the microgrid. By making microgrid's distributed energy resources (DERs) and energy storage components economically viable with artificial intelligence and machine learning incorporated into the cost-optimization process, the demand for and growth of these technologies will be accelerated significantly. this paper focuses on employing reinforcement learning (RL) algorithms to control energy flow in an AC microgrid. By incorporating artificial intelligence and machine learning into the energy management system (EMS), the paper aims to optimize costs and facilitate the integration of renewable energy sources. the RL agent is designed to trade energy with the main grid, taking advantage of the energy storage system and achieving cost savings. the RL agent is tested using real spot prices data in Norway from a simulation model that combines Python and MATLAB-Simulink software programs for efficient co-simulation technique. Results show significant cost savings of around 14% for a simple model and 7.5% for a complex dynamic model. © 2024 IEEE.

关键词： Reinforcement learning

来源：评论

学校读者我要写书评

暂无评论

ANN-LSTM Based Tool for Photovoltaic Power Forecasting. 4

ANN-LSTM Based Tool for Photovoltaic Power Forecasting.

引用

4th international conference on smart Grid and Renewable Energy, SGRE 2024

作者： Zahraoui, Younes Korotko, Tarmo Mekhilef, Saad Rosin, Argo Tallinn University of Technology FinEst Centre for Smart Cities Tallinn Estonia Swinburne University of Technology School of Software and Electrical Engineering Melbourne Australia

ISBN: (纸本)9798350306262

Renewable energy resources are currently being utilized in different sectors in order to meet the demands of energy, reduce environmental pollution, decrease the usage of fossil fuels, and achieve social and economic benefits for sustainable development. As the integration of renewable energy resources into electrical energy systems is expanding. Meanwhile, the development of applications for forecasting renewable energy output has also been progressing rapidly. For example, forecasting the power dispatch from the solar photovoltaic (PV) system. therefore, an accurate forecast of the main factors of power generation became highly important in the case of large-scale power systems for intelligent match the power generation with the power demand for efficient energy management. Many applications for forecasting have been performed using artificial intelligence techniques. this paper proposed a framework for predicting PV power output using artificial neural network (ANN) and long short-term memory (LSTM) models-based tools. In this study, the meteorological and power parameters are applied as input variables. In addition, two levels of deep learning are applied to allow a deeper and more comprehensive exploration of the learning mechanism. the proposed framework is evaluated using a centralized unit for a real-time hardware-in-the-Ioop (HIL) test platform. the objective of this research, as indicated by the findings, is to enhance the practical engineering application of deep learning-based intelligent models for predicting PV power generation. © 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

A Survey: Traffic Sign Recognition System using learning Techniques 4

A Survey: Traffic Sign Recognition System using Learning Tec...

引用

4th IEEE international conference on ICT in Business Industry and Government, ICTBIG 2024

作者： Sharma, Priya Devare, Pratiksha Rasal, Ajinkya Kale, Shreyash Jadhav, Ganesh SKNCOE- Vadgaon Sppu Pune Department of Computer Engineering Pune India

ISBN: (纸本)9798331518981

A very important aspect of the development of smart transportation networks and road safety is 'traffic sign recognition'. this survey covers all types of learning techniques applied to traffic sign recognition with respect to effectiveness, challenges, and progress. the study begins with an overview of the foundational methods of traffic sign recognition: traditional image processing approaches and their limitations. Further below, the heart of the survey is modern learning techniques, especially 'machine learning (ML)' and 'deep learning (DL)' approaches. the report reviews employ learning techniques applied in 'traffic sign recognition systems'. It discusses both the most recent developments in deep learning and advanced machine learning as well as conventional image processing. the review ranges from classical techniques such as colour and shape-based recognition to modern techniques such as 'Convolutional Neural Network (CNN),' which have significantly increased recognition accuracy. Several important datasets on which the training and evaluation should be done have been reported. One of them is 'German Traffic Sign Recognition Benchmark', and the challenges in practical applications along with the future research directions in this field have been highlighted. An overview has been provided regarding the effectiveness and evolution of learning techniques to improve 'Traffic sign recognition systems'. © 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

A technique utilizing Machine learning and Convolutional Neural Networks (CNN) for the identification of SQL Injection Attacks 4

A technique utilizing Machine Learning and Convolutional Neu...

引用

4th international conference of Science and Information Technology in smart Administration, ICSINTESA 2024

作者： Setiyaji, Andri Ramli, Kalamullah Hidayatulloh, Zulkifli Yasin Budhi Dharmawan, G.S. Universitas Indonesia Faculty of Engineering Department of Electrical Engineering Depok Indonesia Center of Network Communications Meteorological Climatological and Geophysical Agency Jakarta Indonesia

ISBN: (纸本)9798350376111

Analyzing logs can aid in debugging or optimizing system performance. A comprehension of system efficacy is frequently linked to an awareness of the manner in which the system's resources are utilized. SQL injection attacks, specifically targeting web applications, have become a significant risk in the realm of cybersecurity. SQL injection attacks primarily result in the unauthorized disclosure of user data, allowing for data manipulation, updating, and deletion within web applications. Conventional methods employed to mitigate SQL injections encompass rule-based matching and other associated techniques that have a narrow scope in addressing only a few types of SQL injections. this research study examines code specifically designed to identify and prevent SQL injection attacks. Various supervised Machine learning techniques and Convolutional Neural Network (CNN) models are employed to assess the model. the CNN model that was suggested exhibited a notable accuracy rate of 91% and outperformed other machine learning algorithms. Furthermore, the report gives a comprehensive analysis of several machine learning algorithms employed for the detection of SQL injection attacks. the study evaluates the effectiveness of different methods in detecting SQL injection attacks using F1 Score, accuracy, recall and precision metrics. Also compares the performance of machine learning and CNN models. © 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 Efficient Hybrid Model for Federated learning Systems to Deal with Medical Heterogeneous Datasets 4

An Efficient Hybrid Model for Federated Learning Systems to ...

引用

4th international conference of Science and Information Technology in smart Administration, ICSINTESA 2024

作者： Saad, Tiba Al-Libawy, Hilal University of Babylon College of Engineering Department of Electrical Engineering Babylon Iraq

ISBN: (纸本)9798350376111

Federated learning (FL) is a popular topic for developing Artificial Intelligence (AI) applications. this technology trains its models using data from many clients working together without sharing their data. Data privacy is protected by local training. Because this technology is new, researchers had difficulty dealing with heterogeneous data across clients. Non-identical, independent (non-IID) distribution and data type changes across clients may affect the global model predictions. this study examined how to handle clients with diverse data in quantity and kind. Datasets have been collected on people infected and not infected with the Coronavirus. Two different types of datasets, X-rays, and CT scans were selected and these datasets have been distributed unevenly among four clients participating in the system. A hybrid model has been built consisting of convolutional neural networks and long short-term memory (CNN&LSTM) to train this dataset and predict the diagnosis of this disease. Excellent result was obtained in all clients, reaching 99% in one of these clients. © 2024 IEEE.

关键词： Federated learning

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91页 << < 4 5 6 7 8 9 10 11 12 13 > >>

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：