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

18,624 篇 会议
113 篇 期刊文献
16 册 图书

馆藏范围

18,753 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

12,057 篇 工学
- 9,596 篇 计算机科学与技术...
- 5,512 篇 软件工程
- 3,082 篇 电气工程
- 2,954 篇 控制科学与工程
- 2,531 篇 信息与通信工程
- 963 篇 仪器科学与技术
- 941 篇 交通运输工程
- 934 篇 机械工程
- 643 篇 生物工程
- 632 篇 电子科学与技术（可...
- 561 篇 动力工程及工程热...
- 541 篇 生物医学工程（可授...
- 491 篇 安全科学与工程
- 395 篇 石油与天然气工程
- 394 篇 网络空间安全
- 259 篇 光学工程
3,012 篇 管理学
- 2,264 篇 管理科学与工程(可...
- 1,139 篇 图书情报与档案管...
- 868 篇 工商管理
2,970 篇 理学
- 1,521 篇 数学
- 791 篇 生物学
- 506 篇 统计学（可授理学、...
- 491 篇 物理学
- 398 篇 化学
- 393 篇 系统科学
622 篇 医学
- 509 篇 临床医学
- 444 篇 基础医学(可授医学...
- 264 篇 公共卫生与预防医...
333 篇 法学
- 273 篇 社会学
279 篇 经济学
- 274 篇 应用经济学
173 篇 教育学
150 篇 农学
33 篇 文学
31 篇 军事学
12 篇 艺术学

主题

1,144 篇 data acquisition
762 篇 data mining
572 篇 real-time system...
567 篇 data models
444 篇 intelligent syst...
420 篇 conferences
420 篇 big data
407 篇 cloud computing
375 篇 internet of thin...
361 篇 computational mo...
346 篇 monitoring
321 篇 computer archite...
319 篇 sensor systems
308 篇 machine learning
306 篇 control systems
304 篇 deep learning
304 篇 training
299 篇 feature extracti...
287 篇 robot sensing sy...
284 篇 neural networks

机构

49 篇 university of ch...
42 篇 lviv polytechnic...
30 篇 hubei key labora...
25 篇 school of comput...
20 篇 west ukrainian n...
18 篇 beijing key labo...
17 篇 shenzhen institu...
17 篇 chitkara univers...
16 篇 university of el...
15 篇 school of comput...
15 篇 institute of aut...
14 篇 faculty of compu...
14 篇 school of artifi...
14 篇 shenzhen institu...
14 篇 peng cheng labor...
13 篇 ieee
13 篇 college of compu...
12 篇 key laboratory o...
12 篇 beijing univ pos...
12 篇 yeshwantrao chav...

作者

25 篇 anatoliy sachenk...
22 篇 wu xinyu
18 篇 anatoly sachenko
16 篇 a. sachenko
16 篇 liu yang
16 篇 xiong gang
15 篇 chen chen
13 篇 sachenko anatoli...
12 篇 xinyu wu
12 篇 li yang
12 篇 yang yang
12 篇 wang wei
11 篇 zhang tao
11 篇 wang lei
11 篇 li peng
11 篇 li li
11 篇 kurosh madani
11 篇 sachenko a.
11 篇 wu bin
11 篇 iryna turchenko

语言

17,862 篇 英文
824 篇 其他
83 篇 中文
2 篇 西班牙文

检索条件"任意字段=IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems"

共 18753 条记录，以下是1021-1030 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：

Optimizing Production and Inventory Management for Defective Items in Manufacturing systems 3

Optimizing Production and Inventory Management for Defective...

引用

3rd international conference on intelligent systems, advanced computing, and Communication, ISACC 2025

作者： Ahmed, Khandakar Rabbi Hossain, Arafat Asif, MD Amaddus Bepary Mohammad, Mahathir Rahaman, Mustafizur Dewan, MD Arafat Miyan Research Institute International University of Business Agriculture and Technology Dhaka Bangladesh Central Michigan University Dept. of Business Data Analytics Mt Pleasant United States Southern California State University Dept. of Business Administration and Management Los AngelesCA United States Southern California State University Dept. of Business Administration and Management United States Westcliff University Dept. of Cloud Engineering IrvineCA United States Los Angeles City College Dept. of Computer Science Los Angeles United States

ISBN: (纸本)9798331523893

Manufacturing defective items is one of the challenges for production efficiency and inventory control. Conventional approaches like Economic Order Quantity (EOQ) and Just-in-Time (JIT) often fall short of the flexibility needed to respond to quality variations in real time. It promotes defect detection and control by employing machine learning (ML) for inventory management. Four classifiers were tested using the UCI SECOM dataset (Bagging, AdaBoost, Gradient Boosting, and Random Forest) to identify defective items. We used effective preprocessing techniques to boost model performance, such as SMOTE for class balancing and PCA for reducing dimensionality and standardization. The bagging and random forest classifiers produced 96.6% and 96.9% test accuracies, with good precision and recall scores. Within this context, we propose an Adaptive Inventory Management Framework comprising machine learning algorithms incorporating predictive analytics to reduce waste, optimize production scheduling(s), and improve resource allocation. These results are consistent with defining Industry 4.0 strategies and show that ML has the potential to transform defect management and inventory optimization in manufacturing systems. © 2025 ieee.

关键词： Industry 4.0

来源：评论

学校读者我要写书评

暂无评论

Analysis of Digital Transformation Framework and Implementation Pathway for Power Grids in the Context of New Power systems 4

Analysis of Digital Transformation Framework and Implementat...

引用

4th international conference on intelligent Power and systems, ICIPS 2024

作者： Gong, Xianfu Du, Zhanchao Li, Yaodong Hou, Jinxiu Peng, Bo Guangdong Power Grid Corporation CSG Grid Planning & Research Center Guangzhou China China Electric Power Planning & Engineering Institute Beijing China

ISBN: (纸本)9798331532765

The rise of new power systems, largely driven by renewable energy adoption and advanced grid interconnectivity, has introduced complexities in managing power grids. Digital transformation provides tools for real-time monitoring, adaptive control, and enhanced reliability, addressing the demands of modern power systems. This study presents a comprehensive framework for digital transformation in power grids, exploring specific pathways for implementing AI, IoT, and big data analytics to improve operational efficiency and adaptability. Using simulated data, we evaluate the framework's impact on load forecasting accuracy, asset management, and grid optimization. Results show that adopting a structured digital transformation framework enhances grid resilience, optimizes renewable integration, and supports sustainable energy goals. Policy recommendations for supporting digital grid infrastructure are also provided. © 2024 ieee.

关键词： Power grids

来源：评论

学校读者我要写书评

暂无评论

advanced Deep Learning Approaches for Fault Detection and Localization in Power Distribution systems 3

Advanced Deep Learning Approaches for Fault Detection and Lo...

引用

3rd ieee international conference on Power Electronics, intelligent Control and Energy systems, ICPEICES 2024

作者： Sharma, Nitin Pankaj Rai, J.N. Nagarajan, S.T. Delhi Technological University Department of Electrical Engineering Delhi India

ISBN: (纸本)9798350387193

The usage of Artificial Neural Networks (ANN) in improving electricity gadget operations is a burgeoning field of study, specifically within the context of fault detection and localization in strength distribution networks. This studies investigates the utility of ANNs to plot more efficient and correct methodologies for pinpointing disruptions within energy traces. Employing the Levenberg-Marquardt algorithm inside a MAT LAB environment, the look at entails the development and schooling of an ANN version, which is intricately designed with various configurations of hidden layers and neurons. data preprocessing is a crucial step to nice-music the model's overall performance. The findings of this studies imply a vast improvement in the detection and localization of faults over traditional methods, with the ANN model showing superior precision and swiftness. These promising effects suggest for persisted studies into ANN programs in strength structures, suggesting a capability paradigm shift in future energy device management and upkeep protocols. © 2024 ieee.

关键词： Power distribution faults

来源：评论

学校读者我要写书评

暂无评论

Secure data Transmission in IIoT Using Blockchain Based BI-LSTM

Secure Data Transmission in IIoT Using Blockchain Based BI-L...

引用

2024 international conference on Advancement in Renewable Energy and intelligent systems, AREIS 2024

作者： Skaria, Teena Bamini, A. M. Anusha Chitra, R. Karunya Institute of Technology and Sciences Division of Cse Coimbatore India

ISBN: (纸本)9798350387230

The rapid emergence of the Industrial Internet of Things created an exponential increase in data generation and transmission, posing significant challenges in ensuring data security and integrity. Traditional centralized cloud architectures often struggle with issues related to latency, bandwidth, and vulnerability to cyberattacks. The suggested work presents a Block Chain based data transmission using Deep Learning approach. The solution utilizes BC's decentralized and immutable nature for providing data integrity, and the Bidirectional Long Short Term Memory model enhances predictive capabilities for robust anomaly detection and security threat identification. By combining these technologies, the suggested framework efficiently overcome unauthorized data access and addresses risks of data tampering. Experimental results demonstrate significant improvements in data security, transmission speed, and reliability, proving its suitability for diverse IIoT applications. This approach contributes to make a secure, transparent, and efficient IIoT environment and provides industrial digitalization with better trust and resilience. © 2024 ieee.

关键词： Fog computing

来源：评论

学校读者我要写书评

暂无评论

PTP-Synchronized Tri-Level Sync Generation for Networked Multi-Sensor systems 30

PTP-Synchronized Tri-Level Sync Generation for Networked Mul...

引用

30th ieee international conference on Embedded and Real-Time computing systems and Applications (RTCSA)

作者： Riggers, Christoph Schleusner, Jens Renke, Oliver Blume, Holger Leibniz Univ Hannover Inst Microelect Syst Hannover Germany

ISBN: (纸本)9798350387964;9798350387957

Synchronization of sensor devices is crucial for concurrent data acquisition. Numerous protocols have emerged for this task, and for some multi-sensor setups to operate synchronized, a conversion between deployed protocols is needed. This paper presents a bare-metal implementation of a Tri-Level Sync signal generator on a microcontroller unit (MCU) synchronized to a master clock via the ieee 1588 Precision Time Protocol (PTP). Cameras can be synchronized by locking their frame generators to the Tri-Level Sync signal. As this synchronization depends on a stable analog signal, a careful design of the signal generation based on a PTP-managed clock is required. The limited tolerance of a camera to clock frequency adjustments for continuous operations imposes rate-limits on the PTP-controller. Simulations using a software model demonstrate the resulting controller instabilities from rate-limiting. This problem is addressed by introducing a linear prediction mode to the controller, which estimates the realizable offset change during rate-limited frequency alignment. By adjusting the frequency in a timely manner, a large overshoot of the controller can be avoided. Additionally, a cascading controller design that decouples the PTP from the clock update rate proved to be advantageous to increase the camera's tolerable frequency change. This paper demonstrates that a MCU is a viable platform to perform PTP-synchronized Tri-Level Sync generation. Our open source implementation is available for use by the research community at https://***/IMS-AS-LUH/t41-tri-sync-ptp.

关键词： Precision Time Protocol PTP Tri-Level Sync camera SMPTE PI-controller synchronization MCU

来源：评论

学校读者我要写书评

暂无评论

Federated Learning Empowered Resource Allocation in UAV-Assisted Edge intelligent systems 3

Federated Learning Empowered Resource Allocation in UAV-Assi...

引用

3rd ieee international conference on Computer Communication and Artificial Intelligence, CCAI 2023

作者： Hu, Bintao Isaac, Matilda Akinola, Olukunle Mobolaji Hafizh, Hadyan Zhang, Wenzhang Xi'an Jiaotong-Liverpool University School of Internet of Things suzhou China

ISBN: (纸本)9798350335262

Mobile edge computing (MEC) has been considered a promising advanced technology to support delay-sensitive tasks of user equipment (UE) in the internet of things (IoT) systems, it is necessary to allow multiple UEs to offload their computationally intensive tasks to a flexible edge computing server, such as an unmanned aerial vehicle (UAV)-assisted edge computing server. However, most existing works mainly focused on minimising energy consumption under the transmission and/or processing delay constraints while ignoring privacy-preserving, which will be challenging when dealing with large volumes of raw data. In this paper, we consider a federated learning (FL) empowered UAV-assisted edge intelligent system to minimise the maximum utility cost (which indicates the relationship between latency and energy consumption) to the selected UE for task processing. We propose to jointly optimise the FL task offloading decisions among all UEs and the communication resource allocation under each epoch. This is achieved by devising a federated learning-based edge intelligence offloading decision optimisation algorithm (FEOA). Simulation results show that our proposed schemes outperform the benchmarks in terms of the maximum cost efficiency among all UEs. © 2023 ieee.

关键词： Resource allocation

来源：评论

学校读者我要写书评

暂无评论

DriverSense: A Multi-Modal Framework for advanced Driver Assistance System 16

DriverSense: A Multi-Modal Framework for Advanced Driver Ass...

引用

16th international conference on COMmunication systems and NETworkS, COMSNETS 2024

作者： Vyas, Daiwat Amit Chaturvedi, Manish Institute Infrastructure Technology Research and Management Gujarat India Institute of Technology Nirma University Ahmedabad India Institute of Infrastructure Technology Research and Management Department of Computer Science and Engineering Gujarat India

ISBN: (纸本)9798350383119

Driver distraction, lack of concentration, and increased stress levels are the primary reasons for road accidents. The advanced Driver Assistance System (ADAS) is used in high-end cars to improve the safety of drivers. These systems use an in-vehicle camera to track the eye movement of a driver and analyze the facial expressions to classify the driver's attention level, mood and/or drowsiness. However, these computer vision-based solutions do not classify the stress and distraction level of a driver which are the major causes of fatality. Further, no ADAS is available to the best of our knowledge for two-wheeler (2W) and three-wheeler (3W) vehicle drivers who represent 80% of the driver population in India. These drivers are exposed to more distractions, stress, and risk due to an open environment. Accordingly, this paper proposes DriverSense, a wearable device based vehicle independent framework for ADAS that uses mobility sensors (e.g., gyroscope, accelerometer, GPS, etc.) and physiological sensors (e.g., EEG, PPG, ECG, SPO2, etc.) to detect aggressiveness and stress level of drivers in real time. The framework employs edge computing to reduce communication delays, and machine learning models for computing inferences related to driver behavior. The results of preliminary experiments conducted using the existing datasets and the data of mobility sensors collected in Ahmedabad city of India are encouraging. The aggressiveness of the drivers could be classified with 86.05% accuracy, whereas the stress level was identified with 88.24% accuracy using existing machine learning algorithms. © 2024 ieee.

关键词： advanced Driver Assistance System (ADAS) Driver Behavior Analysis (DBA) intelligent Transportation systems (ITS) Mobility Sensors Physiological Sensors

来源：评论

学校读者我要写书评

暂无评论

Utilizing Web Scraping and Machine Learning for Improving Accuracy of Smartphone Price Prediction

Utilizing Web Scraping and Machine Learning for Improving Ac...

引用

2024 international conference on Advances in data Engineering and intelligent computing systems, ADICS 2024

作者： Vasanth Kumar, V. Tamizhselvan, C. Manoharan, L. Vishnu Sekhar, R. Vinoth Kumar, V. Hindustan Institute Of Technology And Science Department Of Electronics And Communication Engineering Chennai India School Of Computing Srm Institute Of Science And Technology Department Of Data Science And Business Systems Kattankulathur India Hindustan Institute Of Technology And Science Department Of Computer Science And Engineering Chennai India School Of Bioengineering Srm Institute Of Science And Technology Integrated Bioprocessing Laboratory Department Of Biotechnology Kattankulathur India

ISBN: (纸本)9798350364828

Mobile prices play a pivotal role in determining their popularity amongst consumers and their competitive standing within the market. As customers consider their budget while evaluating a mobile phone's specifications and design, estimating the price beforehand becomes essential to cater to their needs and expectations. Hence, accurately forecasting mobile phone prices is a vital step in the product launch process to remain competitive and assess the market dynamics and competitors. The primary aim of this research is to determine the true market value of mobile phones. In this research, the dataset was extracted by means of utilizing a web scraping process from the flipkart website. The main objective of this research is to fetch the most recent dataset based on the most recent features. The extracted dataset is fitted into regression models such as linear regression, decision tree regressor, random forest regressor, KNN regressor, and gradient boosting regressor and performs the comparative analysis. The models are evaluated based on the mean absolute error metric. © 2024 ieee.

关键词： Decision trees

来源：评论

学校读者我要写书评

暂无评论

Convolutional Neural Network-Based Multi-Fruit Classification and Quality Grading with a Gradio Interface

Convolutional Neural Network-Based Multi-Fruit Classificatio...

引用

2024 international conference on Innovative computing, intelligent Communication and Smart Electrical systems, ICSES 2024

作者： Nandhini, E. Vadivu, G. School of Computing Srm Institute of Science and Technology Department of Data Science and Business Systems Kattankulathur Chennai India

ISBN: (数字)9798331543624

ISBN: (纸本)9798331543617

Agricultural products are experiencing significant losses, especially after the harvesting phase, which is the period from fruit storage to the product reaching the consumer's hands. A lack of human resources, time consumption, product handling, and human errors during the post-harvest stage of the fruit grading and sorting process result in huge losses. Deep learning (DL) offers an automated process for classifying and identifying fruits. Developing an architecture for a VGG16 convolutional neural network (CNN) within the Gradio user interface, utilizing five distinct fruit types as the model's dataset, such as apple, banana, guava, orange, apple, and pomegranate. For five different sets of fresh and defect fruits, the proposed model got 91.1% and 89.1% of test accuracy for multi-fruit clas- sification and fruit status prediction, respectively. This machine- based automated model has the potential to reduce losses and enhance fruit grading and sorting efficiency, thereby significantly impacting sustainable and productive agricultural industries through increased productivity. © 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

data-Based Adaptive Optimal Regulation of Smart Grid with Renewable Power and Energy Storage 5

Data-Based Adaptive Optimal Regulation of Smart Grid with Re...

引用

5th ieee international conference on Power, intelligent computing and systems, ICPICS 2023

作者： Wu, Yingjun Chen, Ji Xu, Guowang Zhou, Fei Lin, Chaoyong State Grid Ningbo Electric Supply Company Ningbo China Glory Property Branch of Ningbo Power Transmission and Transformation Construction Co. Ltd. Ningbo China

ISBN: (纸本)9798350333442

The adaptive optimization and regulation of electricity can promote the development and construction of smart grids. In this paper, a data based heuristic dynamic programming (HDP) algorithm is proposed, which can obtain the optimal control strategy of smart grid without knowing the specific model, and overcome the difficulty of obtaining the accurate model of smart grid. Firstly, the working principles of the smart grid and its equipment were introduced. Secondly, a data-based HDP algorithm is proposed for the adaptive optimization problem of smart grids. Finally, the effectiveness of the algorithm was verified through simulation examples. © 2023 ieee.

关键词： Smart power grids

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 << < 99 100 101 102 103 104 105 106 107 108 > >>

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：