检索结果-内蒙古大学图书馆

6th International Conference on Smart Power and Internet Energy Systems, SPIES 2024

作者： Amin, Mahmoud M. Jacob, Aleena Elmorshedy, Mahmoud F. El-Sousy, Fayez F. M. Bhaskar, M.S. Almakhles, Dhafer Manhattan University Manhattan Electrical and Computer Engineering Department RiverdaleNY10471 United States College of Engineering Prince Sultan University Renewable Energy Lab. Riyadh Saudi Arabia Faculty of Engineering Tanta University Electrical Power and Machines Engineering Department Tanta Egypt Prince Sattam bin Abdulaziz University Electrical Engineering Department Al-Kharj16273 Saudi Arabia

ISBN: (纸本)9798350368864

This paper discusses a speed estimation approach that eliminates the need for mechanical sensors to measure the speed of Permanent Magnet Synchronous Generators (PMSGs), commonly utilized in stand-alone power generation systems. The method described utilizes a sensorless technique stemming from an adaptive model reference system (MRAS) to estimate speed. The proposed system includes a wind turbine, switching rectifier, battery storage system, PMSG, bidirectional converter, LC filter, voltage source inverter (VSI), and a three-phase load. Its three primary objectives are to achieve maximum power point tracking (MPPT), regulate the DC link voltage, and preserve a constant magnitude and frequency of the output load voltage. The MRAS not only estimates the PMSG speed but also provides feedback for the MPPT control loop, employing a flow-chain approach. The success of the suggested control strategy and system is validated through various simulations and experiments, which demonstrate the reliability of the estimation method and control approach. © 2024 IEEE.

关键词： Rectifying circuits

来源：评论

学校读者我要写书评

暂无评论

Flexible Localization Method with Motion Estimation for Underwater Wireless Sensor Networks 26

Flexible Localization Method with Motion Estimation for Unde...

引用

26th International Conference on Advanced Communications Technology, ICACT 2024

作者： Ismail, A.S. Hawbani, Ammar Wang, Xingfu Aziz, Samah Abdel Zhao, Liang Saeed, Nasir School of Computer Science and Technology University of Science and Technology of China Anhui Hefei230027 China Zagazig University Faculty of Science Zagazig44519 Egypt School of Computer Science Shenyang Aerospace University Shenyang110136 China United Arab Emirates University Department of Electrical and Communication Engineering Al Ain15551 United Arab Emirates

ISBN: (纸本)9791188428120

Due to the challenging conditions of underwater environments, such as node mobility and large-scale networks, achieving localization in large-scale mobile underwater sensor networks (UWSN) is a difficult task. This paper introduces a scheme known as the Flexible Localization Method with Mobility Estimation (FLMME) for UWSNs by utilizing the expected mobility patterns of underwater objects. FLMME performs localization hierarchically by splitting the process into anchor and ordinary node localization. Each node estimates its next mobility pattern based on previous location information, enabling estimates about its next location. Anchor nodes, holding known locations, manage the localization process to balance accuracy and error trade-offs. Extensive simulations demonstrate that FLMME reduces localization errors and hence increases localization accuracy. © 2024 Global IT Research Institute - GIRI.

关键词： Location

来源：评论

学校读者我要写书评

暂无评论

Inculcation of Sensors in Enhancing Smart Cities: A Review

Inculcation of Sensors in Enhancing Smart Cities: A Review

引用

International Conference on Power Energy, Environment and Intelligent Control (PEEIC)

作者： Trupti V Nandikolmath Sandeep Kumar Jain Savita Yadav Department of Electrical and Electronics Engineering Faculty of Engineering and Technology JAIN (Deemed to be University) Bangalore India Department of Electrical Engineering Vivekananda Global University Jaipur India Department of Computer Science and Engineering (lOT) Noida Institute of Engineering & Technology Greater Noida Uttar Pradesh India

By 2050, experts predict that 75% of people on Earth will live in cities. As such, cities need to be prepared to fulfill the needs of their citizens and provide the best possible services. The idea of a “smart city,” which is an improved system that effectively manages its resources and services via monitoring and communication technology, is often central to the notion of an advanced city. Thus, turning cities into smart entities is a critical step toward global urban sustainability. Beyond creating smart buildings in cities, the main goal is to improve people's quality of life by using newly developed digital technologies and sensing capabilities. The key to smarter communities is their capacity to invest in these technologies, adapt, and socialize in a transparent and inclusive manner while taking into account the needs and values of the local and regional communities. Despite these developments, privacy issues and interruptions in cyber security remain serious weaknesses that need addressed.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Diabetes Prediction Using Machine Learning Techniques: A Case Study from Jordan

Diabetes Prediction Using Machine Learning Techniques: A Cas...

引用

Information Technology (ACIT)

作者： Raed Alazaidah Radwan Batyha Ghassan Samara Esraa Al Henawi Maram Y. Al-Safarini Ahmad A. Samhan Ali Elrashidi Mo’Ath Alluwaici Deana Al-Omari Department of Data Science and AI Faculty IT Zarqa University Zarqa Jordan Department of Computer Science Faculty of IT Applied Science Private University Amman Jordan Department of Computer Science Faculty of IT Zarqa University Zarqa Jordan Department of Software Engineering Faculty of IT Zarqa University Zarqa Jordan Department of Electrical Engineering University of Business and Technology Jeddah Saudi Arabia

ISBN: (数字)9798331540012

ISBN: (纸本)9798331540029

Diabetes is one of the most common diseases in Jordan. It is the main reason of death among Jordanian adult citizens. Worldwide, 48% of all deaths are due to Diabetes occurred before the age of 70 years. Hence, this research is interested in the early prediction of this disease among Jordanian people. To achieve this main objective, Machine Learning (ML) is utilized through a large number of classification models and considering five well-known evaluation metrics. These classification models have been trained on a primary dataset that has been collected for the purpose of the research. The results revealed that BayesNet and NaiveBayes are the best classification models to handle the task of the early prediction of Diabetes in Jordan

关键词： Measurement Machine learning Predictive models Diabetes Bayes methods Information technology Diseases

来源：评论

学校读者我要写书评

暂无评论

Enhancing Machine Learning Performance through Intelligent Data Quality Assessment: An Unsupervised Data-centric Framework

arXiv

引用

arXiv 2025年

作者： Rahal, Manal Ahmed, Bestoun S. Szabados, Gergely Fornstedt, Torgny Samuelsson, Jörgen Department of Mathematics and Computer Science Karlstad University Universitetsgatan 2 Karlstad65188 Sweden Department of Computer Science Faculty of Electrical Engineering Czech Technical University Prague16627 Czech Republic Department of Engineering and Chemical Sciences Universitetsgatan 2 Karlstad65188 Sweden

Poor data quality limits the advantageous power of Machine Learning (ML) and weakens high-performing ML software systems. Nowadays, data are more prone to the risk of poor quality due to their increasing volume and complexity. Therefore, tedious and time-consuming work goes into data preparation and improvement before moving further in the ML pipeline. To address this challenge, we propose an intelligent data-centric evaluation framework that can identify high-quality data and improve the performance of an ML system. The proposed framework combines the curation of quality measurements and unsupervised learning to distinguish high- and low-quality data. The framework is designed to integrate flexible and general-purpose methods so that it is deployed in various domains and applications. To validate the outcomes of the designed framework, we implemented it in a real-world use case from the field of analytical chemistry, where it is tested on three datasets of anti-sense oligonucleotides. A domain expert is consulted to identify the relevant quality measurements and evaluate the outcomes of the framework. The results show that the quality-centric data evaluation framework identifies the characteristics of high-quality data that guide the conduct of efficient laboratory experiments and consequently improve the performance of the ML system. Copyright © 2025, The Authors. All rights reserved.

关键词： Data quality

来源：评论

学校读者我要写书评

暂无评论

Using Arduino Iot Modules As A Low Cost Environmental Research Monitoring System 1

Using Arduino Iot Modules As A Low Cost Environmental Resear...

引用

1st International Conference on computer Science and Emerging Technologies, CSET 2023

作者： Magableh, Murad Marie, Ziyad Mohamed, Rajina R. Bin Ibrahim, Mohd Hafizuddin Jusoh, Julaily Aida Kumar, Rohit Irbid National University Faculty of Business and Financial Science MIS BI and Data Analysis Department Irbid Jordan Al-Istiqlal University Faculty of Administrative Sciences and Informatics Public Administration Department Palestine College of Computing Dan Informatics Universiti Tenaga Nasional Malaysia Politeknik Kuala Terenngganu Department of Electrical Engineering Kuala Terengganu20200 Malaysia UniSZA Faculty of Informatics and Computing Malaysia School of Computer Science and Engineering Jain Deemed to Be University Bangalore India

ISBN: (纸本)9798350341737

Environmental monitoring plays a crucial role in understanding the impact of human activities on our ecosystems. However, the cost and complexity of traditional monitoring systems often hinder widespread deployment, especially in resource-constrained regions. This research paper explores the feasibility and effectiveness of employing Arduino Internet of Things (IoT) modules as a low-cost alternative for environmental research monitoring. The study focuses on designing and implementing an Arduino-based environmental monitoring system capable of gathering real-time data on key environmental parameters, such as temperature, humidity, air quality, and soil moisture. The hardware setup comprises Arduino microcontrollers interfaced with a range of environmental sensors and connectivity modules for data transmission. To assess the system's reliability and accuracy, a series of field experiments were conducted in diverse environmental settings, including urban areas, agricultural zones, and natural habitats. The collected data was compared against measurements from conventional monitoring equipment to validate the Arduino-based system's performance. The research demonstrates that the Arduino IoT modules can effectively monitor and transmit environmental data with a reasonable level of accuracy and stability, making them suitable for various environmental research applications. The low-cost nature of Arduino components and the open-source ecosystem facilitate customization and scalability, enabling researchers and organizations to develop tailored monitoring solutions for specific environmental contexts. Additionally, the paper discusses the challenges and limitations encountered during the deployment of Arduino-based monitoring systems, including power constraints, sensor calibration, and data processing techniques. Furthermore, it explores potential avenues for improvement and optimization to enhance the system's capabilities and data accuracy. In conclusion, this research

关键词： Internet of things

来源：评论

学校读者我要写书评

暂无评论

Stability enhancement of power system with the implementation of power system stabilizer PSS and excitation system IEEE Type-1 15

Stability enhancement of power system with the implementatio...

引用

15th International engineering and Computing Research Conference, EURECA 2021

作者： Khujaev, Abumuslim Vaithilingam, Chockalingam Aravind Alsakati, Ahmad Adel Alnasseir, Jamal School of Computer Science and Engineering Faculty of Innovation and Technology Taylor's University Malaysia Electric Power Engineering Department Faculty of Mechanical and Electrical Engineering Damascus University Syria

Stability of power system is an ability of an electric power system that reaches its stable condition after fault happens in its network. The system is unstable when one generator loses its stable synchronism performance. This paper investigates the transient stability of an IEEE 9-bus system during faults that happen in different bus locations. Additionally, the analysis contributes to the integration of the exciter IEEE type-1 for synchronous generator and integration of power system stabilizer (PSS) to improve the power angle stability in the power system. The fault at bus 4 has the highest amplitude in which it increases to 77.58 degrees for the power angle of Synchronous Generators (SGs). The absence of PSS showed that the existing system oscillated and it is unstable. However, the integration of PSS enables the system to damp the oscillations of power angle and reduce the settling time to 5.69 seconds during the fault at bus 4. Moreover, the PSS is connected to SGs through the excitation system to improve the stability of the system in relative power angle of SGs, speed deviation, and electrical power of SGs. Hence, the integration of PSS and excitation system enhances the transient stability of the power system. © 2021 Institute of Physics Publishing. All rights reserved.

关键词： Synchronous generators

来源：评论

学校读者我要写书评

暂无评论

Multi-Objective Optimization for Neural Network Structure

Multi-Objective Optimization for Neural Network Structure

引用

International CSI computer Conference, CSICC

作者： Maryam Shokoohi Mohammad Teshnehlab Department of Computer Engineering Technical and Vocational University (TVU) Tehran Iran Faculty of Electrical and Computer Engineering K.N. Toosi University of Technology Tehran Iran

This study presents a new algorithm for training flexible perceptron multilayer neural networks. This algorithm is based on the multi-objective evolutionary optimization and tries to find the smallest optimal structure simultaneously by reducing the network error. In this method, a compatibility is established between the mean squared error and the vector length of the parameters of the activation functions by using flexible neurons which cause a greater degree of freedom leading to a faster convergence of the neural network. Then, the network structure decreases and the problem of overfitting and local minimum is prevented based on the values of these parameters and the use of the integration method of neurons. Moreover, it increases the power of the generalizability of the neural network. This method was used for classification problems, and the results were compared with AMGA, BCPA, LASSO, and Early Stopping methods. Based on the results, the algorithm proposed in this study usually works better compared to the similar algorithms. In addition, the proposed algorithm is a systematic method for finding the optimal neural network structure.

关键词： Training Deep learning Systematics Heuristic algorithms Neurons Evolutionary computation Nonhomogeneous media

来源：评论

学校读者我要写书评

暂无评论

Elderly Fall Detection by Sensitive Features Based on Image Processing and Machine Learning

引用

Artificial Intelligence Advances 2022年第1期4卷 9-16页

作者： Mohammad Hasan Olyaei Ali Olyaei Sumaya Hamidi Faculty of Electrical Engineering Sadjad University of TechnologyMashhadIran Department of Computer Engineering Faculty of EngineeringFerdowsi University of MashhadMashhadIran ARIVET Project MashhadIran

The world’s elderly population is growing every *** is easy to say that the fall is one of the major dangers that threaten *** paper offers a Trained Model for fall detection to help the older people live comfortably and alone at *** purpose of this paper is to investigate appropriate methods for diagnosing falls by analyzing the motion and shape characteristics of the human *** machine learning technologies have been proposed for automatic fall *** proposed research reported in this paper detects a moving object by using a background subtraction algorithm with a single *** next step is to extract the features that are very important and generally describe the human shape and show the difference between the human falls from the daily *** features are based on motion,changes in human shape,and oval diameters around the human and temporal head *** features extracted from the human mask are eventually fed in to various machine learning classifiers for fall *** results showed the efficiency and reliability of the proposed method with a fall detection rate of 81%that have been tested with UR Fall Detection dataset.

关键词： Human fall detection Machine learning computer vision Elderly

来源：评论

学校读者我要写书评

暂无评论

Federated Learning in Mobile Networks: A Comprehensive Case Study on Traffic Forecasting

arXiv

引用

arXiv 2024年

作者： Pavlidis, Nikolaos Perifanis, Vasileios Yilmaz, Selim F. Wilhelmi, Francesc Miozzo, Marco Efraimidis, Pavlos S. Koutsiamanis, Remous-Aris Mulinka, Pavol Dini, Paolo Department of Electrical and Computer Engineering Democritus University of Thrace Xanthi Greece Department of Electrical and Electronic Engineering Imperial College London London United Kingdom Barcelona Spain Nokia Bell Labs Stuttgart Germany Department of Automation Production and Computer Sciences IMT Atlantique Inria LS2N Nantes France

The increasing demand for efficient resource allocation in mobile networks has catalyzed the exploration of innovative solutions that could enhance the task of real-time cellular traffic prediction. Under these circumstances, federated learning (FL) stands out as a distributed and privacy-preserving solution to foster collaboration among different sites, thus enabling responsive near-the-edge solutions. In this paper, we comprehensively study the potential benefits of FL in telecommunications through a case study on federated traffic forecasting using real-world data from base stations (BSs) in Barcelona (Spain). Our study encompasses relevant aspects within the federated experience, including model aggregation techniques, outlier management, the impact of individual clients, personalized learning, and the integration of exogenous sources of data. The performed evaluation is based on both prediction accuracy and sustainability, thus showcasing the environmental impact of employed FL algorithms in various settings. The findings from our study highlight FL as a promising and robust solution for mobile traffic prediction, emphasizing its twin merits as a privacy-conscious and environmentally sustainable approach, while also demonstrating its capability to overcome data heterogeneity and ensure high-quality predictions, marking a significant stride towards its integration in mobile traffic management systems. © 2024, CC BY.

关键词： 5G mobile communication systems

来源：评论

学校读者我要写书评

暂无评论

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：

请选择收藏分类：

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

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：