检索结果-内蒙古大学图书馆

The Determination of the Critical Frequency Limitation Time According to Penetration and Switching of Photovoltaic systems and the Analysis of Their Transient Effects

引用

Transactions of the Korean Institute of Electrical Engineers 2023年第3期72卷 341-348页

作者： Jang, Jiyeon Kim, Insu Department of Electrical and Computer Engineering Inha University Korea Republic of Dept. of Electrical Engineering Inha University Korea Republic of

For carbon neutrality, many countries are increasing the rate of renewable energy-based distributed generators (DGs). The DG has advantages such as voltage drop compensation and power loss reduction. However, reverse current flows and overvoltage phenomenons occur due to the penetration of DGs. DGs have different output characteristics from synchronous generators, so when DGs penetrate the grid, DGs inevitably affect the power flow and power quality of the grid. Therefore, it is necessary to check transient stability when DGs penetrate the power system. In this study, the IEEE 9-bus system, a looped system, was set as a testbed. In addition, inverter-based photovoltaic (PV) systems were used as an example of DGs. And the critical frequency limitation time was determined according to the penetration level of DGs. This study also checked the effect of reducing frequency variations through specific methodology of the PV system. Events such as fault occurrence, switch opening, fault clearing, and switch closing were set. And all the simulations for the transient analysis were conducted through DIgSILENT Power Factory. Copyright © The Korean Institute of Electrical Engineers.

关键词： Transient analysis

来源：评论

学校读者我要写书评

暂无评论

A Survey on Artificial Intelligence-Based Cyber Security in IoT Networks 2

A Survey on Artificial Intelligence-Based Cyber Security in ...

引用

2nd IEEE International Conference on Device Intelligence, Computing and Communication Technologies, DICCT 2024

作者： Tyagi, Akshit Singh, Aniket Yadav, Amit Mehra, Pawan Singh Delhi Technological University Dept. of Computer Engineering New Delhi India

ISBN: (纸本)9798350372847

With the growth of network technologies and the increase in data transmission, cyber threats have become more complicated. Artificial Intelligence allows automated detection of cyber-attacks, which is important for IoT security. To achieve this, this research examines the application of deep learning and machine learning methods to DoS protection strategies for the IoT. The study uses performance metrics, and validation methods to stimulate further research on IoT security and intrusion detection systems using ensemble learning. The objective of this study was to explore and enhance the present state of knowledge regarding IoT Security, as well as to produce intrusion detection systems employing ensemble learning. We conducted a comprehensive survey of existing literature by various authors, without undertaking any original experimentation. © 2024 IEEE.

关键词： Cybersecurity

来源：评论

学校读者我要写书评

暂无评论

The Effect of Mode of Control on Voltage Stability in DC Micro-grids Operating with Constant Power Loads 33

The Effect of Mode of Control on Voltage Stability in DC Mic...

引用

33rd Southern African Universities Power engineering Conference, SAUPEC 2025

作者： Zheve, Leon T. Gitau, Michael N. Masike, Lebogang University of Pretoria Dept. of Electrical Electronic and Computer Engineering Pretoria South Africa

ISBN: (纸本)9798331535162

The penetration of renewable energy systems has helped trigger the shift to DC distribution systems. Switching converters are the building blocks of DC distribution systems and these individual blocks have their unique control. Manufacturers of these building blocks tend to overlook the effect of coupling converters together that have closed loop control, and integration engineers face the challenge of voltage instability during integration. Load converters operating with closed-loop control behave as constant power loads and have a destabilizing negative incremental resistance that diminishes the damping of the system at the DC bus they are connected. The mode of control also influences how far the action of constant power loads drives the system into instability. This work compares the average current mode control and voltage mode control applied to small DC network to see which control mode is better to implement for DC distribution grids. Simulations of a small single bus DC distribution system comprising of two constant power loads and a source converter were carried out with the objective of comparing the extent of bus voltage deterioration when using either control modes. The simulation results show that for the same system average current mode control is better at maintaining voltage stability compared voltage mode control. © 2025 IEEE.

关键词： DC distribution systems

来源：评论

学校读者我要写书评

暂无评论

GENAIR: GENERATIVE AI FOR RESILIENT URBAN AIR MOBILITY WITH VTOLS IN DISASTER EVACUATION

GENAIR: GENERATIVE AI FOR RESILIENT URBAN AIR MOBILITY WITH ...

引用

2024 Winter Simulation Conference, WSC 2024

作者： Alsaheal, Abdullah Hoy, William Haro, Priscila Rehman, Asad Celik, Nurcin Dept. of Industrial and Systems Engineering University of Miami Coral GablesFL United States Dept. of Mathematics and Computer Science Saint Louis University Madrid Spain

ISBN: (纸本)9798331534202

Coastal regions face growing threats, making timely and safe evacuation paramount. Current plans rely heavily on congested ground transportation, leading to delays and heightened stress levels. The emerging field of Urban Air Mobility (UAM), utilizing Vertical Take-Off and Landing Vehicles (VTOLs), promises to alleviate these issues by providing solutions for quick evacuation strategies. Here, we aim to leverage Generative Adversarial Networks (GANs) to expand limited datasets with synthetic data specific to disaster scenarios, evacuation routes, airspace considerations, and the impact of real-time weather events, enabling robust simulation of UAM deployment in disaster evacuations. We identified two applicable scenarios: i) UAM for Extreme Weather Emergency Evacuation and ii) Hospital Evacuations using VTOLs as use cases and illustrated their impact. This research seeks to pave the way for optimized, data-driven evacuation planning with UAM and VTOLs, ultimately enhancing the safety and efficiency of evacuations in the face of extreme events. © 2024 IEEE.

关键词： Air mobility

来源：评论

学校读者我要写书评

暂无评论

Harmony Forecast: Using Machine Learning to Predict Relationship Quality 1

Harmony Forecast: Using Machine Learning to Predict Relation...

引用

1st IEEE International Conference on Smart Power Control and Renewable Energy, ICSPCRE 2024

作者： Nallagonda, Harshitha Sai Kondra, Varun Teja Gorla, Srinivas Samantula, Mohankrishna Gitam Deemed to be University Dept. of Computer Science and Engineering Visakhapatnam India

ISBN: (纸本)9798350377002

Several things influence human relations. Many of each other's personality traits can have an impact on a relationship between two people. These characteristics have the power to strengthen their love or spark conflict. Personality traits can be used to evaluate the quality of the relationship between the partners. To determine whether the individual will maintain or end the relationship, the relationship's quality has been evaluated based on personality traits. A thorough analysis has been conducted on the personality traits that impact relationships to determine whether they will have an impact, might have an impact or have no impact at all. A study was carried out to investigate the impact of personality traits on relationships. The relationship quality was assessed based on the personality trait which will make the person stay in the relationship, might or might not stay, or not stay in the relationship. The data collected and the pre-existing data combined was used to calculate the relationship quality. © 2024 IEEE.

关键词： Adversarial machine learning

来源：评论

学校读者我要写书评

暂无评论

Real-Time Gaze Tracking for Online Examination

Real-Time Gaze Tracking for Online Examination

引用

2025 International Conference on Pervasive Computational Technologies, ICPCT 2025

作者： Bisht, Preyanshu Kumar, Suresh Netaji Subhas University of Technology Dept. of Computer Science and Engineering Delhi India

ISBN: (纸本)9798331508685

The exponential growth in online education has increased the demand for automated systems to ensure academic integrity during online examinations. A real-time proctoring system addresses this need by monitoring a student's eye gaze and head movements during an exam. This system leverages Dlib's pre-trained frontal face detector and 68-point facial landmark predictor to detect facial features and track the direction of eye movement and head position. By analyzing these metrics, the system can flag behaviors associated with potential cheating, such as looking away from the screen for extended periods. This paper discusses the design and implementation of the proctoring system, details the detection algorithms, and evaluates its effectiveness for real-time monitoring. © 2025 IEEE.

关键词： Online systems

来源：评论

学校读者我要写书评

暂无评论

An Efficient Deep Learning Approach for Jute Pest Classification Using Transfer Learning 6

An Efficient Deep Learning Approach for Jute Pest Classifica...

引用

6th International Conference on Electrical engineering and Information and Communication Technology, ICEEICT 2024

作者： Islam, Muhammad Tanvirul Rahman, Md. Sadekur Daffodil International University Dept. of Computer Science and Engineering Dhaka Bangladesh

ISBN: (纸本)9798350385779

Jute is considered as one of the most vital crops in the world. For some countries jute is the principal source of earnings and GDP. One of the primary elements influencing jute yield is jute pests. Accurate pest identification makes it possible to take prompt preventative action to minimize financial losses. Considering the fact, to classify jute pests, the study suggests different jute pest classification models, which are based on transfer learning. The best model offers high performance and resilience. A VCI-validated dataset comprising 7235 images has been utilized in the analysis. The dataset encompasses images classified into 17 distinct jute pest classes. The dataset is already divided into three categories train, test and validation. To increase the dataset size, data augmentation is applied to the training set. To improve performance, all the models were integrated with the transfer learning model. VGG 16, ResNetl0l, DenseNet201, InceptionV3, Xception, and MobileN etV2 were used to train the parameters on the publicly available ImageN et dataset followed by some customized dense layers. The models were assessed using different types of metrics, including confusion matrix, F1 score, precision, and recall. Compared to other models DenseNet201 outclassed other models, acquiring 97% accuracy. The fundamental information and technical support for jute pest classification are provided by this study. © 2024 IEEE.

关键词： Deep learning

来源：评论

学校读者我要写书评

暂无评论

A Photovoltaic Interleaved Boost Integrated CL Resonant Converter for Magnetron Application

A Photovoltaic Interleaved Boost Integrated CL Resonant Conv...

引用

2024 IEEE Energy Conversion Congress and Exposition, ECCE 2024

作者： Molaei, Aref Kanathipan, Kajanan Lam, John York University Dept. of Electrical Engineering and Computer Science Toronto Canada

ISBN: (纸本)9798350376067

A new single-stage high-gain interleaved boost modular CL resonant converter is proposed in this paper for photovoltaic-powered magnetron application. The proposed converter is able to provide high voltage gain for the magnetron which is a device for microwave applications. Perturb and Observe (P&O) method was used to achieve Maximum Power Point Tracking (MPPT) in the integrated interleaved boost stage by controlling the duty-cycle of the two primary leg switches. The operational principles of the converter are briefly discussed in this paper. Results on a 1.7kW, 230V/3.8kV design are presented to verify the proposed converter performance. © 2024 IEEE.

关键词： Magnetrons

来源：评论

学校读者我要写书评

暂无评论

Structured Implementation of ML Algorithms for Cardiovascular Disease Detection 5

Structured Implementation of ML Algorithms for Cardiovascula...

引用

5th IEEE International Conference on Computing, Power, and Communication Technologies, IC2PCT 2024

作者： Arora, Drishti Asif, Farhan Amity University Dept. of Computer Science & Engineering Uttar Pradesh India

ISBN: (纸本)9798350383522

Cardiovascular diseases encompass a range of medical conditions that impact the heart and blood vessels The prediction of heart disease pose considerable complexity and present a formidable challenge within the medical field According to the WHO, heart diseases are the leading cause of death worldwide, claiming approximately 17.9 million lives each year, accounting for around 31% of all global deaths To address the need for accurate heart disease prediction, extensive research has employed advanced machine learning models This study conducted a comprehensive evaluation of seven distinct classification models, combining various physiological factors with well-known machine learning algorithms The model employed in this study includes Naïve Bayes, Logistic Regression, Decision Trees, Random Forest, XGBoost, CatBoost, and Voting Classifiers Using these models, a robust heart disease prediction system is designed, facilitating precise evaluation of an individual's risk The observation shows that through meticulous evaluation and comparison, the Random Forest algorithm, which is a bagging technique, outperforms the existing state-of-the-art methods It exhibited remarkable accuracy, yielding prediction results of approximately 90.16% This exceptional accuracy establishes the random forest algorithm as the pre-eminent model for precise and reliable heart disease prediction within the scope of this study. © 2024 IEEE.

关键词： Cardiovascular Disease Machine Learning Classifiers Performance Evaluation Predictive Analysis

来源：评论

学校读者我要写书评

暂无评论

A Review on Deep Learning Based Question Answering with Natural Language Processing in Healthcare

A Review on Deep Learning Based Question Answering with Natu...

引用

2024 International Conference on Knowledge engineering and Communication systems, ICKECS 2024

作者： Javeed, Abdul Saleem Gopala Krishnan, C. Gitam School of Technology Dept. of Computer Science & Engineering Bengaluru India

ISBN: (纸本)9798350359688

Over the Internet, an efficient approach and promising solution to retrieve significant information envisages the beginning of Question Answering systems (QAS). Because of data sources availability, the deep learning model based on open domain QAS focuses a substantial quantity of research work. Because of the lack of medical datasets, less attention is received in the medical domain. The deep learning (DL) utility increases the development of huge data in the healthcare domain. In the past years, popularity has grown in hardware parallelism and quick data storage availability. The challenge, pipelines, and tasks involved in medical NLP and medical imaging deploy the existing review of research in this work. The medical NLP and imaging fields deploy DL structures with its extensive survey is presented here. Over all 39 research papers are collected for this survey analysis from the years 2017 to 2023. The diagnosis is enhanced with medical imaging, Natural language processing, and DL combination to detect the appropriate combination. Each of the outcomes is shown graphically. The information provided in this survey is quite useful for newcomers carrying out research in medical informatics. © 2024 IEEE.

关键词： and Medical Data Deep Learning Healthcare Natural Language Processing Question Answering

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：