IEEE Access最新文献_第4页

HyCoViT: Hybrid Convolution Vision Transformer With Dynamic Dropout for Enhanced Medical Chest X-Ray Classification HyCoViT：用于增强医学胸部x射线分类的动态Dropout混合卷积视觉变压器

IF 3.4 3区计算机科学

IEEE Access Pub Date : 2025-06-30 DOI: 10.1109/ACCESS.2025.3584065

Omid Almasi Naghash;Nam Ling;Xiang Li

{"title":"HyCoViT: Hybrid Convolution Vision Transformer With Dynamic Dropout for Enhanced Medical Chest X-Ray Classification","authors":"Omid Almasi Naghash;Nam Ling;Xiang Li","doi":"10.1109/ACCESS.2025.3584065","DOIUrl":"https://doi.org/10.1109/ACCESS.2025.3584065","url":null,"abstract":"Medical chest X-ray (CXR) classification necessitates balancing detailed local feature extraction with capturing broader, long-range dependencies, especially when working with limited and heterogeneous datasets. In this paper, we propose HyCoViT, a hybrid model that integrates a custom Convolutional Neural Network (CNN) block with Vision Transformers (ViTs). This approach combines the locality of CNN-based latent space representations with the global attention mechanisms of ViTs. To address overfitting in data-scarce scenarios, we introduce a Dynamic Dropout (DD) algorithm that adaptively adjusts the dropout rate during training. Additionally, we enhance model generalization using a combination of traditional data augmentation and MixUp techniques. We evaluate HyCoViT on a multi-class classification task involving COVID-19, pneumonia, lung opacity, and normal CXR images. While COVID-19 serves as a case study, the model’s design is generalizable to various medical imaging applications. Experimental results show that HyCoViT achieves state-of-the-art (SOTA) performance, with 98.81% accuracy for three-class surpassing the existing CNN-based model by average +4.90%., and SOTA transformer-based average by 2.05%. In four-class classification, HyCoViT achieves the highest accuracy at 96.56%, which is 8.32% higher than the average accuracy of SOTA CNN-based models and 4.96% higher than the average accuracy of other SOTA transformer-based models. These results surpass many existing CNN-based and transformer-based models, demonstrating the robust generalization capabilities of our method. Furthermore, we provide interpretable, attention-based visualizations that highlight crucial lung regions to support context-aware decisions and ultimately improve patient outcomes.","PeriodicalId":13079,"journal":{"name":"IEEE Access","volume":"13 ","pages":"112623-112641"},"PeriodicalIF":3.4,"publicationDate":"2025-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11059244","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144557977","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Revolutionary Unconventional Transmission Line Designs With Higher Line Loadability 具有更高线路负载性的革命性非常规输电线路设计

IF 3.4 3区计算机科学

IEEE Access Pub Date : 2025-06-27 DOI: 10.1109/ACCESS.2025.3583915

Mushfiqul Abedin Khan;Mona Ghassemi

{"title":"Revolutionary Unconventional Transmission Line Designs With Higher Line Loadability","authors":"Mushfiqul Abedin Khan;Mona Ghassemi","doi":"10.1109/ACCESS.2025.3583915","DOIUrl":"https://doi.org/10.1109/ACCESS.2025.3583915","url":null,"abstract":"Traditionally, overhead AC transmission lines have been used to transfer electrical power from the generation to the distribution sector. The capacitance and inductance of these lines are significantly influenced by the size and arrangement of the subconductors in each phase, which in turn affects the transmission capacity. Conventional transmission lines typically employ a circular symmetry for the arrangement of subconductors in each phase. However, by altering the number and placement of these subconductors, the power transfer capacity of the lines can be significantly increased. Unconventional transmission lines leverage this principle by deviating from the traditional circular symmetry, resulting in a lower characteristic or surge impedance (<inline-formula> <tex-math>$Z_{c}$ </tex-math></inline-formula>), which enhances the surge impedance loading (SIL). This paper introduces new designs for unconventional transmission lines, optimized under strict criteria to minimize corona discharge effects while maintaining a narrow corridor width (CW). Compared to a conventional transmission line from the literature—with a SIL of 996 MW and a line width of 24.6 meters (yielding a power density of 40.5 MW/m)—our optimally designed conventional HSIL line achieves a SIL of 1351 MW (a 36% increase) and a line width of only 8.4 meters (a 66% reduction), resulting in a power density of 160.8 MW/m (a 297% increase). Even greater improvements are observed with unconventional HSIL designs, reaching a SIL of 1592 MW—representing a 60% increase over the conventional line and an 18% improvement over the best conventional HSIL design. These findings offer promising prospects for the future of modern transmission networks.","PeriodicalId":13079,"journal":{"name":"IEEE Access","volume":"13 ","pages":"111866-111878"},"PeriodicalIF":3.4,"publicationDate":"2025-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11053762","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144550284","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Digital Twin-Enabled Blockage-Aware Dynamic mmWave Multi-Hop V2X Communication 数字双支持阻塞感知动态毫米波多跳V2X通信

IF 3.4 3区计算机科学

IEEE Access Pub Date : 2025-06-27 DOI: 10.1109/ACCESS.2025.3583879

Supat Roongpraiwan;Zongdian Li;Tao Yu;Kei Sakaguchi

{"title":"Digital Twin-Enabled Blockage-Aware Dynamic mmWave Multi-Hop V2X Communication","authors":"Supat Roongpraiwan;Zongdian Li;Tao Yu;Kei Sakaguchi","doi":"10.1109/ACCESS.2025.3583879","DOIUrl":"https://doi.org/10.1109/ACCESS.2025.3583879","url":null,"abstract":"Millimeter wave (mmWave) technology in vehicle-to-everything (V2X) communication offers unprecedented data rates and low latency, but faces significant reliability challenges due to signal blockages and limited range. This paper introduces a novel system for managing dynamic multi-hop mmWave V2X communications in complex blocking environments. We present a system architecture that integrates a mobility digital twin (DT) with the multi-hop routing control plane, providing a comprehensive, real-time view of the network and its surrounding traffic environment. This integration enables the control plane to make informed routing decisions based on rich contextual data about vehicles, infrastructure, and potential signal blockages. Leveraging this DT-enhanced architecture, we propose an advanced routing algorithm that combines high-precision environmental data with trajectory prediction to achieve blockage-aware mmWave multi-hop V2X routing. Our algorithm anticipates network topology changes and adapts topology dynamically to maintain reliable connections. We evaluate our approach through proof-of-concept simulations using a mobility DT of the Nishishinjuku area. Results demonstrate that our DT-enabled routing strategy significantly outperforms conventional methods in maintaining reliable mmWave V2X connections across various traffic scenarios, including fully connected and mixed traffic environments.","PeriodicalId":13079,"journal":{"name":"IEEE Access","volume":"13 ","pages":"113130-113141"},"PeriodicalIF":3.4,"publicationDate":"2025-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11053827","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144557826","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Eternal-Thing 3.0: Mixed-Mode SoC for Energy Harvesting System Towards Sustainable IoT 永恒物3.0：面向可持续物联网的能量收集系统混合模式SoC

IF 3.4 3区计算机科学

IEEE Access Pub Date : 2025-06-27 DOI: 10.1109/ACCESS.2025.3583798

Saswat Kumar Ram;Sanjeev Mani Yadav;Jayendra Kumar;Priyanka Singh;Banee Bandana Das

{"title":"Eternal-Thing 3.0: Mixed-Mode SoC for Energy Harvesting System Towards Sustainable IoT","authors":"Saswat Kumar Ram;Sanjeev Mani Yadav;Jayendra Kumar;Priyanka Singh;Banee Bandana Das","doi":"10.1109/ACCESS.2025.3583798","DOIUrl":"https://doi.org/10.1109/ACCESS.2025.3583798","url":null,"abstract":"The power requirement in IoT is essential to fulfill the energy demand of the power-hungry sensors at end nodes. The use of fixed batteries restricts sustainability and makes the system costly. This work presents a battery-less solar energy harvesting system (EHS). Designing a state-of-the-art EHS needs a lot of exercise. Proper modeling of each unit makes the system robust and can be tuned at every stage to get an optimum result. The proposed EHS comprises a clock generator, DC-DC converters, analog-to-digital converters (ADCs), a maximum power point tracking (MPPT) unit, and a digital controller. The DC-DC converter and ADCs are designed in Verilog-A. The MPPT module digital controller is designed using Verilog HDL. The digital controller decides the mode of operation of the EHS based on power availability. Verilog-AMS allows us to do the mixed-mode simulation very early, so errors can only be eliminated in the initial stages at the circuit level. The proposed EHS is simulated in the Cadence Virtuoso AMS Designer Simulator (using the Incisive Run tool). The input solar voltage is 1 V to 1.5 V, and the output is 3 V to 3.5 V. The EHS provides supply voltages of 3.3 V, 1.8 V, and 1 V to the end node devices in IoT. The EHS is further designed with the parameters obtained from modeling in Cadence using virtuoso (for analog circuits) and genus (for digital circuits) and finally combined in Innovous (mixed-mode tool) for tape-out.","PeriodicalId":13079,"journal":{"name":"IEEE Access","volume":"13 ","pages":"112765-112776"},"PeriodicalIF":3.4,"publicationDate":"2025-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11053756","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144557866","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Developing Effective Techniques for the Recognition of Shanghai Dialect Text 开发有效的上海话文本识别技术

IF 3.4 3区计算机科学

IEEE Access Pub Date : 2025-06-27 DOI: 10.1109/ACCESS.2025.3583708

Yida Bao;Zheng Zhang;Mohammad Arifuzzaman;Tran Duc Le;Qi Li;Masuzyo Mwanza;Jiaqing Lin;Philippe Gaillard;Jiafeng Ye

{"title":"Developing Effective Techniques for the Recognition of Shanghai Dialect Text","authors":"Yida Bao;Zheng Zhang;Mohammad Arifuzzaman;Tran Duc Le;Qi Li;Masuzyo Mwanza;Jiaqing Lin;Philippe Gaillard;Jiafeng Ye","doi":"10.1109/ACCESS.2025.3583708","DOIUrl":"https://doi.org/10.1109/ACCESS.2025.3583708","url":null,"abstract":"Recognizing Shanghai dialect text is crucial for preserving local dialects, yet research on its automatic distinction from Standard Mandarin remains limited. We construct a carefully balanced dataset specifically for the task of Shanghai dialect recognition and propose a two-stage approach for automatic language classification. In the first stage, we employ Jieba tokenization to retain dialect-specific lexical nuances, ensuring essential semantic and syntactic distinctions are captured. Next, we independently train both a BERT-Chinese-Based classifier and a traditional Support Vector Machine classifier for dialect recognition. The BERT model leverages powerful contextual representations to capture subtle differences between Shanghai dialect and Standard Mandarin, while the Support Vector Machine serves as a conventional baseline. Extensive experiments comparing the two approaches revealed that, although the Support Vector Machine can adequately perform the classification task, the BERT-Based classifier achieves significantly higher accuracy and is more sensitive to the nuanced linguistic features of the dialect. Further analysis through attention visualization reveals how the model specifically attends to unique dialectal features, highlighting distinctive lexical and structural differences between Shanghai dialect and Mandarin text. To the best of our knowledge, this study is the first to apply NLP techniques for language classification between Shanghai dialect and Standard Mandarin, emphasizing the potential for automated dialect recognition as an effective method for dialect documentation and preservation.","PeriodicalId":13079,"journal":{"name":"IEEE Access","volume":"13 ","pages":"111802-111813"},"PeriodicalIF":3.4,"publicationDate":"2025-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11053757","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144550543","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Methodology for Electricity Demand Forecasting Using a Hybrid Approach 基于混合方法的电力需求预测方法

IF 3.4 3区计算机科学

IEEE Access Pub Date : 2025-06-27 DOI: 10.1109/ACCESS.2025.3583740

Fanidhar Dewangan;Monalisa Biswal;Nand Kishor

{"title":"A Methodology for Electricity Demand Forecasting Using a Hybrid Approach","authors":"Fanidhar Dewangan;Monalisa Biswal;Nand Kishor","doi":"10.1109/ACCESS.2025.3583740","DOIUrl":"https://doi.org/10.1109/ACCESS.2025.3583740","url":null,"abstract":"Load forecasting (LF) plays a crucial role in energy production planning and scheduling, simplifying budgeting processes, and improving power supply reliability. The available integrated solutions are superior to conventional approaches while considering the uncertainties of weather conditions. The primary objective of LF is to establish an optimal load model for the power grid, conducted offline, to achieve accurate predictions, thereby minimizing operational costs and enhancing grid stability. In this work, an integrated LF model is proposed that uses modified combined ensemble empirical mode decomposition with adaptive noise (MCEEMDAN), Shannon entropy (SE), and long short-term memory (LSTM) techniques. To demonstrate the efficacy of the proposed method, this manuscript utilizes a real-time dataset containing actual load data, social & temporal variables and meteorological parameters including temperature, humidity, and rainfall, gathered from Raipur region in Chhattisgarh state, India. A comparative analysis of the proposed method is conducted against other available approaches, including various time-series decomposition methods, different machine learning techniques, and alternative test system.","PeriodicalId":13079,"journal":{"name":"IEEE Access","volume":"13 ","pages":"112197-112214"},"PeriodicalIF":3.4,"publicationDate":"2025-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11053796","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144550615","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Combined Diffusion Model and Reinforcement Learning Approach for Solving the Vehicle Routing Problem With Multiple Soft Time Windows 多软时间窗车辆路径问题的联合扩散模型和强化学习方法

IF 3.4 3区计算机科学

IEEE Access Pub Date : 2025-06-27 DOI: 10.1109/ACCESS.2025.3583984

Yu Qiao;Jianjun Miao;Xiaoying Huang

{"title":"A Combined Diffusion Model and Reinforcement Learning Approach for Solving the Vehicle Routing Problem With Multiple Soft Time Windows","authors":"Yu Qiao;Jianjun Miao;Xiaoying Huang","doi":"10.1109/ACCESS.2025.3583984","DOIUrl":"https://doi.org/10.1109/ACCESS.2025.3583984","url":null,"abstract":"The Vehicle Routing Problem with Multiple Soft Time Windows (VRPMSTW) is a challenging combinatorial optimization problem where a fleet of vehicles must deliver goods to a set of customers, adhering to time windows while minimizing costs. In this paper, we propose a novel solution approach that combines a Diffusion Model with Reinforcement Learning (RL) to efficiently solve the VRPMSTW. The Diffusion Model generates feasible vehicle routes by denoising a noise distribution, ensuring that constraints such as vehicle capacity, travel distance, and time windows are respected. Subsequently, the RL module fine-tunes these paths by optimizing the objective function, which minimizes the number of vehicles, travel distance, and time window penalties. We evaluate our approach on benchmark datasets and compare it with other state-of-the-art methods. The results demonstrate that our combined model outperforms traditional heuristics, achieving better optimization in terms of the number of vehicles, travel cost, and time window violations. The proposed method provides a promising solution for solving complex real-world vehicle routing problems with soft time window constraints.","PeriodicalId":13079,"journal":{"name":"IEEE Access","volume":"13 ","pages":"113529-113543"},"PeriodicalIF":3.4,"publicationDate":"2025-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11053837","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144557965","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Enhanced Helicopter Vibration Prediction With Hybrid Sampling and Cost Mining Techniques 基于混合采样和成本挖掘技术的直升机振动预测

IF 3.4 3区计算机科学

IEEE Access Pub Date : 2025-06-27 DOI: 10.1109/ACCESS.2025.3583905

Jeonghun Kim;Keunho Choi;Donghee Yoo

{"title":"Enhanced Helicopter Vibration Prediction With Hybrid Sampling and Cost Mining Techniques","authors":"Jeonghun Kim;Keunho Choi;Donghee Yoo","doi":"10.1109/ACCESS.2025.3583905","DOIUrl":"https://doi.org/10.1109/ACCESS.2025.3583905","url":null,"abstract":"Helicopter vibrations increase pilot workload and accelerate fatigue and wear in structural and mechanical components, potentially resulting in higher maintenance costs and reduced operational safety. To address these challenges, this study develops a machine learning-based prediction model using vibration test data from the cockpit of a Korean utility helicopter. To mitigate the issue of class imbalance in the dataset, two hybrid sampling techniques are proposed and analyzed: first oversampling and last undersampling (FOLU) and first undersampling and last oversampling (FULO). In addition to conventional evaluation based on prediction accuracy, this study adopts a cost-aware perspective by applying both cost-insensitive and cost-sensitive learning frameworks. The models are compared in terms of misclassification-related cost losses under realistic operational conditions. Experimental results confirm that the proposed hybrid sampling methods outperform traditional oversampling and undersampling techniques in prediction performance. Among all configurations, the FULO-based models using deep neural network (DNN) and random forest (RF) achieved the highest prediction accuracy. Moreover, cost-sensitive learning generally reduced misclassification losses compared to cost-insensitive learning; however, in certain cases, the cost-insensitive model yielded lower total costs. These findings indicate that predictive model selection should not be based solely on accuracy metrics, but also on economic efficiency within operational contexts. This study contributes to the literature by demonstrating the practical effectiveness of hybrid sampling in helicopter vibration prediction as well as introducing a cost-aware model evaluation framework suitable for prognostics and health management (PHM) applications in military and civilian rotorcraft operations.","PeriodicalId":13079,"journal":{"name":"IEEE Access","volume":"13 ","pages":"111832-111846"},"PeriodicalIF":3.4,"publicationDate":"2025-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11053851","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144550227","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Function Delivery Network: A Spatial-Temporal Execution Orchestrator for Optimizing Serverless Computing 功能交付网络：优化无服务器计算的时空执行协调器

IF 3.4 3区计算机科学

IEEE Access Pub Date : 2025-06-27 DOI: 10.1109/ACCESS.2025.3583721

Joel R. Corporan;Arshdeep Bahga;Vijay K. Madisetti

{"title":"Function Delivery Network: A Spatial-Temporal Execution Orchestrator for Optimizing Serverless Computing","authors":"Joel R. Corporan;Arshdeep Bahga;Vijay K. Madisetti","doi":"10.1109/ACCESS.2025.3583721","DOIUrl":"https://doi.org/10.1109/ACCESS.2025.3583721","url":null,"abstract":"We present Function Delivery Network (FDN), a novel spatial-temporal execution orchestrator designed to address key limitations in current serverless computing models. The FDN introduces several innovations, including a multi-tenant serverless model, a secure and reusable functional context, and distributed shared memory, to optimize resource allocation and improve performance in high-concurrency and globally distributed scenarios. We implement the FDN on a major cloud platform and evaluate its performance against traditional Function-as-a-Service (FaaS) execution using a variety of benchmark functions. Our results demonstrate significant improvements in resource utilization, execution time, and request completion rates. The FDN reduces function instance allocation by up to 97.82%, improves median response times by 45.45%, and maintains higher request completion rates at high concurrency levels compared to native FaaS execution. The FDN’s adaptive execution window mechanism allows for fine-tuned optimization based on function characteristics and workload patterns. This approach effectively addresses challenges such as cold starts, inefficient resource allocation, and scalability limitations in current serverless platforms. By providing a more efficient and scalable model for serverless computing, the FDN enables more cost-effective and performant cloud-native applications, particularly in scenarios involving high concurrency and global distribution.","PeriodicalId":13079,"journal":{"name":"IEEE Access","volume":"13 ","pages":"112255-112270"},"PeriodicalIF":3.4,"publicationDate":"2025-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11053862","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144550288","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Monte Carlo Simulation-Based Method for Evaluating Sample Thickness Variation to Improve Reliability of Dielectric Strength Assessment 基于蒙特卡罗模拟的样品厚度变化评估方法提高介电强度评估的可靠性

IF 3.4 3区计算机科学

IEEE Access Pub Date : 2025-06-27 DOI: 10.1109/ACCESS.2025.3583892

Keon-Hee Park;Seung-Won Lee;Hae-Jong Kim;Jang-Seob Lim

{"title":"Monte Carlo Simulation-Based Method for Evaluating Sample Thickness Variation to Improve Reliability of Dielectric Strength Assessment","authors":"Keon-Hee Park;Seung-Won Lee;Hae-Jong Kim;Jang-Seob Lim","doi":"10.1109/ACCESS.2025.3583892","DOIUrl":"https://doi.org/10.1109/ACCESS.2025.3583892","url":null,"abstract":"This study investigated the thickness effect (the influence of sample thickness variation) on the assessment of the dielectric breakdown strength in XLPE and PP insulators. A Monte Carlo simulation (MCS) was conducted to quantify the impact of voltage and thickness on the dielectric strength. Aimed at improving power system reliability, the study sought to provide a quantitative basis for the thickness effect and propose a reasonable range of thickness variation, specifically between 0.2 mm and 1.1 mm. The simulation was repeated 1,000 times by modeling thickness deviations ranging from 1% to 10%. Levene’s test was used to assess the homogeneity of variance between an ideal group with a 1% thickness deviation and comparison groups with larger deviations. The proportion of cases where Levene’s test produced a p-value below the significance level reduced below 80% when the thickness variation exceeded 2.5%. This verified that the variance differences were statistically significant. This result (particularly for samples with thicknesses of at most 1 mm) provides a scientific basis for establishing tolerance standards for thickness variation. Thereby, it contributes to enhancing the reliability of dielectric strength testing methods.","PeriodicalId":13079,"journal":{"name":"IEEE Access","volume":"13 ","pages":"113005-113012"},"PeriodicalIF":3.4,"publicationDate":"2025-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11053799","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144557842","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0