Electronics最新文献_第4页

RoGraphER: Enhanced Extraction of Chinese Medical Entity Relationships Using RoFormer Pre-Trained Model and Weighted Graph Convolution RoGraphER：利用 RoFormer 预训练模型和加权图卷积增强中医实体关系提取能力

Electronics Pub Date : 2024-07-23 DOI: 10.3390/electronics13152892

Qinghui Zhang, Yaya Sun, Pengtao Lv, Lei Lu, Mengya Zhang, Jinhui Wang, Chenxia Wan, Jingping Wang

{"title":"RoGraphER: Enhanced Extraction of Chinese Medical Entity Relationships Using RoFormer Pre-Trained Model and Weighted Graph Convolution","authors":"Qinghui Zhang, Yaya Sun, Pengtao Lv, Lei Lu, Mengya Zhang, Jinhui Wang, Chenxia Wan, Jingping Wang","doi":"10.3390/electronics13152892","DOIUrl":"https://doi.org/10.3390/electronics13152892","url":null,"abstract":"Unstructured Chinese medical texts are rich sources of entity and relational information. The extraction of entity relationships from medical texts is pivotal for the construction of medical knowledge graphs and aiding healthcare professionals in making swift and informed decisions. However, the extraction of entity relationships from these texts presents a formidable challenge, notably due to the issue of overlapping entity relationships. This study introduces a novel extraction model that leverages RoFormer’s rotational position encoding (RoPE) technique for an efficient implementation of relative position encoding. This approach not only optimizes positional information utilization but also captures syntactic dependency information by constructing a weighted adjacency matrix. During the feature fusion phase, the model employs an entity attention mechanism for a deeper integration of features, effectively addressing the challenge of overlapping entity relationships. Experimental outcomes demonstrate that our model achieves an F1 score of 83.42 on datasets featuring overlapping entity relations, significantly outperforming other baseline models.","PeriodicalId":504598,"journal":{"name":"Electronics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141810513","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

TSTL-GNN: Graph-Based Two-Stage Transfer Learning for Timing Engineering Change Order Analysis Acceleration TSTL-GNN：基于图的两阶段迁移学习，用于时序工程变更单分析加速

Electronics Pub Date : 2024-07-23 DOI: 10.3390/electronics13152897

Wencheng Jiang, Zhenyu Zhao, Zhiyuan Luo, Jie Zhou, Shuzheng Zhang, Bo Hu, Peiyun Bian

{"title":"TSTL-GNN: Graph-Based Two-Stage Transfer Learning for Timing Engineering Change Order Analysis Acceleration","authors":"Wencheng Jiang, Zhenyu Zhao, Zhiyuan Luo, Jie Zhou, Shuzheng Zhang, Bo Hu, Peiyun Bian","doi":"10.3390/electronics13152897","DOIUrl":"https://doi.org/10.3390/electronics13152897","url":null,"abstract":"Timing Engineering Change Order (ECO) is time-consuming in IC design, requiring multiple rounds of timing analysis. Compared to traditional methods for accelerating timing analysis, which focus on a specific design, timing ECO requires higher accuracy and generalization because the design changes considerably after ECO. Additionally, there are challenges with slow acquisition of data for large designs and insufficient data for small designs. To solve these problems, we propose TSTL-GNN, a novel approach using two-stage transfer learning based on graph structures. Significantly, considering that delay calculation relies on transition time, we divide our model into two stages: the first stage predicts transition time, and the second stage predicts delay. Moreover, we employ transfer learning to transfer the model’s parameters and features from the first stage to the second due to the similar calculation formula for delay and transition time. Experiments show that our method has good accuracy on open-source and industrial applications with an average R2score/MAE of 0.9952/13.36, and performs well with data-deficient designs. Compared to previous work, our model reduce prediction errors by 37.1 ps on the modified paths, which are changed by 24.27% on average after ECO. The stable R2 score also confirms the generalization of our model. In terms of time cost, our model achieved results for path delays consuming up to 80 times less time compared to open-source tool.","PeriodicalId":504598,"journal":{"name":"Electronics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141811776","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Increasing Offline Handwritten Chinese Character Recognition Using Separated Pre-Training Models: A Computer Vision Approach 利用分离式预训练模型提高离线手写汉字识别率：计算机视觉方法

Electronics Pub Date : 2024-07-23 DOI: 10.3390/electronics13152893

Xiaoli He, Bo Zhang, Yuan Long

{"title":"Increasing Offline Handwritten Chinese Character Recognition Using Separated Pre-Training Models: A Computer Vision Approach","authors":"Xiaoli He, Bo Zhang, Yuan Long","doi":"10.3390/electronics13152893","DOIUrl":"https://doi.org/10.3390/electronics13152893","url":null,"abstract":"Offline handwritten Chinese character recognition involves the application of computer vision techniques to recognize individual handwritten Chinese characters. This technology has significantly advanced the research in online handwriting recognition. Despite its widespread application across various fields, offline recognition faces numerous challenges. These challenges include the diversity of glyphs resulting from different writers’ styles and habits, the vast number of Chinese character labels, and the presence of morphological similarities among characters. To address these challenges, an optimization method based on a separated pre-training model was proposed. The method aims to enhance the accuracy and robustness of recognizing similar character images by exploring potential correlations among them. In experiments, the HWDB and Chinese Calligraphy Styles by Calligraphers datasets were employed, utilizing precision, recall, and the Macro-F1 value as evaluation metrics. We employ a convolutional self-encoder model characterized by high recognition accuracy and robust performance. The experimental results demonstrated that the separated pre-training models improved the performance of the convolutional auto-encoder model, particularly in handling error-prone characters, resulting in an approximate 6% increase in precision.","PeriodicalId":504598,"journal":{"name":"Electronics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141813674","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Augmenting Knowledge for Individual NVR Prediction in Different Spatial and Temporal Cross-Building Environments 在不同时空的跨楼宇环境中为个人 NVR 预测提供知识补充

Electronics Pub Date : 2024-07-23 DOI: 10.3390/electronics13152901

Mintai Kim, Sungju Lee

{"title":"Augmenting Knowledge for Individual NVR Prediction in Different Spatial and Temporal Cross-Building Environments","authors":"Mintai Kim, Sungju Lee","doi":"10.3390/electronics13152901","DOIUrl":"https://doi.org/10.3390/electronics13152901","url":null,"abstract":"Natural ventilation is a critical method for reducing energy consumption for heating, cooling, and ventilating buildings. Recent research has focused on utilizing environmental IoT data from both inside and outside buildings for NVR prediction based on a deep learning model. To design an accurate NVR prediction model while considering individual building environments, various knowledge-sharing methods can be applied, such as transfer learning and ensemble models for cross-building prediction. However, the characteristics of learning data and model parameters should be considered when applying transfer learning and ensemble models to predict NVR with different spatial and temporal domains. In this paper, we propose a way to design an NVR prediction model for a cross-building environment by normalizing the training data, selecting transfer learning layers that are well-suited to the data environment, and augmenting NVR knowledge via ensemble methods. Based on the experimental results, we confirm that the proposed knowledge-sharing deep learning approach, while considering the normalizing of training data, the selecting transfer learning layers, and augmenting the NVR knowledge approach, can improve the accuracy up to 11.8% in the two different offices and seasons.","PeriodicalId":504598,"journal":{"name":"Electronics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141810223","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Comparative Analysis of Digital Self-Interference Cancellation Methods for Simultaneous Transmit and Receive Arrays 同时发射和接收阵列的数字自干扰消除方法比较分析

Electronics Pub Date : 2024-07-23 DOI: 10.3390/electronics13152908

Dujuan Hu, Li Yang, Xiujun Zhang, Yan Xue, Xizhang Wei, Tairan Lin

引用次数: 0

Optimal Process Design for Wake-Up Free Hf0.5Zr0.5O2 Ferroelectric Capacitors: Toward Low-Power Devices with Enhanced Ferroelectric Performance 无唤醒 Hf0.5Zr0.5O2 铁电电容器的最佳工艺设计：实现具有增强铁电性能的低功耗器件

Electronics Pub Date : 2024-07-23 DOI: 10.3390/electronics13152895

Hui Wang, Jiabin Qi, Xinyu Xie, Zongfang Liu, Wenhao Wu, Choonghyun Lee

引用次数: 0

Adaptive Real-Time Tracking of Molten Metal Using Multi-Scale Features and Weighted Histograms 利用多尺度特征和加权直方图对熔融金属进行自适应实时跟踪

Electronics Pub Date : 2024-07-23 DOI: 10.3390/electronics13152905

Yifan Lei, Degang Xu

{"title":"Adaptive Real-Time Tracking of Molten Metal Using Multi-Scale Features and Weighted Histograms","authors":"Yifan Lei, Degang Xu","doi":"10.3390/electronics13152905","DOIUrl":"https://doi.org/10.3390/electronics13152905","url":null,"abstract":"In this study, we study the tracking of the molten metal region in the dross removal process during metal ingot casting, and propose a real-time tracking method based on adaptive feature selection and weighted histogram. This research is highly significant in metal smelting, as efficient molten metal tracking is crucial for effective dross removal and ensuring the quality of metal ingots. Due to the influence of illumination and temperature in the tracking environment, it is difficult to extract suitable features for tracking molten metal during the metal pouring process using industrial cameras. We transform the images captured by the camera into a multi-scale feature space and select the features with the maximum distinction between the molten metal region and its surrounding background for tracking. Furthermore, we introduce a weighted histogram based on the pixel values of the target region into the mean-shift tracking algorithm to improve tracking accuracy. During the tracking process, the target model updates based on changes in the molten metal region across frames. Experimental tests confirm that this tracking method meets practical requirements, effectively addressing key challenges in molten metal tracking and providing reliable support for the dross removal process.","PeriodicalId":504598,"journal":{"name":"Electronics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141812569","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Humidity Diffusion Process Analysis and Life Prediction of a VSC-HVDC Control Protection Device Based on a Finite Element Simulation Method 基于有限元仿真方法的 VSC-HVDC 控制保护装置的湿度扩散过程分析和寿命预测

Electronics Pub Date : 2024-07-23 DOI: 10.3390/electronics13152888

Changgeng Li, Yutao Cheng, Xiaochao Hou

{"title":"Humidity Diffusion Process Analysis and Life Prediction of a VSC-HVDC Control Protection Device Based on a Finite Element Simulation Method","authors":"Changgeng Li, Yutao Cheng, Xiaochao Hou","doi":"10.3390/electronics13152888","DOIUrl":"https://doi.org/10.3390/electronics13152888","url":null,"abstract":"Voltage Source Converter-based High-Voltage Direct Current Transmission (VSC-HVDC) is essential for integrating renewable energy sources and facilitating inter-regional power transmission. This study evaluates the reliability of control and protection devices within these systems, which are crucial for the stable operation of power grids. Humidity significantly affects both the operational conditions and lifespan of these devices. Previous studies, reliant on extensive full-condition fatigue testing, have lacked effective test models and detailed analyses of mechanisms. To address this gap, a humidity diffusion model was developed to comprehensively investigate moisture diffusion mechanisms. Using the insights gained, the Hallberg–Peck model was applied to predict the lifespan of these devices, quantitatively assessing how changes in humidity affect their reliability. This approach employs a stringent failure criterion, leading to a conservative predicted lifespan. This method achieved a prediction accuracy of 85.648% compared to the benchmarks in GB/T 2423.50-2012, validating the accuracy of our model and the effectiveness of our simulation technology under stringent conditions. This research provides vital theoretical data and serves as an essential tool for guiding the precise maintenance of equipment in varying environmental humidity levels.","PeriodicalId":504598,"journal":{"name":"Electronics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141813871","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Two-Area Automatic Generation Control for Power Systems with Highly Penetrating Renewable Energy Sources 高渗透率可再生能源电力系统的双区自动发电控制

Electronics Pub Date : 2024-07-23 DOI: 10.3390/electronics13152907

L. H. Lam, Le Khoa Nam, Nguyen Khac Tien Dung, Nguyen Huu Hieu

{"title":"Two-Area Automatic Generation Control for Power Systems with Highly Penetrating Renewable Energy Sources","authors":"L. H. Lam, Le Khoa Nam, Nguyen Khac Tien Dung, Nguyen Huu Hieu","doi":"10.3390/electronics13152907","DOIUrl":"https://doi.org/10.3390/electronics13152907","url":null,"abstract":"Currently, renewable energy sources (RESs) are gradually replacing traditional power sources that use fossil fuels. In some countries, such as Vietnam, RESs are developed on a massive scale and are concentrated in some key areas. This causes negative impacts on a power system when its transmission system is not deployed synchronously to release their capacity from these new renewable energy plants. An important challenge today is to ensure frequency stability in power systems with high uncertainty in RES output power. Additionally, the system requires solutions to prevent transmission line overloads during periods when RESs make a substantial contribution to the electricity generation capacity. Therefore, this paper builds an automatic generation control (AGC) system for a two-area power system with high penetration of RESs. This AGC system model aims to maintain system frequency stability amid unpredictable changes in RESs while also ensuring that tie-lines transmit the predetermined power levels to mitigate frequent congestion. By continuously monitoring and adjusting the system’s frequency, the challenges posed by the inherent variability of RESs can be effectively mitigated. The AGC model is simulated on DIgSILENT PowerFactory software and tested with a 106-bus system. The simulation results of this study show that the AGC system operates effectively, ensuring that the frequency returns to the rated value and maintaining the exchange capacity on the tie-lines after occurrences of RES power decrease events.","PeriodicalId":504598,"journal":{"name":"Electronics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141811455","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Data-Driven Control for Modular Multilevel Converters Based on Model-Free Adaptive Control with an Event-Triggered Scheme 基于无模型自适应控制与事件触发方案的模块化多电平转换器数据驱动控制

Electronics Pub Date : 2024-07-23 DOI: 10.3390/electronics13152899

Ying Fang, Yanhua Liu, Aolong Fu, S. Shi, Zhenbin Zhang

引用次数: 0