2022 IEEE 4th Eurasia Conference on IOT, Communication and Engineering (ECICE)最新文献_第7页

Study on Evaluation Model of International Chinese Teachers’ Digital Competence in Online Teaching Based on K-Means Clustering Algorithm 基于k均值聚类算法的国际汉语教师在线教学数字能力评价模型研究

2022 IEEE 4th Eurasia Conference on IOT, Communication and Engineering (ECICE) Pub Date : 2022-10-28 DOI: 10.1109/ECICE55674.2022.10042913

Liqing Yang, Qicheng Wang, Tianyu Wang, Xintong Ma

{"title":"Study on Evaluation Model of International Chinese Teachers’ Digital Competence in Online Teaching Based on K-Means Clustering Algorithm","authors":"Liqing Yang, Qicheng Wang, Tianyu Wang, Xintong Ma","doi":"10.1109/ECICE55674.2022.10042913","DOIUrl":"https://doi.org/10.1109/ECICE55674.2022.10042913","url":null,"abstract":"The research aim of this paper is to evaluate the digital competence of international Chinese teachers.In order to accurately and objectively evaluate the international Chinese teachers’ digital competence standards, we used methods of data mining.The research procedure included the establishment of indicators of teachers’ digital competence and the construction of models.We chose the European Teachers’ Digital Competence Framework which includes 22 research indicators as the index dimension and used a developed convolutional neural network, k clustering and the fuzzy clustering algorithm. We created an evaluation model as a result. The results of several tests show that the model is stable and plausible. The model can be used to analyze the trend and distribution of digital ability among international Chinese teachers, as well as to evaluate international Chinese teachers’ s digital ability. The innovation of the result is the creation of a theoretical evaluation model to evaluate teachers’ digital ability.","PeriodicalId":282635,"journal":{"name":"2022 IEEE 4th Eurasia Conference on IOT, Communication and Engineering (ECICE)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133957695","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

Study of Turns Impact on ESD-immunity of High-voltage nLDMOSs with a Constant Floating-poly 恒浮聚高压nLDMOSs匝数对抗静电性影响的研究

2022 IEEE 4th Eurasia Conference on IOT, Communication and Engineering (ECICE) Pub Date : 2022-10-28 DOI: 10.1109/ECICE55674.2022.10042892

Xing-Chen Mai, Xiu-Yuan Yang, Shen-Li Chen, Ting-En Lin, Yu-Jie Chung

引用次数: 0

Real-Time Dynamic Configuration of Firewall Rules for High-Speed IoT Networks 高速物联网防火墙规则的实时动态配置

2022 IEEE 4th Eurasia Conference on IOT, Communication and Engineering (ECICE) Pub Date : 2022-10-28 DOI: 10.1109/ECICE55674.2022.10042899

Yu-An Shao, C. Chao

{"title":"Real-Time Dynamic Configuration of Firewall Rules for High-Speed IoT Networks","authors":"Yu-An Shao, C. Chao","doi":"10.1109/ECICE55674.2022.10042899","DOIUrl":"https://doi.org/10.1109/ECICE55674.2022.10042899","url":null,"abstract":"The Internet of Things (IoT) is indispensable to modern society. It has entered the mainstream trend recently owing to its ability to read data and connect systems. IoT network platforms comprise various applications, leading to an influx of heavy and varying network traffic, allowing hackers to launch large-scale network attacks easily. When hackers gain control of an IoT device, they can initiate large-scale botnet attacks even through nonconventional computing devices such as cameras and routers. For example, Dyn, a domain name system provider, experienced large-scale distributed denial-of-service attacks on its IoT devices in 2016, causing companies, such as Twitter and Amazon, to suffer the consequences. Therefore, adapting to large-scale changes in network traffic in real-time is imperative. Firewalls are the foundation of device security. Therefore, when large-scale changes in network traffic occur, it is necessary to ensure the effectiveness of firewalls to reduce the probability of successful attacks. This study proposes a system that can adjust the order of firewall rules in real-time to monitor the traffic in high-speed IoT networks. When the system detects a sudden increase in the number of packets, the firewall rules are reordered and applied immediately to ensure security. Additionally, the original filtering effect of the firewall is maintained without being compromised. The test results indicate that high-speed network firewall performance has improved significantly with no abnormality detected in the filtering effect.","PeriodicalId":282635,"journal":{"name":"2022 IEEE 4th Eurasia Conference on IOT, Communication and Engineering (ECICE)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132827429","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

License Plate Recognition Model For Tilt Correction Based on Convolutional Neural Network 基于卷积神经网络的车牌倾斜校正识别模型

2022 IEEE 4th Eurasia Conference on IOT, Communication and Engineering (ECICE) Pub Date : 2022-10-28 DOI: 10.1109/ECICE55674.2022.10042868

Chien-Chang Chen, Yu-Yang Lin, Jing-Chung Shen

{"title":"License Plate Recognition Model For Tilt Correction Based on Convolutional Neural Network","authors":"Chien-Chang Chen, Yu-Yang Lin, Jing-Chung Shen","doi":"10.1109/ECICE55674.2022.10042868","DOIUrl":"https://doi.org/10.1109/ECICE55674.2022.10042868","url":null,"abstract":"The purpose of the study was to discuss how a tilted license plate (LP) affects the accuracy of LP recognition and how to improve a recognition system. The character segmentation on tilted LP usually causes character segmentation to be incomplete or out of range, which leads to a decrease in the accuracy rate of character recognition. We propose a method to improve the accuracy of LP recognition and reduce the prediction model training time for the recognition system. The study has four steps which are LP location, LP correction, character segmentation, and character recognition. Firstly, LP was located and zoomed in with YOLOv4 to reduce irrelevant noise and background value. Secondly, the system analyzed pixel changes of each angle with a horizontal projection and corrected the horizontal tilt angle for the LP. Then, the system used vertical projection to move the upper and lower half pixels of the LP in opposite directions. By analyzing the projection status of each angle, the system then corrected the vertical tilt angle for the LP. Thirdly, the system performed character segmentation on the corrected LP. This was done by extracting each character. Lastly, given more than 9,000 character images from step three, the recognition system with Convolutional Neural Network (CNN) trained the prediction model with the feature selection of the maximum pooling layer. Finally, the recognition system accuracy of predicting the uncorrected LP is 96.1% after 25 epochs, while the recognition accuracy of predicting corrected LP is 99% after 10 epochs. The accuracy of LP recognition was increased from 96.1 to 99% after LP tilt correction. CNN training time was decreased from 25 epochs to 10 epochs.","PeriodicalId":282635,"journal":{"name":"2022 IEEE 4th Eurasia Conference on IOT, Communication and Engineering (ECICE)","volume":" 52","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113947563","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

Solar Power Photovoltaic Output Forecasting Using Multiple Methods Approach, Case Study: Cambodia 使用多种方法预测太阳能光伏发电产量，案例研究:柬埔寨

2022 IEEE 4th Eurasia Conference on IOT, Communication and Engineering (ECICE) Pub Date : 2022-10-28 DOI: 10.1109/ECICE55674.2022.10042844

Volak Nou, Wusheng Shi

{"title":"Solar Power Photovoltaic Output Forecasting Using Multiple Methods Approach, Case Study: Cambodia","authors":"Volak Nou, Wusheng Shi","doi":"10.1109/ECICE55674.2022.10042844","DOIUrl":"https://doi.org/10.1109/ECICE55674.2022.10042844","url":null,"abstract":"Solar energy is one of the most potential renewable energy sources of sunlight. Due to increase and satisfying demand for energy in developing countries like Cambodia, solar power energy is the main and significant energy to the procedure for supply local to reduce import power energy from neighboring’s countries. In this case, the ability to an accurate solar output forecasting is critical for planning to decide based on forecast conditions, while many forecasting methods have been improved for forecasted values. However, the specific research on solar power PV output forecasting in Cambodia is still lacking to secure better accuracy during the rapidly extending inquiry of energy. This study is conducted to investigate a trial of short-term forecasting of solar power photovoltaic output in Bavet city, Cambodia, using several methods for comparisons such as Neural Network (NN), Linear Regression (LR), and Autoregressive Moving Average (ARMA). This process is based on the daily reality historical data from $mathrm{I}^{mathrm{s}mathrm{t}}$ January 2018 to 1$0^{mathrm{t}mathrm{h}}$ January 2019 which were recorded by Nation Control Center (NCC). Weather daily index data is obtained from the Renewable Energy Community of NASA Power Data Access Viewer Website Forecast of Global Energy Resources. The reliability of the forecasting of the three methods was assessed by using Mean Absolute Percentage Error (MAPE), Mean Absolute Error (MAE), Mean Square Error (MSE), and Root Mean Square Error (RMSE). Based on the simulation result of these three models, the Neural Network model showed better accuracy and results that were promising and beneficial for solar forecasting in Cambodia.","PeriodicalId":282635,"journal":{"name":"2022 IEEE 4th Eurasia Conference on IOT, Communication and Engineering (ECICE)","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134183867","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

Ensemble and Unsupervised Machine Learning Applied on Laser Ablation Quality Study of Silicon Nitride during CMOS-MEMS Post Processing 集成和无监督机器学习在CMOS-MEMS后处理过程中氮化硅激光烧蚀质量研究中的应用

2022 IEEE 4th Eurasia Conference on IOT, Communication and Engineering (ECICE) Pub Date : 2022-10-28 DOI: 10.1109/ECICE55674.2022.10042858

Chien-Chung Tsai, Chih-Chun Chan

引用次数: 0

Development of Tool Management System based on Django Web Framework 基于Django Web框架的工具管理系统的开发

2022 IEEE 4th Eurasia Conference on IOT, Communication and Engineering (ECICE) Pub Date : 2022-10-28 DOI: 10.1109/ECICE55674.2022.10042890

Jenn‐Yih Chen, Yi-Ling Lin, B. Lee

{"title":"Development of Tool Management System based on Django Web Framework","authors":"Jenn‐Yih Chen, Yi-Ling Lin, B. Lee","doi":"10.1109/ECICE55674.2022.10042890","DOIUrl":"https://doi.org/10.1109/ECICE55674.2022.10042890","url":null,"abstract":"To maintain process stability and yield improvement in a small and diverse market, digitization equipment and managing tools intelligently through the IoT are necessary. Although many traditional manufacturing factories have used IoT technologies, they cannot control the tracking flow and condition of each cutting tool owing to a lack of systematic tools. This easily causes machine downtime or even damage to the machine spindle due to tool-related problems. Therefore, the tool management system (TMS) in this study is designed based on a browser/server (B/S) web architecture and is designed to use a non-relational database for storing tool data with a non-fixed structure. The TMS is proposed to integrate two management modes: tool management and engineering development. The functions of tool management are mainly about querying the database through specific codes and keeping the usage records oftools. It enables processing staff, purchasing staff, warehousing staff, and administrators to have useful information on each tool at each stage. In addition to recording the usage of the tools, when the inventory level of the tools is lower than the safety level, the purchaser is immediately notified to place an order with the tool supplier for shortening the tool preparation time. On the other hand, the functions of the engineering development are designed for CAD/CAM manufacturing staff to query the tool inventory through the TMS to obtain suitable matching components in real-time. DXF files are used to assemble tool components and generate 3D models in CAM software for simulation tests. Then, the production staffprepares the tools according to the tool list from the simulation. The staff of the measurement department also measures and updates the tool compensation data of the TMS. Thus, the operator quickly places the tool into the corresponding number on the tool magazine (or turret head) and update the correct compensation value of the CNC controller via TCP/IP.","PeriodicalId":282635,"journal":{"name":"2022 IEEE 4th Eurasia Conference on IOT, Communication and Engineering (ECICE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129292524","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

D3QN-based Elevator Scheduling Algorithm for Robots 基于d3qn的机器人电梯调度算法

2022 IEEE 4th Eurasia Conference on IOT, Communication and Engineering (ECICE) Pub Date : 2022-10-28 DOI: 10.1109/ECICE55674.2022.10042835

Yan Ke, Yun-Shuai Yu, Cheng-Tung Sun, Chia-Yen Wu

引用次数: 0

Image Recognition of River Water Gauges Using Polynomial Regression Model for Predicting Binarization Threshold 基于多项式回归模型预测二值化阈值的河流水位仪图像识别

2022 IEEE 4th Eurasia Conference on IOT, Communication and Engineering (ECICE) Pub Date : 2022-10-28 DOI: 10.1109/ECICE55674.2022.10042942

Jui-Fa Chen, Po-Chun Wang, Sin-Man Wong, Yu-Ting Liao

{"title":"Image Recognition of River Water Gauges Using Polynomial Regression Model for Predicting Binarization Threshold","authors":"Jui-Fa Chen, Po-Chun Wang, Sin-Man Wong, Yu-Ting Liao","doi":"10.1109/ECICE55674.2022.10042942","DOIUrl":"https://doi.org/10.1109/ECICE55674.2022.10042942","url":null,"abstract":"Taiwan is frequently affected by typhoons. Typhoons bring heavy rainfall and cause rapid river level rise and even flooding. In the past, high-accuracy but costly equipment, which could not be widely distributed, was used for hydrological observation. It caused us unable to obtain regional hydrological information in real-time. Currently, CCTV has been widely distributed in rivers in Taiwan, and real-time weather information can be accessed through the Internet by the public. Using CCTV and public weather information, we analyzed the images of the water level gauge to provide real-time regional hydrological information for early flood warnings. The image binarization is used for the analysis of water levels. However, because of the differences in environmental factors such as time, weather, and sunrise/sunset time, a set of different thresholds must be used for the binarization in image processing. In this study, a polynomial regression model for predicting the binarization threshold was proposed. According to the changes in environmental factors, the threshold required for image binarization was predicted in real-time, thereby improving the image recognition rate of water gauges.","PeriodicalId":282635,"journal":{"name":"2022 IEEE 4th Eurasia Conference on IOT, Communication and Engineering (ECICE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129800702","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

Detection and Prediction of Diabetes Using Simple Fuzzy-Perceptron Learning Network 基于简单模糊感知器学习网络的糖尿病检测与预测

2022 IEEE 4th Eurasia Conference on IOT, Communication and Engineering (ECICE) Pub Date : 2022-10-28 DOI: 10.1109/ECICE55674.2022.10042896

L. Liao, Wei Huang

引用次数: 0