2023 International Technical Conference on Circuits/Systems, Computers, and Communications (ITC-CSCC)最新文献_第9页

A Two-Stage Lesion Recognition System for Diagnostic Support in Colon NBI Endoscopy 用于结肠NBI内镜诊断支持的两阶段病变识别系统

2023 International Technical Conference on Circuits/Systems, Computers, and Communications (ITC-CSCC) Pub Date : 2023-06-25 DOI: 10.1109/ITC-CSCC58803.2023.10212618

Yongfei Wu, Daisuke Katayama, Tetsushi Koide, Toru Tamaki, Shigeto Yoshida, Shin Morimoto, Yuki Okamoto, S. Oka, Shinji Tanaka

引用次数: 0

Detection Welding Performance of Industrial Robot Using Machine Learning 基于机器学习的工业机器人焊接性能检测

2023 International Technical Conference on Circuits/Systems, Computers, and Communications (ITC-CSCC) Pub Date : 2023-06-25 DOI: 10.1109/ITC-CSCC58803.2023.10212676

Onjira Duongthipthewa, K. Meesublak, Atsushi Takahashi, C. Mitsantisuk

{"title":"Detection Welding Performance of Industrial Robot Using Machine Learning","authors":"Onjira Duongthipthewa, K. Meesublak, Atsushi Takahashi, C. Mitsantisuk","doi":"10.1109/ITC-CSCC58803.2023.10212676","DOIUrl":"https://doi.org/10.1109/ITC-CSCC58803.2023.10212676","url":null,"abstract":"Automated welding robots have become an essential component in manufacturing industries due to their precision and increased productivity. Furthermore, they eliminate the need for human workers to be exposed to toxic fumes and bright light during welding processes, ensuring worker safety. However, any failure in welding robots can lead to poor product quality and impact a company's credibility. Therefore, it is critical to predict the welding performance of these machines to maintain product quality. This study proposes the use of spectrogram image classification to classify the quality of welding products. Using a TM-1400 WGIII welding robot, 180 welding datasets were collected to determine the conditions of the welding robot based on different welding wire lengths. Current and voltage signals of the welding robot were studied to identify suitable input parameters and machine learning algorithms were utilized to improve the accuracy of the predictive welding quality. The experiment resulted in an accuracy of 89% based on a 70% training sets and 30% testing sets of data, indicating that spectrogram image classification is an effective technique to monitor the condition of welding robots, improve welding quality, and increase product quality control. This method can be beneficial for both small- and large-scale industries such as automotive, energy, and construction.","PeriodicalId":220939,"journal":{"name":"2023 International Technical Conference on Circuits/Systems, Computers, and Communications (ITC-CSCC)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130723960","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

Semantic Segmentation of River Video for Efficient River Surveillance System 高效河流监测系统中河流视频的语义分割

2023 International Technical Conference on Circuits/Systems, Computers, and Communications (ITC-CSCC) Pub Date : 2023-06-25 DOI: 10.1109/ITC-CSCC58803.2023.10212938

Haruki Inoue, Takafumi Katayama, Tian Song, T. Shimamoto

引用次数: 0

Classifying Cybercrime and Threat on Thai Online News: A Comparison of Supervised Learning Algorithms 分类网络犯罪和威胁在泰国在线新闻:监督学习算法的比较

2023 International Technical Conference on Circuits/Systems, Computers, and Communications (ITC-CSCC) Pub Date : 2023-06-25 DOI: 10.1109/ITC-CSCC58803.2023.10212562

Pongsarun Boonyopakorn, N. Wisitpongphan, Ukid Changsan

{"title":"Classifying Cybercrime and Threat on Thai Online News: A Comparison of Supervised Learning Algorithms","authors":"Pongsarun Boonyopakorn, N. Wisitpongphan, Ukid Changsan","doi":"10.1109/ITC-CSCC58803.2023.10212562","DOIUrl":"https://doi.org/10.1109/ITC-CSCC58803.2023.10212562","url":null,"abstract":"Nowadays, there are many news and articles being offered on the Internet from various sources. This news can generally be classified into different domains, such as politics, entertainment, sports, technology, etc. Over the past decade, news related to cybercrime and threats were often classified into either crime or technology domains. However, contents related to such news should be alerted to all citizens as fast as possible in order to prevent further damage. Therefore, in this research paper, we aim to categorize news related to cybercrimes or threats from a pool of news of different topics. The challenge of this work is to be able to handle new types of threats such as call center scams, ransomware as well as other new threats which exploit the vulnerability of new technology/application. To tackle this problem, we have developed methods and processes to classify news into domains related to cybercrimes and threats using various Machine Learning techniques: Naive Bayes, KNN, SVM, Decision Trees, Random Forest, and Gradient Boosting. Using the dataset of 5,000 news articles, which consists of 3,500 general news and 1,500 cybercrime related news, the best technique that did the best in categorizing cybercrime related news is SVM, with an accuracy of 93.66% and a cross-validation accuracy of 92.34%. The second best technique is Random Forest with an accuracy of 92.46% and a cross-validation accuracy of 92.25%.","PeriodicalId":220939,"journal":{"name":"2023 International Technical Conference on Circuits/Systems, Computers, and Communications (ITC-CSCC)","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131408171","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

Effects of Low-Geometrical-Precision PCB Manufacturing on mmWave Passive Metasurfaces 低几何精度PCB制造对毫米波无源超表面的影响

2023 International Technical Conference on Circuits/Systems, Computers, and Communications (ITC-CSCC) Pub Date : 2023-06-25 DOI: 10.1109/ITC-CSCC58803.2023.10212582

Panithan La-aiddee, P. Sangwongngam, P. Pongpaibool, D. Tancharoen, L. Wuttisittikulkij, P. Vanichchanunt

引用次数: 0

Implementation of a 4-Phase Square Waves Generator and its Application for Measurement of Frequency Characteristics of an RCPF 四相方波发生器的实现及其在RCPF频率特性测量中的应用

2023 International Technical Conference on Circuits/Systems, Computers, and Communications (ITC-CSCC) Pub Date : 2023-06-25 DOI: 10.1109/ITC-CSCC58803.2023.10212678

Lina Sato, K. Shouno, H. Tanimoto, C. Muto, S. Moriyama, C. Takahashi, Michitaka Yoshino

引用次数: 0

Enhancing MobileNetV2 Performance with Layer Replication and Splitting for 3D Face Recognition Task Using Distributed Training 使用分布式训练增强MobileNetV2的层复制和分割性能，用于3D人脸识别任务

2023 International Technical Conference on Circuits/Systems, Computers, and Communications (ITC-CSCC) Pub Date : 2023-06-25 DOI: 10.1109/ITC-CSCC58803.2023.10212828

Kritpawit Soongswang, Phattharaphon Romphet, C. Chantrapornchai

{"title":"Enhancing MobileNetV2 Performance with Layer Replication and Splitting for 3D Face Recognition Task Using Distributed Training","authors":"Kritpawit Soongswang, Phattharaphon Romphet, C. Chantrapornchai","doi":"10.1109/ITC-CSCC58803.2023.10212828","DOIUrl":"https://doi.org/10.1109/ITC-CSCC58803.2023.10212828","url":null,"abstract":"In this paper, we propose the operators, which are layer replication and splitting, to modify the CNN network. The algorithm for exploring suitable modifications to the prototype MobileNetV2 architecture for the 3D face recognition task is presented. The algorithm consists of two steps. The first step involves splitting the input and searching for the optimal position to expand the network through layer replication. The second part explores the architecture modification by altering the split input layer position within the model. Experiments demonstrate that the discovered model provides a more cost-effective performance, with only 0.015% increased size compared to a vanilla MobileNet V2, while delivering 6.99% higher accuracy than the previous 3D MobileNetV2 and 9.15% more accuracy than the vanilla MobileNetV2, with a total of 3,801,136 parameters. Using distributed data training on multi-GPUs, the total training time can be reduced by 75% while maintaining good accuracy compared to traditional single-GPU training.","PeriodicalId":220939,"journal":{"name":"2023 International Technical Conference on Circuits/Systems, Computers, and Communications (ITC-CSCC)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114382299","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

Evaluation of a PUF Embedded in the Delay Testable Boundary Scan Circuit 嵌入延迟可测试边界扫描电路的PUF的评估

2023 International Technical Conference on Circuits/Systems, Computers, and Communications (ITC-CSCC) Pub Date : 2023-06-25 DOI: 10.1109/ITC-CSCC58803.2023.10212656

Hayato Miki, Eisuke Ohama, H. Yotsuyanagi, M. Hashizume

引用次数: 0

Two Autoscaling Approaches on Kubernetes Clusters Against Data Streaming Applications Kubernetes集群针对数据流应用的两种自动伸缩方法

2023 International Technical Conference on Circuits/Systems, Computers, and Communications (ITC-CSCC) Pub Date : 2023-06-25 DOI: 10.1109/ITC-CSCC58803.2023.10212432

Papon Choonhaklai, C. Chantrapornchai

{"title":"Two Autoscaling Approaches on Kubernetes Clusters Against Data Streaming Applications","authors":"Papon Choonhaklai, C. Chantrapornchai","doi":"10.1109/ITC-CSCC58803.2023.10212432","DOIUrl":"https://doi.org/10.1109/ITC-CSCC58803.2023.10212432","url":null,"abstract":"This paper is aimed to study the performance comparison of two autoscaling approaches against data streaming and visualization applications under Kubernetes clusters. In particular, vertical and horizontal scaling methods are focused. The experimental setup has been done extensively based on the architecture stack which includes Apache Kafka, Apache Spark, Filebeat, Logstash, Elasticsearch, Kibana, Prometheus, and Grafana. The performance and resource utilization of the data flow display system in Kubernetes clusters are evaluated using Apache JMeter. Three metrics: CPU utilization, response time, throughput, and error rate are used. The experimental results show that on average, the CPU utilization of the horizontally scaled system is higher by 18.48% compared to the non-scaling system, while the vertically scaled system uses 49.45% using less CPU resources than the non-scaling system. The average response time of the horizontally scaled system is 65.60% lower than the non-scaling system, while the vertically scaled system is 1.19% lower than the non-scaling system. The error rate of the horizontally scaled system is 0.04%, but the error rate of the vertically scaled system is as high as 15.16%.","PeriodicalId":220939,"journal":{"name":"2023 International Technical Conference on Circuits/Systems, Computers, and Communications (ITC-CSCC)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124091620","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

Implementation of an RCPF and its Measurement Circuitry for the Method Based on Superposition 基于叠加法的RCPF及其测量电路的实现

2023 International Technical Conference on Circuits/Systems, Computers, and Communications (ITC-CSCC) Pub Date : 2023-06-25 DOI: 10.1109/ITC-CSCC58803.2023.10212681

Kanata Fukagawa, K. Shouno, H. Tanimoto, C. Muto, S. Moriyama, C. Takahashi, Michitaka Yoshino

引用次数: 0