2023 IEEE International Conference on Cybernetics and Innovations (ICCI)最新文献_第2页

Globally Harmonized System Label detection using Color Segmentation 基于颜色分割的全局协调系统标签检测

2023 IEEE International Conference on Cybernetics and Innovations (ICCI) Pub Date : 2023-03-30 DOI: 10.1109/ICCI57424.2023.10112447

Thidarat Pinthong, M. Ketcham, Thittaporn Ganokratanaa, Patiyuth Pramkeaw, Narumol Chumuang

引用次数: 0

Real-Time Credit Card Fraud Detection Surveillance System 实时信用卡欺诈检测监控系统

2023 IEEE International Conference on Cybernetics and Innovations (ICCI) Pub Date : 2023-03-30 DOI: 10.1109/ICCI57424.2023.10112320

Pattarawan Thongthawonsuwan, Thittaporn Ganokratanaa, Patiyuth Pramkeaw, Narumol Chumuang, M. Ketcham

{"title":"Real-Time Credit Card Fraud Detection Surveillance System","authors":"Pattarawan Thongthawonsuwan, Thittaporn Ganokratanaa, Patiyuth Pramkeaw, Narumol Chumuang, M. Ketcham","doi":"10.1109/ICCI57424.2023.10112320","DOIUrl":"https://doi.org/10.1109/ICCI57424.2023.10112320","url":null,"abstract":"In this research, the system that detects administrative behavior, credit card and developing corruption from credit cards through LINE applications. The objective of this research 1) To develop a risk notification system or suspect to be corruption of credit cards through the connection channels of LINE application 2) to measure the accuracy of the system developed. As for the notification to prevent the risk of credit card corruption The research methods are divided into 5 steps, namely Step 1, Step System analysis. Is a study and analysis to determine the needs of steps 2 steps, system design Is the process of designing tools used in research. Step 3 System development Is the process of developing the tools used in research. Step 4, the process of testing and correcting the system. Is the process of testing the tools used in research. Step 5 Summary Discuss results and suggestions. The research results are summarized as follows The results of the measurement and completeness of the data are very good as 86.67 percent. The results of the measurement of the correct conditions are as good as 80 percent and the performance measurement of time is in The criteria is as good as 86.67 percent. In conclusion, the corruption system from credit cards through the application alert. LINE can be used appropriately.","PeriodicalId":112409,"journal":{"name":"2023 IEEE International Conference on Cybernetics and Innovations (ICCI)","volume":"194 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122433263","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

Data Imputation with Genetic Algorithm and Multiple Linear Regression for Improving Performance of Prediction Model 基于遗传算法和多元线性回归的数据输入提高预测模型的性能

2023 IEEE International Conference on Cybernetics and Innovations (ICCI) Pub Date : 2023-03-30 DOI: 10.1109/ICCI57424.2023.10112242

Surawach Amphan, Pokpong Songmuamg

引用次数: 0

Mobile Bot Application for Identification of Trypanosoma evansi Infection through Thin-Blood Film Examination Based on Deep Learning Approach 基于深度学习方法的埃文锥虫薄血膜检测移动机器人应用

2023 IEEE International Conference on Cybernetics and Innovations (ICCI) Pub Date : 2023-03-30 DOI: 10.1109/ICCI57424.2023.10112327

Rangsan Jomtarak, V. Kittichai, Morakot Kaewthamasorn, Suchansa Thanee, Apinya Arnuphapprasert, Kaung Myat Naing, T. Tongloy, S. Boonsang, S. Chuwongin

{"title":"Mobile Bot Application for Identification of Trypanosoma evansi Infection through Thin-Blood Film Examination Based on Deep Learning Approach","authors":"Rangsan Jomtarak, V. Kittichai, Morakot Kaewthamasorn, Suchansa Thanee, Apinya Arnuphapprasert, Kaung Myat Naing, T. Tongloy, S. Boonsang, S. Chuwongin","doi":"10.1109/ICCI57424.2023.10112327","DOIUrl":"https://doi.org/10.1109/ICCI57424.2023.10112327","url":null,"abstract":"Trypanosomiasis caused Trypanosoma evansi is current public health concern especially, in south Asia and Southeast Asia. Although polymerase chain reaction is currently used as a standard method, the techniques required skilled personnel, were performed in multiple steps, and required expensive instruments. Fundamental microscopic approach also has limitation in use by facing both inter- and intra-variability of interpretation by examiners. New automatic tool with the microscopic examination is needed. The study aimed to develop the mobile application-based YOLO neural network algorithms to predict T. evansi blood stages from thin-blood film examination. YOLO v4 tiny model is outperformed to localize and classify unseen images with the best performance at 95% of sensitivity, specificity, precision, accuracy and F1 score, respectively, with less misclassification rate than 5%. Simulation implementation platform, calling CiRA bot, give the empirical result and reliably comparable to that from the computational experiment studied with the area under ROC and precision-recall curves as 0.964 and 0.962, respectively. The result obtained from the CIRA bot platform is good enough for further distribution in field site. In the future, the study could contribute human and animal public health staff to simply identify the unicellular parasitic flagellate infection and also benefit them for designing the strategy in prevention and treatment of the disease.","PeriodicalId":112409,"journal":{"name":"2023 IEEE International Conference on Cybernetics and Innovations (ICCI)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127467142","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: 1

Intelligent Forecasting of Energy Consumption using Temporal Fusion Transformer model 基于时间融合变压器模型的能源消耗智能预测

2023 IEEE International Conference on Cybernetics and Innovations (ICCI) Pub Date : 2023-03-30 DOI: 10.1109/ICCI57424.2023.10112297

Sorawut Jittanon, Y. Mensin, C. Termritthikun

{"title":"Intelligent Forecasting of Energy Consumption using Temporal Fusion Transformer model","authors":"Sorawut Jittanon, Y. Mensin, C. Termritthikun","doi":"10.1109/ICCI57424.2023.10112297","DOIUrl":"https://doi.org/10.1109/ICCI57424.2023.10112297","url":null,"abstract":"The increasing demand for electrical energy is a major problem of carbon dioxide emissions. As well, the inefficient use of electricity is also concerning. Smart grids can make electricity use more efficient by integrating other technologies into the electrical system. Forecasting is one of those technologies which can improve electricity consumption efficiency. Precise forecasting can balance the demand and supply of electrical generation, and with the growing use of renewable energy sources such as solar and wind, more accurate forecasting is necessary. Our objective was to find a forecasting model that can best fit demand forecasting. Transformer is the name of the model that we applied in the forecasting task. The N-BEATS and N-HiTS models were used to compare with Transformer. The result is shown in mean absolute percentage error (MAPE). The Transformer model had the lowest MAPE (4.5980%) compared to the N-BEATS (5.0266%) and N-HiTS (7.9865%) models, indicating that it provides a more accurate prediction. The model's hyperparameters were set to the same values so that their results could be compared properly.","PeriodicalId":112409,"journal":{"name":"2023 IEEE International Conference on Cybernetics and Innovations (ICCI)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125214318","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

Prediction and Efficiency of Stroke Disease using data mining technique 基于数据挖掘技术的脑卒中疾病预测及效率研究

2023 IEEE International Conference on Cybernetics and Innovations (ICCI) Pub Date : 2023-03-30 DOI: 10.1109/ICCI57424.2023.10112495

Wiwit Suksangaram, Waratta Hemtong

引用次数: 0

Pillow for Detecting Snoring with Embedded Techniques for Elderly People with Snoring Problems 有打呼问题的老年人用嵌入式技术检测打呼枕头

2023 IEEE International Conference on Cybernetics and Innovations (ICCI) Pub Date : 2023-03-30 DOI: 10.1109/ICCI57424.2023.10112489

Worawut Yimyam, M. Ketcham, Thittaporn Ganokratanaa, Patiyuth Pramkeaw, Narumol Chumuang

引用次数: 0

International Conference on Cybernetics and Innovations 国际控制论与创新会议

2023 IEEE International Conference on Cybernetics and Innovations (ICCI) Pub Date : 2023-03-30 DOI: 10.1109/icci57424.2023.10112540

引用次数: 0

Welcome Message from the ICCI2023 General Co-Chairs ICCI2023大会共同主席欢迎辞

2023 IEEE International Conference on Cybernetics and Innovations (ICCI) Pub Date : 2023-03-30 DOI: 10.1109/icci57424.2023.10112532

引用次数: 0

Sorting Red and Green Chilies by Digital Image Processing 利用数字图像处理技术对红辣椒和绿辣椒进行分类

2023 IEEE International Conference on Cybernetics and Innovations (ICCI) Pub Date : 2023-03-30 DOI: 10.1109/ICCI57424.2023.10112254

Narumol Chumuang, M. Ketcham, Thittaporn Ganokratanaa, Patiyuth Pramkeaw, Jiratha Chongsri, Worawut Yimyam

引用次数: 0