2023 20th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON)最新文献_第9页

Precision coordinate transformations for Thai national geodetic infrastructure 泰国国家大地测量基础设施的精确坐标变换

2023 20th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON) Pub Date : 2023-05-09 DOI: 10.1109/ECTI-CON58255.2023.10153290

Korakod Butwong, Thayathip Thongtan, Kriengkrai Boonterm

{"title":"Precision coordinate transformations for Thai national geodetic infrastructure","authors":"Korakod Butwong, Thayathip Thongtan, Kriengkrai Boonterm","doi":"10.1109/ECTI-CON58255.2023.10153290","DOIUrl":"https://doi.org/10.1109/ECTI-CON58255.2023.10153290","url":null,"abstract":"Ground station receivers or networks’ location uses different geodetic datums. The geodetic datum defines size and shape of the Earth model and origin of orientation of coordinate systems used to map the Earth. They are modified to converge to the International Terrestrial Reference Frame (ITRF). The Thailand geodetic reference frame has been maintained by the Royal Thai Survey Department (RTSD); currently, it is based on GNSS permanent networks. Precise orbit and clock solutions, earth orientation parameters and tropospheric gradients are applied as fixing parameters to estimate station positions using a network approach where all station coordinates are simultaneously adjusted; defined as a zero-order network. They are determined with respected to ITRF with centimetre precisions and accuracies. The shape of the Earth varies over time due to oceanic tides and plate movements. Changing are more gradually when earthquakes and volcanic eruptions happen. ITRF and other geodetic datums are changing continually; therefore, frame transformations are required. The latest adjusted coordinates are based on ITRF2005, 2008 and 2014 frame and velocities are set at the epoch 2008.83, 2013.81 and 2021.93 respectively. Constraints are cast in form of transformation parameters. The grid shift is then generated to transform from global coordinate systems to local geocentric reference frames. GNSS measurements obtained from another set of ground stations are used as check coordinates. Transformed coordinates are at 1 centimetre-level of accuracy both horizontally and vertically at 95 percent confidence level. Coordinate transformations can be applied to map Thailand based on one map on one datum policy.","PeriodicalId":340768,"journal":{"name":"2023 20th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON)","volume":"88 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123330782","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

Combined Diffusion Adaptation on Adaptive Leaky Criterion and Orthogonal Gradient Algorithm 基于自适应泄漏准则和正交梯度算法的联合扩散自适应

2023 20th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON) Pub Date : 2023-05-09 DOI: 10.1109/ECTI-CON58255.2023.10153328

S. Sitjongsataporn, Piyaporn Nurarak

引用次数: 0

Image-based Thai Food Recognition and Calorie Estimation using Machine Learning Techniques 基于图像的泰国食物识别和使用机器学习技术的卡路里估计

2023 20th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON) Pub Date : 2023-05-09 DOI: 10.1109/ECTI-CON58255.2023.10153183

Rattikorn Sombutkaew, O. Chitsobhuk

{"title":"Image-based Thai Food Recognition and Calorie Estimation using Machine Learning Techniques","authors":"Rattikorn Sombutkaew, O. Chitsobhuk","doi":"10.1109/ECTI-CON58255.2023.10153183","DOIUrl":"https://doi.org/10.1109/ECTI-CON58255.2023.10153183","url":null,"abstract":"A wide range of health-related innovation have been developed to serve as an alternative personal health monitoring and tracking on exercise and dietary planning. The goal is to enable individuals to keep themselves healthy and disease-free. Assessing food calories helps to assist consumers in determining their calories intake each meal, leading to a strategy that regulates the amount of food they consume, and contributing to improve a control on nutrition consumption and weight loss. In this paper, we proposed a calorie estimation system on an android mobile application. Calorie estimation is performed using a food image captured from a mobile camera and the depth image from AR core library. The food area is segmented using our finetuned Mask R-CNN with Thai food image dataset. Finally, machine learning methods including Linear Regression, Support Vector Regression, K-Nearest Neighbor, and Deep Neural Network are used to estimate the amount of food calories included in a meal of each image. As a result, Deep Neural Network offers best prediction results with the most accurate prediction, the lowest error rate and the highest R-Square score.","PeriodicalId":340768,"journal":{"name":"2023 20th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134003960","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

Development of a Class Materials Search System using LINE Chatbot 利用 LINE 聊天机器人开发班级材料搜索系统

2023 20th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON) Pub Date : 2023-05-09 DOI: 10.1109/ECTI-CON58255.2023.10153145

Budsakorn Thaiprasert, Pannawat Chimprasert, Warunya Saeninyod, Phattanard Phattanasri, Aranee Pangarad

{"title":"Development of a Class Materials Search System using LINE Chatbot","authors":"Budsakorn Thaiprasert, Pannawat Chimprasert, Warunya Saeninyod, Phattanard Phattanasri, Aranee Pangarad","doi":"10.1109/ECTI-CON58255.2023.10153145","DOIUrl":"https://doi.org/10.1109/ECTI-CON58255.2023.10153145","url":null,"abstract":"Self-learning enables students to learn at their own pace. The process itself has changed significantly from reading textbooks to viewing ebooks on electronic devices, asking questions on online discussion boards or watching video clips from other parts of the world. The change has come with a massive increase in the amount of information available. It is time-consuming for a student to obtain the exact item of class material wanted. We developed a search system that can store relevant class materials in its own database and give suggestions when a student needs them. The system is built as a chatbot in the LINE application, using the NLP algorithm, to interact between users and the system via Artificial Intelligence technology. The system was developed for two subjects in Electrical Engineering: Signals and Systems and Control Systems. It was able to correctly interpret the users’ requests with up to 80% accuracy. It can give suggestions of class materials based on rankings given by users’ scores. This search system makes self-learning less time consuming and may provide more encouragement to students.","PeriodicalId":340768,"journal":{"name":"2023 20th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128024864","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

Unscented Kalman Filter for State of Charge Estimation of Lithium Titanate Battery 无气味卡尔曼滤波在钛酸锂电池电量状态估计中的应用

2023 20th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON) Pub Date : 2023-05-09 DOI: 10.1109/ECTI-CON58255.2023.10153143

Joshua Chun-Ken Dardchuntuk, D. Banjerdpongchai

引用次数: 1

On the lactone content distribution estimation in Andrographis paniculata (burm.f.) wall.ex nees using Hyperspectral Images and U-Net Network 穿心莲壁内酯含量分布估计。需要使用高光谱图像和U-Net网络

2023 20th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON) Pub Date : 2023-05-09 DOI: 10.1109/ECTI-CON58255.2023.10153360

N. Rojrattanatrai, T. Kasetkasem, T. Phatrapornant, C. Theerawitaya, D. Chungloo, S. Cha-um, Masahiro Yamaguchi

{"title":"On the lactone content distribution estimation in Andrographis paniculata (burm.f.) wall.ex nees using Hyperspectral Images and U-Net Network","authors":"N. Rojrattanatrai, T. Kasetkasem, T. Phatrapornant, C. Theerawitaya, D. Chungloo, S. Cha-um, Masahiro Yamaguchi","doi":"10.1109/ECTI-CON58255.2023.10153360","DOIUrl":"https://doi.org/10.1109/ECTI-CON58255.2023.10153360","url":null,"abstract":"Hyperspectral reflectance data in the VNIR-SWIR range (400-2500nm) are commonly used to non-destructively and contactless measure the chemical composition of the plants. Most traditional methods are based on non-spatial analysis, that method required the average spectral data to represent the entire image, resulting in the loss of spatial information. To address this issue, we utilize a U-Net network to preserve spatial information while also allowing for the identification and quantification of lactone content in the image. The resulting distribution map provides a clear visualization of lactone content throughout the field or crop, making it easy to identify areas with high or low lactone levels. The pre-processing method includes image registration, outlier removal, spectral smoothing, and normalization. These steps are designed to correct errors and improve the quality of the image and masking. According to the experimental results, the U-Net model achieved R2, RMSE, and DICE of 0.718, 11.66, and 89.92%, respectively. The results show that using hyperspectral images combined with the U-Net network can perform a reliable and accurate prediction model for determining lactone content in A. paniculata.","PeriodicalId":340768,"journal":{"name":"2023 20th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON)","volume":"75 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123868063","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

Low Latency PDM-to-PCM Decoder 低延迟pdm - pcm解码器

2023 20th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON) Pub Date : 2023-05-09 DOI: 10.1109/ECTI-CON58255.2023.10153161

Rithea Sum, Chanon Khongprasongsiri, W. Suwansantisuk, P. Kumhom

{"title":"Low Latency PDM-to-PCM Decoder","authors":"Rithea Sum, Chanon Khongprasongsiri, W. Suwansantisuk, P. Kumhom","doi":"10.1109/ECTI-CON58255.2023.10153161","DOIUrl":"https://doi.org/10.1109/ECTI-CON58255.2023.10153161","url":null,"abstract":"The output from a digital Micro-Electrical- Mechanical System (MEMS) microphone in the form of PDM often needs to be converted to PCM before further processing, as PCM signals are easier to analyze. The current hardware-based PDM-to-PCM converters uses cascaded integrator-comb (CIC) based and finite impulse response (FIR) filters, which result in high hardware utilization to achieve a high signal-to-noise ratio (SNR). To strike a balance between performance and power consumption, a one-dimensional convolutional neural network (1D-CNN) has been applied in a PDM-to-PCM converter. Although this method resolves the aforementioned issues, an improvement to the system latency and throughput is possible. This paper proposes a fast method for a hardware-based PDM-to-PCM converter by cascading a digital low-pass filter and an existing ID-CNN-based low-pass filter. The approximation results show that the output PCM signal has the mean absolute error (MAE) of only 0.0026 compared to the original PCM signal. The proposed method has been implemented on the Xilinx PYNQ-ZI field programmable gate array (FPGA). While there is a slight increase in hardware utilization due to an additional required hardware, the latency has improved by 61% compared to the existing ID-CNN-based PDM-to-PCM converter. This research reduces the time taken to process each PCM data from PDM in a hardware-based system.","PeriodicalId":340768,"journal":{"name":"2023 20th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125071965","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

Exams Item Analysis, Online Examination, and Education Evaluation System Via Internet 考试项目分析，在线考试，基于互联网的教育评价系统

2023 20th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON) Pub Date : 2023-05-09 DOI: 10.1109/ECTI-CON58255.2023.10153296

Kamonlak Chaidee, Kanchana Boontasri, E. Chaidee, Kittichai Punthura, Narong Kumtip, Yotsanan Pankham

{"title":"Exams Item Analysis, Online Examination, and Education Evaluation System Via Internet","authors":"Kamonlak Chaidee, Kanchana Boontasri, E. Chaidee, Kittichai Punthura, Narong Kumtip, Yotsanan Pankham","doi":"10.1109/ECTI-CON58255.2023.10153296","DOIUrl":"https://doi.org/10.1109/ECTI-CON58255.2023.10153296","url":null,"abstract":"The objective of this study is to develop an exams item bank management system on the internet. The exam item analysis system is used to determine the reliability of the exams using K-R 20 and K-R 21 formulas. The difficulty and power of discrimination values are determined using a choice analysis and percentages of high and lower groups technique. The create exams set system can be performed randomly or identified through the difficulty level. The examination can be performed online and the exam results can be immediately announced. The grading system is used to support the decision-making to evaluate learning achievement. The system’s accuracy was tested and found to be accurate compared with the hand calculation results. The system was tested with a sample group and satisfaction was assessed through questionnaires. The satisfaction of teachers and students was highest, while that of administrators was high. The developed exams item bank management system operates as a web application with a security system for supporting in learning activity.","PeriodicalId":340768,"journal":{"name":"2023 20th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON)","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117311072","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

Three-phase Self-Excited Induction Generator Operating as Single-phase Induction Generator using Static VAR Compensator 采用静态无功补偿器的三相自激感应发电机作为单相感应发电机工作

2023 20th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON) Pub Date : 2023-05-09 DOI: 10.1109/ECTI-CON58255.2023.10153314

S. Yukhalang, T. Sopapirm, V. Kinnares

引用次数: 0

A Development of LVDT Demodulator Circuit Based on FPAA Chip 基于FPAA芯片的LVDT解调电路的研制

2023 20th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON) Pub Date : 2023-05-09 DOI: 10.1109/ECTI-CON58255.2023.10153207

K. Angkeaw, Surachai Chanchay, P. Thongdit

引用次数: 0