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2018 International Conference on Engineering, Applied Sciences, and Technology (ICEAST)最新文献

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The Analysis of a Microwave Sensor Signal for Detecting a Kick Gesture 一种用于踢腿动作检测的微波传感器信号分析
2018 International Conference on Engineering, Applied Sciences, and Technology (ICEAST) Pub Date : 2018-07-01 DOI: 10.1109/ICEAST.2018.8434455
Rathachai Chawuthai, R. Sakdanuphab
{"title":"The Analysis of a Microwave Sensor Signal for Detecting a Kick Gesture","authors":"Rathachai Chawuthai, R. Sakdanuphab","doi":"10.1109/ICEAST.2018.8434455","DOIUrl":"https://doi.org/10.1109/ICEAST.2018.8434455","url":null,"abstract":"A hands-free operation is a solution for people who require a hand to do an action but both right and left hands are busy carrying something. There are many techniques, and most of them use sensors to check a command from humans such as voice and movement. A kick gesture is one technique that people can kick into the air to invoke an operation of a target device such as a kick-activation liftgate of a car. In this paper, we use a microwave sensor to detect the movement of a human's foot and employ machine learning techniques to analyses the sensor data. It has found that the Logistic Regression technique provides the best accuracy, and the model can be simply programmed in an embedded system.","PeriodicalId":138654,"journal":{"name":"2018 International Conference on Engineering, Applied Sciences, and Technology (ICEAST)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130128714","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: 2
Traffic Light Color Identification for Automatic Traffic Light Violation Detection System 用于交通信号灯违章自动检测系统的交通信号灯颜色识别
2018 International Conference on Engineering, Applied Sciences, and Technology (ICEAST) Pub Date : 2018-07-01 DOI: 10.1109/ICEAST.2018.8434400
P. Wonghabut, J. Kumphong, R. Ung-arunyawee, W. Leelapatra, T. Satiennam
{"title":"Traffic Light Color Identification for Automatic Traffic Light Violation Detection System","authors":"P. Wonghabut, J. Kumphong, R. Ung-arunyawee, W. Leelapatra, T. Satiennam","doi":"10.1109/ICEAST.2018.8434400","DOIUrl":"https://doi.org/10.1109/ICEAST.2018.8434400","url":null,"abstract":"Automatic traffic light violation detection system relies on color detection of traffic light appeared in video frames. Presence of red light in video frame triggers detection software routine to identify vehicles violating traffic light. Detection of red light in video frames can be difficult due to: fading or dimming of red light, obscurity from large vehicles and flare. In this paper, we present a software technique based on HSV (Hue, Saturation, Value) color model to eliminate difficulties in red light detection mentioned above and is able to identify all colors of traffic light which gives 96% detection accuracy.","PeriodicalId":138654,"journal":{"name":"2018 International Conference on Engineering, Applied Sciences, and Technology (ICEAST)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114819049","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: 12
Automatic Labeling for Thai News Articles Based on Vector Representation of Documents 基于文档向量表示的泰语新闻文章自动标注
2018 International Conference on Engineering, Applied Sciences, and Technology (ICEAST) Pub Date : 2018-07-01 DOI: 10.1109/ICEAST.2018.8434457
Wiphada Jirasirilerd, Pikulkaew Tangtisanon
{"title":"Automatic Labeling for Thai News Articles Based on Vector Representation of Documents","authors":"Wiphada Jirasirilerd, Pikulkaew Tangtisanon","doi":"10.1109/ICEAST.2018.8434457","DOIUrl":"https://doi.org/10.1109/ICEAST.2018.8434457","url":null,"abstract":"Nowadays, the most powerful news source in the world comes from online media on the Internet. The information comes from the SNS, video clips, audio clips or various news websites. In this competitive world, many news websites are mainly focused on publishing their contents to the website as fast as they can without taking time to label them correctly. This leads to a problem where readers cannot find news that they are interested in from a large amount of information on the website. In this paper, we propose a method to automatically label articles on the Thai language website using distributed representation of documents. The semantic similar words are extracted from paragraph vectors of each category of news and assign them as labels. We apply the convolutional neural network with binary classification approach to separate words from sentences and the result of the experiments indicated that our method can be applied to automatically label Thai news article effectively.","PeriodicalId":138654,"journal":{"name":"2018 International Conference on Engineering, Applied Sciences, and Technology (ICEAST)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134291457","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
Dynamic Structure Adaptive Actuator Failure Compensation Scheme for Robotic Systems 机器人系统动态结构自适应驱动器故障补偿方案
2018 International Conference on Engineering, Applied Sciences, and Technology (ICEAST) Pub Date : 2018-07-01 DOI: 10.1109/ICEAST.2018.8434490
Thummaros Rugthum
{"title":"Dynamic Structure Adaptive Actuator Failure Compensation Scheme for Robotic Systems","authors":"Thummaros Rugthum","doi":"10.1109/ICEAST.2018.8434490","DOIUrl":"https://doi.org/10.1109/ICEAST.2018.8434490","url":null,"abstract":"This paper proposes a new adaptive actuator failure compensation scheme with dynamic controller structure. The adaptive control design use the concept of dynamic controller structure to improve the performance of a robotic system by reducing the number of possible actuator failure patterns that a controller needs to consider at any given time. With the decrease of failure patterns, the number of estimated parameters in the system is also reduced; thus, the adaptation of uncertain parameters is more efficient. The dynamic structure adaptive actuator failure compensation scheme improve the transient response of the system while maintains desired closed-loop stability and asymptotic output tracking, despite unknown actuator failures. The simulation results are studied to confirm the control performance.","PeriodicalId":138654,"journal":{"name":"2018 International Conference on Engineering, Applied Sciences, and Technology (ICEAST)","volume":"63 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126112684","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
Teleoperation of Humanoid Robot by Motion Capturing Using KINECT 基于KINECT动作捕捉的仿人机器人遥操作
2018 International Conference on Engineering, Applied Sciences, and Technology (ICEAST) Pub Date : 2018-07-01 DOI: 10.1109/ICEAST.2018.8434458
C. Vongchumyen, Chitrin Bamrung, Wasita Kamintra, Akkradach Watcharapupong
{"title":"Teleoperation of Humanoid Robot by Motion Capturing Using KINECT","authors":"C. Vongchumyen, Chitrin Bamrung, Wasita Kamintra, Akkradach Watcharapupong","doi":"10.1109/ICEAST.2018.8434458","DOIUrl":"https://doi.org/10.1109/ICEAST.2018.8434458","url":null,"abstract":"In this research, present a control ROBOBUILDER by using human gesture and detect motion by technology Motion controller in the part of the KINECT and convert signal into the process. In this study aim to developed control the ROBOBUILDER using hardware, software and networks to work within the system. By using a robot resembling a human-based Digital Servo to operate and use an algorithm to find the angle to control Servo Motor include using Arduino added in WI-FI module to send commands to control. Robot in addition to the convenience of controlling a robot to a more natural and as an alternative to control such a robot to use in a dangerous situation to humans, such as a nuclear submarine or space can also be used or for fun for users of alleges.","PeriodicalId":138654,"journal":{"name":"2018 International Conference on Engineering, Applied Sciences, and Technology (ICEAST)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130485552","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: 3
High Performance BLDC Motor Control for Electric Vehicle 电动汽车高性能无刷直流电机控制
2018 International Conference on Engineering, Applied Sciences, and Technology (ICEAST) Pub Date : 2018-07-01 DOI: 10.1109/ICEAST.2018.8434499
W. Khan-ngern, Wiwat Keyoonwong, Narongrit Chatsiriwech, Pongsakorn Sangnopparat, Ponghiran Mattayaboon, Pattarakij Worawalai
{"title":"High Performance BLDC Motor Control for Electric Vehicle","authors":"W. Khan-ngern, Wiwat Keyoonwong, Narongrit Chatsiriwech, Pongsakorn Sangnopparat, Ponghiran Mattayaboon, Pattarakij Worawalai","doi":"10.1109/ICEAST.2018.8434499","DOIUrl":"https://doi.org/10.1109/ICEAST.2018.8434499","url":null,"abstract":"This paper presents about design of high performance brushless dc motor (BLDC) control for electric vehicle (EV) which focusing on rear differential of electric car uses electronic control system or well known as electronic differential system (EDs). The advantage of EDs is help to adjust wheel speed while cornering by driving two BLDC motor attached to two rear wheels that two wheel speed is different. This system can accurately control process by monitoring output and feeding some of it back to compare actual output with desired output so as to reduce the error. It is well known as closed loop control system. The speed of BLDC is experimentally measured by a tachometer. The steering angle and speed of EV is calculated by equations derived from Ackemuuui-Jesntsnd model using Arduino. Load simulation using MATLAB Simulink. The experimental results electronic differential using will enhances efficiency of electric vehicle driving system.","PeriodicalId":138654,"journal":{"name":"2018 International Conference on Engineering, Applied Sciences, and Technology (ICEAST)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129019856","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: 9
Apparatus for Inspection of Low-Coercivity Magnetic Force Microscopy Tips 低矫顽力磁力显微镜针尖检验装置
2018 International Conference on Engineering, Applied Sciences, and Technology (ICEAST) Pub Date : 2018-07-01 DOI: 10.1109/ICEAST.2018.8434451
B. Damrongsak, Worachote Photaram, K. Saengkaew, I. Cheowanish, P. Damrongsak
{"title":"Apparatus for Inspection of Low-Coercivity Magnetic Force Microscopy Tips","authors":"B. Damrongsak, Worachote Photaram, K. Saengkaew, I. Cheowanish, P. Damrongsak","doi":"10.1109/ICEAST.2018.8434451","DOIUrl":"https://doi.org/10.1109/ICEAST.2018.8434451","url":null,"abstract":"In hard disk drive manufacturing, magnetic force microscopy (MFM) is employed to provide feedback for process control. This requires accurate and precise measurement of the intensity and the width of the write field generated from fabricated recording heads. Thus, the response of MFM tips when exposed to the write field must be consistency, run to run and machine to machine; however, no specific tool that can inspect and separate out-of-spec or defective MFM tips is available so far. In this present work, we designed and developed a new apparatus that is suitable to quantitatively evaluate the performance of low-coercivity MFM tips. The detailed discussion of the design of the proposed system is given as well as the inspection algorithm. Basically, a solenoid coil is used as a magnetic field generator which can generate the field strength up to 500 Oe, enough to saturate the tip magnetization. When the tip was exposed, a phase difference of the oscillating MFM tip, which is directly proportional to the field intensity, is employed as a measure of the tip response. In addition, the capability of the implemented apparatus to inspect low-coercivity MFM tips was demonstrated. Results were then compared with those obtained from a conventional MFM machine with the reference magnetic write head as a test sample. Several tests with different sets of low-coercivity MFM tips were carried out to evaluate the implemented system. Results showed that it can distinguish the response of different MFM tips; however, as the results were not too different, only three samples were selected to present here, including the tips with typical magnetic response, low response and out-of-spec response. The measured phase shifts of those samples were 54.5 ± 0.3, 36.3 ± 0.3 and 15.4 ± 0.2 degrees, respectively.","PeriodicalId":138654,"journal":{"name":"2018 International Conference on Engineering, Applied Sciences, and Technology (ICEAST)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127592513","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 Convolutional Neural Network for Segmentation of Background Texture and Defect on Copper Clad Lamination Surface 基于卷积神经网络的覆铜箔表面背景纹理和缺陷分割
2018 International Conference on Engineering, Applied Sciences, and Technology (ICEAST) Pub Date : 2018-07-01 DOI: 10.1109/ICEAST.2018.8434483
Harn Sison, Poom Konghuayrob, S. Kaitwanidvilai
{"title":"A Convolutional Neural Network for Segmentation of Background Texture and Defect on Copper Clad Lamination Surface","authors":"Harn Sison, Poom Konghuayrob, S. Kaitwanidvilai","doi":"10.1109/ICEAST.2018.8434483","DOIUrl":"https://doi.org/10.1109/ICEAST.2018.8434483","url":null,"abstract":"This research interprets the design and test process of copper clad lamination surface defects detection. The system was included four following stages: image acquisition, image pre-processing and segmentation, convolutional neural network design and image classification. Image processing method and pattern recognition algorithm are utilized in the system. First, the author applies the smoothing filters to eliminate noise from the images and segmenting a defect from background texture. Then, the convolutional neural network architecture is created to learn local feature of defect and background texture. Finally, defect and background images from segmentation step are collected and fed into a convolutional neural network to train and perform the classification task. The classification results demonstrate that the proposed method can re-checked false positive detect from the conventional Sobel edge detection, Hence the accuracy was increased from 78.1% to 98.2%.","PeriodicalId":138654,"journal":{"name":"2018 International Conference on Engineering, Applied Sciences, and Technology (ICEAST)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117292125","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: 4
Improved Gesture Recognition Using Deep Neural Networks on sEMG 基于表面肌电信号的深度神经网络改进手势识别
2018 International Conference on Engineering, Applied Sciences, and Technology (ICEAST) Pub Date : 2018-07-01 DOI: 10.1109/ICEAST.2018.8434493
Raquib-ul Alam, Shams Rashid Rhivu, M. A. Haque
{"title":"Improved Gesture Recognition Using Deep Neural Networks on sEMG","authors":"Raquib-ul Alam, Shams Rashid Rhivu, M. A. Haque","doi":"10.1109/ICEAST.2018.8434493","DOIUrl":"https://doi.org/10.1109/ICEAST.2018.8434493","url":null,"abstract":"Proper classification and detection of hand muscle movements have always been an important aspect for prosthesis control. The muscular movements can be best understood practically by the analysis of non-invasive surface electromyography (sEMG). But the challenge is to differentiate various types of finger movements with high accuracy. For this purpose, we used deep convolutional neural networks to differentiate and classify a total of ten individual and combined finger movements using a two channel sEMG. We used a database of ten participants with two electrodes attached on their forearms performing our preselected movements. Our aim was to increase the maximum classification accuracy using best practices of neural network and evaluating numerous hyperparameters. The final testing accuracy was approximately 98.88 to 100% for our dataset which is significantly higher than many conventional processes.","PeriodicalId":138654,"journal":{"name":"2018 International Conference on Engineering, Applied Sciences, and Technology (ICEAST)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115724648","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: 13
Evaluation of Wind Energy Production Using Weibull Distribution and Artificial Neural Networks 基于威布尔分布和人工神经网络的风能生产评价
2018 International Conference on Engineering, Applied Sciences, and Technology (ICEAST) Pub Date : 2018-07-01 DOI: 10.1109/ICEAST.2018.8434474
Khanittha Wannakam, S. Jiriwibhakorn
{"title":"Evaluation of Wind Energy Production Using Weibull Distribution and Artificial Neural Networks","authors":"Khanittha Wannakam, S. Jiriwibhakorn","doi":"10.1109/ICEAST.2018.8434474","DOIUrl":"https://doi.org/10.1109/ICEAST.2018.8434474","url":null,"abstract":"Wind turbine power generation planning requires production estimation. Wind power is uncertain depending on the location, wind speed and wind turbine efficiency. This paper presents a method for evaluating wind energy production using Weibull distribution and Artificial neural networks to compare the data recorded by Promthep Alternative Energy Station, Phuket, Thailand. The results show that wind energy estimation using artificial neural networks produces the most accurate results. Mean Absolute Percentage Error is used to determine the minimum error value. Minimal error of training data is 2.524% and the test data is 3.3041%.","PeriodicalId":138654,"journal":{"name":"2018 International Conference on Engineering, Applied Sciences, and Technology (ICEAST)","volume":"153 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128347274","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
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