T. Nguyen, Ching-Hwa Cheng, Don-Gey Liu, Song-Toan Tran, Minh-Hai Le
In this paper, we implemented a direct Time of Flight (ToF) method to calculate the distance of a pulsed-LiDAR in high background lights on a Red Pitaya platform. In this proposed system, we utilized the Red Pitaya Kit to simulate the generation of LiDAR pulses. Another Kit used to capture, process data, and estimate the distance. Signals are acquired, including high-intensity background noise because LiDARs are requested to work in worse environments like sunlight, electric light, fog, etc. To overcome this problem, we proposed an Overlapping-edge (OE) technique to be combined with the Leading-edge (LE) method to detect pulses in noisy environments. Moreover, the sampling rate of the ADC in this platform was limited to 125Msps. Therefore, we performed an interpolation algorithm, namely Center of Mass (CoM), to increase the accuracy of the estimated distance. The experiment was performed on simulated signals with a signal-to-noise ratio of -8.5dB. The obtained result showed that the average success rate of measurements increased 7.56% compared with the Leading-edge method and the average accuracy reached nearly 7.1cm. In conclusion, we have built a high noise Pulse-LiDAR source and calculate distance on a Red Pitaya platform with a low cost and highly stable accuracy. The performance of a LiDAR system was also evaluated in this study.
{"title":"An Overlapping and Leading Edge Detection Combined Technique for Distance Estimation under High-Background Lights in a Pulsed-LiDAR System","authors":"T. Nguyen, Ching-Hwa Cheng, Don-Gey Liu, Song-Toan Tran, Minh-Hai Le","doi":"10.1145/3475971.3475974","DOIUrl":"https://doi.org/10.1145/3475971.3475974","url":null,"abstract":"In this paper, we implemented a direct Time of Flight (ToF) method to calculate the distance of a pulsed-LiDAR in high background lights on a Red Pitaya platform. In this proposed system, we utilized the Red Pitaya Kit to simulate the generation of LiDAR pulses. Another Kit used to capture, process data, and estimate the distance. Signals are acquired, including high-intensity background noise because LiDARs are requested to work in worse environments like sunlight, electric light, fog, etc. To overcome this problem, we proposed an Overlapping-edge (OE) technique to be combined with the Leading-edge (LE) method to detect pulses in noisy environments. Moreover, the sampling rate of the ADC in this platform was limited to 125Msps. Therefore, we performed an interpolation algorithm, namely Center of Mass (CoM), to increase the accuracy of the estimated distance. The experiment was performed on simulated signals with a signal-to-noise ratio of -8.5dB. The obtained result showed that the average success rate of measurements increased 7.56% compared with the Leading-edge method and the average accuracy reached nearly 7.1cm. In conclusion, we have built a high noise Pulse-LiDAR source and calculate distance on a Red Pitaya platform with a low cost and highly stable accuracy. The performance of a LiDAR system was also evaluated in this study.","PeriodicalId":337890,"journal":{"name":"Proceedings of the 3rd International Electronics Communication Conference","volume":"63 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122198679","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}
In present, mental health issues are very important that could affect the population around the world. In Thailand, it is in an ever-changing economic and political period, including the COVID-19 epidemic that has a direct economic impact on the well-being of the people and making people in a state that causes more mental health problems, especially those who have suffered from career failure as well as those who are laid off or unemployed. This research aims to determine the factor influencing working stress of operative employee at automotive industry in Ladkrabang estate, Thailand. Data was gathered from 368 respondents by using convenience sampling method. This research shows the predictor of working stress are role in organization, career development, and relationship at work. In addition, organizational structure and climate have no effect on working stress of employees at automotive industry.
{"title":"Factors Influencing Working Stress Of Operative Employees: A Case Of Automotive Industry In Ladkrabang Estate","authors":"Supot Chaisin, N. Rojniruttikul","doi":"10.1145/3475971.3475981","DOIUrl":"https://doi.org/10.1145/3475971.3475981","url":null,"abstract":"In present, mental health issues are very important that could affect the population around the world. In Thailand, it is in an ever-changing economic and political period, including the COVID-19 epidemic that has a direct economic impact on the well-being of the people and making people in a state that causes more mental health problems, especially those who have suffered from career failure as well as those who are laid off or unemployed. This research aims to determine the factor influencing working stress of operative employee at automotive industry in Ladkrabang estate, Thailand. Data was gathered from 368 respondents by using convenience sampling method. This research shows the predictor of working stress are role in organization, career development, and relationship at work. In addition, organizational structure and climate have no effect on working stress of employees at automotive industry.","PeriodicalId":337890,"journal":{"name":"Proceedings of the 3rd International Electronics Communication Conference","volume":"365 5","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120892187","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}
This work presents the effects of internet usage, mobile subscription, ICT export, and ICT import on Gross Domestic Product in the context of Thailand by utilizing the Bayesian vector autoregression (BVAR) model with the 24 periods of annual modified data running from 1993 to 2016. This model shows the interactions between these five variables and the forecast of GDP. The results from this work revealed that internet usage, mobile subscription, and ICT export positively affect GDP in the short run manner. Whereas ICT import showed little evidence of a negative effect on GDP. Also, this work confirms the superior forecast performance of BVER over traditional VAR. According to the results of the analysis, we hence recommend that government authorities should 1) invest or support the investments in ICT infrastructure related to internet and mobile utilization, 2) reduce the cost of acquiring internet and mobile equipment and the cost of accessing the internet and mobile service, and 3) support the ICT exporters.
{"title":"ICT and Thai Economic Growth Nexus in the Bayesian VAR Model","authors":"N. Rojniruttikul, Adirek Vajrapatkul","doi":"10.1145/3475971.3475978","DOIUrl":"https://doi.org/10.1145/3475971.3475978","url":null,"abstract":"This work presents the effects of internet usage, mobile subscription, ICT export, and ICT import on Gross Domestic Product in the context of Thailand by utilizing the Bayesian vector autoregression (BVAR) model with the 24 periods of annual modified data running from 1993 to 2016. This model shows the interactions between these five variables and the forecast of GDP. The results from this work revealed that internet usage, mobile subscription, and ICT export positively affect GDP in the short run manner. Whereas ICT import showed little evidence of a negative effect on GDP. Also, this work confirms the superior forecast performance of BVER over traditional VAR. According to the results of the analysis, we hence recommend that government authorities should 1) invest or support the investments in ICT infrastructure related to internet and mobile utilization, 2) reduce the cost of acquiring internet and mobile equipment and the cost of accessing the internet and mobile service, and 3) support the ICT exporters.","PeriodicalId":337890,"journal":{"name":"Proceedings of the 3rd International Electronics Communication Conference","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114903894","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}
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