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16.
Somkiat Tangjitsitcharoen, Jettanong Klaewsongkram
DEVELOPMENT OF ENUMERATOR ON ANDROID PLATFORM FOR COUNTING ELISPOT Conference
Association for Computing Machinery, 2025, ISBN: 979-840071792-5, (Cited by: 0).
@conference{Tangjitsitcharoen2025180,
title = {DEVELOPMENT OF ENUMERATOR ON ANDROID PLATFORM FOR COUNTING ELISPOT},
author = {Somkiat Tangjitsitcharoen and Jettanong Klaewsongkram},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-105011694640&doi=10.1145%2f3719384.3719410&partnerID=40&md5=6c0dc845ce603c1321b61c29f6dec4c2},
doi = {10.1145/3719384.3719410},
isbn = {979-840071792-5},
year = {2025},
date = {2025-01-01},
journal = {ACM International Conference Proceeding Series},
pages = {180 – 188},
publisher = {Association for Computing Machinery},
abstract = {The objective of this research is to create an object-detecting Android application for ELISpot immunoassay reading. The ability to accurately, quickly, and cheaply conduct immunoassay tests will guarantee that public healthcare industries are operating and helping patients in rural areas effectively. The past reliance on purchased laboratory equipment, and the rampant cost of health services has led to the privatization of healthcare industries and the negligence of rural area healthcare facilities. Therefore, this research is intended to help spread ELISpot test capability to smaller less-funded programs by creating an accessible ELISpot reading system in the form of an application and the hardware required. Object detection solutions present 2 issues; computational intensity and image quality. An Android application containing the enumeration algorithm was also designed. In order to implement object detection capability on mobile devices, the parameters used were extracted from a Faster R-CNN neural network model trained from a set of immunoassay images provided by the laboratory. The annotation of the images was done using LabelImage, whose output of .xml was converted to .csv and tfrecord files respectively. The computational accuracy tested over the samples averages out at 98% accuracy. While other design parameters such as image processing speed, system weight, and process throughput time are all satisfactory. With the project completed successfully, it is believed that with the upcoming technologies of deep learning super sampling (DLSS) With this kept in mind, true deep learning capable object detection applications operated on a mobile device will soon become more widespread and accessible. © 2024 Copyright held by the owner/author(s).},
note = {Cited by: 0},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
The objective of this research is to create an object-detecting Android application for ELISpot immunoassay reading. The ability to accurately, quickly, and cheaply conduct immunoassay tests will guarantee that public healthcare industries are operating and helping patients in rural areas effectively. The past reliance on purchased laboratory equipment, and the rampant cost of health services has led to the privatization of healthcare industries and the negligence of rural area healthcare facilities. Therefore, this research is intended to help spread ELISpot test capability to smaller less-funded programs by creating an accessible ELISpot reading system in the form of an application and the hardware required. Object detection solutions present 2 issues; computational intensity and image quality. An Android application containing the enumeration algorithm was also designed. In order to implement object detection capability on mobile devices, the parameters used were extracted from a Faster R-CNN neural network model trained from a set of immunoassay images provided by the laboratory. The annotation of the images was done using LabelImage, whose output of .xml was converted to .csv and tfrecord files respectively. The computational accuracy tested over the samples averages out at 98% accuracy. While other design parameters such as image processing speed, system weight, and process throughput time are all satisfactory. With the project completed successfully, it is believed that with the upcoming technologies of deep learning super sampling (DLSS) With this kept in mind, true deep learning capable object detection applications operated on a mobile device will soon become more widespread and accessible. © 2024 Copyright held by the owner/author(s).
17.
Ravee Bunduwongse, Somkiat Tangjitsitcharoen
Virtual Reality Application of Lathe Machine Training Journal Article
In: Engineering Journal, vol. 29, no. 3, pp. 59 – 77, 2025, ISSN: 01258281, (Cited by: 0).
@article{Bunduwongse202559,
title = {Virtual Reality Application of Lathe Machine Training},
author = {Ravee Bunduwongse and Somkiat Tangjitsitcharoen},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-105002127229&doi=10.4186%2fej.2025.29.3.59&partnerID=40&md5=99ba0d3a45a5c12a7860fa072cc2736e},
doi = {10.4186/ej.2025.29.3.59},
issn = {01258281},
year = {2025},
date = {2025-01-01},
journal = {Engineering Journal},
volume = {29},
number = {3},
pages = {59 – 77},
publisher = {Chulalongkorn University, Faculty of Fine and Applied Arts},
abstract = {This study aims to utilize Virtual Reality (VR) technology to develop an industrial training application with content focusing on Machining operation using lathe machine. The focus of the study is to present the content being taught in manufacturing laboratory classes about lathe machining operations in the virtual world. Machining operations demonstrated within this application includes turning, facing, chamfering, cutoff, internal and external threading. The user journey is designed to guide users through the content tailored aimed to familiarize them with the order of operation and safety guidelines. This educational tool further provides the freedom of the user to repeat the process without restriction to their location, time, or resource, as opposed to conventional hands-on laboratory. The study involves the research of the laboratory content, development planning, assets creation, functional design and implementation, and integration with Salesforce platform as learning assessment database tool. This study emphasizes future content expansion and is therefore developed with modularity in mind to best promote future content enrichment. The application resulted in the ability to represent a total of 5 machining operations. © 2025, Chulalongkorn University, Faculty of Fine and Applied Arts. All rights reserved.},
note = {Cited by: 0},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
This study aims to utilize Virtual Reality (VR) technology to develop an industrial training application with content focusing on Machining operation using lathe machine. The focus of the study is to present the content being taught in manufacturing laboratory classes about lathe machining operations in the virtual world. Machining operations demonstrated within this application includes turning, facing, chamfering, cutoff, internal and external threading. The user journey is designed to guide users through the content tailored aimed to familiarize them with the order of operation and safety guidelines. This educational tool further provides the freedom of the user to repeat the process without restriction to their location, time, or resource, as opposed to conventional hands-on laboratory. The study involves the research of the laboratory content, development planning, assets creation, functional design and implementation, and integration with Salesforce platform as learning assessment database tool. This study emphasizes future content expansion and is therefore developed with modularity in mind to best promote future content enrichment. The application resulted in the ability to represent a total of 5 machining operations. © 2025, Chulalongkorn University, Faculty of Fine and Applied Arts. All rights reserved.
18.
Panathorn Kankaew, Parames Chutima
Utilizing Six Sigma for Effective Pore Defect Reduction in Plastic Water Tanks Journal Article
In: Key Engineering Materials, vol. 1016, pp. 105 – 112, 2025, ISSN: 10139826, (Cited by: 0).
@article{Kankaew2025105,
title = {Utilizing Six Sigma for Effective Pore Defect Reduction in Plastic Water Tanks},
author = {Panathorn Kankaew and Parames Chutima},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-105009237652&doi=10.4028%2fp-S08yFc&partnerID=40&md5=6b0e1815d436ff9d84da28355632c5f8},
doi = {10.4028/p-S08yFc},
issn = {10139826},
year = {2025},
date = {2025-01-01},
journal = {Key Engineering Materials},
volume = {1016},
pages = {105 – 112},
publisher = {Trans Tech Publications Ltd},
abstract = {Plastic water tanks made from FDA-approved Polyethylene (PE) are widely used due to their advantageous qualities, including being free of heavy metals, UV-stable, odorless, durable, and suitable for food-grade applications. A rotational molding process creates a smooth inner surface without corners, reducing dirt adhesion. However, a case study revealed pore defects on the outer surface of the tanks, compromising UV stability and customer satisfaction. This study aims to address these pore defects by establishing new standards and improving both internal processes and external factors affecting mold heating. Utilizing Six Sigma methodology, the study employs data analysis and design of experiments (DOE) to identify and regulate critical parameters affecting the manufacturing process. The Six Sigma approach, which encompasses the Define, Measure, Analyze, Improve, and Control (DMAIC) phases, was applied to enhance process capability, minimize variations and machine errors, reduce waste, and increase customer satisfaction. By effectively addressing the root causes of porosity defects, the study aims to improve processes and enhance product quality. © 2025 Trans Tech Publications Ltd, All Rights Reserved.},
note = {Cited by: 0},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Plastic water tanks made from FDA-approved Polyethylene (PE) are widely used due to their advantageous qualities, including being free of heavy metals, UV-stable, odorless, durable, and suitable for food-grade applications. A rotational molding process creates a smooth inner surface without corners, reducing dirt adhesion. However, a case study revealed pore defects on the outer surface of the tanks, compromising UV stability and customer satisfaction. This study aims to address these pore defects by establishing new standards and improving both internal processes and external factors affecting mold heating. Utilizing Six Sigma methodology, the study employs data analysis and design of experiments (DOE) to identify and regulate critical parameters affecting the manufacturing process. The Six Sigma approach, which encompasses the Define, Measure, Analyze, Improve, and Control (DMAIC) phases, was applied to enhance process capability, minimize variations and machine errors, reduce waste, and increase customer satisfaction. By effectively addressing the root causes of porosity defects, the study aims to improve processes and enhance product quality. © 2025 Trans Tech Publications Ltd, All Rights Reserved.
19.
Kantawatchr Chaiprabha, Gridsada Phanomchoeng, Parames Chutima, Ninshu Ma, Kaamutsup Sungkaksem, Setthibhak Suthithanakom, Ratchatin Chancharoen
Advancing Industry 5.0: Collaborative Welding Robotics With Precision, Safety, and Flexibility Journal Article
In: IEEE Access, vol. 13, pp. 124734 – 124751, 2025, ISSN: 21693536, (Cited by: 0).
@article{Chaiprabha2025124734,
title = {Advancing Industry 5.0: Collaborative Welding Robotics With Precision, Safety, and Flexibility},
author = {Kantawatchr Chaiprabha and Gridsada Phanomchoeng and Parames Chutima and Ninshu Ma and Kaamutsup Sungkaksem and Setthibhak Suthithanakom and Ratchatin Chancharoen},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-105010974144&doi=10.1109%2fACCESS.2025.3588515&partnerID=40&md5=6f03438cbeb02c50ebb4c142610da7ec},
doi = {10.1109/ACCESS.2025.3588515},
issn = {21693536},
year = {2025},
date = {2025-01-01},
journal = {IEEE Access},
volume = {13},
pages = {124734 – 124751},
publisher = {Institute of Electrical and Electronics Engineers Inc.},
abstract = {This study presents a digital twin-based seam correction framework for collaborative robotic laser welding. The framework addresses key manufacturing challenges, including dimensional inconsistencies, motion inversion, and lightweight part deformation, which significantly impact welding quality. Digital twin technology enables comprehensive analysis and supports real-time deviation monitoring and compensation. Experimental results demonstrate a reduction in maximum seam deviation from 2.9 mm to <0.2 mm, achieving an average deviation <0.1 mm. The system ensures precise laser beam positioning, leading to waterproof welding. Bézier curves are used in the seam correction, providing a flexible and scalable approach. This research contributes to improving welding accuracy and adaptability in flexible production environments while minimizing resource consumption and material waste. © 2013 IEEE.},
note = {Cited by: 0},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
This study presents a digital twin-based seam correction framework for collaborative robotic laser welding. The framework addresses key manufacturing challenges, including dimensional inconsistencies, motion inversion, and lightweight part deformation, which significantly impact welding quality. Digital twin technology enables comprehensive analysis and supports real-time deviation monitoring and compensation. Experimental results demonstrate a reduction in maximum seam deviation from 2.9 mm to <0.2 mm, achieving an average deviation <0.1 mm. The system ensures precise laser beam positioning, leading to waterproof welding. Bézier curves are used in the seam correction, providing a flexible and scalable approach. This research contributes to improving welding accuracy and adaptability in flexible production environments while minimizing resource consumption and material waste. © 2013 IEEE.
20.
Sanyapong Petchrompo, Sunny Modhara, Andy Kirwan, Ajith Kumar Parlikad, Naruemon Wattanapongsakorn
A two-step post-optimality approach for a multi-objective railway maintenance planning problem Journal Article
In: Computers and Industrial Engineering, vol. 192, 2024, (Cited by: 4; All Open Access, Green Open Access, Hybrid Gold Open Access).
@article{Petchrompo2024,
title = {A two-step post-optimality approach for a multi-objective railway maintenance planning problem},
author = {Sanyapong Petchrompo and Sunny Modhara and Andy Kirwan and Ajith Kumar Parlikad and Naruemon Wattanapongsakorn},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85193575560&doi=10.1016%2fj.cie.2024.110207&partnerID=40&md5=6790331853aeae10988aa5bf03315c3e},
doi = {10.1016/j.cie.2024.110207},
year = {2024},
date = {2024-01-01},
journal = {Computers and Industrial Engineering},
volume = {192},
note = {Cited by: 4; All Open Access, Green Open Access, Hybrid Gold Open Access},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
21.
Lugnapis Kaewwhangsakul, Nantachai Kantanantha
Exploring the Characteristics of Time Series Data Affecting Forecasting Errors Using LSTM Conference
Association for Computing Machinery, 2024, ISBN: 979-840071820-5, (Cited by: 0).
@conference{Kaewwhangsakul20248,
title = {Exploring the Characteristics of Time Series Data Affecting Forecasting Errors Using LSTM},
author = {Lugnapis Kaewwhangsakul and Nantachai Kantanantha},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85207097394&doi=10.1145%2f3695220.3695224&partnerID=40&md5=69cbea1076542f9f0e9401cca11b0a4d},
doi = {10.1145/3695220.3695224},
isbn = {979-840071820-5},
year = {2024},
date = {2024-01-01},
journal = {ACM International Conference Proceeding Series},
pages = {8 – 13},
publisher = {Association for Computing Machinery},
abstract = {This paper investigates the predictive capabilities of Long Short-Term Memory (LSTM) models using diverse time series data relevant to lifestyle decisions and business planning, such as stock prices, exchange rates, gold prices, and weather conditions. The main contributions include analyzing 42 datasets from Kaggle.com to identify influential features impacting LSTM prediction accuracy. Findings reveal varying prediction accuracy across datasets due to different data characteristics, with some datasets exhibiting high Mean Absolute Percentage Error (MAPE) when they process Coefficient of Variation (CV) exceeding 50%. Additionally, datasets with non-normal distributions and high kurtosis show greater prediction errors. These findings underscore the significance of considering dataset features for accurate LSTM predictions in real-world applications. © 2024 Owner/Author.},
note = {Cited by: 0},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
This paper investigates the predictive capabilities of Long Short-Term Memory (LSTM) models using diverse time series data relevant to lifestyle decisions and business planning, such as stock prices, exchange rates, gold prices, and weather conditions. The main contributions include analyzing 42 datasets from Kaggle.com to identify influential features impacting LSTM prediction accuracy. Findings reveal varying prediction accuracy across datasets due to different data characteristics, with some datasets exhibiting high Mean Absolute Percentage Error (MAPE) when they process Coefficient of Variation (CV) exceeding 50%. Additionally, datasets with non-normal distributions and high kurtosis show greater prediction errors. These findings underscore the significance of considering dataset features for accurate LSTM predictions in real-world applications. © 2024 Owner/Author.
22.
Racha Lertsakwanit, Amonsiri Vilasdaechanont
Ocular Prosthesis Fabrication Scheduling Using Genetic Algorithm Journal Article
In: Engineering Journal, vol. 28, no. 11, pp. 69 – 79, 2024, ISSN: 01258281, (Cited by: 0; All Open Access, Gold Open Access).
@article{Lertsakwanit202469,
title = {Ocular Prosthesis Fabrication Scheduling Using Genetic Algorithm},
author = {Racha Lertsakwanit and Amonsiri Vilasdaechanont},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85211902150&doi=10.4186%2fej.2024.28.11.69&partnerID=40&md5=741779df0c1862a54ba9a102e4ba5ba9},
doi = {10.4186/ej.2024.28.11.69},
issn = {01258281},
year = {2024},
date = {2024-01-01},
journal = {Engineering Journal},
volume = {28},
number = {11},
pages = {69 – 79},
publisher = {Chulalongkorn University, Faculty of Fine and Applied Arts},
abstract = {This research examines an ocular prosthesis centre’s operation and incorporates scheduling decision techniques to optimise its fabrication. A customised eye prosthesis is a make-to-order product which involves several labour-intensive processes and inherently poses scheduling challenges. As a result, patients' fitment dates are appointed with extra time to account for potential delays. The objective of scheduling is to minimise both total completion time and tardiness. The methodology begins with a process review of the customised eye prosthesis fabrication and criteria. Subsequently, a Mixed Integer Linear Programming (MILP) model is formulated to solve the assignment and sequencing problems. It is found during this stage that computational time increases significantly as the number of orders increases. To solve this problem, a Genetic Algorithm (GA) is proposed to find a near-optimal solution in a reasonable computational time. Instances selected for experiment are based on characteristics of a tertiary hospital’s ocular prosthesis centre. Small instances are experimented to validate the proposed algorithm against the MILP model. The GA demonstrates near-optimal solutions with a variance of one percent, with reasonable computational time. Practical-size problems are subsequently solved using the proposed algorithm. In conclusion, the proposed GA yields satisfactory solutions with acceptable runtime for this application. © 2024, Chulalongkorn University, Faculty of Fine and Applied Arts. All rights reserved.},
note = {Cited by: 0; All Open Access, Gold Open Access},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
This research examines an ocular prosthesis centre’s operation and incorporates scheduling decision techniques to optimise its fabrication. A customised eye prosthesis is a make-to-order product which involves several labour-intensive processes and inherently poses scheduling challenges. As a result, patients' fitment dates are appointed with extra time to account for potential delays. The objective of scheduling is to minimise both total completion time and tardiness. The methodology begins with a process review of the customised eye prosthesis fabrication and criteria. Subsequently, a Mixed Integer Linear Programming (MILP) model is formulated to solve the assignment and sequencing problems. It is found during this stage that computational time increases significantly as the number of orders increases. To solve this problem, a Genetic Algorithm (GA) is proposed to find a near-optimal solution in a reasonable computational time. Instances selected for experiment are based on characteristics of a tertiary hospital’s ocular prosthesis centre. Small instances are experimented to validate the proposed algorithm against the MILP model. The GA demonstrates near-optimal solutions with a variance of one percent, with reasonable computational time. Practical-size problems are subsequently solved using the proposed algorithm. In conclusion, the proposed GA yields satisfactory solutions with acceptable runtime for this application. © 2024, Chulalongkorn University, Faculty of Fine and Applied Arts. All rights reserved.
23.
Punyaanek Srisurin, Agustin Guerra, Pisit Jarumaneeroj
In: International Journal of Technology, vol. 15, no. 6, pp. 1678 – 1696, 2024, ISSN: 20869614, (Cited by: 1; All Open Access, Gold Open Access).
@article{Srisurin20241678,
title = {Traffic Simulation Models to Enhance Signal Timing in an Oversaturated Network: A Comparative Study of Optimizing Individual Intersections versus the Entire Network},
author = {Punyaanek Srisurin and Agustin Guerra and Pisit Jarumaneeroj},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85214941856&doi=10.14716%2fijtech.v15i6.7123&partnerID=40&md5=4ae07b585a99793dbe65a7b2ef854916},
doi = {10.14716/ijtech.v15i6.7123},
issn = {20869614},
year = {2024},
date = {2024-01-01},
journal = {International Journal of Technology},
volume = {15},
number = {6},
pages = {1678 – 1696},
publisher = {Faculty of Engineering, Universitas Indonesia},
abstract = {The objective of this study is to investigate the variations in performance of a network with multiple oversaturated intersections—particularly delays and queue lengths—generated by two different signal timing approaches, namely (i) the classical isolated signal timing approach that aims to optimize each intersection's signal timing independently and (ii) the network optimization approach that focuses more on the network's holistic performance. In doing so, two signal timing models are herein developed using Synchro—a powerful traffic simulation tool—based on the information of a real oversaturated network with six consecutive intersections located on a major arterial street of Bangkok, Thailand, during the weekday evening peak period. The results of this simulation indicate that optimal cycle lengths and the allocation of green intervals are two key success factors that help reduce average delays and queue lengths at these intersections. To this end, excessive green intervals tend to result in greater delays and queue lengths, as the remaining approaches would experience excessively long red intervals. Furthermore, the key factor that helps enhance the network's holistic performance is the allocation of coordinated green intervals considering vehicular flows on all traffic corridors. In this regard, we find that the network optimization approach is considerably more efficient, as it could help reduce average delays and queue lengths by 43.5% and 61.9% compared to the base case scenario—which is 9.7% and 9.4% better than the isolated signal timing approach, respectively. © (2024), (Faculty of Engineering, Universitas Indonesia). All rights reserved.},
note = {Cited by: 1; All Open Access, Gold Open Access},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The objective of this study is to investigate the variations in performance of a network with multiple oversaturated intersections—particularly delays and queue lengths—generated by two different signal timing approaches, namely (i) the classical isolated signal timing approach that aims to optimize each intersection's signal timing independently and (ii) the network optimization approach that focuses more on the network's holistic performance. In doing so, two signal timing models are herein developed using Synchro—a powerful traffic simulation tool—based on the information of a real oversaturated network with six consecutive intersections located on a major arterial street of Bangkok, Thailand, during the weekday evening peak period. The results of this simulation indicate that optimal cycle lengths and the allocation of green intervals are two key success factors that help reduce average delays and queue lengths at these intersections. To this end, excessive green intervals tend to result in greater delays and queue lengths, as the remaining approaches would experience excessively long red intervals. Furthermore, the key factor that helps enhance the network's holistic performance is the allocation of coordinated green intervals considering vehicular flows on all traffic corridors. In this regard, we find that the network optimization approach is considerably more efficient, as it could help reduce average delays and queue lengths by 43.5% and 61.9% compared to the base case scenario—which is 9.7% and 9.4% better than the isolated signal timing approach, respectively. © (2024), (Faculty of Engineering, Universitas Indonesia). All rights reserved.
24.
Mark Ching-Pong Poo, Zaili Yang, Yui-yip Lau, Pisit Jarumaneeroj
Assessing the impact of Arctic shipping routes on the global container shipping network’s connectivity Journal Article
In: Polar Geography, vol. 47, no. 3, pp. 219 – 239, 2024, ISSN: 1088937X, (Cited by: 1; All Open Access, Hybrid Gold Open Access).
@article{Poo2024219,
title = {Assessing the impact of Arctic shipping routes on the global container shipping network’s connectivity},
author = {Mark Ching-Pong Poo and Zaili Yang and Yui-yip Lau and Pisit Jarumaneeroj},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85203686839&doi=10.1080%2f1088937X.2024.2399775&partnerID=40&md5=45ce2c427892e7fd6ef29fc7d2daf112},
doi = {10.1080/1088937X.2024.2399775},
issn = {1088937X},
year = {2024},
date = {2024-01-01},
journal = {Polar Geography},
volume = {47},
number = {3},
pages = {219 – 239},
publisher = {Taylor and Francis Ltd.},
abstract = {Amidst the intensifying impact of climate change, the extension of navigable periods along Arctic Shipping Routes (ASRs) has garnered attention as a maritime route for container vessels. The urgency to comprehend the reverberations of ASRs on the global container shipping network (GCSN) led to the development of the Latitudinal Centrality Index (LCI), which integrates latitude and centrality in maritime analysis. This index evaluates ASRs’ influence across 968 port nodes within the GCSN. By exploring scenarios encompassing seasonal fluctuations over the years, this study delves into the sway of ASRs compared to a benchmark state devoid of ASR engagement. The study’s revelations highlight a discovery: the assimilation of ASRs augments interconnectivity, or resilience, within the GCSN. The GCSN thrives as a cohesive and adaptable entity upon full integration of ASRs, indicating a promising trajectory for global container shipping. © 2024 The Author(s). Published with license by Taylor & Francis Group, LLC.},
note = {Cited by: 1; All Open Access, Hybrid Gold Open Access},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Amidst the intensifying impact of climate change, the extension of navigable periods along Arctic Shipping Routes (ASRs) has garnered attention as a maritime route for container vessels. The urgency to comprehend the reverberations of ASRs on the global container shipping network (GCSN) led to the development of the Latitudinal Centrality Index (LCI), which integrates latitude and centrality in maritime analysis. This index evaluates ASRs’ influence across 968 port nodes within the GCSN. By exploring scenarios encompassing seasonal fluctuations over the years, this study delves into the sway of ASRs compared to a benchmark state devoid of ASR engagement. The study’s revelations highlight a discovery: the assimilation of ASRs augments interconnectivity, or resilience, within the GCSN. The GCSN thrives as a cohesive and adaptable entity upon full integration of ASRs, indicating a promising trajectory for global container shipping. © 2024 The Author(s). Published with license by Taylor & Francis Group, LLC.
25.
Thanachot Sae-Jia, Natt Leelawat, Jing Tang, Rie Murakami, Yuki Taoka, Eri Ota, Proadpran Punyabukkana
Institute of Electrical and Electronics Engineers Inc., 2024, ISBN: 979-835035395-2, (Cited by: 0).
@conference{Sae-Jia2024158,
title = {Realizing Global Citizen Solutions for Sustainable Development Goals: A Collaborative Engineering Course Between Thai and Japanese Students},
author = {Thanachot Sae-Jia and Natt Leelawat and Jing Tang and Rie Murakami and Yuki Taoka and Eri Ota and Proadpran Punyabukkana},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85216577660&doi=10.1109%2fISCIT63075.2024.10793683&partnerID=40&md5=dda4c0a2b94d943f9e0023656d4bab25},
doi = {10.1109/ISCIT63075.2024.10793683},
isbn = {979-835035395-2},
year = {2024},
date = {2024-01-01},
journal = {Conference Proceeding - 23rd International Symposium on Communications and Information Technologies, ISCIT 2024},
pages = {158 – 162},
publisher = {Institute of Electrical and Electronics Engineers Inc.},
abstract = {One of the problems faced by engineering and science students is focusing solely on technical knowledge while needing more cultural context. In today's interconnected world, addressing global challenges necessitates collaborative efforts from individuals across nations. Accordingly, a joint course between Chulalongkorn University in Thailand and the Tokyo Institute of Technology in Japan has been established. The recent theme of the course, 'Gamification towards Sustainable Development Goals (SDGs),' aimed to foster global citizenship and address SDGs through multicultural collaboration. This study examines the similarities and differences in problem identification between Thai and Japanese student groups participating in the course. Data was collected from discussions, presentations, and group assignments throughout the course. The findings indicate that while both groups share common concerns, such as waste management, language barriers, and transportation issues, their perspectives and proposed solutions are influenced by cultural characteristics. Thai students emphasized infrastructural inadequacies and local traditions, whereas Japanese students focused on efficiency and the impacts of tourism. The study highlights the importance of understanding cultural nuances in collaborative international projects to achieve effective and innovative solutions to global challenges. © 2024 IEEE.},
note = {Cited by: 0},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
One of the problems faced by engineering and science students is focusing solely on technical knowledge while needing more cultural context. In today's interconnected world, addressing global challenges necessitates collaborative efforts from individuals across nations. Accordingly, a joint course between Chulalongkorn University in Thailand and the Tokyo Institute of Technology in Japan has been established. The recent theme of the course, 'Gamification towards Sustainable Development Goals (SDGs),' aimed to foster global citizenship and address SDGs through multicultural collaboration. This study examines the similarities and differences in problem identification between Thai and Japanese student groups participating in the course. Data was collected from discussions, presentations, and group assignments throughout the course. The findings indicate that while both groups share common concerns, such as waste management, language barriers, and transportation issues, their perspectives and proposed solutions are influenced by cultural characteristics. Thai students emphasized infrastructural inadequacies and local traditions, whereas Japanese students focused on efficiency and the impacts of tourism. The study highlights the importance of understanding cultural nuances in collaborative international projects to achieve effective and innovative solutions to global challenges. © 2024 IEEE.
26.
Akira Kodaka, Natt Leelawat, Naohiko Kohtake
Monitoring Industrial Zone Activities Through Wavelet Analysis of Air Quality Time Series Data Conference
Institute of Electrical and Electronics Engineers Inc., 2024, ISBN: 979-835035395-2, (Cited by: 0).
@conference{Kodaka2024229,
title = {Monitoring Industrial Zone Activities Through Wavelet Analysis of Air Quality Time Series Data},
author = {Akira Kodaka and Natt Leelawat and Naohiko Kohtake},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85216562490&doi=10.1109%2fISCIT63075.2024.10793691&partnerID=40&md5=b482331d388ec7d51261718121b0a60c},
doi = {10.1109/ISCIT63075.2024.10793691},
isbn = {979-835035395-2},
year = {2024},
date = {2024-01-01},
journal = {Conference Proceeding - 23rd International Symposium on Communications and Information Technologies, ISCIT 2024},
pages = {229 – 234},
publisher = {Institute of Electrical and Electronics Engineers Inc.},
abstract = {One significant element brought about by the Busi-ness Continuity Management System (BCMS) is the operation and maintenance of processes, capabilities, and response struc-tures that allow an organization to overcome interruptions. The outbreak of COVID-19 necessitated a forced change in this system structure. In this study, Rojana Industrial Park in Phra N akhon Si Ayutthaya Province, Thailand was chosen for a study site where the authors have been conducting ongoing research, to understand changes in industrial park activities affected by the pandemic. Wavelet analysis was employed to capture the time series change patterns of atmospheric composition. This approach aims to identify the altered realities of how BCMS adapts to rapid situational changes from a new perspective which is air quality. Comparing the concentration changes of NO2 and PM2.5 between pre-pandemic 2019 and post-pandemic 2021 onward, no significant changes were observed in the relatively short-term industrial park activities ranging from a few days to a week; low coherence in high-frequent change of air quality. In contrast, significant changes were confirmed in the long-term concentration change patterns over 16 days or more; high coherence in low-frequency. This suggests that industrial park activities, including production activities and the movement of people and goods related to these activities, may have changed before and after the pandemic. © 2024 IEEE.},
note = {Cited by: 0},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
One significant element brought about by the Busi-ness Continuity Management System (BCMS) is the operation and maintenance of processes, capabilities, and response struc-tures that allow an organization to overcome interruptions. The outbreak of COVID-19 necessitated a forced change in this system structure. In this study, Rojana Industrial Park in Phra N akhon Si Ayutthaya Province, Thailand was chosen for a study site where the authors have been conducting ongoing research, to understand changes in industrial park activities affected by the pandemic. Wavelet analysis was employed to capture the time series change patterns of atmospheric composition. This approach aims to identify the altered realities of how BCMS adapts to rapid situational changes from a new perspective which is air quality. Comparing the concentration changes of NO2 and PM2.5 between pre-pandemic 2019 and post-pandemic 2021 onward, no significant changes were observed in the relatively short-term industrial park activities ranging from a few days to a week; low coherence in high-frequent change of air quality. In contrast, significant changes were confirmed in the long-term concentration change patterns over 16 days or more; high coherence in low-frequency. This suggests that industrial park activities, including production activities and the movement of people and goods related to these activities, may have changed before and after the pandemic. © 2024 IEEE.
27.
Ampan Laosunthara, Natt Leelawat, Takumi Ohashi, Titaya Sararit, Mongkonkorn Srivichai, Jing Tang
Institute of Electrical and Electronics Engineers Inc., 2024, ISBN: 979-835035395-2, (Cited by: 1).
@conference{Laosunthara2024122,
title = {Awareness of Disaster Risk and Preparedness: Insights from a Survey of Children and Adults in Thailand},
author = {Ampan Laosunthara and Natt Leelawat and Takumi Ohashi and Titaya Sararit and Mongkonkorn Srivichai and Jing Tang},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85216570493&doi=10.1109%2fISCIT63075.2024.10793697&partnerID=40&md5=3ac3343998aa02cd815c2a98ec2a162c},
doi = {10.1109/ISCIT63075.2024.10793697},
isbn = {979-835035395-2},
year = {2024},
date = {2024-01-01},
journal = {Conference Proceeding - 23rd International Symposium on Communications and Information Technologies, ISCIT 2024},
pages = {122 – 127},
publisher = {Institute of Electrical and Electronics Engineers Inc.},
abstract = {Enhancing disaster awareness and preparedness is crucial for building resilient societies. This study comprehensively assessed the levels of disaster awareness and preparedness among children and adults in Thailand through qualitative and quantitative surveys. Children strongly emphasized the importance of disaster education in school curricula, leveraging multimedia channels for risk communication, and implementing early warning systems. In contrast, adults exhibited a greater understanding of the significance of business continuity and disaster management technologies. These findings revealed disparities in disaster awareness across age groups. The insights from this study suggest age-specific engineering system approaches to information dissemination, contributing to the development of inclusive disaster preparedness strategies that incorporate diverse stakeholder perspectives. Children highlighted the need for practical training on survival skills, accessible disaster communication through SMS alerts, and monitoring systems for timely information dissemination. Adults, on the other hand, placed greater importance on business continuity planning and recognized the usefulness of technologies like satellite imagery for disaster management. By identifying these gaps and areas for improvement, this research provides valuable guidance for tailoring interventions, fostering a culture of preparedness, and harnessing technological solutions that resonate with the needs and concerns of different age cohorts within Thai society. © 2024 IEEE.},
note = {Cited by: 1},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
Enhancing disaster awareness and preparedness is crucial for building resilient societies. This study comprehensively assessed the levels of disaster awareness and preparedness among children and adults in Thailand through qualitative and quantitative surveys. Children strongly emphasized the importance of disaster education in school curricula, leveraging multimedia channels for risk communication, and implementing early warning systems. In contrast, adults exhibited a greater understanding of the significance of business continuity and disaster management technologies. These findings revealed disparities in disaster awareness across age groups. The insights from this study suggest age-specific engineering system approaches to information dissemination, contributing to the development of inclusive disaster preparedness strategies that incorporate diverse stakeholder perspectives. Children highlighted the need for practical training on survival skills, accessible disaster communication through SMS alerts, and monitoring systems for timely information dissemination. Adults, on the other hand, placed greater importance on business continuity planning and recognized the usefulness of technologies like satellite imagery for disaster management. By identifying these gaps and areas for improvement, this research provides valuable guidance for tailoring interventions, fostering a culture of preparedness, and harnessing technological solutions that resonate with the needs and concerns of different age cohorts within Thai society. © 2024 IEEE.
28.
Penpitcha Arayachookiat, Kumpol Saengtabtim, Akira Kodaka, Natt Leelawat, Jing Tang, Kenji Watanabe
Institute of Electrical and Electronics Engineers Inc., 2024, ISBN: 979-835035395-2, (Cited by: 0).
@conference{Arayachookiat2024247,
title = {Preliminary Plan for Data Collection on Stakeholder Information Interdependence in Area-Business Continuity Management: A Case Study of Flood Management in Thai Industrial Zones},
author = {Penpitcha Arayachookiat and Kumpol Saengtabtim and Akira Kodaka and Natt Leelawat and Jing Tang and Kenji Watanabe},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85216535244&doi=10.1109%2fISCIT63075.2024.10793677&partnerID=40&md5=abfebc955936d63a6b9bc352ecc342d7},
doi = {10.1109/ISCIT63075.2024.10793677},
isbn = {979-835035395-2},
year = {2024},
date = {2024-01-01},
journal = {Conference Proceeding - 23rd International Symposium on Communications and Information Technologies, ISCIT 2024},
pages = {247 – 252},
publisher = {Institute of Electrical and Electronics Engineers Inc.},
abstract = {The 2011 flood in Thailand exposed significant vulnerabilities in industrial areas, highlighting the necessity for enhanced disaster risk management through Area-Business Continuity Management (Area-BCM). This preliminary study focuses on identifying how stakeholders rely on information from each other to improve disaster preparedness and response. The research involves systematically identifying Area-BCM stakeholders and designing interview questions, which are evaluated by experts using the Index of Item-Objective Congruence (IOC) to ensure relevance and clarity. All interview questions surpassed the IOC threshold of 0.5, confirming their effectiveness in capturing information interdependencies. Expert feedback led to refinements in the questions, underscoring the importance of tailored data collection. This initial plan provides a critical foundation for understanding information interdependence and highlights the importance of well-designed data collection methods. The findings have significant implications for developing more resilient disaster management strategies in industrial areas, emphasizing the need for precise and relevant stakeholder communication to enhance Area-BCM effectiveness. © 2024 IEEE.},
note = {Cited by: 0},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
The 2011 flood in Thailand exposed significant vulnerabilities in industrial areas, highlighting the necessity for enhanced disaster risk management through Area-Business Continuity Management (Area-BCM). This preliminary study focuses on identifying how stakeholders rely on information from each other to improve disaster preparedness and response. The research involves systematically identifying Area-BCM stakeholders and designing interview questions, which are evaluated by experts using the Index of Item-Objective Congruence (IOC) to ensure relevance and clarity. All interview questions surpassed the IOC threshold of 0.5, confirming their effectiveness in capturing information interdependencies. Expert feedback led to refinements in the questions, underscoring the importance of tailored data collection. This initial plan provides a critical foundation for understanding information interdependence and highlights the importance of well-designed data collection methods. The findings have significant implications for developing more resilient disaster management strategies in industrial areas, emphasizing the need for precise and relevant stakeholder communication to enhance Area-BCM effectiveness. © 2024 IEEE.
29.
Sushank Chaudhary, Nitinun Sinpan, Pruk Sasithong, Sunita Khichar, Panithan La-Aiddee, Natt Leelawat, Amir Parnianifard, Suvit Poomrittigul, Lunchakorn Wuttisittikulkij
In: IEEE Access, vol. 12, pp. 196969 – 196983, 2024, ISSN: 21693536, (Cited by: 2; All Open Access, Gold Open Access).
@article{Chaudhary2024196969,
title = {Proximal Policy Optimization for Crowd Evacuation in Complex Environments - A Metaverse Approach at Krung Thep Aphiwat Central Terminal, Thailand},
author = {Sushank Chaudhary and Nitinun Sinpan and Pruk Sasithong and Sunita Khichar and Panithan La-Aiddee and Natt Leelawat and Amir Parnianifard and Suvit Poomrittigul and Lunchakorn Wuttisittikulkij},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85211992072&doi=10.1109%2fACCESS.2024.3515153&partnerID=40&md5=1136034d905fd93d139dc7dcb4af0b0b},
doi = {10.1109/ACCESS.2024.3515153},
issn = {21693536},
year = {2024},
date = {2024-01-01},
journal = {IEEE Access},
volume = {12},
pages = {196969 – 196983},
publisher = {Institute of Electrical and Electronics Engineers Inc.},
abstract = {Efficient crowd evacuation from railway platforms is critical for passenger safety during emergencies. This study introduces a novel dynamic emergency evacuation route generator using the Proximal Policy Optimization (PPO) algorithm within a custom-built 3D simulation environment developed in Unity. We independently created a detailed digital twin of Krung Thep Aphiwat Central Terminal, Thailand's largest train station, and implemented all elements of the simulation, including the Social Force Model, to accurately replicate crowd behaviors and interactions during evacuation scenarios. Through extensive training over 3,000,000 episodes, our PPO-based model achieved significant improvements in evacuation efficiency. The results indicate that in a major emergency scenario, increasing the number of agents in the station reduced the number of remaining passengers from 111 to just 6, highlighting the model's effectiveness. Similarly, in a minor emergency scenario, the average number of remaining passengers dropped from 38 to 1 with the addition of more agents. These findings confirm the model's ability to adapt to different emergency conditions, offering a practical and scalable solution for enhancing evacuation strategies in high-density environments. Furthermore, increasing the agents' sight range also improved evacuation efficiency, with a 20-meter sight range yielding the best results. © 2013 IEEE.},
note = {Cited by: 2; All Open Access, Gold Open Access},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Efficient crowd evacuation from railway platforms is critical for passenger safety during emergencies. This study introduces a novel dynamic emergency evacuation route generator using the Proximal Policy Optimization (PPO) algorithm within a custom-built 3D simulation environment developed in Unity. We independently created a detailed digital twin of Krung Thep Aphiwat Central Terminal, Thailand's largest train station, and implemented all elements of the simulation, including the Social Force Model, to accurately replicate crowd behaviors and interactions during evacuation scenarios. Through extensive training over 3,000,000 episodes, our PPO-based model achieved significant improvements in evacuation efficiency. The results indicate that in a major emergency scenario, increasing the number of agents in the station reduced the number of remaining passengers from 111 to just 6, highlighting the model's effectiveness. Similarly, in a minor emergency scenario, the average number of remaining passengers dropped from 38 to 1 with the addition of more agents. These findings confirm the model's ability to adapt to different emergency conditions, offering a practical and scalable solution for enhancing evacuation strategies in high-density environments. Furthermore, increasing the agents' sight range also improved evacuation efficiency, with a 20-meter sight range yielding the best results. © 2013 IEEE.
30.
Teerapat Tappanom, Natt Leelawat, Kumpol Saengtabtim, Jing Tang
Agent-Based Modeling for Forest Fire Simulation in Chiang Mai, Thailand Conference
Institute of Electrical and Electronics Engineers Inc., 2024, ISBN: 979-835035395-2, (Cited by: 0).
@conference{Tappanom2024265,
title = {Agent-Based Modeling for Forest Fire Simulation in Chiang Mai, Thailand},
author = {Teerapat Tappanom and Natt Leelawat and Kumpol Saengtabtim and Jing Tang},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85216587908&doi=10.1109%2fISCIT63075.2024.10793674&partnerID=40&md5=38609d128e56d8a84283b20b981e6366},
doi = {10.1109/ISCIT63075.2024.10793674},
isbn = {979-835035395-2},
year = {2024},
date = {2024-01-01},
journal = {Conference Proceeding - 23rd International Symposium on Communications and Information Technologies, ISCIT 2024},
pages = {265 – 270},
publisher = {Institute of Electrical and Electronics Engineers Inc.},
abstract = {Forest fires have a significant impact on ecosystems and human life, especially in northern Thailand, where Chiang Mai is severely affected. Traditional methods for detecting forest fires have limitations, so there is a need for advanced simulation models. This research uses Agent-Based Modeling (ABM) to develop a forest fire simulation for Chiang Mai. The methodology involves collecting historical data, performing Multiple Regression Analysis, designing the simulation, and testing it. Data from 1998 to 2021, including temperature, relative humidity, wind speed/direction, burn area, and slope, were collected from various sources. Multiple regression analysis identified wind speed as the most significant factor affecting burn area. The forest fire simulation, designed using ZF Wang's spread model and tested with AnyLogic, showed that wind direction and speed are crucial in fire spread. The simulation accurately predicted high-risk areas, helping in proactive planning and response. This study confirms that wind is a critical factor in forest fire spread, providing a valuable tool for fire districts to improve preparedness and management. Future research should focus on refining the model with localized data and integrating real-time detection to improve its accuracy and applicability. © 2024 IEEE.},
note = {Cited by: 0},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
Forest fires have a significant impact on ecosystems and human life, especially in northern Thailand, where Chiang Mai is severely affected. Traditional methods for detecting forest fires have limitations, so there is a need for advanced simulation models. This research uses Agent-Based Modeling (ABM) to develop a forest fire simulation for Chiang Mai. The methodology involves collecting historical data, performing Multiple Regression Analysis, designing the simulation, and testing it. Data from 1998 to 2021, including temperature, relative humidity, wind speed/direction, burn area, and slope, were collected from various sources. Multiple regression analysis identified wind speed as the most significant factor affecting burn area. The forest fire simulation, designed using ZF Wang's spread model and tested with AnyLogic, showed that wind direction and speed are crucial in fire spread. The simulation accurately predicted high-risk areas, helping in proactive planning and response. This study confirms that wind is a critical factor in forest fire spread, providing a valuable tool for fire districts to improve preparedness and management. Future research should focus on refining the model with localized data and integrating real-time detection to improve its accuracy and applicability. © 2024 IEEE.