ICA-SYMP 2021The 2021 2nd International Symposium on Instrumentation, Control, Artificial Intelligence, and Robotics

Final Program & Abstract Book

King Mongkut’s University of Technology ThonburiBangkok, Thailand20-22 January 2021

The 2021 2nd International Symposium

on Instrumentation, Control, Artificial Intelligence, and Robotics

Final Program & Abstract Book

King Mongkut's University of Technology Thonburi, Bangkok, Thailand

20-22 January 2021

Organized by

ECTI Association of Thailand

Co-Organized by

Artificial Intelligence Association of Thailand

Thai Robotics Society

Technical Co-Sponsor

IEEE Thailand Section

2021 ICA-SYMP Committee

Advisory Committee Sinchai Kamolphiwong, PSU Thanaruk Theeramunkong, SIIT Witaya Wannasuphoprasit, CU Organizing Committee General Chair David Banjerdpongchai, CU Technical Program Chair Waree Kongprawechnon, SIIT Technical Program Co-Chairs Chowarit Mitsantisuk, KU Satit Mangkalajan, KMUTNB Technical Program Committee Charusluk Viphavakit, CU Kitsuchart Pasupa, KMITL Somying Thainimit, KU Kanjanapan Sukvichai, KU Amphawan Julsereewong, KMITL Benjamas Panomruttanarug, KMUTT Sanchai Dechanupaprittha, KU Rardchawadee Silapunt, KMUTT Witthawas Pongyart, KMUTNB Special Session Chairs Kou Yamada, Gunma U, Japan Poogyeon Park, POSTECH, Korea Natt Leelawat, CU, Thailand Publication Chairs Peerayot Sanposh, KU Itthisek Nilkhamhang, SIIT

Information System Chair Kitsuchart Pasupa, KMITL

Financial Chair Sudchai Boonto, KMUTT Registration Chair Tanagorn Jennawasin, KMUTT Issarapong Khuankrue, KMUTT Sponsor and Exhibition Chairs Pakpoom Patompak, PIM Sawai Pongsawatd, KMITL Local Arrangement Chair Sudchai Boonto, KMUTT Publicity Chairs Napasool Wongvanich, KMITL Young Soo Suh, Ulsan, Korea International Program Chairs Hla Myo Tun, YTU, Myanmar Nam Hoai Nguyen, HUST, Vietnam Zool H. Ismail, MJIIT, UTM, Malaysia Kou Yamada, Gunma U, Japan Dinh Hoa Nguyen, Kyushu U, Japan Lesnanto Putranto, UGM, Indonesia Norhaliza Abdul Wahab, UTM, Malaysia Sutthiphong Srigrarom, NUS, Singapore Noraisyah Mohamed Shah, UM, Malaysia Astria Nur Irfansyah, ITS, Indonesia Juntao Fei, Hohai University, China Oumar Diene, Federal University of Rio de Janeiro, Brazil General Secretary Sungwan Boksuwan, KMITL

Copyright Page

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For reprint or republication permission, email to IEEE Copyrights Manager at pubs-permissions@ieee.org. All rights reserved.

Copyright ©2021 by IEEE.

2021 ICA-SYMP CATALOG NUMBERS

IEEE CATALOG NUMBER: CFP21R12-ART

ISBN: 978-1-7281-8760-0

Table of Contents

Welcome Messages 1 Keynote Speeches Keynote Speaker I 8 Keynote Speaker II 9 Technical Program at a Glance 10 Program in Details (by Paper ID) 11 Exhibition 12 Abstracts of Regular & Position Papers Session: ThuA1 14 Session: ThuB1 18 Session: ThuC1 21 Session: ThuA2 24 Session: ThuB2 27 Session: ThuC2 30 Session: ThuA3 34 Session: ThuB3 37 Session: ThuC3 41 Best Papers 43 Author Index 44 Additional Reviewers 47 Sponsors 49

1

Welcome Messages

2

Welcome Message from President of ECTI Association

On behalf of ECTI (Electrical Engineering, Electronics, Computer, Telecommunication, and Information Technology) Association, Thailand, it is a pleasure for us to welcome you to the 2021 Second International Symposium on Instrumentation, Control, Artificial Intelligence, and Robotics (ICA-SYMP), January 20-22, 2021, at KMUTT Knowledge Exchange for Innovation Center (KX), Bangkok, Thailand. This year, it is the second time of the symposium organized by ECTI Association, together with technical co-sponsorship from IEEE Thailand Section, Artificial Intelligence Association of Thailand (AIAT), and Thailand Robotics Society (TRS). Even though ICA-SYMP 2021 is a small-scale event, we ensure that the conference is high quality, fruitful, and informative. All authors and academia are well organized in terms of closer discussion, friendly atmosphere, as well as a good participation. On behalf of ECTI Association, we would like to express our sincere appreciation and gratitude to the ICA-SYMP organizing committee, sponsors, and institution partners, technical reviewers, and all authors who participate in ICA-SYMP 2021.

Associate Professor Dr. Sinchai Kamolphiwong

President of ECTI Association

3

Welcome Message from President of AIAT

The ICA-SYMP 2021 is the second annual international symposium organized by Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI) Association, and technically co-sponsored by IEEE Thailand Section, Artificial Intelligence Association of Thailand (AIAT) and Thailand Robotics Society (TRS). The conference aims to provide an international platform to present technological advances, launch new ideas and showcase research work in various areas, including instrumentation and measurement, artificial intelligence, image processing and computer vision, robotics, automation and system integration, control theory, power control and energy systems, cyber-physical systems and IoT, and control applications. The Artificial Intelligence Association of Thailand is honoured to co-host the ICA-SYMP, which is an international symposium under the IEEE Control Systems Society Thailand. As the co-host, we would like to thank David Banjerdpongchai, the general chair, as well as Kongprawechnon, the program chair for the great effort in arrangement of this event. We also appreciate the presenters, the reviewers, the organizing team for their contribution. We look forward to seeing you soon at ICA-SYMP 2021 at the KMUTT Knowledge Exchange for Innovation Center (KX), Bangkok, Thailand, during January 20-22, 2021.

Professor Dr. Thanaruk Theeramunkong

President of Artificial Intelligence Association of Thailand (AIAT)

4

Welcome Message from President of TRS

On behalf of Thai Robotics Society (TRS), it is my honor to welcome you to ICA-SYMP 2021 the second international symposium organized by Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI) Association and co-organized by TRS and AIAT. This symposium brings a great opportunity for participants to learn from the renown researchers in Robotics, Artificial Intelligence, Automation, and Control Engineering. The Robotics, Automation, and Intelligent Systems are changing rapidly covering all segments from manufacturing to service, society to individual, and enterprise to person. Robotics is in the emerging era that enables in anything, anywhere and anytime. Founded in year 2000, Thai Robotics Society (TRS) is a nonprofit organization dedicating to create and support robotics activities in Thailand. During the COVID-19 pandemic, robotics plays an important role to assist the medical team to support the health care system. As a co-organizer of the ICA-SYMP 2021, I hope you are delighted to participate in a unique forum of ICA-SYMP 2021 either online or onsite and enjoy knowledge sharing and enriching innovation. I wish you have a fruitful exchange and make a good collaboration during the symposium.

Associate Professor Dr. Witaya Wannasuphoprasit

President of Thai Robotics Society

5

Welcome Message from General Chair

On behalf of the organizing committee, it is our great pleasure to warmly welcome you to the 2020 Second International Symposium on Instrumentation, Control, Artificial Intelligence, and Robotics (ICA-SYMP 2021). The second symposium is held on January 20-22, 2021 at King Mongkut University of Technology Knowledge Exchange for Innovation Center (KX), Bangkok, Thailand. ICA-SYMP 2021 is organized by the Automatic Control Systems Technical Committee of Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology Association (ECTI Association) with collaboration of Artificial Intelligence Association of Thailand (AAIT) and Thai Robotics Society (TRS). In addition, ICA-SYMP 2021 is technically supported by IEEE Thailand which enables the accepted regular papers to appear in the IEEE Xplore Digital Library. The aim of the symposium is to provide academic faculty and students, researchers and engineers a forum to present their researches, and exchange new findings and experiences pertaining their researches on instrumentation, automatic control, artificial intelligence, robotics and the related topics. Due to the ongoing pandemic of COVID-19, we decided to organize the symposium in an online mode. Both domestic audience and overseas colleagues can remotely take part in the symposium. We believe that this symposium is well-attended by participants from ASEAN countries and Asia as well as from around the world. We hope that ICA-SYMP 2021 provides plenty of opportunities of engaging discussion among participants which can lead to further collaborations in the future. With your active participation, we are confident that ICA-SYMP 2021 will be successful as an important event in the development of instrumentation, automatic control, artificial intelligence, robotics.

We take this opportunity to express our sincere thanks to ICA-SYMP 2021 keynote speakers, TPC chair and co-chairs, technical program committee, authors of contributed papers, and anonymous reviewers for their invaluable support. We acknowledge strong support from the organizing committee members and local staff for their very hard working to make the symposium a success. We are grateful to the financial sponsors and industrial exhibitors who enable the symposium to successfully achieve its objectives. It is hoped that ICA-SYMP 2021 serves as a networking and collaborative platform to your organizations.

Wish you enjoy the technical program of ICA-SYMP 2021 and for those who travel to Bangkok, wish you have a nice and safe stay.

Professor Dr. David Banjerdpongchai, General Chair

6

Welcome Message from Technical Program Chairs

ICA-SYMP 2021 (IEEE Conference Record Number 50206) is the second annual international symposium organized by Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI) Association, and technically co-sponsored by IEEE Thailand Section, Artificial Intelligence Association of Thailand (AIAT) and Thailand Robotics Society (TRS). The conference aims to provide an international platform to present technological advances, launch new ideas and showcase research work in the field of instrumentation, robotics, automation, control, and artificial intelligence. Due to the COVID-19 pandemic, The 2021 2nd International Symposium on Instrumentation, Control, Artificial Intelligence & Robotics (ICA-SYMP 2021) will be held at KMUTT Knowledge Exchange and Innovation Center in Bangkok, Thailand as a hybrid conference. We received 44 submissions from various fields, including Instrumentation and Measurement, Artificial Intelligence, Image Processing and Computer Vision, Robotics, Automation and System Integration, Control Theory, Power Control and Energy Systems, Cyber-Physical Systems and IoT and Control Applications. All papers are thoroughly reviewed by at least two anonymous reviewers, and the conference acceptance rate for regular papers is 64.4%.

We appreciate the reviewers and program committee members who are all experts from various international organizations in related areas. They spent their valuable time reviewing and evaluating submitted papers. We express our special thanks to the technical program committee: Charusluk Viphavakit, Kitsuchart Pasupa, Somying Thainimit, Kanjanapan Sukvichai, Benjamas Panomruttanarug, Sanchai Dechanupaprittha, Rardchawadee Silapunt, Witthawas Pongyart, and the special program chairs: Natt Leelawat, Kou Yamada, and Itthisek Nilkhamhang for their great contributions to compile the reviewing results. We thank our general chair, David Banjerdpongchai for his support in both publication, paper submission and registration, and online conference setup. Finally, we express our biggest gratitude to all the authors who submitted their valuable papers, who were accepted and made their presentations, and who joined active discussion at the sessions. Thank you for all your effort, cooperation, and kindness.

Waree Kongprawechnon

Technical Program Chair

Chowarit Mitsantisuk

Technical Program Co-Chair

Satit Mangkalajan

Technical Program Co-Chair

7

Keynote Speeches

8

Keynote Speaker I of ICA-SYMP 2021 Professor Dr. Manukid Parnichkun Asian Institute of Technology, Thailand Title Driverless Car Technologies Abstract Driverless car was widely known for the first time from DARPA Grand Challenge in 2004 which was a competition of driverless cars in the desert area. The competition was evolved to DARPA Urban Challenge in 2007 which was a competition in an urban area. Since then researches and developments of driverless cars have been conducted extensively for commercialization purposes for example; driverless cars by Google, an electrical car with driver assisting functions by Tesla. Today most of the car manufacturers research and develop driverless cars actively. In Thailand, the Thai Robotics Society started its activity on driverless cars since 2005. Thailand Intelligent Vehicle Challenge was organized by the society during 2007-2009. The competition became more challenged with the platform of the bicycle in the BicyRobo Thailand Championship organized during 2010-2012. This talk will present the key devices and control algorithms behind driverless car technologies. Technologies used by Google cars and Tesla will be firstly presented and compared. In the latter part of the talk, the control algorithms used for speed control, heading control, waypoints tracking, and obstacles avoidance of driverless cars, unmanned bicycle, and autonomous forklift developed at the Asian Institute of Technology (AIT) will be presented. Short Bio Manukid Parnichkun is currently a professor at the Mechatronics program, Asian Institute of Technology. He received B.Eng. from Mechanical Engineering, Chulalongkorn University in 1991, M.Eng. and Ph.D. from Precision Machinery Engineering, the University of Tokyo in 1993 and 1996 respectively. He joined the Asian Institute of Technology as an assistant professor in 1996. He was promoted to Associate Professor in 2001, and professor in 2016. He supervised and graduated 21 doctoral students and 172 master students. He was the founding committee of the Thai Robotics Society (TRS) and later became editor-in-chief of the society journal. He was elected to be the president of the Thai Robotics Society during 2003-2005. He organized and chaired several conferences and robot competitions. His research interests are Mechatronics, Robotics, Control, and Measurement.

9

Keynote Speaker II of ICA-SYMP 2021 Dr. Ben Parslew The University of Manchester, UK Title Exploring Lunar Caves using Highly Mobile Robotics Abstract Lunar pit craters are a mysterious topographical feature on the Moon, believed to be openings to underground lava tubes. These pits have steep walls and can be tens or hundreds of meters in diameter, making them extremely challenging to explore. However, understanding the formation of lunar lava tubes has a high geological significance, warranting the risk of descending into these subsurface tunnels. A viable route to investigating pit craters is to deploy highly mobile robotic devices that can negotiate complex topography and conduct remote scientific sampling missions. This presentation discusses the development of lunar mobile robotics, along with the specific challenges associated with lunar subsurface missions – high-temperature variation, unknown surface debris, and strict system mass budgets. An overview will be given of the current state-of-the-art in this field, as well as ongoing work on lunar hopping robotics conducted at The University of Manchester. This includes the development of computational and experimental models of the lunar terradynamics, and also the design of a hopping robotic platform that will explore lunar pit craters in the future. Short Bio Ben Parslew is a senior lecturer in Aerospace Engineering at the University of Manchester, and an Adjunct Professor at the International School of Engineering, Faculty of Engineering, Chulalongkorn University. His background is in aerodynamics, biomechanics, and bioinspired robotics. He has a particular interest in the locomotion of animals, including hopping, swimming, and flying. Ben obtained his undergraduate degree in Aerospace Engineering from UMIST in 2003, and Master’s in Fluid Dynamics from The University of Manchester in 2005. Ben completed a Ph.D. in Animal Flight Modelling in 2010 and was then awarded an EPSRC Doctoral Prize Fellowship in 2011 to continue this work at Manchester. Ben was later employed as a research associate funded by BAE Systems and then went on to become a lecturer at Manchester in 2013, teaching courses in Modelling and Simulation and UAV Design. He was recently appointed as an Adjunct Professor in Aerospace Engineering at Chulalongkorn University, where he teaches courses on Experimental Flight Mechanics and Biomimetics.

10

ICA-SYMP Technical Program at a Glance

20 January 2021 22 January 2021

08:30-09:00 Main Room

09:00-09:15

09:15-09:45

09:45-10:15

10.15-10.25

10:25-10:30

Track A (Room V1) Track B (Room V2) Track C (Room V3)

10:30-12:00 ECTI-SICE I Artificial Intelligence I Cyber-Physical Systems and IoT

12:00-13:15

13.15-13.30

Main Room Track A (Room V1) Track B (Room V2) Track C (Room V3)

13:30-15:00 Workshop by Ascendas ECTI-SICE II Artificial Intelligence II Control Theory and Applications

15:00-15:15 Break

Main Room Track A (Room V1) Track B (Room V2) Track C (Room V3)

15:15-16:30 Workshop by Ascendas Robotics Image Processing and Computer Vision AIAT Workshop

16:30-17.45

17.45-18.00

18:00-18.30

21 January 2021

Main Room

Opening Ceremony

Keynote Speaker I (Professor Dr. Manukid Parnichkun)

Keynote Speaker II (Dr. Ben Parslew)

Break

Webinar on Control Systems Society, Thailand Chapter

Main Room

Lunch

Break

Break

Main Room

Award Ceremony

Exhibition by Azbil (Thailand), EGAT and Yogokawa (Thailand)

Exbihition by Azbil (Thailand)

Exhibition by Azbil (Thailand), EGAT and Yogokawa (Thailand)

11

Program in Details (by Paper ID) 20 January 2021

Main Room 13:30-14.30 Workshop by Ascendas 14.30-14.40 Break 14.40-16:30 Workshop by Ascendas

21 January 2021 Main Room

09:00-09:15 Opening Ceremony 09:15-09:45 Keynote Speaker I (Professor Dr. Manukid Parnichkun) 09:45-10:15 Keynote Speaker II (Dr. Ben Parslew) 10.15-10.25 Exbihition by Azbil (Thailand)

Track A – ThuA1 (Room V1) Track B – ThuB1 (Room V2) Track C – ThuC1 (Room V3)

ECTI-SICE I Artificial Intelligence I Cyber-Physical Systems and IoT

10:30-10:45 1570667109 1570669074 1570679485 10:45-11:00 1570671005 1570679466 1570681994 11:00-11:15 1570672146 1570671697 1570680543 11:15-11:30 1570679372 1570672266 1570682054 11:30-11:45 1570679887 1570674906

11:45-12:00 1570679614

12:00-13:15 Lunch Main Room

13.15-13.30 Exhibition by Azbil (Thailand), EGAT and Yogokawa (Thailand) Track A – ThuA2 (Room V1) Track B – ThuB2 (Room V2) Track C – ThuC2 (Room V3)

ECTI-SICE II Artificial Intelligence II Control Theory and Applications

13:30-13:45 1570672196 1570675636 1570641877 13:45-14:00 1570672185 1570676091 1570666604 14:00-14:15 1570676267 1570676284 1570679340 14:15-14:30 1570688803 1570666091 1570676272 14:30-14:45 1570688810 1570672095 1570679484 14:45-15:00 1570672963 15:00-15:15 1570679346

Track A – ThuA3 (Room V1) Track B – ThuB3 (Room V2) Track C – ThuC3 (Room V3)

Robotics Image Processing and Computer Vision AIAT Workshop

15:15-15:30 1570665658 1570665561 AITA2021-0101 15:30-15:45 1570666797 1570670928 AITA2021-0002 15:45-16:00 1570667046 1570674885 AITA2021-0003 16:00-16:15 1570671766 1570676227

16:15-16:30 1570672159

Main Room 17.45-18.00 Exhibition by Azbil (Thailand), EGAT and Yogokawa (Thailand) 18:00-18.30 Award Ceremony

22 January 2021

Main Room 09:15-10:15 Webinar on Control Systems Society, Thailand Chapter

12

Exhibition

Exhibition will be held virtually on January 21.

No Exhibition Company 1 Azbil (Thailand) Co., Ltd. 2 Electricity Generating Authority of Thailand (EGAT) 3 Yokogawa (Thailand) Ltd.

13

Abstracts of Regular & Position Papers

Thursday 21, 2021

14

Session: ThuA1 Room V1 - ECTI-SICE Special Session on Advances on Control Engineering and Applications I Chair: Tanagorn Jennawasin, Kou Yamada Time: 10.30-12.00

10.30-10.45 Paper ID – 1570667109

Robust Fault-Tolerant Control Using Multiplex Feedback Control

Daisuke Koyama, Kotaro Hashikura, Md Abudus samal Kamal and Kou Yamada (Gunma University, Japan)

Abstract — In this paper, we propose a design method of a control system with low-sensitivity, robust stability and fault-tolerant control using a multiplex feedback control. In general, it is well-known that the control system with low-sensitivity is difficult to have a robust stability. However, the control system with low-sensitivity does not always lack the robust stability. Yu et al. propose a control system with low-sensitivity and robust stability using a double feedback control. However, Yu et al. do not consider a fault-tolerance of the control system such as the breaking controller. In this paper, we consider the fault-tolerance of the control system using multiplex feedback control with low-sensitivity and robust stability, and propose the design method of its control system with low-sensitivity, robust stability and fault-tolerance.

10.45-11.00 Paper ID - 1570671005

An Operator Method for H2 Preview Output Regulation in Output Feedback Setting

Kotaro Hashikura (Gunma University, Japan); Fuga Miyamoto and Akira Kojima (Tokyo Metropolitan University, Japan); Md Abudus samal Kamal and Kou Yamada (Gunma University, Japan)

Abstract — This paper develops a design method of H2 preview control in an output feedback setting. The control objectives are to attain the output regulation constraint and H2 suboptimal control performance. The proposed design method enables to construct preview output feedback controllers respecting both of steady-state and transient-response responses. The main direction for deriving the output feedback controller is to construct an exosystem observer, which estimates the states of the controlled plant and exosystem. In order to determine the exosystem observer gain, we employ an operator Sylvester equation, which reveals that the exosystem-observer-based controller possesses the Youla-parameter-based structure. By utilizing that Youla-parameter-based structure, we show that the proposed controller is designed by solving matrix equations and LMIs despite the infinite-dimensionality of the preview control system."

15

11.00-11.15 Paper ID - 1570672146

The Parameterization of All Stabilizing Minimum-Phase Controllers for Minimum-Phase Strictly Proper Plants

Dayu Zhang, Kotaro Hashikura, Md Abudus samal Kamal and Kou Yamada

(Gunma University, Japan)

Abstract — In the present paper, we examine the parameterization of all stabilizing minimum-phase controllers for minimum-phase strictly proper plants. The parameterization problem is the problem in which all stabilizing controllers for plants are sought. Since this parameterization can successfully search for all stabilizing minimum-phase controllers, it is used as a tool for many control problems. Glaria and Goodwin gave a simple parameterization of stabilizing controllers for linear minimum-phase plants. However the difficulty remains that the parameterization of all stabilizing controllers given by Glaria and Goodwin generally includes improper controllers. In practical applications, the controller is required to be proper. Yamada overcame these problems and proposed the parameterization of all proper internally stabilizing controllers for linear minimum-phase plants. There exist many design methods of proper stabilizing controller for minimum-phase plants, but most of the proposed design methods do not consider the stabilizing minimum-phase controllers. Using the minimum-phase controllers can make the sensitivity function lower and the lower values of sensitivity function suggest further attenuation of the external disturbance. From this viewpoint, it is desirable to clarify the parameterization of all stabilizing minimum-phase controllers for minimum-phase plants. Zhang et al. clarified the parameterization of all stabilizing minimum-phase controllers for minimum-phase biproper plants. The purpose of this paper is to expand the result by Zhang et al. and to propose the parameterization of all stabilizing minimum-phase controllers for minimum-phase strictly proper plants.

16

11.15-11.30 Paper ID - 1570679372

V2V Network Topologies for Vehicle Platoons with Cooperative State Variable Feedback Control

Agung Prayitno (Sirindhorn International Institute of Technology, Thammasat University, Thailand); Itthisek Nilkhamhang (Sirindhorn International Institute of Technolgy, Thammasat University, Thailand) Abstract — This paper aims to study and compare the effect of V2V network topology on vehicle platooning applications, with the objective of maintaining inter-vehicular spacing at all times. The platoon is formulated as a cooperative state variable feedback control problem with constant spacing policy and homogenous agents. The communication topologies considered include predecessor-following (PF), bidirectional (BD), predecessor-following-leader (PFL), bidirectional-leader (BDL), two-predecessor-following (TPF), and two-predecessor-following-leader (TPFL). Simulation analysis is performed under normal operations and when a disturbance occurs in one of the follower vehicles. The effect of the coupling gain is also discussed. For large platoons under normal conditions, more complex topologies, such as TPFL, BDL, and PFL, provide better performance in terms of platoon response. The propagation of disturbance in upstream and/or downstream directions is observed for certain topologies. Increasing the coupling gain can improve the system response of the platoon but also requires more control effort.

11.30-11.45 Paper ID - 1570679887 Convex Optimization Approach to Multi-Objective Design of Two-Stage Compensators for Linear Systems

Tanathorn Supithak and Nicha Wongyimyong (Chulalongkorn University, Thailand); Kou Yamada (Gunma University, Japan); David Banjerdpongchai (Chulalongkorn University, Thailand)

Abstract — The previous design of two-stage compensator of linear systems was focused on the stabilization and low sensitivity. However, it has not considered the time-domain performance of the closed-loop system, especially, reference tracking. This paper aims to propose the design method of the two-stage compensators that additionally achieves good transient response. Using Q-parameterization, the two-stage compensator design can be formulated as a convex optimization problem. The infinite dimensional problem is transformed into a finite dimensional problem by Ritz approximation. Finally, the convex optimization is efficiently solved to give the optimal controller. The numerical results show that the proposed design method on the second order benchmark problem improves the time-domain performance while the closed-loop system is stable and the influence of disturbance to output is attenuated.

17

11.45-12.00 Paper ID – 1570679614 Controller Design for a Level Control System with Valve Stiction: A Data-Driven Approach

Jakkarawut Khamkaew, Krittapas Phannachet and Tanagorn Jennawasin (King Mongkut's University of Technology Thonburi, Thailand)

Abstract — We propose a simple controller design method for a level control system subject to valve stiction. The proposed method is based on fictitious reference iterative tuning (FRIT) technique which can be adopted to tune parameters of simple controllers such as PID controllers by using a one-shot experimental data. In our framework, a simple model of the valve stiction is constructed using a piecewise-linear function, whose inverse model is easily obtained and used as a stiction compensator. The proposed method is applied to a double-tank liquid level system with several types of PID controllers. Numerical simulation is performed to verify effectiveness of the proposed approach.

18

Session: ThuB1 Room V2 - Artificial Intelligence I Chair: Natt Leelawat, Sumek Wisayataksin Time: 10.30-11.45

10.30-10.45 Paper ID – 1570669074

Modelling of an External Force Estimator for an End-Effector of a Robot by Neural Network

Goragod Junplod (King Mongkut's University of Technology Thon, Thailand); Woraphrut Kornmaneesang (National Chung Cheng University, Taiwan); Chen Shyh-Leh (CCU, Japan); Sarawan Wongsa (King Monkut's University of Technology Thonburi, Thailand) Abstract — This paper proposes a method to estimate external forces on an end effector of a robot manipulator by using a neural network model. To avoid the use of an expensive force sensor in the training purpose, the proposed method implements the indirect training method by including an inverse dynamic model of the robot manipulator to the training algorithm with available information from a default robot system. In this method, the accurate dynamics equations are necessary, therefore a neural-network-based (NN-based) disturbance observer is introduced to deal with uncertainties in the dynamics equations. Hence, the accuracy of the estimated external force is considerably improved. The performance of the proposed estimation method is evaluated through experiments of a 5-DOF robotic experimental platform. The results reveal that the behavior of the estimated external forces correlates strongly with the applied external forces.

19

10.45-11.00 Paper ID – 1570679466

Call Center Workforce Management with Neural Networks and Reinforcement Learning

Saravut Phikulngoen (King Mongkut's University of Technology Thonburi, Thailand); Wuttipong Kumwilaisak (King Mongkut's University of Technology, Thonburi, Thailand); Nattanun Thatphithakkul (NECTEC, Thailand); Chatchawarn Hansakunbuntheung and Wantanee Phantachat (National Science and Technology Development Agency, Thailand) Abstract — This paper presents a new method of call center workforce management using neural networks and reinforce learning. It automatically allocates a number of agents to different services suitable to some constraints such as call center traffics throughout the operating hours. The proposed method comprises two main components. The first component utilizes a combination between the LSTM network and fully connected networks to predict call center statistics. The predicted parameters from the neural networks are used in the Erlang A framework to compute the call center's essential parameters. The second component is the reinforcement learning module. Its inputs are the computed call center statistics from the neural network. The inputs are fed to the environmental module, which outputs either a reward or a penalty feeding to the reinforce agent module. The reinforce agent module takes action to adjust the call center workforce to maximize its reward. The iterative workforce adjustment adapts along with dynamic call center traffics throughout the operating hours. From our experimental results in real use cases in the Thai Telecommunication Relay Service, the proposed system can outperform workforce management by human supervisors regarding service level agreement and average waiting time.

11.00-11.15 Paper ID – 1570671697

Configurable Hardware Architecture of Multidimensional Convolution Coprocessor

Geranun Boonyuu (King Mongkut’s Institute of Technology Ladkrabang, Thailand); Sumek Wisayataksin (King Mongkut's Institute of Technology Ladkrabang, Thailand) Abstract — We propose a configurable coprocessor for the convolutional neural network (CNN) that suit various models of CNN. It can operate 2D standard convolution, 2D depthwise separable convolution, 3D convolution, and a fully connected layer. The proposed processing cluster consists of 72 processing units (PUs) of half-precision floating-point to assist the main processor in embedded systems. The experimental results on Artix-7 FPGA revealed that our design has 12.16 GOPs per cluster. Moreover, this architecture was designed to be scalable for the systems with higher performance.

20

11.15-11.30 Paper ID – 1570672266

Classification of the Resistance Spot Weld Failure Mode Using Convolutional Neural Network

Watchanun Piriyabunjerd (King Mongkut’s University of Technology Thonburi, Thailand); Chettapong Janya-anurak (KMUTT, Thailand)

Abstract — The resistance spot welding (RSW) is a comprehensive used process in the automotive industry. However, in the production line the quality of the weld is normally roughly assessed from its appearance by human. In this work, we propose the prediction of the quality of the resistance spot weld by using the convolutional neural network (CNN). The architecture of CNN applied in this work was MobileNetV3. The quality of the weld in this work was the failure mode of RSW determined by strength of the weld by tensile shear test. The external apparent image of welds was used as information for predicting the quality of the welds. For building the data set, the RSW was conducted with specific welding conditions and the heat trace image of welds was captured. The parameters of the CNN were trained from the apparent image of the welds and their failure mode. As a result, the CNN model was able to predict the class of the failure mode of the RSW from the welds image with satisfactory F1-score of 94.32% for unseen validation data set.

11.30-11.45 Paper ID – 1570674906 Drone Detection Using YOLOv3 with Transfer Learning on NVIDIA Jetson TX2

Sutthiphong Srigrarom (National University of Singapore & Temasek Laboratories, Singapore)

Abstract — The rise of drones in the recent years largely due to the advancements of drone technology which provide drones the ability to perform many more complex tasks autonomously with the incorporation of technologies such as computer vision, object avoidance and artificial intelligence. However, the misuse of drones such as the Gatwick Airport drone incident resulted in major disruptions which affected approximately 140,000 passengers. To deter this from happening in the future, drone surveillance are extremely crucial. With this, it will be achieved firstly by detection and followed by tracking of drones. This paper presents and investigates the use of a deep learning object detector, YOLOv3 with pretrained weights and transfer learning to train YOLOv3 to specifically detect drones.We demonstrated that the detection results from YOLOv3 after machine learning had an average accuracy of 88.9% at input image size of 416 x 416. Finally, we integrated into NVIDIA Jetson TX2 for real-time drone detection. Index Terms-YOLOv3, Machine Learning, Deep Learning, Drone Detection, Transfer Learning, NVIDIA Jetson TX2.

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Session: ThuC1 Room V3 - Cyber-Physical Systems, IoT, and Multi-Agent Systems Chair: Zool H Ismail, Issarapong Khuankrue Time: 10.30-11.30

10.30-10.45 Paper ID – 1570679485

Data-Driven Model for Failure Analysis of Internet of Things Devices: A Preliminary Study

Thanitnan Kammuang, Watthanai Luealamai and Issarapong Khuankrue (King Mongkut's University of Technology Thonburi, Thailand)

Abstract — This paper proposes the preliminary study of the data-driven failure analysis model on the internet of things (IoT) devices. This model focus on the impact of data transferring both get and receiving data on class C of Low Power Wide Area Network (LoRaWAN). To set up the network, the authors develop the combination of four several technology parts, including 1) the End Device Gateway Network server of LoRa IoT, 2) an Application server for store the data into the database, 3) the Dashboard to show and got the command by the user, and 4) the failure analysis model based on Bayesian belief networks which calculate the probability values that collect the data transferring both uplink and downlink on the network connection in this study. In the testing phase, the authors input the separated data into the data-driven failure analysis model to analyze the time and latency of the connection by the concern of the impact and risk for the failure of the overall system. The model will show the probability value of failure. The authors hope to use the results to clarify that a tested IoT device suitable for use or not.

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10.45-11.00 Paper ID – 1570681994 Smart Multi Level Soil Moisture Sensing System

Warisara Sriphanthaboot, Treetep Saengow, Kasama Kamonkusonman, Minthorn Phunthawornwong and Pongpith Simmanee (King Mongkut's University of Technology Thonburi, Thailand); Rardchawadee Silapunt (King Mongkut’s University of Technology Thonburi, Thailand)

Abstract — This paper presents a prototype design and construction of the smart multi-level soil moisture sensing system. The system consists of 3 3-level soil moisture probes whose length of each is adjustable. The soil moisture probe is equipped with the microcontroller unit, the solar panel, and the long range (LoRa) communication module. The capacitive sensing technique is chosen due to its satisfying accuracy, low cost, and low complexity. Each probe measures the response frequency due to capacitance variation associated with the soil moisture. The response frequency is then transmitted wirelessly over the long range wide area network (LoRaWAN) to the network server. The mathematical model of the actual moisture content (MC) vs measured response frequency was developed. The model was optimized to achieve the optimal correlation R-square of 0.8996. The measured moisture contents are validated by the actual ones. It is found that the average error is only 2.87%MC. The web application is finally developed to display soil moisture contents.

11.00-11.15 Paper ID – 1570680543 Target Search Problem Using Swarm Robotics Strategies - A Systematic Literature Review

Mohd Ghazali Mohd Hamami (Universiti Teknologi MARA, Cawangan Johor, Kampus Pasir Gudang, Malaysia); Zool H Ismail (Universiti Teknologi Malaysia, Malaysia)

Abstract — The target searching problem is a well-known but difficult problem in many research domains, including computational intelligence, artificial intelligence, and robotics. The main purpose is to search the targets with the minimum time required and the obstacles avoidance capability within a certain boundary. Swarm Robotics (SR) is an extended multi-robot system that explored a coordinated task within a large number of robots. Benefit from each agent's cooperation, robustness, flexibility, and scalability, the given task will accomplish swifter compare to a single robot usage. Thus, searching for single or multiple targets with swarm robots is a significant and realistic approach in real-world applications. The purpose of this article is to deliver a systematic literature review (SLR) of the target search problem using SR strategies. This review data extracts from two establish high indexed databases (Scopus and WOS). It gives an insightful foundation view on the SR strategies, the experiment framework, as well as future works directions for new research works in the target search problems.

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11.15-11.30 Paper ID – 1570682054

Classification of Lidar Scan Samples of Cell Tower Antenna Data Using Vox-Net

Amzar Omairi and Zool H Ismail (Universiti Teknologi Malaysia, Malaysia)

Abstract— The classification of cell tower antenna data is trialled by the nature of objects captured in the form of point clouds and scarce availability of lidar scans. Mobile Laser Scanning (MLS) data from outdoor environment are usually characterised by clutter, occlusion, noise, large data size and high quantum of information which makes their classification rather strenuous. Moreover, the variation in point density, size and the geometrical nature limits the incorporation of labelled samples from established benchmark data. In order to overcome this problem, we explore the feasibility of improving classification performance of multiple antenna classes using the Vox-Net deep learning implementing ancillary cell tower lidar scans and comparing it with inclusion of samples from complementary datasets. Vox-Net has been demonstrated to be able to efficiently handle large amounts of point cloud data by integrating a volumetric Occupancy Grid representation with a supervised 3D Convolutional Neural Network (3D CNN) comparing to other systems. The comparison shows that more instances can be recognized in classes with auxiliary data. While the performance in classes without complementary data could deteriorate due to the low number of samples in the designated categories.

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Session: ThuA2 Room V1 - ECTI-SICE Special Session on Advances on Control Engineering and Applications II Chair: Charusluk Viphavakit, Takaaki Hagiwara Time: 13.30-14.45

13.30-13.45 Paper ID – 1570672196

Mathematical Modelling of an Occupant and Wheelchair System Subjected to Vertical Vibrations

Pongtep Weerapong (Gunma University, Thailand); Kotaro Hashikura (Gunma University, Japan); Md Abdus Samad Kamal (Monash University Malaysia, Malaysia); Kou Yamada (Gunma University, Japan)

Abstract — This paper addresses a method for generating mathematical model to investigate the sensitivity of different vibration environments to the whole body vibration that considers the significant biodynamics on lumped parameter model of a seat human exposed to vertical vibration in manual wheelchair. The nine-degree of freedom linear model is developed and can be realized a mechanism consisting of springs and dampers for the response to sinusoidal displacement of the seat. The analysis shows a model has been carried out by validated acceleration ratio and show result acceleration transmissibility for assessing vibration in wheelchair design requires modification.

13.45-14.00 Paper ID – 1570672185 Production of Crawler Robot with Sub Crawler and Verification of Traversing

Ability

Takaaki Hagiwara, Yuito Yamamura, Yuuki Namima, Junya Ogami and Pengfei Li (Saitama Institute of Technology, Japan)

Abstract — A number of rescue robots for quick information gathering and safe rescue operations at the time of earthquake have been developed. Many robots adopt the crawler type. It is suitable for irregular terrain such as rubble and wasteland of the disaster site. In this paper, we focus on the traversing performance of robot functions required, and aim to be able to overcome the higher level difference by seeking the performance to overcome the step. We produce a robot equipped with sub-crawlers and report the results of experiments.

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14.00-14.15 Paper ID – 1570676267

Development and Characterization of a Low-Cost Vibration Monitoring Instrument Based on MEMS Acceleration Sensor

N. Suttiwong (King Mongkut's University of Technology North Bangkok, Thailand) Abstract — This paper describes the design and the error evaluation of a low-cost vibration monitoring instrument based on the MEMS acceleration sensor, which can be applied to various applications for the building structure monitoring. The developed instrument can be utilized to monitor five measuring points simultaneously and remotely on twisted pair conductors up to 100 meters. The design focuses strongly on the instrument mobility, easy to install on the measuring site, real-time processing, and accuracy. The current-loop technique is used in the design of the signal conditioner to enhance the ability of data transmission in a longer distance without noise. The instrument is intended to use with the frequency up to 20 Hz. The sensitivity of the sensor head and monitoring station were calibrated with the standard shaker. The calibration method conforms to ISO16063-21. The accuracy of the overall instrument is at ±0.3 m/s2 at the frequency range of 1 Hz to 20 Hz.

14.15-14.30 Paper ID – 1570688803 Numerical Investigation of Localized Surface Plasmon Resonance (LSPR) Based Sensor for Glucose Level Monitoring

Kawintida Santavanond and Charusluk Viphavakit (Chulalongkorn University, Thailand); Wisarn Patchoo (Bangkok University, Thailand); Hala J El-Khozondar (Islamic University of Gaza, Palestine); Waleed Mohammed (Bangkok Univseriy, Rangsit-Campus, Thailand)

Abstract — This study aims to apply Localized Surface Plasmon

Resonance (LSPR), Maxwell Garnett's formula, and Fabry-Perot theory together to design and develop a LSPR enhanced gold colloidal nanoparticles (AuNPs) sensor to be used in biomedical applications such as detection of glucose level in urine for early stage screening of diabetic patients. In this work, the LSPR based sensor has been designed and studied numerically to detect the glucose level from the change in the effective index resulting in a red shift of the absorption peak. The sensors were designed to have various sizes of the gold nanoparticles in a range between 20 nm and 100 nm by having different molar ratio with Trisodium Citrate (TSC) which acts as stabilizer in the synthesis. The maximum possible sensitivity of the sensor can be achieved with 70 nm diameter of gold nanoparticles at 0.2 volume fraction of AuNP to glucose solution.

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14.30-14.45 Paper ID – 1570688810

Investigation of Contact Angles of SnAgCu Solder Paste Mixed with Graphene Oxide Using Digital Holography Technique

Kavisra Jongjinakool and Tawipon Prakobsang (King Mongkut’s Institute of Technology Ladkrabang, Thailand); Suwan Plaipichit (Srinakharinwirot University, Thailand); Kannachai Kanlayasiri and Mettaya Kitiwan (King Mongkut’s Institute of Technology Ladkrabang, Thailand); Prathan Buranasiri (KMITL, Thailand)

Abstract — Since lead is a pollutant to the environment, therefore lead-free solder paste compounds have been interested in many research teams. The objective of this research is the investigation properties of solder paste with graphene oxide and reduced graphene oxide. In our experimental method the solder pastes of SnAgCu mixed with graphene oxide with bad electrical conductivity and reduced graphene oxide with good electrical conductivity at different concentration by weight of 0.00% ,0.05 % ,0.1% and 0.2% respectively. Subsequently, the shape changes of the compounds have been investigated by using digital in-line holography using laser diode wavelength 635 nm as the light source. The solder paste compounds were melted at 250 ± 5 ° C and were recorded for every 5 seconds. Then, the contact angles of the melted solder paste compound have been determined using their digital holographic reconstructed images.

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Session: ThuB2 Room V2 - Artificial Intelligence II Chair: Jing Tang, Poj Tangamchit Time: 13.30-14.45

13.30-13.45 Paper ID – 1570675636

A Novel Double Pressure Sensors-Based Monitoring and Alarming System for Fall Detection

Prakrankiat Youngkong and Worawit Panpanyatep (King Mongkut's University of Technology Thonburi, Thailand)

Abstract — Considering non-wearable devices or systems, two

technologies, camera-based and sensor-based, are frequently investigated and implemented. Most people who concern very seriously about their privacy choose the sensor-based one. Previously, a pressure sensor-based system called "NEF" was developed to monitor on-bed movements and send out alarming notifications to end-users when undesired events occurred. The system used only one pressure sensor that was placed on the bed or mattress. On-bed positions and patterns were classified with high accuracy. However, the fall event is actually very dynamic. Movements outside the bed shall be included. In this paper, a novel double pressure sensors-based system was proposed. Applying different machine learning techniques, random forest yielded the best fall detection model with 100% accuracy. Further experiments in multiple centers will be investigated.

13.45-14.00 Paper ID – 1570676091

Anomaly Detection of a Reciprocating Compressor Using Autoencoders Chittkasem Charoenchitt and Poj Tangamchit (KMUTT, Thailand)

Abstract — This study introduces a novel approach for early fault detection using an autoencoder under time-varying conditions of a reciprocating compressor. The main strategy of this unprecedented method functions by combining a thermodynamic equation of compressor's discharge temperature with sensors' data to increase the prediction accuracy. This equation enables the model to identify the relationships between variables including the temperature, pressure and molecular weight of gas, thus alleviating the problem of poor data quality. Energy spectrum of vibration signals in the frequency domain was also used as additional features. The model was trained to recognize normal operations with 5-year data sampled every one minute. Two months before a machine shutdown was considered as abnormal period, of which the model wanted to identify it. The result suggested that the model can differentiate between normal and abnormal operations by a substantial margin.

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14.00-14.15 Paper ID – 1570676284

Automatic Bus Stop Detection with Deep Neural Networks and Bi-Directional LSTM

Jitpinun Piriyataravet (King Mongkut's University of Technology Thonburi, Thailand); Wuttipong Kumwilaisak (King Mongkut's University of Technology, Thonburi, Thailand); Jatuporn Chinrungrueng (Nectec, Thailand)

Abstract — This paper presents a novel method in bus stop prediction from bus GPS trajectories. Our proposed bus stop prediction algorithm is based on the deep neural network and time filtering algorithm. Bus speed histograms of all locations along a route are first constructed. A bus speed histogram and a bus heading direction at each location are input features of a deep neural network. A deep neural network consists of the CNN networks and fully connected networks. The outputs from a deep neural network of all locations along a route are inputs to the LSTM network. It outputs soft decisions of bus stop prediction of all locations. The time filtering algorithm refines the results obtained from the LSTM network. It constructs time histograms of all locations and extracts the most probable timestamps of all locations. Then, a linear regression method is used to correct timestamps. Time distributions can be derived from the updated timestamp and are compared with a reference distribution. Locations with time distributions close to the reference distributions are predicted as bus stop locations. We compare our algorithm on a set of GPS data of NSTDA bus service. The proposed technique can outperform conventional bus prediction methods.

14.15-14.30 Paper ID – 1570666091 Effectiveness of Applying HEALTH-EDRM Framework: A Comparison of the COVID-19 Situation in Asia-Oceania Countries and Territories

Kumpol Saengtabtim, Jing Tang and Natt Leelawat (Chulalongkorn University, Thailand)

Abstract — Millions of people in the countries around the world are suffering due to one of the most dangerous disasters the Coronavirus disease 2019 or COVID-19. This research has the main objective to see the effectiveness of the HEALTH-EDRM framework from the World Health Organization (WHO) for dealing with the COVID-19 situation. The data set from the two popular online sources which are ourworldindata.org and worldmeter.info are collected and used for performing the analysis. The t-Test analysis method is used as the main tool for performing the analysis based on the 3 hypotheses related to the COVID-19 situation in Asia-Oceania countries. The result shows a significantly higher effectiveness in the member states which applied the HEALTH-EDRM for dealing with the COVID-19 affected cases, but not with the COVID-19 death cases.

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14.30-14.45 Paper ID – 1570672095

Government COVID-19 Responses and Subsequent Influences on NO2 Variation in Ayutthaya, Thailand

Akira Kodaka (Keio University, Japan); Natt Leelawat and Jing Tang (Chulalongkorn University, Thailand); Yasushi Onda and Naohiko Kohtake (Keio University, Japan)

Abstract — Economic activities controlled by government for preventing COVID-19 influences atmospheric conditions. A satellite-based technology is promising to monitor the change and even non-specialist on geospatial analysis can utilize it by using a cloud-based open platform. This study aims to give scientific interpretation on causes of the atmospheric change by taking government actives into account. Ayutthaya Province in Thailand and Nitrogen dioxide (NO2) were the cases for an area and atmospheric material, respectively. An analysis was conducted with Google Earth Engine by using four dataset including Nitrogen Dioxide of Sentinel-5P. As results, it was revealed that the mean value of NO2 density during January 1 to April 30, 2020, in urban area including industrial zones decreased 12.5% compared to the one in 2019. Facilities closure instructions by the government seemed to be one of the key causes of the phenomena. The decline was statistically tested and resulted in significant difference. As the new daily cases decreased to single digit, the deference became no significant from May 1, 2020. Single time series analysis on NO2 density change would enable to picture brief impact of responses and policies made by government and subsequent economic activities yet other types data of atmospheric materials and actual industrial activities are necessary for further assessment.

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Session: ThuC2 Room V3 - Control Theory and Applications Chair: Sudchai Boonto, Peerayot Sanposh Time: 13.30-15.15

13.30-13.45 Paper ID – 1570641877

Double Loop Neural Network Fractional-Order Terminal Sliding Mode Control of MEMS Gyroscope

Juntao Fei and Zhe Wang (Hohai University, China)

Abstract — This paper proposes a fractional-order nonsingular terminal sliding mode control of a MEMS gyroscope using a double loop recurrent neural network approximator. For higher accuracy and faster convergence, the fractional-order (FO) calculus is employed into the nonsingular terminal sliding mode controller with additional degree of freedom. For the system robustness, the neural network is designed to approximate the lumped uncertainty. The inner recurrent loop and external recurrent loop is employed to provide feedback signal to obtain satisfactory approximation accuracy. Furthermore, the Lyapunov stability theorem is employed to verify the asymptotical stability and convergence of system. Simulations for a MEMS gyroscope are studied to exhibit the superiority of the proposed control strategy.

13.45-14.00 Paper ID – 1570666604 Model Approximation of an Arm of the NAO Robot Using System Identification

Erique Jimenez-Vazquez and Julieta Ayala-Rodriguez (Tecnológico de Monterrey, Mexico); David Navarro-Duran and Edgar Lopez-Caudana (Tecnologico de Monterrey, Mexico)

Abstract — This paper proposes a methodology to obtain a model

approximation for the SoftBank NAOTM robot. It is worth to stress that the NAOTM robot is a closed commercial platform, namely, most of the parameter values are not available. Then, to improve the knowledge about dynamic behavior and to carry out further analysis, a mathematical model is necessary. The identification is achieved by basic knowledge form undergraduate control engineering courses, such as system identification, classic control, state space and robot dynamics. Model identification is used to obtain unknown parameters of a first-order approximation of the mechanical dynamics for the NAOTM robotic arm. Additionally, a theoretical dynamic model is obtained by means of the Euler-Lagrange approach. Both viewpoints are complemented in order to compute the missing model parameters and to obtain a satisfactory approach. This demonstrates that even simple models can replicate without significant error the system dynamics.

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14.00-14.15 Paper ID – 1570679340

Optimal Consensus Control for Multi-Agent Systems with Input Constraints: A State Decomposition Approach

HoSub Lee and In Seok Park (Pohang University of Science and Technology, Korea (South)); PooGyeon Park (POSTECH, Korea (South))

Abstract — This paper presents optimal consensus control for multi-

agent systems with input constraints by using a state decomposition approach. The state decomposition approach is to divide the state space into consensus subspace and its orthonormal complement subspace. The proposed equality condition ensures that consensus subspace is consensus. Therefore, if we design the gain K that orthonormal subspace converges to zero, the consensus is achieved. Solving the proposed optimization problem that minimizes global cost function guarantees consensus control with input constraints of states. To solve the optimization problem, linear matrix inequality (LMI) formulation is used. The simulation results of numerical examples show that the proposed condition achieves multi-agent systems consensus.

14.15-14.30 Paper ID – 1570676272 Optimization Based Dynamics Setpoint Control to Improve Cycle Power Efficiency of the LM6000PF+ Aero Gas Turbine Wissanudech Tawangkan (KMITL, Gulf, Thailand)

Abstract — The efficiency of the Aero Gas Turbine in a combine cycle

power plant (CCPP) is maximum under the conditions that the combustion chamber temperature is highest, the compressor is working at full capacity and all bleed valves are closed. The Inlet Air Heating System is therefore used to improve the efficiency of the machines in low power generation conditions. To ensure stability in response to air temperature and machine capacity changes, this work thus proposes an optimization-based automation system designed to stabilize the CCPP. Results show that under changing conditions, the overall efficiency of the air compressors in low load conditions increases by 3%, shortening the system start time of 15 minutes and improving the efficiency of the combined cycle power plant by an average of 100 BTU / kw.hr. The average fuel cost is reduced by approximately 600,000 baht per month.

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14.30-14.45 Paper ID – 1570679484

Using Differential Evolution for Smart Grid Jukkrit Kluabwang (Rajamangla University of Technology Lanna Tak & Electrical Energy Research Unit, Thailand)

Abstract — This paper shows experimental results of an application of a

conventional differential evolution algorithm (DE) for solving an interesting smart grid problem, namely WCCI/GECCO 2020 Energy Resource Management (ERM) testbed 1. The main purpose of this article is to encourage beginners in smart grid to walk with an AI tool for more understanding approach. Testbed 1 has been developed by a research team in Portugal years ago and it still is a challenged problem suite in electric power system engineering now because it consists of all key parts, demand side, supply side and aggregator, to do a proper day-ahead schedule via DE. DE with different sets of parameters were performed but other algorithms are also welcome to solve the testbed 1 with standardized index called ranking index (RI). RI has been used significantly to monitor and to classify search algorithms applied to the problem. RI is independent from computational machines, according to our three tests with different computers, they spent different time but all obtained RI is the same. Six parameters of DE, number of population, mutation factor, recombination constant, maximum iteration, strategy and boundary constraint, have been varied and also investigated effects on their RI.

14.45-15.00 Paper ID – 1570672963 A Study on Safety Issues of Hybrid Wireless Power Transfer in Laboratory Jarurote Tippayachai and Supaporn Kiattisin (Mahidol University, Thailand); Taweesak Samanchuen (Technology of Information System Management Division, Faculty of Engineering, Mahidol University, Thailand); Kamon Jirasereeamornkul (King Mongkut's University of Technology Thonburi, Thailand); Chainarin Ekkaravarodome (King Mongkut’s University of Technology North Bangkok, Thailand); Thamvarit Singhavilai (Mahidol University, Thailand)

Abstract — Hybrid wireless power transfer (HPT) employs both

magnetic and electric fields to transmit the power across air-gap distance at the resonant frequency, enhancing the potential for charging battery in electric vehicles. While the HPT technology is still under research study, no safety concerns have yet reported during the experiment. This study aims to re-investigate the safety issues of HPT in experiment by creating and testing the HPT prototype. The HPT proposed by Luo is used in our study, consisting of two coupling coils, four aluminium plates, and two compensation capacitors. This HPT prototype is tested in the frequency range of 600 and 700 kHz. To reveal the effects of thermal and EMF leakages, a thermal scan and EMF detector are used in the experiment. The results demonstrated that the prototype of HPT operates at high frequency, high power, and high efficiency. Moreover, the safety issues in experiment are summarized.

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15.00-15.15 Paper ID – 1570679346 An Advanced Time-Delay Controller for Robust Trajectory Control of Manipulator in the Excavator Dong Woo Kim and PooGyeon Park (POSTECH, Korea (South))

Abstract — An advanced time-delay controller with a hold function is

designed. The hold function, which consists of hyperbolic tangent, improves an error convergence by substituting the error to a modified error. Kinematics and dynamics of the 3-link arm are analyzed as the manipulator of the excavator consists of a 3-link arm, which are called boom, arm and bucket. To show the robustness of the advanced time-delay controller, proportional integral derivative controller and adaptive inertia-related controller are designed and compared. The simulations are performed according to the weight of the bucket tip and the trajectory time by using the MATLAB Simulink.

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Session: ThuA3 Room V1 - Robotics Chair: Maroay Phlernjai, Pruittikorn Smithmaitrie Time: 15.15-16.30

15.15-15.30 Paper ID – 1570665658

Development of a Vision Based Ball Catching Robot Kasun Gayashan Hettihewa and Manukid Parnichkun (Asian Institute of Technology, Thailand)

Abstract — This paper investigates an automated solution for ball

catching task using a static camera and an automatically controlled mechanical system. The robot system is able to catch a ball which comes towards the ball catching plane. The robot accomplishes the ball-catching task with different success rates according to the trajectory type and speed of the ball. The thrown ball is visually tracked through a ball detection image processing algorithm. 2D synchronized motion of the ball catcher is coordinated by PID algorithm. Experimental results are conducted to evaluate the robot performance.

15.30-15.45 Paper ID – 1570666797 An Energetic Analysis of Rhomboidal Linkage Robots for Hopping Lunar Exploration John Lo (The University of Manchester, United Kingdom (Great Britain)); Ben Parslew (The University of Manchester, United Kingdom (Great Britain) & Chulalongkorn University, Thailand)

Abstract — In this paper, we present a conceptional design framework

for jumping robots for lunar exploration. A method is developed for spring placement and sizing that maximises the onboard elastic potential energy storage, which is essential for space missions. In the class of rhomboidal linkage robots, the analysis shows that torsion springs placed at the knee joints store more energy than the commonly used extension or linear compression springs; torsion springs store around 80% of the idealized maximum attainable energy storage, compared to only 60% for an extension spring. A physical demonstrator is developed using torsional springs, and exhibits repeatable jumps with an average jump height of 1.2m under earth gravity, equivalent to 7.3m under lunar gravity. However, preliminary trials show the choice of substrate is shown to the influence the jump height. This effect is predicted to be pronounced when jumping from lunar regolith.

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15.45-16.00 Paper ID – 1570667046

Control of TWIR Using LQR Controller and Compound Disturbance Observer Nam H. Nguyen (Hanoi University of Science and Technology, Vietnam)

Abstract — In this paper, a LQR controller in combination with

compound disturbance observer was designed and applied for a two-wheeled inverted pendulum robot (TWIR) in laboratory. The experimental results showed that the designed controller was able to handle with model's uncertainty and unknown input disturbance.

16.00-16.15 Paper ID – 1570671766

Twist-Based Crouching Motion for Multi-Legged Inspection Robot Maroay Phlernjai (Sirindhorn International Institute of Technology & Thammasat University, Thailand); Pran Piyathassrikul (Sirindhorn International Institute of Technology, Thailand); Photchara Ratsamee (Osaka University, Japan)

Abstract — The monitoring and inspection of the condition of buildings,

towers, or large chemical tanks have been dangerous for workers. Also, these processes can also be very costly. A wall climbing multi-legged robot can be used to tackle the problem stated. The robot has to alternatively climb and crouch to move the inspection probe close to the wall surface. The typical wall-sticking crouching motion of hexapods could not do this without an additional actuator at the foot base. This paper proposes a new crouching mechanism using the twisting action of the robot legs. The mathematical model of the twisting crouch is introduced and A prototype test has been done to confirm the validity of the proposed concept.

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16.15-16.30 Paper ID – 1570672159

Aerodynamic Experimental Investigation and Analysis of the Flow and Thrust Generation of the Flexible Flat Flapping Wing Robot Kamonrat Tangudomkit and Pruittikorn Smithmaitrie (Prince of Songkla University, Thailand)

Abstract — For micro unmanned aerial vehicles with the flapping wing

mechanism, the thrust is produced by the unsteady aerodynamics. The produced flapping thrust is similar to the thrust created in nature. However, the aerodynamic flow of the bionic flapping wings and produced thrust relationship has not been truly investigated. This study has found the vortex locations behind the wings that affect the thrust at specific periods of the flapping cycle. The aerodynamic flow field around the flapping wingspan of 33 cm is visually observed and reported by the smoke wire technique. The leading edge and trailing edge vortexes are recorded with a high-speed VDO camera as well as the real-time produced thrust is acquired. It was found that the leading edge vortex occurs near the top wing surface at the 20-degree upstroke wing position, the trailing edge vortex occurs after the 20-degree down stroke and the maximum thrust occurs at the -5-degree down stroke. In addition, the leading and trailing edge vortexes are created beneath the wings during the upstroke and changed to be the jet flow generating the thrust. The produced thrust and flapping stroke relationship are analyzed in this study. The investigation provides the fundamental knowledge to design the flying robot body configuration that could help generating thrust in the desired direction.

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Session: ThuB3 Room V2 - Image Processing and Computer Vision Chair: David Banjerdpongchai, Sutthiphong Srigrarom Time: 15.15-16.15

15.15-15.30 Paper ID – 1570665561

Automatic Speech Recognition for Thai Sentence Based on MFCC and CNNs Kanjanapan Sukvichai, Chaitat Utintu and Warayut Muknumporn (Kasetsart University, Thailand)

Abstract — An automatic speech recognition (ASR) is more important,

especially in the Coronavirus outbreak. ASR for Thai sentence was proposed based on MFCC and CNNs in this research. The MFCC features image created from the Thai speech procedure is explained. The MFCC image is treated as a normal image. Object detection techniques based on CNNs can be used to detect Thai words in the frequency image. You Only Look Once (YOLO) is selected as the word localizer and classifier due to its performance and accuracy. The airport service scenario is explored in this research in order to obtain the performance of the proposed system. The airport information system is selected for the experiments. Speeches were collected from 60 participants with 50% males and 50% females. Speech images are constructed based on MFCC and labeled for specific Thai keywords. The YOLOv3 and Tiny YOLOv3 were trained and the performance was evaluated. Clearly, Tiny YOLOv3 network is good enough for this experiment. New speech data provided from new 20 participants were used to test the proposed system. Resulting in the proposed ASR system based on MFCC and CNNs has a good performance in both speed and accuracy.

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15.30-15.45 Paper ID – 1570670928

Multi-Camera Multi-Drone Detection, Tracking and Localization with Trajectory-Based Re-Identification Sutthiphong Srigrarom (National University of Singapore & Temasek Laboratories, Singapore); Niven Jun Liang Sie and Huimin Cheng (National University of Singapore, Singapore); Kim Hoe Chew (Technical University of Munich, Germany); Mengda Lee (Singapore University of Technology and Design, Singapore); Photchara Ratsamee (Osaka University, Japan)

Abstract — This paper presents a real-time multiple cameras system for

detecting, tracking, localizing multiple moving drones simultaneously in 3 dimensions. The distinct difference of the system is its target re-identification process for information fusion among cameras based on the targets' trajectories and relative locations. Multiple drones are detected by multiple cameras based on motion-based blob detection. A geometry- and camera-based model provides the 2D location of each of the drones in individual camera frame. Then, the trajectories of each of the tracked drones are examined, using drone track feature variable and cross-correlated among cameras for object re-identifications. This allows the individual 2D position information to be integrated to get the overall global 3D positions of all the tracked drones from all cameras. Preliminary outdoor flight demonstrations with 2 drones flying in formation and using 3 cameras show optimal results. The system is able to detect, track, localize and reidentifying individual drone with average positional error of 8%. Index Terms-Multiple cameras, Multiple drones, Tracking, Localization, Trajectory-based, Re-identification, Drone track feature variable, Cross-correlation.

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15.45-16.00 Paper ID – 1570674885

Enabling Continuous Drone Tracking Across Translational Scene Transitions Through Frame-Stitching Jiahe Yi (Nanyang Technological University, Singapore); Kim Hoe Chew (Technical University of Munich, Germany); Sutthiphong Srigrarom (National University of Singapore & Temasek Laboratories, Singapore)

Abstract — This paper introduces a method for enabling the continuous

tracking of drones across translational scene transitions through the introduction of a stationary global frame. The main benefit of such a method is that it allows current pan-tilt-zoom (PTZ) cameras commonly used in security applications to be used in the domain of drone tracking. The first step in the process is to correct for lens distortion with the intrinsic parameters of the camera obtained through calibration. The motion of the camera frame is then estimated using the optical flow of tracked features from frame to frame. Information obtained about the translational motion of the frame is then used to construct a global frame on which object tracking is performed. Results from the comparison of object detection and tracking performed on two clips with and without pre-processing to construct the global frame show an improvement in tracking performance when the technique was applied to the video. The method was shown to successfully compensate for the relative velocity of objects in the frame relative to the frame, with no sudden changes of velocity during the scene transition. In addition, the introduction of a global frame enabled the continuous tracking of a stationary drone that was reassigned to a new track in the original video.

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16.00-16.15 Paper ID – 1570676227

Stabilize Quadcopter's Position Using Vision-Based Corner Detector from Top-Down Camera's Footage Khoa Anh Vo, Tinh Van Tran, Cuong Manh Le and Minh-Thien Duong (Ho Chi Minh City University of Technology and Education, Vietnam); Le My Ha (Ho Chi Minh City University of Technology and Education & Faculty of Electrical and Electronics Engineering, Vietnam)

Abstract — In this paper, a method to stabilize a quadcopter prototype's

position using feature extraction and tracking from camera footage was implemented. The quadcopter's position and linear velocity are determined from images captured by a downward-facing camera. First, Shi-Tomasi technique was used to detect corners in the images and from this method, displacement of the quadcopter is yielded. Linear velocity was then calculated using the quadcopter's displacement. Once the linear velocity of the quadcopter has been estimated, the cascade PID controller is proposed to stabilize the hovering quadcopter's position. A quadcopter prototype is built to evaluate the proposed method and the experimental results showed that the quadcopter remained its position for approximately 70 seconds before it started to drift.

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Session: ThuC3 Room V3 - International Workshop on Artificial Intelligence Theory and Application Chair: Thanaruk Theeramunkong Time: 15.15-16.00

15.15-15.30 Paper ID – AITA2021-0101

Comparison between Intensity and k-means clustering based method for treatment classification of Posterior Capsular Opacification Raisha Shrestha (Sirindhorn International Institute of Technolgy, Thammasat University, Thailand), Waree Kongprawechnon (Sirindhorn International Institute of Technolgy, Thammasat University, Thailand), Toshiaki Kondo (Sirindhorn International Institute of Technolgy, Thammasat University, Thailand), Teesid Leelasawassuk (NECTEC, Thailand), Nattapon Wongcumchang (NECTEC, Thailand)

Abstract — Posterior Capsular Opacification (PCO) has been under study

since few decades and research have been carried out to analyze its properties. This research is focused on classification of PCO on basis of treatment requirement. Two methods: (i) digital image processing based intensity method and (ii) unsupervised machine learning based k-means clustering method have been used to detect PCO and further classify it into treatment required and not yet required PCO. Validation is achieved by comparing our classification with clinical classification. Further confusion matrices are used to get F1 scores and accuracy values. F1-score for method i is 0.966 with 5 False Negatives, likewise for F1-score for method ii is 0.98 with 0 False Negatives. Our obtained calculation values and plots show that method ii is better than method i and also is eligible for treatment classification of PCO.

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15.30-15.45 Paper ID – AITA2021-0002

Analysis of Abstractive Summarization Behavior using Transformer Models Sawittree Jumpathong (Sirindhorn International Institute of Technolgy, Thammasat University, Thailand), Prachya Boonkwan (NECTEC, Thailand), Sitthaa Phaholphinyo (NECTEC, Thailand), Thepchai Supnithi (NECTEC, Thailand), Thanaruk Theeramunkong (Sirindhorn International Institute of Technolgy, Thammasat University, Thailand)

Abstract — Automatic text summarization is important because of the

enormous amount of textual data that increases exponentially. It is time-consuming and laborious to find the information from huge textual data manually. Text summarization is one of techniques that can solve this problem. Transformer is one of the deep learning techniques based on sequences-to-sequences models and it is a popular encoder-decoder framework. Therefore, we are interested to apply these models on abstractive Thai text summarization for studying about behavior of abstractive summarization using Transformer Models. In this paper, we examine the use of the Transformer model in abstractive Thai text summarization and analyse behavior of abstractive summarization using Transformer Models. We focused on three things that are interesting which consist of the position of main ideas, word substitution with similar words and errors of the system summary.

15.45-16.00 Paper ID – AITA2021-0003

Khmer Text-To-Speech Using Tacotron 2 Sreyroth Phem (Sirindhorn International Institute of Technolgy, Thammasat University, Thailand), Thanaruk Theeramunkong (Sirindhorn International Institute of Technolgy, Thammasat University, Thailand), Kobkrit Viriyayudhakorn (iApp, Thailand)

Abstract — This paper proposes a method for implementing Khmer Text-

To-Speech by using Tacotron 2 PyTorch Implementation of Natural TTS Synthesis by Conditioning Wavenet On Mel Spectrogram Predictions to introduce a new structure of building the first Khmer Speech Synthesis. In this framework, we need a dataset which is approximately 12 hours of Khmer waveform audios and the audio script. Additionally, the Khmer Word Segmentation is required. The Khmer Word Segmentation is applied to the audio script of the dataset. Then, the waveform audios is pruned and cleaned the silence which is hidden in each audio file. After that, we trained both audio file and script together using Tacotron 2 and WaveGlow model. Moreover, the accuracy of the Khmer TTS, compared with the original voice are used to verify the performance of the framework. The experimental results show that the introduced implementation satisfies the evaluation criteria in term of understandable voice output and accuracy. Nevertheless, it's a major trade-off between them.

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Best Paper Award

Paper ID 1570641877

Title: Double Loop Neural Network Fractional-Order Terminal Sliding Mode Control of MEMS Gyroscope

Authors: Juntao Fei and Zhe Wang Affiliation: Hohai University, Chaina

Paper ID 1570671697

Title: Configurable Hardware Architecture of Multidimensional Convolution Coprocessor

Authors: Geranun Boonyuu, Sumek Wisayataksin Affiliation: King Mongkut’s Institute of Technology Ladkrabang, Thailand

Paper ID 1570672095

Title: Government COVID-19 Responses and Subsequent Influences on NO2 Variation in Ayutthaya, Thailand

Authors: Akira Kodaka, Natt Leelawat, Jing Tang, Yasushi Onda and Naohiko Kohtake Affiliation: Keio University, Japan; Chulalongkorn University, Thailand; Chulalongkorn

University, Thailand; Keio University, Japan; Keio University, Japan Paper ID 1570679887

Title: Convex Optimization Approach to Multi-Objective Design of Two-Stage Compensators for Linear Systems

Authors: Tanathorn Supithak, Nicha Wongyimyong, Kou Yamada and David Banjerdpongchai

Affiliation: Chulalongkorn University, Thailand; Chulalongkorn University, Thailand; Gunma University, Japan; Chulalongkorn University, Thailand

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Author Index

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Author Index

A Ayala-Rodriguez, Julieta ThuC2.2 B Banjerdpongchai, David ThuA1.5 Boonyuu, Geranun ThuB1.3 Buranasiri, Prathan ThuA2.5 C Charoenchitt, Chittkasem ThuB2.2 Cheng, Huimin ThuB3.2 Chew, Kim Hoe ThuB3.2 ThuB3.3 Chinrungrueng, Jatuporn ThuB2.3 D Duong, Minh-Thien ThuB3.4 E Ekkaravarodome, Chainarin ThuC2.6 El-Khozondar, Hala ThuA2.4 F Fei, Juntao ThuC2.1 H Ha, Le My ThuB3.4 Hagiwara, Takaaki ThuA2.2 Hansakunbuntheung, Chatchawarn ThuB1.2 Hashikura, Kotaro ThuA1.3 ThuA2.1 ThuA1.1 ThuA1.2 Hettihewa, Kasun ThuA3.1 I Ismail, Zool ThuC1.3 ThuC1.4 J Janya-anurak, Chettapong ThuB1.4 Jennawasin, Tanagorn ThuA1.6 Jimenez-Vazquez, Erique ThuC2.2 Jirasereeamornkul, Kamon ThuC2.6 Jongjinakool, Kavisra ThuA2.5 Junplod, Goragod ThuB1.1

K Kamal, Md Abdus Samad ThuA2.1 Kamal, Md Abudus samal ThuA1.3 ThuA1.1 ThuA1.2 Kammuang, Thanitnan ThuC1.1 Kamonkusonman, Kasama ThuC1.2 Kanlayasiri, Kannachai ThuA2.5 Khamkaew, Jakkarawut ThuA1.6 Khuankrue, Issarapong ThuC1.1 Kiattisin, Supaporn ThuC2.6 Kim, Dong Woo ThuC2.7 Kitiwan, Mettaya ThuA2.5 Kluabwang, Jukkrit ThuC2.5 Kodaka, Akira ThuB2.5 Kohtake, Naohiko ThuB2.5 Kojima, Akira ThuA1.2 Kornmaneesang, Woraphrut ThuB1.1 Koyama, Daisuke ThuA1.1 Kumwilaisak, Wuttipong ThuB1.2 ThuB2.3 L Le, Cuong ThuB3.4 Lee, HoSub ThuC2.3 Lee, Mengda ThuB3.2 Leelawat, Natt ThuB2.5 ThuB2.4 Li, Pengfei ThuA2.2 Lo, John ThuA3.2 Lopez-Caudana, Edgar ThuC2.2 Luealamai, Watthanai ThuC1.1 M Miyamoto, Fuga ThuA1.2 Mohammed, Waleed ThuA2.4 Mohd Hamami, Mohd Ghazali ThuC1.3 Muknumporn, Warayut ThuB3.1 N Namima, Yuuki ThuA2.2 Navarro-Duran, David ThuC2.2 Nguyen, Nam ThuA3.3 Nilkhamhang, Itthisek ThuA1.4

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O Ogami, Junya ThuA2.2 Omairi, Amzar ThuC1.4 Onda, Yasushi ThuB2.5 P Panpanyatep, Worawit ThuB2.1 Park, In Seok ThuC2.3 Park, PooGyeon ThuC2.7 ThuC2.3 Parnichkun, Manukid ThuA3.1 Parslew, Ben ThuA3.2 Patchoo, Wisarn ThuA2.4 Phannachet, Krittapas ThuA1.6 Phantachat, Wantanee ThuB1.2 Phikulngoen, Saravut ThuB1.2 Phlernjai, Maroay ThuA3.4 Phunthawornwong, Minthorn ThuC1.2 Piriyabunjerd, Watchanun ThuB1.4 Piriyataravet, Jitpinun ThuB2.3 Piyathassrikul, Pran ThuA3.4 Plaipichit, Suwan ThuA2.5 Prakobsang, Tawipon ThuA2.5 Prayitno, Agung ThuA1.4 R Ratsamee, Photchara ThuB3.2 ThuA3.4 S Saengow, Treetep ThuC1.2 Saengtabtim, Kumpol ThuB2.4 Samanchuen, Taweesak ThuC2.6 Santavanond, Kawintida ThuA2.4 Shyh-Leh, Chen ThuB1.1 Sie, Niven Jun Liang ThuB3.2 Silapunt, Rardchawadee ThuC1.2 Simmanee, Pongpith ThuC1.2 Singhavilai, Thamvarit ThuC2.6 Smithmaitrie, Pruittikorn ThuA3.5 Srigrarom, Sutthiphong ThuB3.2 ThuB1.5 ThuB3.3 Sriphanthaboot, Warisara ThuC1.2 Sukvichai, Kanjanapan ThuB3.1 Supithak, Tanathorn ThuA1.5 Suttiwong, N. ThuA2.3

T Tang, Jing ThuB2.5 ThuB2.4 Tangamchit, Poj ThuB2.2 Tangudomkit, Kamonrat ThuA3.5 Tawangkan, Wissanudech ThuC2.4 Thatphithakkul, Nattanun ThuB1.2 Tippayachai, Jarurote ThuC2.6 Tran, Tinh ThuB3.4 U Utintu, Chaitat ThuB3.1 V Viphavakit, Charusluk ThuA2.4 Vo, Khoa ThuB3.4 W Wang, Zhe ThuC2.1 Weerapong, Pongtep ThuA2.1 Wisayataksin, Sumek ThuB1.3 Wongsa, Sarawan ThuB1.1 Wongyimyong, Nicha ThuA1.5 Y Yamada, Kou ThuA1.2 ThuA1.3 ThuA2.1 ThuA1.5 ThuA1.1 Yamamura, Yuito ThuA2.2 Yi, Jiahe ThuB3.3 Youngkong, Prakrankiat ThuB2.1 Z Zhang, Dayu ThuA1.3

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Additional Reviewers

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Additional Reviewers

Syukron Alfarozi Seksan Laitrakun Ahsan Ali Thananchai Leephakpreeda Widhyakorn Asdornwised Zongying Liu Surachat Chantarachit Sanparith Marukatat Sarun Chattunyakit Worawat Nakawiro Werapon Chiracharit Jonglak Pahasa Choopong Chuaypen Chuaypen Wisarn Patchoo Somrudee Deepaisarn Pakpoom Patompak Nat Dilokthanakul Maroay Phlernjai Suradej Duangpummet Porpin Pungetmongkol Kittipong Ekkachai Sillawat Romphochai Jittat Fakcharoenphol Miti Ruchanurucks Takaaki Hagiwara Peerayot Sanposh Nguyen Duy Hung Thunyaset Sethaput Jenq-Neng Hwang Jitkomut Songsiri Tanagorn Jennawasin Yodyium Tipsuwan Teerasit Kasetkasem Taravichet Titijaroonroj Issarapong Khuankrue Wiput Tuvayanond Somsak Kittipiyakul Sarawan Wongsa Preecha Kocharoen Kuntpong Woraratpanya Woraphrut Kornmaneesang Prakrankiat Youngkong Worapoj Kreesuradej

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Sponsors

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Sponsors

ICA-SYMP sincerely thanks our sponsors for supporting our mission and making the

symposium possible.

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