eeecs 2020 - web venue

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EEECS 2020 Program and Abstracts

The 7th International Conference on Electronics,

Electrical Engineering, Computer Science 2020

December 21-22, 2020

Gachon University, Korea

Sponsored by

Korea Culture & Contents Technology Association (KOCTA), Immersive Content Display Center (ICDC),

Computer and Communication Engineering for Capacity Building (CCC)

Copyright ⓒ 2020 KOCTA.

Program & Abstracts EEECS2020

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Contents

1 Messages ........................................................................................................................................... 3

1.1 Message from General Chair ....................................................................................................... 3

2 Committee ........................................................................................................................................ 4

2.1 Organizing Committee ................................................................................................................. 4

2.2 Technical Program Committee ..................................................................................................... 5

3 Keynote Speeches ............................................................................................................................. 7

4 Program at a Glance ........................................................................................................................ 9

5 Technical Program ......................................................................................................................... 11

RS1 Regular Session: Smart Contents Protection ...................................................................... 11

RS2 Regular Session: Multimedia Contents & Systems ............................................................. 11

RS3 Regular Session: Intelligent Signal and Image Processing 1 ............................................... 12

RS5 Regular Session: High Performance Computing Systems ................................................... 12


RS7 Regular Session: Immersive Display, Network & Contents ................................................. 13

RS8 Regular Session: Artificial Intelligence for Embedded Systems .......................................... 14

SS1 Special Session: Smart Multimedia Applications ............................................................... 14

SS2 Special Session: Immersive Content Display ...................................................................... 15

6 Abstracts ......................................................................................................................................... 16

RS1 Regular Session: Smart Contents Protection ...................................................................... 16

RS2 Regular Session: Multimedia Contents & Systems ............................................................. 17


RS5 Regular Session: High Performance Computing Systems ................................................... 20


RS7 Regular Session: Immersive Display, Network & Contents ................................................. 23

RS8 Regular Session: Artificial Intelligence for Embedded Systems .......................................... 24

SS1 Special Session: Smart Multimedia Applications ............................................................... 26

SS2 Special Session: Immersive Content Display ...................................................................... 27

7 Author Index .................................................................................................................................. 30

EEECS2020 Program & Abstracts

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1 Messages

1.1 Message from General Chair

It is a great pleasure for me to welcome you to the 7th International Conference on

Electronics, Electrical Engineering, Computer Science (7th EEECS 2017) from December

21 to December 22, 2020. This year’s conference marks the seventh EEECS starting from

2016. The EEECS is a conference of the Korea Culture & Contents Technology Association

(KOCTA) and represents large number of gatherings of researchers and industry

professionals in the corresponding fields.

This year’s conference brings together more than 50 delegates from around the Asian

countries to discuss the latest advances in this vibrant and constantly evolving field. The

topics covered in the program include overall areas in Electronics, Electrical Engineering,

and Computer Science. In line with recent research trends, many artificial intelligence-related

papers have been accepted with the diligent work of the technical program committee.

2020 has been a very challenging year due to the COVID-19 pandemic. This conference

is originally planned to be held in Gachon University, Korea. But due to the COVID-19

spread out, it has been converted to a fully online conference. Nonetheless this difficulty

situation, the committee would thank all participants and paper authors contributing this

conference more active. Through this online platform, EEECS 2020 continues to share an

insight into the recent research and cutting-edge technologies in those fields of ICT.

The EEECS2020 has been made up by many volunteers who contributed to the various

processes and it would not be possible for me to name all of them in this short message. In

particular, the Technical Program Committee, led by our indefatigable TPC Chairs and

supported by the TPC members, completed a thorough peer-review process of technical and

special session papers to select a comprehensive and high-quality technical program for the

conference. This program is augmented and complemented by two Keynote Speeches, two

special sessions and several regular sessions. In addition, all Organizing Committees worked

tirelessly to ensure the best quality experience for the delegates during the technical sessions

and the social programs.

Also I would like to thank the groups of KOCTA and ICDC, Kwangwoon University,

Korea and CCC, Mae Fah Luang University. Finally, I would also like to thank all participants

and supporters for their contribution to the conference. It is a fantastic experience for me to

serve as the General Chair of EEECS2020 and it is my hope that you find the conference

stimulating, fulfilling and enjoyable. Please enjoy the conference!

7th EEECS 2020 General Chair

Taek Keun Hwangbo


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2 Committee

2.1 Organizing Committee

Honorary Chair

Byunggi Kim, Soongsil University, Korea

Kosin Chamnongthai, KMUTT, Thaniland

General Chair

Taek-Geun HwangBo, Gachon University, Korea

Technical Program Co-Chairs

Seung Hyun Lee, Kwangwoon University, Korea

Kyoungro Yoon, Konkuk University, Korea

Chayapol Kamyod, Mae Fah Luang University, Thailand

Special Session Chairs

Jiman Hong, Soongsil University, Korea

Sang Kyun Kim, Myungji University, Korea

Sangwoon Lee, Namseoul University, Korea

Workshop Chairs

Jin Young Kim, Kwangwoon University, Korea

Youngseop Kim, Dankook University, Korea

Publicity Chairs

Young-Ho Seo, Kwangwoon University, Korea

Hae Chul Choi, Hanbat National University, Korea

Dong Myung Shin, LSWare Inc, Korea

Publication Chairs

Youngmo Kim, Soongsil University, Korea

Finance & Registration Co-Chairs

Youngwhan Lee, Wonkwang University, Korea

Cheong Ghil Kim, Namseoul University, Korea

Local Arrangement Chair

Seok Hee Oh, Gachon University, Korea

Information System Chair

Seungmin Lee, Namseoul University, Korea

Ui Jin Jang, Soongsil University, Korea

General Secretaries

Su-Kyung Yoon, Jeonbuk National University, Korea


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2.2 Technical Program Committee

Chair

Seung Hyun Lee, Kwangwoon University, Korea

Kyoungro Yoon, Konkuk University, Korea

Chayapol Kamyod, Mae Fah Luang University, Thailand

Members

Jiman Hong, Soongsil University, Korea

Hidehiro Kanemitsu, Tokyo University of Technology, Japan

Jin Young Kim, Kwangwoon University

Young-Ho Seo, Kwangwoon University, Korea

Kosin Chamnongthai, KMUTT, Thaniland

Punnarumol Temdee, Mae Fah Luang University, Thailand

Hamed Yahoui, Université Lyon 1, France

Youngmo Kim, Soongsil University, Korea

Roungsan Chaisricharoen, Mae Fah Luang University, Thailand

Jun-yu Dong, Ocean University of China, China

Muwei Jian, Shandong University of Finance and Economics, China

Nattapol Aunsri, Mae Fah Luang University, Thailand

Seok Hee Oh, Gachon University, Korea

Santichao Wicha, Mae Fah Luang University, Thailand

Sang Kyun Kim, Myungji University, Korea

Su-Kyung Yoon, Jeonbuk National University, Korea

Seok Yoon Kim, Soongsil University, Korea

Ji Hwan Kim, Sogang University, Korea

Hae Chul Choi, Hanbat National University, Korea

Ui Jin Jang, Soongsil University, Korea

Moo Wan Kim, Tokyo University of Information Sciences, Japan

Youngseop Kim, Dankook University, Korea

Tae Young Byun, Daegu Catholic University

Su-Yeon Kim, Deagu University

Apiradee Ampawasiri, Provincial Electricity Authority, Thailand

Cheong Ghil Kim, Namseoul University, Korea

Choong Pyo Hong, LG Electronics, Korea

Chompoo Suppatoomsin, Vongchavalitkul University, Thailand

Byung In Moon, Kyungpook National University, Korea

Fumitaka Ono, Tokyo Polytechnic University, Japan

Guodong Wang, Qingdao University, China

Hae Kyung Chung, Konkuk University, Korea


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Hui Xia, Qingdao University, China

Jae-sang Cha, Seoul National University of Science and Technology, Korea

Je Ho Park, Dankook University, Korea

Jia Zhao, Nanchang Institute of Technology, China

Jianbo Li, Qingdao University, China

Jin Ho Ahn, Hoseo University, Korea

Jung Hoon Lee, Gyeongsang National University, Korea

Seungmin Lee, Namseoul University, Korea

Sunghwa Lim, Namseoul University, Korea

Muhammad Arshad Awan, Allama Iqbal Open University, Pakistan

Qian Zhang, Taishan University, China

Sang Woon Lee, Namseoul University, Korea

Sasalak Tongkaw, Songkhla Rajabhat University, Thailand

Sooncheol Kwon, Kwangwoon University, Korea

Takaaki Ishikawa, Waseda University, Japan

Won Gee Hong, Daegu University, Korea

Woo Chan Park, Sejong University, Korea

Taebum Lim, KETI, Korea

Yiying Zhang, Tianjin University of Science&Technology, China

Yong Hwan Lee, Wonkwang University, Korea

Yongsoo Choi, Sungkyul University, Korea

Young Choong Park, KETI, Korea

Young Ho Seo, Mokwon University, Korea


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3 Keynote Speeches

Monday, 21st December 2020, 14:30 - 15:30

Categorization and Measurement by using heat information

Prof. Kosin Chamnongthai

King Mongkut's University of Technology Thonburi

Abstract

Thermal signal and thermal image recently become another important and interesting information

comparing with conventional signals representingbrightness, sound, distance, etc. In some

conditions such as nighttime, it is almost impossible to get brightness information to process and

categorize object types. As a case study, thermal signal is regarded to be able to apply for vehicle-

type categorizationat night time and dark areas, since vehicles generally gets heat from their

engines, and their heat patterns can be categorized and recognized the vehicle types. Similarly, food

that is normally cooked in the warm or even hot temperature level is regardedas possible to classify

and recognize food types and their ingredients by using heat pattern. In this talk, research cases of

nighttime vehicle-type categorization and food calorie measurement are explained and discussed in

order to understand the trend ofthermal signal applications.

Biography

Kosin Chamnongthai currently works as professor at

Electronic and Telecommunication Engineering Department,

Faculty of Engineering, King Mongkut's University of

Technology Thonburi (KMUTT), and also serves as

presidentof ECTI Association (2018-2019). He served as

editor of ECTI e-magazine during 2011-2015, associate

editor of ECTI-CIT Trans during 2011-2016, associate editor

of ECTI-EEC Trans during 2003-2010, associate editor of

ELEX (IEICE Trans) during 2008-2010, andchairman of

IEEE COMSOC Thailand during 2004-2007.

He has received B.Eng. in Applied Electronics from the University of Electro-communications,

Tokyo, Japan in 1985, M.Eng. in Electrical Engineering from Nippon Institute of Technology, Saitama,

Japan in 1987, and Ph.D.in Electrical Engineering from Keio University, Tokyo, Japan in 1991. His

research interests include computer vision, image processing, robot vision, signal processing, and

pattern recognition. He is a senior member of IEEE, and a member of IEICE, TESA, ECTI,AIAT,

APSIPA, TRS, and EEAAT.


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Monday, 21st December 2020, 13:40 - 14:30

Toward autonomous container-based task scheduling for efficient IoT

processing

Prof. Hidehiro Kanemitsu

Tokyo University of Technology

Abstract

Current information processing pardaigms handle IoT data, multimedia streams, large volume

file, and so on. Objectives of such information processing involeves data analysis, data format

transformation, and calcuration. In IoT systems, various kinds of data should be processed

efficiently in heterogeneous systems across regions to share information sharing, e.g., among smart

cities. As for the processing system, a virtualized environment such as cloud and container-based

ones have been adopted for utilize application processes among computatinal resources. Thus, one

of current and future issues in terms of various data processing models is how each "task" should be

processed across heterogeneous virtualized systems. In this presentation, I introduce our research

topics for container-based task allocation and scheduling schemes on multiple clouds. The topic

includes algorithms for chaining each container-based service function (SF) in order to process IoT

data efficiently.

Biography

Hidehiro Kanemitsu received his B.S. degreein Science from Waseda

University, Japan, andM.S. and Ph.D. degrees in Global Informationand

Telecommunication Studies from WasedaUniversity, Japan. His research

interests includeparallel and distributed computing, grids, peerto-peer

computing, and web service technology. He has published several

prestigious journals and proceedings in terms of distributed computing

area such as IEEE TPDS, JPDC, IEEE CLOUD, and IEEE ICWS. He is

currently a senior assistant professor at theSchool of Computer Science,

Tokyo Universityof Technology, Japan. He is a member of IEICE,IPSJ,

and IEEE.


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4 Program at a Glance

Monday, 21st December 2020

10:45 – 12:00 Regular Session 1: Smart Contents Protection

Chair: Su-Kyung Yoon (Jeonbuk National University, Korea)

Papers: RS1-1, RS1-2, RS1-3, RS1-4, RS1-5

12:00 – 13:15 Lunch Break

13:15 – 13:30 Pre-arrangement

Plenary Session:

Chair: Chayapol Kamyod (Mae Fah Luang University, Thailand)

Message from General Chair:

Taek-Geun HwangBo (Gachon University, Korea)

Keynote Speech: Toward autonomous container-based task

scheduling for efficient IoT processing

Invited Speaker: Prof. Hidehiro Kanemitsu

(Tokyo University of Technology, Japan)

Keynote Speech: Categorization and Measurement by using heat

information

Invited Speaker: Prof. Kosin Chamnongthai

(King Mongkut's University of Technology Thonburi,

Thailand)

13:30 – 13:40

13:40 – 14:30

14:30 – 15:30

15:30 – 15:45 Break

15:45 – 17:00 Special Session 1: Smart Multimedia Applications

Chair: Jeong-geun Kim (Yonsei University, Korea)

Papers: SS1-1, SS1-2, SS1-3, SS1-4, SS1-5

Special Session 2: Immersive Content Display

Chair: Sunghwa Lim (Namseoul University, Korea)

Papers: SS2-1, SS2-2, SS2-3, SS2-4, SS2-5

Regular Session 8: Artificial Intelligence for Embedded Systems

Chair: Youngmo Kim (Soongsil University, Korea)



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Tuesday, 22nd December 2020

10:45 – 12:00 Regular Session 2: Multimedia Contents & Systems

Chair: Seok Hee Oh (Gachon University, Korea)


Regular Session 5: High Performance Computing Systems

Chair: Yong Hwan Lee (Wonkwang University, Korea)


12:00 – 13:15 Lunch Break

13:15 – 14:30 Regular Session 3: Intelligent Signal and Image Processing 1

Chair: Youngseop Kim (Dankook University, Korea)


Regular Session 7: Immersive Display, Network & Contents

Chair: Jin Young Kim (Kwangwoon University, Korea)

Papers: RS7-1, RS7-2, RS7-3, RS7-4

14:30 – 14:45 Break

14:45 – 16:00 Regular Session 6: Intelligent Signal and Image Processing 2

Chair: Kyoungro Yoon (Konkuk University, Korea)


16:00 – 16:10 Break

16:10 – 17:00 Conference Closing and Award


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5 Technical Program

RS1 Regular Session: Smart Contents Protection

Monday, 21st December 2020, 10:45 – 12:00


RS1-1

Cached Transaction Executor for Distributed Computing of Single Ledger

Blockchain

EEECS204

YongJoon Joe, Seong-Bo Kim, Dong-Myong Shin (LSware Inc.)

RS1-2

An Original Video Detection Method Using Feature Information of

Immersive 360-Degree Video

EEECS228

Injae Yoo, Jaecheng Lee (Beyond Tech Inc.), Byeongchan Park, Youngmo Kim, Seok-

Yoon Kim (Soongsil University)

RS1-3

Metadata Structure of Usage History for Transparent Settlement and

Distribution of Theme, Background and Signal Music

EEECS229

Ulugbek Ruizive, Byeongchan Park, Youngmo Kim, Seok-Yoon Kim (Soongsil

University)

RS1-4

A Study on Usage Duplication Avoiding Method Using Blockchain in

Theme, Background and Signal Sound Sources

EEECS231

Seyoung Jang, Seok-Yoon Kim (Soongsil University)

RS1-5

A Study on Performance Enhancement of BI-LSTM Single-Text

Sentiment Model Using Bootstrap Method with Limitation in Number of

Tokens

EEECS232

Seunghyun Ji, Youngmo Kim, Seok-Yoon Kim (Soongsil University)

RS2 Regular Session: Multimedia Contents & Systems

Tuesday, 22nd December 2020, 10:45 – 12:00


RS2-1

Energy-efficient Heterogenous Multiple Wireless Interfaces for

Smartphones

EEECS239

Se Won Lee (Pukyong National University), Sung-Hwa Lim (Namseoul University)

RS2-2

Automatic Vending Device Capable of Ordering Products Through Voice

and Control Method Thereof

EEECS207

HaeKyung Chung (Konkuk University), JangHyok Ko (Shamyook University)

RS2-3

User Experience Study of Unmanned Order Payment Kiosk in Fast Food

Store

EEECS216

Seungmin Lee (Namseoul University)


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RS2-4 Apparatus and Method that Guides the Information of The Locker EEECS215

JangHyok Ko (Shamyook University), HaeKyung Chung (Konkuk University)

RS2-5 Finding Longest Path on a Task Graph for Smartphone Applications EEECS244

Se Won Lee (Pukyong National University), Sung-Hwa Lim (Namseoul University)

RS3 Regular Session: Intelligent Signal and Image Processing 1



RS3-1 Optimized Image Link of Audio Video Bridge (AVB) System EEECS208

Byoungman An, Youngseop Kim (Dankook University)

RS3-2 Vehicle Tracking based on Deep Learning EEECS218

Hyochang Ahn (Far East University), Yong-Hwan Lee (Wonkwang University)

RS3-3 Video-based Point Cloud Compression with Versatile Video Coding EEECS233

Daehyeok Kwon, Haechul Choi (Hanbat National University)

RS3-4

Enhancement of 3d Point Cloud Data Using Orthogonal Projection and

Super Resolution Network

EEECS248

Seonghwan Park, Seongbae Rhee, Kyuheon Kim, Hyukmin Kwon, Jeongil Seo (Kyung

Hee University)

RS3-5

Performance Analysis of Subword Tokenization Methods for Language

Modeling

EEECS241

Hosung Park, Hyunsoon Son, Gyujin Kim, Ji-Hwan Kim (Sogang University)

RS5 Regular Session: High Performance Computing Systems



RS5-1 Bank and buffer system design for low power L1 cache memory EEECS217

Bosung Jung, Junghoon Lee (Gyeongsang National University)

RS5-2 PCM Buffer Cache on PCM Hybrid Memory for IoT Devices EEECS210

Su-Kyung Yoon (Jeonbuk National University)

RS5-3 Data Management Techniques for Graph Processing EEECS211

Su-Kyung Yoon (Jeonbuk National University)

RS5-4

Implementation of KD-tree Builder for Real-time Ray and Sound Tracing

Applications

EEECS225


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Woonam Chung, Sukwon Choi, Woochan Park (Sejong University), Cheong-Ghil Kim

(Namseoul University)

RS5-5 A Design of Inverse Cosine Calculator for Sound Tracing Applications EEECS226

JinYoung Lee, Woochan Park (Sejong University), Cheong-Ghil Kim (Namseoul

University)




RS6-1 Evaluation on Single Image Reflection Removal EEECS219

Hyochang Ahn (Far East University), Yong-Hwan Lee (Wonkwang University)

RS6-2

Deep Learning Based Viewport Super Resolution by Using 2d Warping

Method for 360-Degree Video

EEECS249

Seongbae Rhee, Seonghwan Park, Kyuheon Kim (Kyung Hee University)

RS6-3 Subjective quality evaluation of point clouds compared to natural video EEECS234

Aram Baek, Haechul Choi (Hanbat National University)

RS6-4

Frequency-Tuned Spectrogram with Residual Convolutional Neural

Networks for Acoustic Scene Classification in Muti-Device Environment

EEECS242

Soonshin Seo, Changmin Kim, Donghyun Lee, Hosung Park, Hyunsoon Son, Gyujin

Kim, Ji-Hwan Kim (Sogang University)

RS6-5 Comparison of CNN and YOLO for Object Detection EEECS220

Yong-Hwan Lee (Wonkwang University), Youngseop Kim (Dankook University)

RS7 Regular Session: Immersive Display, Network & Contents



RS7-1 ANN-based Body Temperature Monitoring for Home Healthcare System EEECS252

Kyu-Nam Choi, Taeg-Keun Hwangbo (Gachon University)

RS7-2 Promoting of Online PBL For Collaborative Skills Enhancement EEECS250

Santichai Wicha, Panarumol Temdee (Mae Fah Luang University)

RS7-3 CIA And IoT Communication Models EEECS251

Chayapol Kamyod (Mae Fah Luang University)


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RS7-4

A Study of Proxy Based Information Crawling on Multi-Screen Digital

Signage

EEECS237

Heechan Yang, Daeseung Park, Sangwoon Lee, Cheong Ghil Kim (Namseoul

University), Chayapol Kamyode (Mae Fah Luang University)

RS8 Regular Session: Artificial Intelligence for Embedded Systems



RS8-1

Implementation of Contactless Vehicular Ambient Lighting Control

System Based on the Machine Learning Method

EEECS206

SangYub Lee, Youngchan Kim (Korea Electronics Technology Institute)

RS8-2

Development of KNN-based Haar face detection system using low-power

neuromorphic chip

EEECS212

YoungChan Kim, YeoWool Lee, Inpyo Cho, SangYub Lee (Korea Electronics

Technology Institute)

RS8-3

Uninserted Error Checking Technique Using RBF Tester for Low Power

Low Cost PCB Tester

EEECS213

InPyo Cho, YeoWool Lee, JaeKyu Lee, SangYub Lee (Korea Electronics Technology

Institute)

RS8-4

A Study on the Structure of Learning Image Dataset for Object

Recognition in Construction Sites based on Transfer Learning

EEECS214

Jaekyu Lee, Chulgoo Kim, InPyo Cho, Sangyub Lee (Korea Electronics Technology

Institute)

RS8-5

Development of a digital twin sensor platform for disaster monitoring and

management

EEECS221

Changsuk Yoon, Minsang Yu, Young-Han Kim, Hyun-Seok Ahn, Tae-Beom Lim

(Korea Electronics Technology Institute)

SS1 Special Session: Smart Multimedia Applications



SS1-1

A Contactless Personal Health Monitoring System Using Raspberry Pi

Based Smart Mirror

EEECS236

Jiwoong Han, Changhoon Kim, Daeseung Park, Sangwoon Lee, Cheong Ghil Kim

(Namseoul University)

SS1-2

Problem-Based Learning Model for Students Knowledge Acquisition of

Logical Design for Interactive Programming Course

EEECS240


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Waralak Chongdarakul, Khwunta Kirimasthong (Mae Fah Luang University)

SS1-3

An Assistive Technology for the Elderly Farmers: A Case Study of a

Cymbidium Orchid Caring System

EEECS245

Kesmanee Runjarean, Nattanicha Thammakhankhom, Warisara Luetan, Prasara

Jakkaew, Sirichai Hemrungrote (Mae Fah Luang University)

SS1-4

The Combined Model of Blended Learning with Flipped Classroom: A

New Learning Strategy for Covid-19 Pandemic Situation

EEECS246

Worasak Rueangsirarak, Punnarumol Temdee (Mae Fah Luang University)

SS1-5

Applying Problem-Based Learning with Direct Instruction Improve

Students Critical Thinking and Teamwork in Thai Undergraduates

EEECS247

Nilubon Kurubanjerdjit, Soontarin Nupap (Mae Fah Luang University)

SS2 Special Session: Immersive Content Display



SS2-1

DUET-Based Separation of Multiple User Signals for Digital Drone

Signage Systems

EEECS205

Isaac Sim, Young Ghyu Sun, Soo Hyun Kim, Donggu Lee, Jiyoung Lee, Jin Young Kim

(Kwangwoon University)

SS2-2 A Study on The Performance Evaluation of Webxr Device Api EEECS223

Daehyeon Lee, Munyoung Lee, Kye-Dong Jung, Soonchul Kwon (Kwangwoon

University)

SS2-3 A Study on Digital Signage Data Transmission System using RDS EEECS224

SangWoon Lee (Namseoul University)

SS2-4

A Study of Smart Contents Management System Using Machine

Learning for Digital Signage

EEECS235

Daeseung Park, Jiwoong Han, Sangwoon Lee, Cheong Ghil Kim (Namseoul

University)

SS2-5

System Modeling and Implementation of XR Environment -Focused on

VFX Production for TV Drama-

EEECS222

Jungwoon Park, Seokhee Oh (Gachon University)


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6 Abstracts

RS1 Regular Session: Smart Contents Protection



RS1-

1

Cached Transaction Executor for Distributed Computing of Single Ledger

Blockchain

EEECS204

YongJoon Joe LSware Inc.

Seong-Bo Kim LSware Inc.

Dong-Myong Shin LSware Inc.

Efficient distributed and concurrent computing for blockchain is a complex problem, especially when achieving

scalability with multiple nodes. We approach this problem by preprocessed computing plan by RWKS(Read/Write Key

Set information) pre-checking. This paper shows a value preloading design which utilizes RWKS; a by-product of the

distributed computing planning. Based on this feature, we could accelerate the transaction execution speed by relaxing

the I/O load.

RS1-2

An Original Video Detection Method Using Feature Information of

Immersive 360-Degree Video

EEECS228

Injae Yoo Beyond Tech Inc.

Jaecheng Lee Beyond Tech Inc.

Byeongchan Park Soongsil University

Youngmo Kim Soongsil University

Seok-Yoon Kim Soongsil University

As the immersive 360-degree videos are distributed, piracy activity is also increasing, causing copyright

infringement. Filtering technology to determine the illegal reproduction has been mainly researched and used mainly for

the 2D videos, and it is difficult to apply that technology to immersive 360-degree videos without modification, so a new

filtering technology for them is required. In this paper, we propose an original video detection method using feature

information to determine whether or not a immersive 360-degree video is illegally copied. The proposed method detects

the original video by extracting robust feature information such as size change, brightness change, resolution change, and

rotation change of the immersive 360-degree video, and comparing it with the immersive 360-degree video to which the

attack was applied.

RS1-3

Metadata Structure of Usage History for Transparent Settlement and

Distribution of Theme, Background and Signal Music

EEECS229

Ulugbek Ruizive Soongsil University

Byeongchan Park Soongsil University



It is difficult to transparently settle and distribute the theme, background and signal music, of which the monitoring

is difficult because it is usually used outside of common music. In addition, it is hard to grasp the exact usage history due


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to different rights management information among each related organizations. In this paper, we propose a metadata

structure to integrate different music rights management informations and to write usage history information on the

blockchain ledger in the form of smart contract, which can be used as the usage monitoring information for transparent

settlement and distribution of theme, background and signal music.

RS1-4

A Study on Usage Duplication Avoiding Method Using Blockchain in Theme,

Background and Signal Sound Sources

EEECS231

Seyoung Jang Soongsil University


The current process of collecting usage fees in theme, backgrounds and signal(TMS) sound sources other than

common music are mainly categorized into two types, flat-rate and usage-based system used according to the license

compensation method and usage permission types. However, the duplicated/conflicted usage information often causes

credibility issues, which makes the transparent settlement and distribution process of TMS sound sources difficult. To

improve the credibility of TMS sound source usage information, in this paper, we propose a method to prevent usage

duplication/conflict of sound sources using a blockchain technology that processes usage information.

RS1-5

A Study on Performance Enhancement of BI-LSTM Single-Text Sentiment

Model Using Bootstrap Method with Limitation in Number of Tokens

EEECS232

Seunghyun Ji Soongsil University



Since the performance of Bi-LSTM model for single-text sentiment analysis is affected by the volume of training

dataset and complexity of the model, the performance of prediction may be degraded if the size of the dataset is small or

the number of tokens gets bigger. To relieve this problem, this paper proposes a performance enhancement method that

uses bootstrap technique, token normalization and limitation in number of tokens. The experimental results of the

proposed method shows that it has led to 5% higher accuracy than the previous sentiment analysis method.

RS2 Regular Session: Multimedia Contents & Systems



RS2-1 Energy-efficient Heterogenous Multiple Wireless Interfaces for Smartphones EEECS239

Se Won Lee Pukyong National University

Sung-Hwa Lim Namseoul University

The wireless communication module is one of the devices that consume the most energy of a smart mobile terminal.

If we can implement an multi-channel multi-interface environment using these heterogeneous communication modules,

data transmission performance can be improved by increasing parallelism. Also, these heterogeneous modules have

different data rates, transmission ranges, and power consumption. In this paper, we propose a power efficient data

transmission method using heterogeneous communication networks.

RS2-2

Automatic Vending Device Capable of Ordering Products Through Voice and

Control Method Thereof

EEECS207

HaeKyung Chung Konkuk University


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JangHyok Ko Shamyook University

Disclosed is an automatic sales device capable of ordering products through voice and a control method thereof, and

the automatic sales device capable of ordering products through voice according to an embodiment of the present

application accommodates a plurality of products, and based on product selection information A product receiving unit

in communication with the product discharge port through which the selected product is discharged, a product information

display unit displaying the plurality of products so that the user can identify them, a voice receiving the user's voice input

and extracting the product selection information from the voice input It may include a recognition unit and a control unit

for controlling the product selected based on the product selection information to move to the product discharge port.

RS2-3

User Experience Study of Unmanned Order Payment Kiosk in Fast Food

Store

EEECS216

Seungmin Lee Namseoul University

Recently, domestic and foreign studies on the unmanned order payment system of the restaurant industry, which are

rapidly growing recently, are insufficient. Therefore, there is a lack of understanding of users' perception of unmanned

order settlement system. The purpose of this study is to investigate the effect of user experience factors of unmanned

order payment service of fast food restaurant on satisfaction The purpose of this study is to examine the relationship

between user's satisfaction and intention. Through this study, we can understand the psychology and behavior of users

who use unmanned order settlement service and prepare a strategic foundation that can be used in various industries.

RS2-4 Apparatus and Method that Guides the Information of The Locker EEECS215

JangHyok Ko Shamyook University

HaeKyung Chung Konkuk University

The goods storage application can acquire information about the size of the goods that the user wants to store in

advance, and obtain information on the usage status of the goods storage box (information on the presence or absence of

empty space, etc.). It is possible to effectively provide only information on a storage box having a slot that enables the

actual storage of goods (owned goods). In addition, it provides the function to reserve the slot of the inventory box in

advance, and can guide the exact location of the reserved inventory box, so that users can quickly find the reserved

inventory box without hesitation. In particular, by providing AR-based directions information (internal directions

information), it is possible to help you find the location of the storage box you want to visit faster and at a glance.This

service can provide service functions such as extended payment and reservation function. In addition, it can be easily

used not only for domestic users but also for overseas users, so you can expect tourism effects. For example, an item for

selecting a language, a sign-up window display item, and the like may be displayed on the main screen along with an

intuitive logo. Therefore, not only domestic users but also foreign users (foreign users) can simply subscribe and easily

receive the services provided. The application can determine the user's current location through a GPS sensor and provide

accurate information about the matching item storage box based on this. In addition, it is possible to provide a service

function that allows direct guidance of an optimal place to store items through destination search.

RS2-5 Finding Longest Path on a Task Graph for Smartphone Applications EEECS244

Se Won Lee Pukyong National University

Sung-Hwa Lim Namseoul University

In a smartphone application, a bunch of tasks should be executed in serial or in parallel with some dependency to

complete a mission. Therefore, the task group to be executed can be a directed acyclic graph (i.e., task graph). For real-

time applications, it is very important to find out the expected time to complete the given task graph to see whether the

task graph will finished within its deadline. In this paper, we studied a method to find out the longest path on a task graph

for real-time smartphone applications using PERT/CPM approach.


19




RS3-1 Optimized Image Link of Audio Video Bridge (AVB) System EEECS208

Byoungman An Dankook University

Youngseop Kim Dankook University

Recently, processing huge amount of video data in vehicle network has become a very important task. It is significant

not only for a transmission management but also, for reducing a latency between devices. In this paper, we propose a new

design and optimization method of Audio Video Bridge (AVB) technology. A proposal plays a significant role in reducing

the delay between a talker device and a listener device. The approach on realistic test cases showed that there was a delay

reduction about 52%. It is expected that the optimization method for in-vehicle environment can greatly shorten the time

period in the design and development process. It will greatly benefit the industry since analyzing the latency between

each function in a short period of time is very meaningful.

RS3-2 Vehicle Tracking based on Deep Learning EEECS218

Hyochang Ahn Far East University

Yong-Hwan Lee Wonkwang University

Since traffic jams and accidents are becoming a big social problem, vehicle detecting and tracking are useful to

provide important information such as identifying road traffic conditions. However, vehicle detecting and tracking based

on camera image are affected by environmental factors, such as camera installation and illumination. This paper proposes

a deep learning-based vehicle segmentation and tracking method to classify and track vehicles in a complex background.

Using YOLO model as deep learning, the proposed scheme is more effective and robust to track vehicles in various

environments.

RS3-3 Video-based Point Cloud Compression with Versatile Video Coding EEECS233

Daehyeok Kwon Hanbat National University

Haechul Choi Hanbat National University

A point cloud is a 3D data representation used in immersive media applications including virtual/augmented reality,

immersive telepresence, autonomous driving and cultural heritage archival. Recently, the Motion Picture Experts Group,

a international standard body, has released video-based point cloud compression (V-PCC) to represent and compress point

cloud data. The V-PCC converts the point cloud data from 3D to 2D and then the converted 2D data is coded by a legacy

video encoder. The refernce software of V-PCC, called Test Model category 2, emploies the High Efficiency Video Coding

(HEVC) standard as the video encoder. Recently, Versatiel Video Coding (VCC) standard is released by the MPEG, which

has better coding efficiency than HEVC. This paper introduce a V-PCC based coding method that replaces HEVC with

VVC to compress point cloud data higher. Some VVC coding tools are selectively turned on or off accoridng to their

coding performance for point cloud data. Experimental results show that the proposed scheme achieves average of 23.7%

BD-rate reduction in D1, 32.6% BD-rate reduction in D2, and 22.1% BD-rate reduction in luma component, respectively.

RS3-4

Enhancement of 3d Point Cloud Data Using Orthogonal Projection and Super

Resolution Network

EEECS248

Seonghwan Park Kyung Hee University

Seongbae Rhee Kyung Hee University


20

Kyuheon Kim Kyung Hee University

Hyukmin Kwon Kyung Hee University

Jeongil Seo Kyung Hee University

With the development of media technology, research to provide more immersive media is actively progressing.

Especially, the technology on improving image quality such as super resolution by using deep learning network is widely

researched. Also, 3D point cloud is one of the emerging immersive media contents, which represents 3D media using 3

dimensional coordinates with color information. In this paper, we propose a method of enhancing 3D point cloud data by

applying deep learning network to 3D point cloud data with orthogonal projection.

RS3-5

Performance Analysis of Subword Tokenization Methods for Language

Modeling

EEECS241

Hosung Park Sogang University

Hyunsoon Son Sogang University

Gyujin Kim Sogang University

Ji-Hwan Kim Sogang University

In this paper, unigram-based subword tokenization is applied to language models. Subword tokenization is an

effective way to avoid Out-of-Vocabulary (OOV) problems in speech recognition, natural language processing (NLP).

These language-related processings require a vocabulary generated from training data. However, limited vocabulary size

increases the amount of unknown words. The OOV problem is that the unknown words make language processing

inaccurate. Subword tokenization refers to dividing text into meaningful tokens. Subword tokenization assumes that a

word consists of multiple pieces of subword. This method makes rare words decomposed into subwords to avoid OOV

problems. It also allows language models to have a reasonable size of vocabulary. Unigram language model tokenization

shows superior performance among a variety of subword tokenization methods. This tokenization makes vocabulary by

using the probability of subword occurrence given by training corpus. Experimental results with Korean corpus of

KsponSpeech show that unigram language model-based subword tokenization leads to significant improvements on n-

gram based language modeling.

RS5 Regular Session: High Performance Computing Systems



RS5-1 Bank and buffer system design for low power L1 cache memory EEECS217

Bosung Jung Gyeongsang National University

Junghoon Lee Gyeongsang National University

Today, with the advent of the 4th industrial revolution, IoT (Internet of Things) systems are rapidly developing.

Accordingly, with the advent of various large-capacity applications, low-power and high-performance memory for

computing systems is being demanded. In this paper, we propose an effective structure to reduce the energy consumption

of the L1 cache memory, which occurs most frequently in the cache system. The proposed cache memory system is largely

composed of two parts, the L1 main cache memory and the buffer cache. The main cache memory is 2-banks, and each

bank consists of a 2-way association map. In the buffer cache operation, data is copied with the access algorithm proposed

in this paper when an access success occurs from the L1 main cache memory. According to our simulation, the proposed

L1 cache system can reduce the energy-delay product by around 55%, compared with 4-way set associative cache memory.


21

RS5-2 PCM Buffer Cache on PCM Hybrid Memory for IoT Devices EEECS210

Su-Kyung Yoon Jeonbuk National University

In this paper, we present a technique for using PCM as a buffer cache in DRAM/PCM hybrid memory for IoT devices.

In this system, a small amount of PCM is introduced as a write buffer cache to reduce system stability and power

consumption due to DRAM buffer usage. The proposed technique records data attributes for the data requested to be

written, and a write block is created by analyzing the association of data and grouping them. As results of experiments,

the proposed system can reduce the energy consumption by 7.5%. compared to conventional system.

RS5-3 Data Management Techniques for Graph Processing EEECS211

Su-Kyung Yoon Jeonbuk National University

Recently, the use of memory-intensive applications such as graph processing is increasing. Memory-intensive

applications require a large amount of main memory for processing. However, DRAM, which is used as a basic

component of main memory, has reached its scaling limit. In this paper, to solve this problem, we design a method of

prefetching data by predicting data to be requested in advance in PCM-based hybrid memory. According to the

experimental results, the proposed system reduces the execution time by 4.9%.

RS5-4

Implementation of KD-tree Builder for Real-time Ray and Sound Tracing

Applications

EEECS225

Woonam Chung Sejong University

Sukwon Choi Sejong University

Woochan Park Sejong University

Cheong-Ghil Kim Namseoul University

In order to support the dynamic scene rendering based on ray and sound tracing algorithms, an optimized data

structure called acceleration structure (AS), such as KD-tree structure, should be built for every frame at run-time. In this

paper, for the efficient implementation of the AS builder hardware, a novel KD-tree build algorithm with computational

complexity of Nlog(N) has been divided into software part and hardware part. In the software part, sorted information of

triangles is generated. In the hardware part, the KD-tree for each image frame is built with the sorted triangle information.

According to experimental results, the proposed hardware architecture could reduce the tree build latency by about

50%~150% compared to the software-only approach.

RS5-5 A Design of Inverse Cosine Calculator for Sound Tracing Applications EEECS226

JinYoung Lee Sejong University

Woochan Park Sejong University

Cheong-Ghil Kim Namseoul University

Sound tracing is a technology that generates sound by finding a sound propagation path from a sound source to a

listener and calculating it in real-time. These calculations have to deal with complex operations such as trigonometric

functions. In this paper, the inverse cosine function with a very small error value is implemented in hardware by

effectively constructing the table method. Since the sound tracing application field does not require relatively high

accuracy, a method that can obtain an approximation value within a reasonable allowable range with a small hardware

size was proposed.


22




RS6-1 Evaluation on Single Image Reflection Removal EEECS219

Hyochang Ahn Far East University


An undesired negative image has occurred in photographs taken across partial reflections such as glass windows and

electronic display. Efficient removing reflection given a single image is emerging in recent research on image processing.

This paper discusses and evaluates two published image reflection removal methods, and compares the performance of

the processing time and quality of those schemes with common datasets. As benchmarking tests are presented, and we

propose to modify one of the methods to reduce the run-time with small effects on similar image quality.

RS6-2

Deep Learning Based Viewport Super Resolution by Using 2d Warping

Method for 360-Degree Video

EEECS249

Seongbae Rhee Kyung Hee University

Seonghwan Park Kyung Hee University

Kyuheon Kim Kyung Hee University

Recently, 360-degree video has been increasingly used in monitoring systems. Since a 360-degree video requires a

considerably high transmission bandwidth, it has a limitation in providing a network based monitoring services. In order

to overcome this limitation, this paper proposes the method of transmitting a relatively lower-quality video and

reproducing it as a high-resolution video through deep learning Super Resolution(SR) network. Although many SR

networks have shown significant performance in a legacy 2D video, the application of SR to 360-degree video is limited

due to the radial distortion of the wide-angle lens. Therefore, in this paper, we propose the spatial transformation suitable

for SR network to overcome radial distortion.

RS6-3 Subjective quality evaluation of point clouds compared to natural video EEECS234

Aram Baek Hanbat National University

Haechul Choi Hanbat National University

Point clouds are continually evolving as a representative way of expressing 3D contents. In order to evaluate the

quality of these point clouds, various objective or subjective quality evaluation methods are being studied. In this paper,

a subjective quality evaluation was performed in comparison with natural video to compare the several quality of the

point clouds. As the experimental results, the measurement for each quality of the point clouds is compared and analyzed.

RS6-4

Frequency-Tuned Spectrogram with Residual Convolutional Neural

Networks for Acoustic Scene Classification in Multi-Device Environment

EEECS242

Soonshin Seo Sogang University

Changmin Kim Sogang University

Donghyun Lee Sogang University

Hosung Park Sogang University

Hyunsoon Son Sogang University

Gyujin Kim Sogang University


23

Ji-Hwan Kim Sogang University

In this paper, we proposed an acoustic scene classification system in a multi-device environment using frequency-

tuned spectrogram and residual convolutional neural networks. It aims to maximize the distance of training samples

between acoustic scene classes and to minimize the distance of training samples between multi-devices. The inter-class

and inter-device standard deviations on the frequency axis are calculated by using the training dataset. These statistics are

used to tune the log-mel spectrogram. Frequency-tuned spectrogram and the log-mel spectrogram are used as input

features of two-pathway residual convolutional neural networks. Our proposed system achieved an overall accuracy of

71.7% for the TAU Urban Acoustic Scenes 2020 Mobile dataset.

RS6-5 Comparison of CNN and YOLO for Object Detection EEECS220


Youngseop Kim Dankook University

Object detection has to play an important role in the field of comupter vision. Many kind of research have rapidly

increased along with applying neural network and its improved structures since 2012. There are representative object

detection algorithms, which are convolutional neural networks and YOLO. This paper presents two representative

methods, based on CNN and YOLO which solve the problem of CNN bounding box. We have compared the performance

of two methods in terms of accuracy, speed and cost. Compared with the latest advanced solution, YOLO v3 achieves a

good trade-off between speed and accuracy.

RS7 Regular Session: Immersive Display, Network & Contents



RS7-1 ANN-based Body Temperature Monitoring for Home Healthcare System EEECS252

Kyu-Nam Choi Gachon University

Taeg-Keun Hwangbo Gachon University

One of the most important indicators in home healthcare systems is body temperature. Many diseases are the first to

cause changes in human body temperature. Therefore, continuous observation of body temperature is the starting point

of home healthcare in the fastest way to detect disease. Conventional methods of temperature measurement are

inconvenient for the elderly and for those living alone. To solve the above problem, a temperature measurement system

using a smart mirror system equipped with a camera, a contactless temperature camera and a laser distance sensor is

proposed. By detecting the face based on deep learning, automatically tracking the target of measurement, and using the

temperature camera through the ANN-based adaptive distance compensation, accurate temperature measurement is

possible in real time. The results of the proposed system show very good performance. The experiment was carried out

for a week in a general home, and as a result of comparing the axillary body temperature measured with a mercury

thermometer as a reference standard, the accuracy was 92%, showing high diagnostic accuracy.

RS7-2 Promoting of Online PBL For Collaborative Skills Enhancement EEECS250

Santichai Wicha Mae Fah Luang University

Panarumol Temdee Mae Fah Luang University

This paper investigates a Problem based learning (PBL) model which focuses on how to improve the collaborative

skills construction in online classroom. The empirical study conducted with Business intelligence class from School of

Information technology, Mae Fah Luang University, Thailand. The results of this study indicates that online PBL as a


24

learning environment that supported self-directed and collaborative learning skills during they worked on online PBL

program projects.

RS7-3 CIA And IoT Communication Models EEECS251

Chayapol Kamyod Mae Fah Luang University

Agriculture is a major contributor to the Thailand economy. Accordingly, young, and smart farmers in Thailand have

gained more interest and applied various IoT solutions and applications to enhance their production’s quality and quantity.

Nevertheless, general IoT solutions that are available in the market cannot provide full functionalities to serve different

types of agricultural processes. Therefore, various IoT solutions from different vendors were applied. Some farmers used

customized IoT solutions for their specific production processes such as fertilization and irrigation. Accordingly, various

IoT deployments can create complexity and vulnerability. Therefore, security of the system should also be considered at

this beginning employment state to reduce possible risks when scaling the production processes or system. This paper

examines security of IoT communication models by using the commonly used framework called the Cybersecurity Cube

which represents three principles of information security or CIA triad. The study represents various vulnerabilities of

different IoT communication models.

RS7-4

A Study of Proxy Based Information Crawling on Multi-Screen Digital

Signage

EEECS237

Heechan Yang Namseoul University

Daeseung Park Namseoul University

Sangwoon Lee Namseoul University

Cheong Ghil Kim Namseoul University

Chayapol Kamyod Mae Fah Luang University

With the advancement of network and multimedia technologies, digital signage via the Internet or Cloud has been a

dramatic transformation. As one of emerging commercial advertisement channel, it is important to have the functions of

collecting the data generated by sensors or other edge nodes and crawling the user request for a corresponding documents

in the distributed systems. In this paper, we survey the structure of the recent network-based digital signage platform and

introduce a new proxy based information crawing system architecture for multi-screen digital signage.

RS8 Regular Session: Artificial Intelligence for Embedded Systems



RS8-1

Implementation of Contactless Vehicular Ambient Lighting Control System

Based on the Machine Learning Method

EEECS206

Sangyub Lee Korea Electronics Technology Institute

Youngchan Kim Korea Electronics Technology Institute

This paper is about the implementation of a system that controls ambient lighting, which is an emotional lighting in

a vehicle. Ambient lighting is an in-vehicle lighting assistant that provides a function to change the color to proper the

user's emotions in car. Existing ambient lighting control allows the user to access the central control display or head unit

system and activate the corresponding function within the system. In this paper, we propose a method of implementing

an in-vehicle emotional lighting control system based on a machine learning algorithm that can easily recognize the user's

intention using a simple gesture without the user's direct device manipulation using a magnetic field sensor module.


25

RS8-2

Development of KNN-based Haar face detection system using low-power

neuromorphic chip

EEECS212

YoungChan Kim Korea Electronics Technology Institute

YeoWool Lee Korea Electronics Technology Institute

Inpyo Cho Korea Electronics Technology Institute

SangYub Lee Korea Electronics Technology Institute

In this paper, we propose a facial recognition system that can be used in a low-power environment such as an

embedded system by using a neuromorphic chip equipped with a KNN matching function. The Haar cascade classifier

method proposed by Paul Viola and Michael Jonse extracting the Haar features of an image to detect face has a lot of

real-time computation, so it is difficult to find a face in a video feed with a high frame rate in a low-clock MCU. Therefore,

in this study, we introduce a system that improves traditional Haar cascade classifier method by vectorizing the human

facial Haar features on a neuromorphic chip connected to an embedded environment, and calculating them at once. In

addition, this system can be applied to fields requiring face recognition (for example, driver's front gaze system) and

shows the possibility of realization through prototype examples.

RS8-3

Uninserted Error Checking Technique Using RBF Tester for Low Power Low

Cost PCB Tester

EEECS213

InPyo Cho Korea Electronics Technology Institute

YeoWool Lee Korea Electronics Technology Institute

JaeKyu Lee Korea Electronics Technology Institute

SangYub Lee Korea Electronics Technology Institute

The PCB inspector is a device that checks whether the PCB is correctly manufactured at the end of the SMT line. In

this paper, we propose an uninterpolated error inspection technique that can be used for low-power, low-cost PCB

inspection machines. In high-end equipment, high-performance lighting, cameras, and processors can be used to perform

PCB inspections, but in low-end equipment, sufficient lighting, cameras, and processors cannot be used, so an appropriate

algorithm and accelerator must be used. Using the algorithm and RBF accelerator, an image of 10,000 pixels is inspected,

and even Arduino class hardware can perform the inspection in 30 milliseconds on average.

RS8-4

A Study on the Structure of Learning Image Dataset for Object Recognition

in Construction Sites based on Transfer Learning

EEECS214

Jaekyu Lee Korea Electronics Technology Institute

Chulgoo Kim Korea Electronics Technology Institute

InPyo Cho Korea Electronics Technology Institute

Sangyub Lee Korea Electronics Technology Institute

In this paper, we conducted a study on the structure of the learning image data set for object recognition in

construction sites based on transfer learning. In particular, we explored the structure of image data sets such as VOC, MS

COCO and KITTI, and we conducted a study on the composition of the data file for describing image information. The

construction site images that we collected were converted to the KITTI data format, and we created a model to recognize

objects in the construction site using the transformed KITTI image data set format based on transfer learning.

RS8-5

Development of a digital twin sensor platform for disaster monitoring and

management

EEECS221

Changsuk Yoon Korea Electronics Technology Institute

Minsang Yu Korea Electronics Technology Institute


26

Young-Han Kim Korea Electronics Technology Institute

Hyun-Seok Ahn Korea Electronics Technology Institute

Tae-Beom Lim Korea Electronics Technology Institute

Recently, as IoT systems have been widely adopted in various industrial fields, continuous and immediate data

collection in the field has become possible. This enables more accurate analysis and prediction that reflects reality

compared to existing theoretical simulations. Now, it is possible to effectively monitor and predict the various disasters

that occur continuously and frequently. The disaster monitoring and management system is expected to have great

effectiveness in economic and social aspects. However, sufficient research has not been conducted on the digital twin

system structure and management software framework for effective application. In this paper, the sensor processing

platform constructing the digital twin infrastructure for effective disaster monitoring and management is presented.

SS1 Special Session: Smart Multimedia Applications



SS1-1

A Contactless Personal Health Monitoring System Using Raspberry Pi Based

Smart Mirror

EEECS236

Jiwoong Han Namseoul University

Changhoon Kim Namseoul University




The internet of things (IoT) is rapidly expanding its application range with the commercialization of 5G service. In

this paper, we propose a Raspberry Pi based samrt mirror for a contactless personal health monitoring, which may make

our lives more convenient by adding IoT functions to our daily used item of mirrors. The smart mirror to be implemented

will use a technology of measuring bio-signal in a contactless manner using Lepton thermal imaging sensor, remote

photoplethysmography (rPPG) with regular color video camera, and so on. The general features of the smart mirror will

be provided on the basis of open source MagicMirror including news, weather, calendar, and multimedia service.

SS1-2

Problem-Based Learning Model for Students Knowledge Acquisition of

Logical Design for Interactive Programming Course

EEECS240

Waralak Chongdarakul Mae Fah Luang University

Khwunta Kirimasthong Mae Fah Luang University

Developing the learning approach supportive to the students in the field of digital technology implementation for

business study has been challenged. This research employed Problem Oriented Project Based Learning (POPBL) principle

to construct the multidisciplinary learning model to promote knowledge acquisition of the first-year undergraduate

students in DTBI curriculum. The student performance evaluation is designed for project works and problem-solving

assessments of which students can eventually accomplish outcome of the real business initiation. The assessment result

presents the evaluation score and useful feedback for improvement.

SS1-3

An Assistive Technology for the Elderly Farmers: A Case Study of a

Cymbidium Orchid Caring System

EEECS245

Kesmanee Runjarean Mae Fah Luang University


27

Nattanicha Thammakhankhom Mae Fah Luang University

Warisara Luetan Mae Fah Luang University

Prasara Jakkaew Mae Fah Luang Universityty

Sirichai Hemrungrote Mae Fah Luang University

Most elderly orchid farmers in Thailand currently rely on a traditional farming process, which requires intensive

care with a lot of time spending. To improve efficiency, many pieces of the literature suggest using wireless sensor

networks as an assistive technology in controlling the farming's environment, such as temperature, humidity, soil moisture.

However, the deployment of such a system with its initially high investment has not gained much popularity among those

elderly farmers. Unlike other previous works in this paper, we mainly focus on designing a smart care system with an

easy-to-use user interface design. We aim to investigate the significance of a user-friendly application and the efficiency

improvement obtained from adopting wireless sensor technology over a traditional approach.

SS1-4

The Combined Model of Blended Learning with Flipped Classroom: A New

Learning Strategy for Covid-19 Pandemic Situation

EEECS246

Worasak Rueangsirarak Mae Fah Luang University

Punnarumol Temdee Mae Fah Luang University

In Thailand, blended learning was introduced to be the strategy for teaching management during the COVID-19

pandemic situation. Therefore, the proposed combined model of blended learning with flipped classroom was designed

to help the lecturers to organize the online teaching for their students. The idea is to focus on two event activities, one is

the self-learning through the LMS and another is the wrapped up lecture by the facilitator. Additionally, the class is

conducted with both synchronous and asynchronous mode. The case study is conducted with the Information Technology

students who enrolled in the Cloud Computing course. As the results, the proposed teaching model can enhance the

students’ knowledge retention more than those of the traditional classroom with the t-Test analysis show its significance

of P-value at 0.014<0.05.

SS1-5

Applying Problem-Based Learning with Direct Instruction Improve Students

Critical Thinking and Teamwork in Thai Undergraduates

EEECS247

Nilubon Kurubanjerdjit Mae Fah Luang University

Soontarin Nupap Mae Fah Luang University

This study aimed to assess the effectiveness of 1) critical thinking and 2) collaborative learning skills of Thai

undergraduate students in a sample of Mae Fah Luang University in Chiang Rai, Thailand. The case study focused on 42

Digital Technology for Business Innovation (DTBI) major in school of Information Technology students who enrolled in

“Digital Business Initiation in Practices” course. We endeavoured to apply problem-based learning strategy in order to

stimulate critical thinking and collaborative learning to work as a team of the students. The results revealed the application

of PBL strategy improved the critical thinking of students significantly as well as the high performance on their works

and their roles playing within their team in a collaborative learning environment.

SS2 Special Session: Immersive Content Display



SS2-1

DUET-Based Separation of Multiple User Signals for Digital Drone Signage

Systems

EEECS205

Isaac Sim Kwangwoon University


28

Young Ghyu Sun Kwangwoon University

Soo Hyun Kim Kwangwoon University

Donggu Lee Kwangwoon University

Jiyoung Lee Kwangwoon University

Jin Young Kim Kwangwoon University

In this letter, we study a scenario based on degenerate unmixing estimation technique (DUET) that separates original

signals from mixture of FHSS signals with two antennas. We have shown that the assumptions for separating mixed

signals in DUET can be applied to drone based digital signage recognition signals and proposed the DUET-based

separation scheme (DBSS) to classify the mixed recognition drone signals by extracting the delay and attenuation

components of the mixture signal through the likelihood function and the short-term Fourier transform (STFT). In

addition, we propose an iterative algorithm for signal separation with the conventional DUET scheme. Numerical results

showed that the proposed algorithm is more separation-efficient compared to baseline schemes. DBSS can separate all

signals within about 0.56 seconds when there are fewer than nine signage signals.

SS2-2 A Study on The Performance Evaluation of Webxr Device Api EEECS223

Daehyeon Lee Kwangwoon University

Munyoung Lee Kwangwoon University

Kye-Dong Jung Kwangwoon University

Soonchul Kwon Kwangwoon University

Recently, with the development of various virtual environment technologies, they are fused with reality or are

defining and researching a new reality. In particular, research on extended reality is being actively conducted in the web

environment. However, the current released tentative version has poor stability. Therefore, in this paper, a study was

conducted on the performance evaluation of WebXR Device API. For the experiment, a real model, the same 3D model,

and a ground environment for the match rate comparison were made, and the match rate between the real model and the

3D model was compared. As a result of the experiment, 92.6%, 88.9%, and 88.8% of the results were confirmed from the

front, left, and right.

SS2-3 A Study on Digital Signage Data Transmission System using RDS EEECS224

SangWoon Lee Namseoul University

In this paper, we propose a transmission system configuration method using FM radio RDS (Radio Data System) as

a method for transmitting data for expression to digital signage. FM RDS transmits data using an FM broadcasting

network that is used worldwide, and has a feature that can reliably transmit data even in natural disasters such as

earthquakes and typhoons. When data is transmitted to a digital signage using this characteristic, it is possible to transmit

important messages including a disaster warning even in a situation in which the data channel over the communication

network transmitted through the digital signage is paralyzed.

In recent years, we have been experiencing an explosive expansion of artificial intelligence (AI) technology in a

number of applications. Furthermore, we do not doubt that the impact of AI technology on our future world will exceed

SS2-4

A Study of Smart Contents Management System Using Machine Learning

for Digital Signage

EEECS235


Jiwoong Han Namseoul University




29

our imagination. In this work, we introduce a system architecture of data driven smart digital signage using machine

learning. Variety of datasets may come not only in real time from sensors around the digital display but also from the

contensts management system. The proposed the digital signage contents management system using machine learning is

expected to allow different content to be scheduled auttonomously and displayed at different times according to the

situation. As a result, this improvements eventually make smart decisions to make better services for customers.

In this study, the concept of Cross Reality (eXtended Reality) was used to build a virtual production system that

could be applied to superior imaging and to produce special effects images used in actual TV dramas. In the process, the

advantages of real-time rendering were actively revealed, enabling directors and actors to check the video results in real-

time, and ensuring that camera matching in the second half of the work can be carried out smoothly. This study is

meaningful as a success story to confirm that introducing a virtual production system helps to maintain the highest quality

of the video while meeting the production schedule.

SS2-5

System Modeling and Implementation of XR Environment -Focused on

VFX Production for TV Drama-

EEECS222

Jungwoon Park Gachon University

Seokhee Oh Gachon University


30

7 Author Index

A

－ Ahn, Hyochang: RS3-2, RS6-1

－ Ahn, Hyun-Seok: RS8-5

－ An, Byoungman: RS3-1

B

－ Baek, Aram: RS6-3

C

－ Cho, InPyo: RS8-2, RS8-3, RS8-4

－ Choi, Haechul: RS3-3, RS6-3

－ Choi, Kyu-Nam: RS7-1

－ Choi, Sukwon: RS5-4

－ Chongdarakul, Waralak: SS1-2

－ Chung, HaeKyung: RS2-2, RS2-4

－ Chung, Woonam: RS5-4

H

－ Han, Jiwoong: SS1-1, SS2-4

－ Hemrungrote, Sirichai: SS1-3

－ Hwangbo, Taeg-Keun: RS7-1

J

－ Jakkaew, Prasara: SS1-3

－ Jang, Seyoung: RS1-4

－ Ji, Seunghyun: RS1-5

－ Joe, YongJoon: RS1-1

－ Jung, Bosung: RS5-1

K

－ Kamyod, Chayapol: RS7-3, RS7-4

－ Kim, Changhoon: SS1-1

－ Kim, Changmin: RS6-4

－ Kim, Cheong-Ghil:

RS5-4, RS5-5, RS7-4, SS1-1, SS2-4

－ Kim, Chulgoo: RS8-4

－ Kim, Gyujin: RS3-5, RS6-4

－ Kim, Ji-Hwan: RS3-5, RS6-4

－ Kim, Jin Young: SS2-1

－ Kim, Kyuheon: RS3-4, RS6-2

－ Kim, Seok-Yoon:

RS1-2, RS1-3, RS1-4, RS1-5

－ Kim, Seong-Bo: RS1-1

－ Kim, Soo Hyun: SS2-1

－ Kim, YoungChan: RS8-1, RS8-2

－ Kim, Young-Han: RS8-5

－ Kim, Youngmo: RS1-2, RS1-3, RS1-5

－ Kim, Youngseop: RS3-1, RS6-5

－ Kirimasthong, Khwunta: SS1-2

－ Ko, JangHyok: RS 2-2, RS2-4

－ Kurubanjerdjit, Nilubon: SS1-5

－ Kwon, Daehyeok: RS3-3

－ Kwon, Hyukmin: RS3-4

－ Kwon, Soonchul: SS2-2

L

－ Lee, Daehyeon: SS2-2

－ Lee, Donggu: SS2-1

－ Lee, Donghyun: RS6-4

－ Lee, Jaecheng: RS1-2

－ Lee, Jaekyu: RS8-3, RS8-4

－ Lee, JinYoung: RS5-5

－ Lee, Jiyoung: SS2-1

－ Lee, Junghoon: RS5-1

－ Lee, SangWoon:

RS7-4, SS2-3, SS1-1, SS2-4

－ Lee, SangYub:

RS8-1, RS8-2, RS8-3, RS8-4

－ Lee, Se Won: RS2-1, RS2-5

－ Lee, Seungmin: RS2-3

－ Lee, YeoWool: RS8-2, RS8-3

－ Lee, Yong-Hwan: RS3-2, RS6-1, RS6-5

－ Lim, Sung-Hwa: RS2-1, RS2-5

－ Lim, Tae-Beom: RS8-5

－ Luetan, Warisara: SS1-3

N

－ Nupap, Soontarin: SS1-5

O

－ Oh, Seokhee: SS2-5

P


31

－ Park, Byeongchan: RS1-2, RS1-3

－ Park, Daeseung: RS7-4, SS1-1, SS2-4

－ Park, Hosung: RS3-5, RS6-4

－ Park, Jungwoon: SS2-5

－ Park, Seonghwan: RS3-4, RS6-2

－ Park, Woochan: RS5-4, RS5-5

R

－ Rhee, Seongbae: RS3-4, RS6-2

－ Rueangsirarak, Worasak: SS1-4

－ Ruizive, Ulugbek: RS1-3

－ Runjarean, Kesmanee: SS1-3

S

－ Seo, Jeongil: RS3-4

－ Seo, Soonshin: RS6-4

－ Shin, Dong-Myong: RS1-1

－ Sim, Isaac: SS2-1

－ Son, Hyunsoon: RS3-5, RS6-4

－ Sun, Young Ghyu: SS2-1

T

－ Temdee, Punnarumol: SS1-4

－ Thammakhankhom, Nattanicha: SS1-3

－ Temdee, Panarumol: RS7-2

W

－ Wicha, Santichai: RS7-2

Y

－ Yang, Heechan: RS7-4

－ Yoo, Injae: RS1-2

－ Yoon, Changsuk: RS8-5

－ Yoon, Su-Kyung: RS5-2, RS5-3

－ Yu, Minsang: RS8-5

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