스마트 시티를 위한 Docker 기반의 모바일 엣지 컴퓨팅 프레임워크 설계

제목 : 스마트 시티를 위한 Docker 기반의 모바일 엣지 컴퓨팅 프레임워크 설계
저자 : 채민수, 한상욱, 윤건일, 조유진, 김영민, 송찬영, 이화민
게재지 : 2020년 한국인터넷정보학회 추계학술발표대회 논문집
장소 : 여수, 여수엑스포컨벤션센터
교신저자 : 이화민

초록
스마트 신호등과 같은 다양한 IoT 기기들로부터 대량의 데이터를 실시간으로 수집하는 경우 트래픽 부하와 집중된 트래픽으로 인한 레이턴시 저하가 발생한다. 그러나 기존 코어 클라우드의 경우 클라이언트에서 클라우드 서버가 있는 IDC까지의 물리적인 레이턴시 한계가 존재한다. 레이턴시를 최소화하기 위하여 Docker 기반의 모바일 엣지 컴퓨팅 프레임워크를 설계하였다.

Acknowledgments
본 연구는 과학기술정보통신부 및 정보통신기획평가원의 대학ICT연구센터육성지원사업의 연구결과로 수행되었음 (IITP-2020-2015-0-00403)
이 논문은 2019년도 정부(과학기술정보통신부)의 재원으로 한국연구재단 -현장맞춤형 이공계 인재양성지원사업의 지원을 받아 수행된 연구임(No. 2019H1D8A1105622).

Outdoor Particulate Matter Correlation Analysis and Prediction Based Deep Learning in the Korea

Title : Outdoor Particulate Matter Correlation Analysis and Prediction Based Deep Learning in the Korea
Journal : Electronics
Authors : Minsu Chae, Sangwook Han, HwaMin Lee
Corresponding author : HwaMin Lee
DOI : https://doi.org/10.3390/electronics9071146

Abstract
Particulate matter (PM) has become a problem worldwide, with many deleterious health effects such as worsened asthma, affected lungs, and various toxin-induced cancers. The International Agency for Research on Cancer (IARC) under the World Health Organization (WHO) has designated PM as a group 1 carcinogen. Although Korea Environment Corporation forecasts the status of outdoor PM four times a day, whichever is higher among PM10 and PM2.5. Korea Environment Corporation forecasts for the stages of PM. It remains difficult to predict the value of PM when going out. We correlate air quality and solar terms, address format, and weather data, and PM in the Korea. We analyzed the correlation between address format, air quality data, and weather data, and PM. We evaluated performance according to the sequence length and batch size and found the best outcome with a sequence length of 7 days, and a batch size of 96. We performed PM prediction using the Long Short-Term Recurrent Unit (LSTM), the Convolutional Neural Network (CNN), and the Gated Recurrent Unit (GRU) models. The CNN model suffered the limitation of only predicting from the training data, not from the test data. The LSTM and GRU models generated similar prediction results. We confirmed that the LSTM model has higher accuracy than the other two models.

Acknowledgments
This research supported by the MSIT (Ministry of Science and ICT), Korea, under the ITRC (Information Technology Research Center) support program (IITP-2019-2015-0-00403) supervised by the IITP (Institute for Information & communications Technology Planning & Evaluation) and by Soonchunhyang Research Fund.

생징후 데이터를 이용한 딥러닝 기반의 심정지 예측

제목 : 생징후 데이터를 이용한 딥러닝 기반의 심정지 예측
저자 : 채민수, 윤건일, 박찬영, 조유진, 이화민
게재지 : 2020년 한국인터넷정보학회 춘계학술발표대회 논문집
장소 : 제주도, 오션스위츠 제주호텔
교신저자 : 이화민

초록
병원에는 다양한 원인으로 입원하는 환자들이 있다. 심정지의 초기 발견 및 초기대응이 중요하다. 본 논문에서는 순천향대학교 천안병원의 2016년부터 2019년까지의 병동 환자들을 대상으로 심정지 예측에 대한 연구를 진행하였다. 딥 러닝 학습 시 측정시간, 나이, 성별, DBP, SBP, 맥박, 호흡, 체온, 심정지 여부를 1시간 단위로 레코드를 만들어 72개의 레코드 단위로 학습하였다. LSTM 모델을 적용하여 심정지 예측를 수행하였다. 수행결과 정확도는 약 99.9%, MAE는 0.00006517576735498417, RMSE는 0.003397121177224215 이다.

Acknowledgments
이 논문은 과학기술정보통신부의 재원으로 한국연구재단 바이오․의료기술개발사업의 지원을 받아 수행된 연구임(No. NRF-2019M3E5D1A02069073).
본 연구는 순천향대학교 학술연구비 지원으로 수행하였습니다.

CNN and LSTM models for predicting particulate matter in the Republic of Korea

Title : CNN and LSTM models for predicting particulate matter in the Republic of Korea
Published in : The 8th International Conference on Information, System and Convergence Applications International Symposium on Innovation in Information Technology and Application 2020 (ICISCA 2020)
Author : Minsu Chae, Sangwook Han, HwaMin Lee
Corresponding author : HwaMin Lee
Location : Ton Duc Thang University, Ho Chi Minh, Vietnam and Online

Abstract
Recently, fine dust has become a problem all over the world. Many countries set regulations for PM10 and PM2.5. Because fine dust adversely affects human health, it is important to alert PM10 and PM2.5 in each city. Predictions for PM10 and PM2.5 are required to alert. We propose a hybrid model of the CNN(Convolutional Neural Network) model and the LSTM(Long Short-Term Memory) model to predict the PM10 and PM2.5 in the Republic of Korea. In addition, we evaluate the performance of the CNN model, the LSTM model, and the proposed hybrid model. As a result of the performance evaluation, the proposed hybrid model has high accuracy.

Acknowledgments
This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT & Future Planning (NRF-2017R1A2B4010570).

A performance comparison of linux containers and virtual machines using Docker and KVM

Title : A performance comparison of linux containers and virtual machines using Docker and KVM
Journal : Cluster Computing
Authors : MinSu Chae, HwaMin Lee, Kiyeol Lee
Corresponding author : HwaMin Lee
DOI : https://doi.org/10.1007/s10586-017-1511-2

Abstract
Virtualization is a foundational element of cloud computing. Since cloud computing is slower than a native system, this study analyzes ways to improve performance. We compared the performance of Docker and Kernel-based virtual machine (KVM). KVM uses full virtualization, including ×86 hardware virtualization extensions. Docker is a solution provided by isolation in userspace instead of creating a virtual machine. The performance of KVM and Docker was compared in three ways. These comparisons show that Docker is faster than KVM.

Acknowledgments
This work was supported by the National Research Foundation of Korea (NRF) Grant funded by the Korea government (Ministry of Science and ICT) (No. NRF-2017R1A2B4010570) and the Soonchunhyang University Research Fund.

Design of middleware to support auto-scaling in Docker-based multi host environment

Title : Design of middleware to support auto-scaling in Docker-based multi host environment
Published in : The 14th KIPS International Conference on Ubiquitous Information Technologies and Applications (CUTE 2019)
Author : Minsu Chae, Sangwook Han, HwaMin Lee
Corresponding author : HwaMin Lee
Location : University of Macau, Macau, China

Abstract
With the spread of smart devices, the use of big data, and the proliferation of the Internet of Things, virtualization technology for cloud servers have become important worldwide. Also, research has been conducted to efficiently manage the resources of hosts in VMs. Container-based virtualization has less performance degradation than VMs because there is no emulation for the operating system. Using the Docker API is slow to measure. In this paper, we implement the resource measurement module of Job nodes and design middleware that supports auto-scaling in auto-scaling module and Docker-based multi-host environment.

Acknowledgments
This research supported by the MSIT(Ministry of Science and ICT), Korea, under the ITRC(Information Technology Research Center) support program(IITP-2019-2014-1-00720 & IITP-2019-2015-0-00403) supervised by the IITP(Institute for Information & communications Technology Planning & Evaluation).

A Design of Cardiac Arrest Early Warning System in Hospital

Title : A Design of Cardiac Arrest Early Warning System in Hospital
Published in : The 3rd International Conference on Interdisciplinary Research on Computer Science, Psychology, and Education (ICICPE’ 2019)
Author : SangWook Han, MinSu Chae, Min Hong, HwaMin Lee
Corresponding author : HwaMin Lee
Location : Vinoasis Phu Quoc Hotel, Phu Qoc, Vietnam

Abstract
Recently, increasing heart failure patients due to the increase in elderly patients, high probability for these patients, the arrhythmia. The number of cardiac arrests in hospitals is also increasing, and mortality rates are more than twice as high as those transferred from general wards to the intensive care unit through the emergency room or other routes. Existing patient monitoring methods in hospitals are measured using 24-hour Holter monitoring. This method requires carrying the device and measuring up to 48 hours. Also, the patient’s activities are very uncomfortable because of the communication line. Currently, many hospitals use the Modified Early Warning Score (MEWS) as a standard for early detection of deterioration in general ward patients. However, the prediction rate is very low and there is little help. Many people are working hard to detect heart attacks early because computerized systems vary from hospital to hospital, it is difficult to apply the developed system to various hospital environments. This study discusses the factors and methods necessary to solve these problems.

Acknowledgments
This research was supported by MSIT(Ministry of Science and ICT), Korea, under the ITRC(Information Technology Research Center) support program(IITP-2019-2014-1-00720) supervised by the IITP(Institute for Information & communications Technology Planning & Evaluation) and the Bio & Medical Technology Development Program of the National Research Foundation (NRF)(No.NRF-2019M3E5D1A02069073).

Serverless Framework for Efficient Resource Management in Docker Environment

Title : Serverless Framework for Efficient Resource Management in Docker Environment
Journal : Lecture Notes in Electrical Engineering book
Authors : Sangwook Han, Minsu Chae, HwaMin Lee
Corresponding author : HwaMin Lee
DOI : https://doi.org/10.1007/978-981-13-9341-9_32

Abstract
APIs provided by the Docker is executed through the container engine. Thus, it is a reality that the speed of creation and deletion of containers or requests for information is very slow. The load is even worse when many containers sending API requests at once. In this paper, we propose a method to apply module related to resource management in a container to reduce the load on API request generated in serverless environment. And we propose a new framework that manages resources of several containers or multiple Docker serves.

Acknowledgments
This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT & Future Planning (NRF-2017R1A2B4010570) and the Ministry of Science and ICT, Korea, under the ITRC (Information Technology Research Center) support program (IITP-2017-2015-0-00403) supervised by the IITP (Institute for Information & communications Technology Promotion).

PROGRAMMING PRACTICE SYSTEM AND METHOD

발명의 명칭
(EN) PROGRAMMING PRACTICE SYSTEM AND METHOD
(FR) SYSTÈME ET PROCÉDÉ DE PRATIQUE DE PROGRAMMATION
(KO) 프로그래밍 실습 시스템 및 방법
출원번호 : PCT/KR2019/014559
출원일자 : 2019년 10월 31일
출원국가 : 국제
발명자
이화민 LEE, Hwa-Min
채민수 CHAE, Min-Su

특허권자
순천향대학교 산학협력단
SOONCHUNHYANG UNIVERSITY INDUSTRY ACADEMY COOPERATION FOUNDATION

지정국 : AE, AG, AL, AM, AO, AT, AU, AZ, BA, BB, BG, BH, BN, BR, BW, BY, BZ, CA, CH, CL, CN, CO, CR, CU, CZ, DE, DJ, DK, DM, DO, DZ, EC, EE, EG, ES, FI, GB, GD, GE, GH, GM, GT, HN, HR, HU, ID, IL, IN, IR, IS, JO, JP, KE, KG, KH, KN, KP, KW, KZ, LA, LC, LK, LR, LS, LU, LY, MA, MD, ME, MG, MK, MN, MW, MX, MY, MZ, NA, NG, NI, NO, NZ, OM, PA, PE, PG, PH, PL, PT, QA, RO, RS, RU, RW, SA, SC, SD, SE, SG, SK, SL, SM, ST, SV, SY, TH, TJ, TM, TN, TR, TT, TZ, UA, UG, US, UZ, VC, VN, ZA, ZM, ZW
아프리카지역 지식재산기구(ARIPO) (BW, GH, GM, KE, LR, LS, MW, MZ, NA, RW, SD, SL, ST, SZ, TZ, UG, ZM, ZW)
유라시아 특허청(EAPO) (AM, AZ, BY, KG, KZ, RU, TJ, TM)
유럽 특허청(EPO) (AL, AT, BE, BG, CH, CY, CZ, DE, DK, EE, ES, FI, FR, GB, GR, HR, HU, IE, IS, IT, LT, LU, LV, MC, MK, MT, NL, NO, PL, PT, RO, RS, SE, SI, SK, SM, TR)
아프리카 지식재산권기구(OAPI) (BF, BJ, CF, CG, CI, CM, GA, GN, GQ, GW, KM, ML, MR, NE, SN, TD, TG)

요약서
(EN)
Disclosed is a programming practice system and method. A programming practice system according to one aspect of the present invention comprises: a client device including one or more computing devices and transmitting a program source file or a compile request signal input from a learner or teacher; a web server connected to the client device through a network; and a docker server connected to the web server through the network, generating a development environment in advance as an image, and generating a container on the basis of the image.
(FR)
La présente invention concerne un système et un procédé de pratique de programmation. Un système de pratique de programmation selon un aspect de la présente invention comprend : un dispositif de client comprenant un ou plusieurs dispositifs informatiques et transmettant un fichier source de programme ou un signal de demande de compilation, entré à partir d’un élève ou d’un enseignant ; un serveur web connecté au dispositif de client à travers un réseau ; et un serveur de menu fixe, connecté au serveur web à travers le réseau, générant un environnement de développement à l’avance sous la forme d’une image et générant un contenant en fonction de l’image.
(KO)
본 발명은 프로그래밍 실습 시스템 및 방법을 개시한다. 본 발명의 일 측면에 따른 프로그래밍 실습 시스템은, 하나 이상의 컴퓨팅 디바이스를 포함하며, 학습자 또는 교사로부터 입력되는 프로그램 소스 파일 또는 컴파일 요청 신호를 전송하는 클라이언트 장치; 상기 클라이언트 장치와 네트워크를 통해 접속되는 웹 서버; 및 상기 웹 서버와 네트워크를 통해 접속되며, 개발 환경을 이미지로 미리 생성하고, 상기 이미지를 바탕으로 컨테이너를 생성하는 도커 서버;를 포함한다.

연구사사
이 발명을 지원한 국가연구개발사업
과제고유번호 20141007200051001
부처명 과학기술정보통신부
연구관리전문기관 정보통신기술진흥센터(IITP)
연구사업명 대학ICT연구센터육성지원사업
연구과제명 웰니스 삶을 위한 WellTEC 코칭 서비스 및 콘텐츠 개발
기 여 율 1/2
주관기관 순천향대학교
연구기간 2014.06.01 ~ 2018.12.31

이 발명을 지원한 국가연구개발사업
과제고유번호 20150004030041001
부처명 과학기술정보통신부
연구관리전문기관 정보통신기술진흥센터(IITP)
연구사업명 대학ICT연구센터육성지원사업
연구과제명 IoT보안기술연구
기 여 율 1/2
주관기관 순천향대학교 산학협력단
연구기간 2015.06.01 ~ 2018.12.31