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).

크롤링을 이용한 자동매칭 게임톡 웹 서비스

제목 : 크롤링을 이용한 자동매칭 게임톡 웹 서비스
저자 : 반영태, 한상욱, 이도경, 윤건일, 이화민
게재지 : 2019년 한국정보처리학회 추계학술발표대회 논문집
교신저자 : 이화민
장소 : 제주도, 제주대학교
DOI : https://doi.org/10.3745/PKIPS.y2019m10a.1169

초록
최근 많은 이용자들이 음성채팅을 이용하여 게임을 즐긴다. 하지만 많은 사람들이 게임 내에서 지원하는 음성 채팅을 사용하지 않고 별도의 음성 프로그램을 사용하고 있다. 현재 게임 내 음성채팅과 외부 음성채팅 모두 편의 기능이 많이 부족하며, 가장 큰 문제점으로는 사용자 본인이 직접 음성 채팅에 참여하는 유저를 구해야 한다는 것이다. 본 논문에서는 이러한 불편한 상황을 없애기 위하여 자동으로 음성 채팅이 가능한 사람을 모집하여 좀 더 편안한 게임 환경을 제공할 수 있는 음성 채팅 웹 서비스를 개발 하였다. 웹 크롤링 기술을 이용하여 외부 커뮤니티등의 구인 글을 크롤링 하여 설정한 조건과 구인 조건이 일치하면 사이트 사용자 뿐 만 아니라 미사용자 간의 매칭도 빠르게 지원 하도록 개발하였다.

Acknowledgments
이 성과는 2017년도 정부(과학기술정보통신부)의 재원으로 한국연구재단의 지원을 받아 수행된 연구임(NRF-2017R1A2B4010570)
본 연구는 과학기술정보통신부 및 정보통신기술진흥센터의 대학ICT연구센터육성 지원사업의 연구결과로 수행되었음(IITP-2019-2015-0-00403)

Docker-based Cloud System for Computer Programming Labs

Title : Docker-based Cloud System for Computer Programming Labs
Published in : The 14th International Conference on Computer Science & Education (ICCSE 2019)
Author : Minsu Chae, Sangwook Han, HwaMin Lee
Corresponding author : HwaMin Lee
Location : The Oshawa Campus of Durham College and University of Ontario Institute of Technology(UOIT) Durham College, Toronto, Canada
URL : https://ieeexplore.ieee.org/document/8845470

Abstract
Recently, the importance of software education has been emphasized all over the world. In Korea, software education has been introduced for elementary schools that have applied for software education since 2015, and software education has been adopted as a regular subject in all elementary schools since 2017. As the importance of the software industry grows, interest in coding education is increasing. In Korea, students must complete 16 hours of instruction in elementary school and 34 hours in middle school from 2019. In Korea, however, there are not enough professional teachers who majored in software, and many schools have poor laboratory environments. For successful software coding education, a basic hands-on environment should be supported. It is also difficult for the teacher to analyze and score all students’ program sources during class. In this paper, we propose a computer labs management system that can be executed within seconds by using images already generated by Docker for software education at school. And we implemented a programming practice management system using Docker. Our system provides the ability for teachers to automatically identify and score students’ source code as they conduct coding training.

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 ITRC (Information Technology Research Center) support program (IITP-2019-2015-0-00403) supervised by the IITP(Institute for Information & communications Technology Promotion).

Arrhythmia Classification System Using Deep Neural Network

Title : Arrhythmia Classification System Using Deep Neural Network
Published in : The 11th International Conference on Ubiquitous and Future Networks(ICUFN 2019)
Author : EunKwang Jeon, Sangwook Han, MinSu Chae, HwaMin Lee
Corresponding author : HwaMin Lee
Location : SHERATON ZAGREB Hotel, Zagreb, Croatia

Abstract
Previous studies on arrhythmia were used to diagnose the abnormally fast, slow, or irregular heart rhythm through ECG (Electrocardiogram), which is one of the biological signals. ECG has the form of P-QRS-T wave, and many studies have been done to extract the features of QRS-complex and R-R interval. However, in the conventional method, the P-QRS-T wave must be accurately detected, and the feature value is extracted through the P-QRS-T wave. If an error occurs in the peak detection or feature extraction process, the accuracy becomes very low. Therefore, in this paper, we implement a system that can perform PVC (Premature Ventricular Contraction) and PAC (Premature Atrial Contraction) classification by using P-QRS-T peak value without feature extraction process using deep neural network. The parameters were updated for PVC and PAC classification in the learning process using P-QRS-T peak without feature value. As a result of the performance evaluation, we could confirm higher accuracy than the previous studies and omit the process of feature extraction, and the time required for the preprocessing process to construct the input data set is relatively reduced.

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) supervised by the IITP(Institute for Information & communications Technology Planning & Evaluation) and Basic Science Research Program through the National Research Foundation of Korea (NRF-2017R1A2B4010570).

Energy efficient VM scheduling for big data processing in cloud computing environments

Title : Energy efficient VM scheduling for big data processing in cloud computing environments
Journal : Journal of Ambient Intelligence and Humanized Computing
Authors : SangWook Han, SeDong Min, HwaMin Lee
Corresponding author : HwaMin Lee
DOI : https://doi.org/10.1007/s12652-019-01361-8

Abstract
Recently, the cloud computing platform has come to be widely used to analyze large amounts of data collected in real-time from SNS or IoT sensors. In order to analyze big data, a large number of VMs are created in the cloud server, and that many PMs are needed to handle it. When VMs are allocated to PMs in cloud computing, each VM is allocated by a VM scheduling algorithm. However, existing scheduling algorithms waste substantial PM resources due to the low density of VM. This waste of resources dramatically reduces the energy efficiency of the entire cloud server. Therefore, minimizing idle PMs by increasing the density of VMs allocated to PMs is critical for VM scheduling. In this paper, a VM relocation method is suggested to improve the energy efficiency by increasing the density of VMs using the Knapsack algorithm. In addition, it is possible through the proposed method to achieve efficient VM relocation in a short period by improving the Knapsack algorithm. Therefore, we proposed the effective resource management method of cloud cluster for big data analysis.

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 and Future Planning (NRF-2017R1A2B4010570) and by the Soonchunhyang University Research Fund.

불안장애 환자들을 위한 스마트밴드

제목 : 불안장애 환자들을 위한 스마트밴드
저자 : 한상욱, 최다빈, 이화민
게재지 : 2019년 한국정보처리학회 춘계학술발표대회 논문집
교신저자 : 이화민
장소 : 서울, 숭실대학교
DOI : https://doi.org/10.3745/PKIPS.y2019m05a.735

초록
본 연구에서는 불안장애를 가진 사람들이 겪는 불안한 상황들을 수치화하여 보호자와 불안해하는 본인에게 불안 상황을 해소할 수 있도록 하여 일상생활에 도움을 주고자 한다. 이를 관리 할 수 있도록 아두이노(Arduino) 센서를 활용하여 심박수 데이터와 체내의 전기 전도도 데이터를 수집할 수 있다. 수집한 데이터들은 애플리케이션 DB에 저장되어 캘린더 형식의 UI 화면에서 저장된 데이터들을 날짜마다 확인할 수 있으며 특정 수치 이상 증가 시에 저장된 번호로 SMS알림을 주어 현재 사용자의 상황을 알려 줄 수 있다.

Acknowledgments
본 연구는 과학기술정보통신부 및 정보통신기술진흥센터의 대학ICT연구센터육성 지원사업의 연구결과로 수행되었음 (IITP-2019-2014-1-00720).

눈 깜빡임 수 검출을 이용한 안구 관리 프로그램

제목 : 눈 깜빡임 수 검출을 이용한 안구 관리 프로그램
저자 : 한상욱, 원예지, 이화민
게재지 : 2019년 한국정보처리학회 춘계학술발표대회 논문집
장소 : 서울, 숭실대학교
교신저자 : 이화민
DOI : https://doi.org/10.3745/PKIPS.y2019m05a.693

초록
IT 기술은 끊임없는 발전을 거듭하고 있으며 현 인류는 기계와 더불어 살고 있다. Desktop, 스마트폰, 노트북 및 태블릿PC는 물론이고, 스마트 워치와 같은 ‘웨어러블 디바이스(Wearable Device)’의 등장으로 기계 속 세상에 그들과 함께 살고 있다하여도 과언이 아니다. 단연 잦은 기기 사용으로 인해 가장 영향을 크게 받는 인간의 신체 부위는 ‘눈’이다. 휴대용 기기(Portable Device)는 휴대에 용이해야 한다는 특징 때문에 그 크기가 점차 작아지고 있다. 따라서 작은 기기에 부착된 화면 역시 크기가 감소하였다. 장시간 작은 화면을 집중하여 보게 되면 눈의 피로가 금방 쌓이게 된다. 이로 인해 안구 건조 증 및 시력 저하 발생률이 증가하게 되는데, 영상처리 기술을 이용하여 안구의 깜박임을 감지하고 일정 수치 이하로 깜박임 횟수가 미달될 경우에 안구 운동을 권장하는 프로그램을 개발 하였다.

Acknowledgments
“본 연구는 과학기술정보통신부 및 정보통신기술진흥센터의 대학ICT연구센터육성 지원사업의 연구결과로 수행되었음” (IITP-2019-2014-1-00720)

Development of Cloud Based Air Pollution Information System Using Visualization

Title : Development of Cloud Based Air Pollution Information System Using Visualization
Journal : Computers, Materials & Continua
Authors : SangWook Han, JungYeon Seo, Dae-Young Kim, SeokHoon Kim, HwaMin Lee
Corresponding author : HwaMin Lee
DOI : https://doi.org/10.32604/cmc.2019.06071

Abstract
Air pollution caused by fine dust is a big problem all over the world and fine dust has a fatal impact on human health. But there are too few fine dust measuring stations and the installation cost of fine dust measuring station is very expensive. In this paper, we propose Cloud-based air pollution information system using R. To measure fine dust, we have developed an inexpensive measuring device and studied the technique to accurately measure the concentration of fine dust at the user’s location. And we have developed the smartphone application to provide air pollution information. In our system, we provide collected data based analytical results through effective data modeling. Our system provides information on fine dust value and action tips through the air pollution information application. And it supports visualization on the map using the statistical program R. The user can check the fine dust statistics map and cope with fine dust accordingly.

Acknowledgments
This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science and ICT (NRF-2017R1A2B4010570) and by Soonchunhyang Research Fund.

Serverless Framework for Efficient Resource Management in Docker Environment

Title : Serverless Framework for Efficient Resource Management in Docker Environment
Published in : The 10th International Conference on Computer Science and its Applications (CSA 2018)
Author : Sangwook Han , Minsu Chae , HwaMin Lee
Corresponding author : HwaMin Lee
Location : Double Tree by Hilton Hotel, Kuala Lumpur, Malaysia

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).