OSRVM의 형상 매개변수에 따른 승용 차량의 공력성능 해석

한현욱(Hyun Wook Han),박현호(Hyun Ho Park),김문상(Moon Sang Kim),하종백(Jong Paek Ha),김용년(Yong Nyun Kim) 한국자동차공학회 2011 한국자동차공학회 부문종합 학술대회 Vol.2011 No.5

This study investigates the effects of OSRVM configurations such as mounting locations, housing heights, stalk heights, shrouding depths, stalk depths, and housing lengths, etc. on the aerodynamic performance of the passenger car. In order to validate the flow solver, FLUENT which is a very well-known commercial code, the flow field around an Ahmed body was analyzed numerically and compared with the experimental data. The predicted aerodynamic performance shows a good agreement with the experimental data. In the present paper, only three parameters, which are the mounting locations, stalk heights, and housing heights are studied and presented.

차량 성능 개선을 위한 OSRVM의 최적 형상 연구

한현욱(Hyun Wook Han),박현호(Hyun Ho Park),김문상(Moon Sang Kim),하종백(Jong Paek Ha),김용년(Yong Nyun Kim) 한국자동차공학회 2011 한국자동차공학회 학술대회 및 전시회 Vol.2011 No.11

This study investigates the effects of OSRVM configurations such as bezel, stalk lengths, and head planview shape, etc. on the aerodynamic performance of the passenger car. In order to validate the flow solver, FLUENT which is a very well-known commercial code, the flow field around an Ahmed Body was analyzed numerically and compared with the experimental data. The predicted aerodynamic performance shows a good agreement with the experimental data. In the present paper, two parameters, which are the bezel and stalk length, are considered and presented. The other parameters will be studied in the near future.

OSRVM의 형상 및 장착 위치가 차량의 공력성능에 미치는 영향

한현욱(Hyun Wook Han),박현호(Hyun Ho Park),김문상(Moon Sang Kim),하종백(Jong Paek Ha),김용년(Yong Nyun Kim) 한국자동차공학회 2013 한국 자동차공학회논문집 Vol.21 No.3

This study investigates the effects of OSRVM mounting location and its configurations such as stalk height and housing height on the aerodynamic performance of the passenger car. In order to validate the flow solver, FLUENT which is very well known commercial code, the flow field around an Ahmed Body was analyzed numerically and compared with the experimental data. The predicted aerodynamic performance and flow patterns around a car show good agreements with the experimental data. Mounting location and stalk height should be designed while OSRVM is mounted on the car to evaluate the aerodynamic performance precisely. Housing height, however, may be designed independent of the car because the aerodynamic interference between housing height and car configuration is negligible.

OSRVM의 형상 및 장착 위치에 따른 승용 차량의 공력성능 해석

한현욱(Hyun Wook Han),김지웅(Ji Woong Kim),김문상(Moon Sang Kim),하종백(Jong Paek Ha),김용년(Yong Nyun Kim) 한국자동차공학회 2010 한국자동차공학회 학술대회 및 전시회 Vol.2010 No.11

This paper investigates the effects of OSRVM configurations such as mounting locations, housing heights, stalk heights, etc. on the aerodynamic performance of a passenger car. In the present paper, only one parameter, which is the mounting locations, is studied and presented. The other parameters will be studied in the near future. The OSRVM is mounted at the locations of -10㎜, -5㎜, 10㎜, 20㎜, 30㎜, 40㎜, and 50㎜ from the original location of the OSRVM. FLUENT, which is a very well-known commercial code, is used to analyze the aerodynamic performance of the passenger car.

공력소음 해석절차 구축 및 OSRVM 외형변경에 따른 공력소음해석

박현호(Hyun Ho Park),한현욱(Hyun Wook Han),김문상(Moon Sang Kim),하종백(Jong Paek Ha),김용년(Yong Nyun Kim) 한국자동차공학회 2011 한국자동차공학회 부문종합 학술대회 Vol.2011 No.5

The transient flow field around an OSRVM is analyzed using the FLUENT and the sound radiation is predicted using the Ffowkes Williams and Hawkings analogy to analyze the wind noise around an OSRVM. Numerical results are compared with the available experimental data to validate the flow solver accuracy and the established analysis procedure. Five design key parameters of OSRVM, which are housing heights, stalk heights, shrouding depths, stalk depths, and housing lengths, are selected and parametric studies are performed numerically to figure out the effects of geometric shapes on the wind noise. In the present paper, however, only one parameter, which is the stalk heights, is studied and presented. The other parameters will be studied in the near future.

헬스케어 빅데이터 유통을 위한 블록체인기술 활성화 방안

유형원,이은솔,고우균,한호성,한현욱,Yu, Hyeong Won,Lee, Eunsol,Kho, Wookyun,Han, Ho-seong,Han, Hyun Wook 한국빅데이터학회 2018 한국빅데이터학회 학회지 Vol.3 No.1

미래 의학의 핵심은 개인을 중심으로 한 정밀의료(Precision Medicine)의 실현이다. 이것이 가능하기 위해서는 헬스케어 데이터를 언제 어디서나 열람, 관리 및 유통 할 수 있는 개방형 생태계를 갖추어야 한다. 하지만, 헬스케어 데이터는 민감한 개인정보를 다루기 때문에 상당한 수준의 신뢰성과 보안성이 동시에 요구된다. 이를 해결하기 위한 방안으로 최근 의료계에서도 블록체인 기술에 주목하고 있다. 블록체인 기술은 거래정보를 중앙 서버에 저장 및 관리하는 기존의 정보통신 인프라와는 달리 유통되는 데이터를 네트워크에 참여하는 모든 사용자가 분산 및 관리하는 방식의 분산 운영망 이다. 본 연구에서는 블록체인 기술을 이용해 헬스케어 데이터 유통 실증에 필요한 기술적 및 법리적 제반 사항, 코렌(KOREN SDI)망 기반 헬스케어 빅데이터 유통 실증 연구의 소개 및 헬스케어 분야에서 블록체인 기술을 활성화하기 위한 정책적 전략에 대해 논의한다. At the core of future medicine is the realization of Precision Medicine centered on individuals. For this, we need to have an open ecosystem that can view, manage and distribute healthcare data anytime, anywhere. However, since healthcare data deals with sensitive personal information, a significant level of reliability and security are required at the same time. In order to solve this problem, the healthcare industry is paying attention to the blockchain technology. Unlike the existing information communication infrastructure, which stores and manages transaction information in a central server, the block chain technology is a distributed operating network in which a data is distributed and managed by all users participating in the network. In this study, we not only discuss the technical and legal aspects necessary for demonstration of healthcare data distribution using blockchain technology but also introduce KOREN SDI Network-based Healthcare Big Data Distribution Demonstration Study. In addition, we discuss policy strategies for activating blockchain technology in healthcare.

의료기기 네트워크 트래픽 보안 관련 머신러닝 알고리즘 성능 비교

고승형,박준호,왕다운,강은석,한현욱,Seung Hyoung Ko,Joon Ho Park,Da Woon Wang,Eun Seok Kang,Hyun Wook Han 한국IT서비스학회 2023 한국IT서비스학회지 Vol.22 No.5

As the computerization of hospitals becomes more advanced, security issues regarding data generated from various medical devices within hospitals are gradually increasing. For example, because hospital data contains a variety of personal information, attempts to attack it have been continuously made. In order to safely protect data from external attacks, each hospital has formed an internal team to continuously monitor whether the computer network is safely protected. However, there are limits to how humans can monitor attacks that occur on networks within hospitals in real time. Recently, artificial intelligence models have shown excellent performance in detecting outliers. In this paper, an experiment was conducted to verify how well an artificial intelligence model classifies normal and abnormal data in network traffic data generated from medical devices. There are several models used for outlier detection, but among them, Random Forest and Tabnet were used. Tabnet is a deep learning algorithm related to receive and classify structured data. Two algorithms were trained using open traffic network data, and the classification accuracy of the model was measured using test data. As a result, the random forest algorithm showed a classification accuracy of 93%, and Tapnet showed a classification accuracy of 99%. Therefore, it is expected that most outliers that may occur in a hospital network can be detected using an excellent algorithm such as Tabnet.

딥러닝 기반 병원네트워크 이상행위 탐지 시스템에 관한 연구

김강현(Kim Kang Hyun),정성수(Jung Sung Soo),한현욱(Han Hyun Wook) 한국통신학회 2022 한국통신학회 학술대회논문집 Vol.2022 No.11

인공지능 기반 정보보호핵심원천기술 연구

이상준 ( Sang-jun Lee ),민경일 ( Min Kyung Il ),남상도 ( Nam Sang Do ),임준성 ( Lim Joon Sung ),한근희 ( Keunhee Han ),한현욱 ( Hyun Wook Han ) (사)한국빅데이터학회 2021 한국빅데이터학회 학회지 Vol.6 No.2

최근, 예상치 못하고 지능적인 보다 고도화된 사이버 의료 위협 공격이 증가하고 있는 추세이다. 하지만 다양한 패턴의 사이버 의료 위협 공격 대응에 있어, 물리적인 차단과 의료기기 교체와 같은 규칙 기반 보안방법론은 인력 부족, 고가의 비용 부담 등의 한계를 지닌다. 이를 해결하기 위한 방안으로 최근 의료계에서도 인공지능 기술에 주목하고 있다. 인공지능 기술은 기존의 규칙 기반의 보안 프로그램과는 달리 과거의 이상행태를 스스로 학습하여 보안 위협 감지 및 예측을 가능케 하는 기술이다. 본 연구에서는 의료기관 통합의료정보시스템 내 의료정보 데이터를 수집 및 학습하여 AI 기반 네트워킹 행동 적응형 정보 플랫폼 개발 연구 방법론에 대한 소개를 포함한다. 이를 통해 규칙 기반의 보안 프로그램의 기술적 제반사항 소개와 제약 사항 대비 의료정보분야에서의 인공지능 기술을 활성화하기 위한 전략에 대해 논의한다. Recently, unexpected and more advanced cyber medical treat attacks are on the rise. However, in responding to various patterns of cyber medical threat attack, rule-based security methodologies such as physical blocking and replacement of medical devices have the limitations such as lack of the man-power and high cost. As a way to solve the problems, the medical community is also paying attention to artificial intelligence technology that enables security threat detection and prediction by self-learning the past abnormal behaviors. In this study, there has collecting and learning the medical information data from integrated Medical-Information-Systems of the medical center and introduce the research methodology which is to develop the AI-based Net-Working Behavior Adaptive Information data. By doing this study, we will introduce all technological matters of rule-based security programs and discuss strategies to activate artificial intelligence technology in the medical information business with the various restrictions.

데이터통합과 메타분석을 위한 그래프 통계량 추출과 검증

심성률 ( Sung Ryul Shim ),임요환 ( Yo Hwan Lim ),홍명희 ( Myunghee Hong ),송규선 ( Gyuseon Song ),한현욱 ( Hyun Wook Han ) (사)한국빅데이터학회 2021 한국빅데이터학회 학회지 Vol.6 No.2

본 연구의 목적은 개별연구들이 정확한 통계량을 제시하지 않고 그래프로만 나타내었을 경우 그래프로부터 통계량을 추출해내는 구체적인 방법을 기술한 것으로서 데이터통합과 정량적합성을 위한 메타분석을 가능하게 한다. 특히 메타분석(meta-analysis)은 체계적·객관적으로 대상문헌을 선택한 후 개별 연구들의 결과를 계량화하여 이를 통합된 효과크기(effect size)로 제시함으로써 근거중심의학(evidence based medicine)를 위한 올바른 의사결정을 할 수 있게 하는 중요한 분석도구이다. 데이터통합과 메타분석을 위해서 그래프로부터 정확한 통계수치를 추출하는 전산도구인 Adobe Acrobat Reader 와 Python기반의 JupyterLab 소프트웨어의 소개와 적용에 대한 주요사항을 알아보았다. 사용된 예제자료는 선행연구를 통해서 통계결과가 검증되어졌고 ClinicalTrials.gov에서 원자료 확보가 가능한 것을 사용하였다. 원자료와 각 전산 도구들의 측정값을 각각 메타분석한 결과 통계적으로 유의한 차이는 없었다. 또한 연구자들간의 측정 신뢰도를 확인하였으며 높은 일치도를 나타내었다. 만약 그래프로부터 통게수치를 추출해야만 할 경우 연구의 완결성 유지를 위해서 전통적 사용 방법들보다는 전산 도구를 이용한 측정이 권고된다. The objective of this study was to describe specific approaches for data extraction from graph when statistical information is not directly reported in some articles, enabling data intergration and meta-analysis for quantitative data synthesis. Particularly, meta-analysis is an important analysis tool that allows the right decision making for evidence-based medicine by systematically and objectively selects target literature, quantifies the results of individual studies, and provides the overall effect size. For data integration and meta-analysis, we investigated the strength points about the introduction and application of Adobe Acrobet Reader and Python-based Jupiter Lab software, a computer tool that extracts accurate statistical figures from graphs. We used as an example data that was statistically verified throught an previous studies and the original data could be obtained from ClinicalTrials.gov. As a result of meta-analysis of the original data and the extraction values of each computer software, there was no statistically significant difference between the extraction methods. In addition, the intra-rater reliability of between researchers was confirmed and the consistency was high. Therefore, In terms of maintaining the integrity of statistical information, measurement using a computational tool is recommended rather than the classically used methods.