• Journal of Digital Convergence
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• v.15 no.5
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• pp.161-172
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• 2017

The purpose of this research is to take a look at what are research autonomy's factors of the government-supported research institutes with a new angle and how these factors influence on organizational effectiveness at the same time. ultimately, this research will suggest what government should guarantee and support researcher of the government-supported research institutes. In the groundwork, this research divides the level of research autonomy individual and organizational level, and divides the type of research autonomy intrinsic and extrinsic autonomy and also organizational commitment, and measure job satisfaction for organizational effectiveness. consequently, intrinsic autonomy which is associated with 'selection of research project', 'freely and lively traffic in ideas', 'choice of research methodology', 'utilization of research's result' is much more important than extrinsic autonomy for researchers to improve organizational effectiveness.

• Journal of Korean Society of Transportation
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• v.35 no.4
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• pp.332-347
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• 2017

Analysis of the interaction between the automated vehicles and manual vehicles is very important in analyzing the performance of automated cooperative driving environments. In particular, the automated vehicle platooning can affect the driving behavior of adjacent manual vehicles. The purpose of this study is to analyze the lane change behavior of the manual vehicles in automated vehicle platonning environment and to conduct the experiment and questionnaire surveys in three stages. In the first stage, a video questionnaire survey was conducted, and responsive behaviors of manual vehicles were investigated. In second stage, the driving simulator experiments were conducted to investigate the lane change behaviors of in automated vehicle platonning environments. To analyze the lane change behavior of the manual vehicles, lane change durations and acceleration noise, which are indicators of traffic flow stability, were used. The driving behavior of manual vehicles were compared across different market penetration rates (MPR) of automated vehicles and human factors. Lastly, NASA-TLX (NASA Task Load Index) was used to evaluate the workload of the manual vehicle drivers. As a result of the analysis, it was identified that manual vehicle drivers had psychological burdens while driving in automated vehicle platonning environments. Lane change durations were longer when the MPR of the automated vehicles increased, and acceleration noise were increased in the case of 30-40 years old or female drivers. The results from this study can be used as a fundamental for more realistic traffic simulations reflecting the interaction between the automated vehicles and manual vehicles. It is also expected to effectively support the establishment of valuable transportation management strategy in automated vehicle environments.

• Clinical and Experimental Pediatrics
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• v.46 no.6
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• pp.585-590
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• 2003

Purpose : This study is designed to determine the prevalence of cardiovascular autonomic neuropathy and its relationship to risk factors in adolescents with diabetes mellitus(DM). Methods : Ninety-two diabetic patients(80 with type 1 DM and 12 with type 2 DM), ranging from eight to 26 years of age, were studied for cardiovascular autonomic function, and the relationship to age, duration of diabetes, glycated hemoglobin(HbA1c), urinary albumin excretion, and the presence of diabetic retinopathy and abnormal nerve conduction velocities(NCV) were analysed. Autonomic function was assessed by measuring heart rate variation during valsalva manoeuvre, deep breathing and standing from a lying position(30 : 15 ratio), and postural hypotension. Results : Among patients with type 1 DM, 22.5% had early, 8.7% had definite, and 1.3% had severe autonomic dysfunction, and among patients with type 2 DM, 16.7% had early, 8.3% had definite, and 8.3% had severe autonomic dysfunction. On logistic regression analysis including both type 1 and type 2 diabetic patients, the age of the patient(OR=1.133(1.003-1.279), P<0.05) and duration of diabetes(OR=1.148(1.009-1.307), P<0.05) significantly predicted cardiovascular autonomic dysfunction while HbA1c, blood pressure, urinary albumin excretion, and presence of diabetic retinopathy and abnormal NCV did not. The valsalva ratio was borderline or abnormal in 31.5% of patients, the heart rate variation on deep breathing in 41.3%, the 30 : 15 ratio in 14.1%, and postural hypotension in 9.8% of patients. The valsalva ratio and the heart rate variation on deep breathing significantly predicted cardiovascular autonomic dysfunction, but the 30 : 15 ratio and postural hypotension did not. Conclusion : Cardiovascular autonomic dysfunction was found in 32.6% of diabetic patients and 10.8 % of patients had definite or severe involvement. The risk of cardiovascular autonomic dysfunction increased with the patient's age and the duration of DM. This study suggests that the valsalva ratio and the heart rate variation on deep breathing are the most useful tests in evaluating the cardiovascular autonomic function in children and adolescents with DM.

• Smart Media Journal
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• v.11 no.9
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• pp.9-20
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• 2022

Deep reinforcement learning(RL) is an end-to-end data-driven control method that is widely used in the autonomous driving domain. However, conventional RL approaches have difficulties in applying it to autonomous driving tasks due to problems such as inefficiency, instability, and uncertainty. These issues play an important role in the autonomous driving domain. Although recent studies have attempted to solve these problems, they are computationally expensive and rely on special assumptions. In this paper, we propose a new algorithm MCDT that considers inefficiency, instability, and uncertainty by introducing a method called uncertainty sequence modeling to autonomous driving domain. The sequence modeling method, which views reinforcement learning as a decision making generation problem to obtain high rewards, avoids the disadvantages of exiting studies and guarantees efficiency, stability and also considers safety by integrating uncertainty estimation techniques. The proposed method was tested in the OpenAI Gym CarRacing environment, and the experimental results show that the MCDT algorithm provides efficient, stable and safe performance compared to the existing reinforcement learning method.

• 대학교육
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• s.89
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• pp.66-75
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• 1997

우리나라에서 대학입학은 직접적인 관련 집단의 민감한 사안일 뿐만 아니라, 모든 국민의 공통적인 관심사이다. 그런 만큼 대학입학 전형제도는 대학입학 전형의 의미에 비추어 도출되는 규범적 원칙들에 기초하여 신중하게 수립되어야 한다. 전형요소 설정의 타당성, 전형유형 설정의 공정성, 전형과정의 자율성 등의 준거에 비추어 새 대학입학 전형제도의 정책논리를 비판적으로 고찰하고 발전방향을 제시하고자 한다.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2023.11a
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• pp.100-102
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• 2023

항로추종성능은 자율운항선박(MASS)의 중요한 자율제어기능 중 하나이다. 이는 선박의 안전성을 보장하기 위해 중요하며, 자율운항선박의 설계 단계에서 사전 평가가 필수적이다. 본 연구는 자율운항선박의 항로추종성능 평가를 위한 전산유체역학(CFD) 모델과 LOS 알고리즘 연계 방안을 제안한다. 먼저, 자율운항선박의 정수 중 거리 이탈 편차를 이용한 항로 추종 성능 평가 모델 개발에 관하여 기술했다. 먼저, 항로 추종을 수행하는 선박 주변의 난류 흐름은 비압축성 뉴턴 유체의 가정하에 비정상 RANS(Reynolds Averaged Navier-Stokes) 법을 이용하여 수치적으로 계산되었다. 중첩격자계법을 CFD 모델에 적용함으로써 거리 이탈 편차를 이용하는 LOS(Line-of-Sight) 가이던스 알고리즘에 의한 타의 회전 및 이에 따른 선체의 6 자유도 움직임을 CFD 환경에서 구현하였다. 개발된 자유 항주 선박 CFD 모델을 이용하여 항로 추종 시뮬레이션 평가 결과, 설정된 항로에서 선박의 정수 중 항로 추종 제어는 파도, 조류, 및 바람과 같은 외부 교란의 부재로 LOS 알고리즘에 의한 우현/좌현 측 변침뿐만 아니라 직진 경로의 추종도 성공적으로 수행됨을 확인하였다. 선체, 프로펠러, 타의 복잡한 상호작용을 정도 높게 해석할 수 있는 자유 항주 선박 CFD 모델과 LOS 알고리즘의 결합은 자율운항선박의 항로 추종 성능 평가를 정량적으로 평가하는 데 기여할 것으로 기대된다.

• Proceedings of the Korean Information Science Society Conference
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• 2002.04a
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• pp.859.2-897
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• 2002

네트워크의 급격한 발전에 따라 컴퓨터의 보안 문제가 계속 대두되고 있다. 이러한 보안관리 시스템으로 이동 에이전트를 이용한 침입탐지 시스템이 계속 연구되어지고 있다. 본 논문에서는 기존의 침입탐지시스템을 고찰하고 작은 에이전트의 그룹으로 구성된 자율성을 가진 이동 에이전트를 기반으로 한 모듈 접근방식의 시스템을 위한 모델링을 제공한다. 제안된 모델은 침입 정보를 동적으로 수집하고 탐지 에이전트를 학습시키고 탐지한다. 이동 에이전트는 통신 비용절감, 로컬자원 사용의 한계에서의 독립, 관리의 편의성 제공. 비동기 연산 등 다양한 이점을 가지고, 분산 연산을 위만 유동성 있는 구조를 제공한다.

• Journal of Korean Society of Transportation
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• v.36 no.1
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• pp.38-50
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• 2018

Emerging automated driving environments will lead to a mixed traffic flow depending on the interaction between automated vehicles (AVs) and manually driven vehicles (MVs) because the market penetration rate (MPR) of AVs will gradually increase over time. Understanding the characteristics of mixed traffic conditions, and developing a method to control both AV and MV maneuverings smoothly is a backbone of the traffic management in the era of automated driving. To facilitate smooth vehicle interactions, the maneuvering of AVs should be properly determined by various traffic and road conditions, which motivates this study. This study investigated whether the aggressiveness of AV maneuvering, defined as automated driving aggressiveness (ADA), affect the performance of mixed traffic flow. VISSIM microscopic simulation experiments were conducted to derive proper ADAs for satisfying both the traffic safety and the operational efficiency. Traffic conflict rates and average travel speeds were used as indicators for the performance of safety and operations. While conducting simulations, level of service(LOS) and market penetration rate(MPR) of AVs were also taken into considerations. Results implies that an effective guideline to manage the ADA under various traffic and road conditions needs to be developed from the perspective of traffic operations to optimize traffic performances.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2003.10a
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• pp.801-804
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• 2003

The autopilot system of vessel is proposed to take service safety sorority, to elevate service efficiency, to decrease labor and to improve working environment. Ultimate purpose of it is to minimize the number of crew by guaranteeing economical efficiency of shipping service. Recently, the research is being achieving to compensate various nonlinear parameters of vessel and apply it is course keeping control, track keeping control, roll-rudder stabilization, dynamic ship positioning and automatic mooring control etc. using optimizing control technique. Relation between rudder angle controlled by steering machine of vessel and ship-heading angle, and load condition of ship are nonlinear, which affect various parameters of shipping service. The speed and direction of waves, velocity and quantity of wind, which also cause the non-linearity of it. Therefore the autopilot system of ship requires the robust control algorithm can overcome various non-linearity. On this paper, we design the autopilot system of ship, which overcome nonlinear parameters and disturbance of it using Fuzzy Algorithm, evaluate the proposed algorithm and its excellence through simulation

• Journal of the Korea Institute of Information and Communication Engineering
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• v.7 no.7
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• pp.1509-1513
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• 2003

The autopilot system of vessel is proposed to take service safety and security, to elevate service efficiency, to decrease labor and to improve working environment. Ultimate purpose of the proposed system is to minimize the number of crew by guaranteeing economical efficiency of shipping service. Recently, the research is being achieved to compensate various nonlinear parameters of vessel and apply it to course keeping control, track keeping control, roll-rudder stabilization, dynamic ship positioning and automatic mooring control etc. using optimizing control technique. Relation between rudder angle controlled by steering machine of vessel and ship-heading angle, and load condition of ship is nonlinear, which affects various parameters of shipping service. The speed and direction of waves, velocity and quantity of wind, which also cause the non-linearity of it. Therefore the autopilot system of ship requires the robust control algorithm can overcome various non-linearity. On this paper, we design the autopilot system of ship, which overcomes nonlinear Parameters and disturbance of it using Fuzzy Algorithm, evaluate the proposed algorithm and its excellence through simulation.