• Korean Journal of Psychosomatic Medicine
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• v.20 no.1
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• pp.14-17
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• 2012

There were several documents that might reflect the great concern on the education of psychosomatic medicine in medical school from the 1960s. But the hour of class and proportion of psychosomatic medicine have been quite small among the total lecture time of psychiatry. Notwithstanding the importance of biopsychosocial perspective in practice and research there have been no agreement on the goal and content of teaching psychosomatic medicine in the medical school curriculum. Consultation-liaison psychiatric activity in the hospital were currently under-developed and educational content and process were not systematic. We should have established the goal of psychosomatic education in the medical school that includes making doctor who could not only cure disease but also care the ill patients. And we should develop the curriculum that covers essential area of psychosomatic medicine and checking system to monitor the process of education. With the continuance of psychosomatic perspectives from medical school education to clinical subspecialty we can make progress in this field.

• KDI Journal of Economic Policy
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• v.9 no.1
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• pp.27-42
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• 1987

본논문(本論文)에서는 우리나라의 노동시장(勞動市場)의 구조(構造)를 동학적(動學的)으로 살펴보고 이에 따른 정책과제(政策課題)를 도출(導出)하기 위해 취업(就業)과 실업상태(失業狀態)를 번갈아 움직이는 노동자(勞動者) 행태(行態)의 결정요인(決定要因)을 실증분석(實證分析)하였다. 분석방법(分析方法)으로는 직업탐색이론(職業探索理論)을 이용(利用)하여 이론적(理論的)인 가설(假說)을 도출(導出)하였고, 계량적(計量的) 검증(檢證)을 위해 회귀모형(回歸模型)을 정형화(定型化)하였다. 통계자료(統計資料)는 1985년(年) 한해 동안의 "경제활동인구조사(經濟活動人口調査)"의 매월(每月) "테이프"에서 같은 근로자(勤勞者)를 11개월(個月) 동안 추적하여 분석(分析)을 위한 표본(標本)으로 이용(利用)하였다. 임금(賃金)은 취업(就業)에서 실업(失業)으로 변화(變化)할 확률(確率)에 대해 부(負)의 효과(效果)를 보이고 실업(失業)에서 벗어나 재취업(再就業)할 확률(確率)에도 부(負)의 효과(效果)를 나타내어 이론(理論)에서 도출(導出)된 가설(假設)이 검증(檢證)되었다. 연령(年齡)이 상태간(狀態間) 이동(移動)에 미친 효과(效果)는 부(負)의 값을 보였다. 그러나 이 효과(效果)는 일정한 연령(年齡)이 지나면 정(正)의 효과(效果)로 바뀌는 비선형성(非線型性)을 보였다. 이러한 결과(結果)에 입각(立脚)하여 우리는 높은 임금(賃金)을 받는 근로자(勤勞者)일수록 이직(移職)의 가능성(可能性)이 낮고 또한 실업상태(失業狀態)에서 재취직(再就職)의 가능성(可能性)이 낮다는 사실(事實) 등을 알 수 있다. 이에 따른 정책적(政策的) 시사점(示唆點)의 하나는 직업훈련(職業訓鍊)을 단순히 양적(量的)으로 확대(擴大)하기보다는 연령체계(年齡體系)에 맞추어 그 내용을 질적(質的)으로 조정(調整)하는 것이 바람직하다는 것이다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.10
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• pp.2215-2222
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• 2010

A Wireless Access for Vehicular Environment (WAVE) system based on Orthogonal Frequency Division Multiplexing (OFDM) is made for vehicle to vehicle wireless communications. The physical layer standard of the WAVE system is very similar to that of the IEEE802.11a wireless local area network (WLAN). Therefore, the performance of the WAVE system is degraded by continual channel variation in the WAVE multipath fading channels after starting initial channel estimation. In this paper, we research the performance improvement of equalization in 64 Quadrature Amplitude Modulation (QAM) transmission in WAVE environment. The proposed algorithms use the training sequence and the midamble sequence which is used for fast channel variation such as WAVE environments. Additionally, various interpolation methods are also used for the channel tracking.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.9
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• pp.3841-3848
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• 2012

The process of an analysis of alternatives(AoA) attempts to select the best and balanced solution among a set of multiple candidate solutions under the constraints of cost, schedule, performance and risk(CSPR). The traditional AoA for the acquisition of a new weapon system has usually centered on the sequence of the requirement analysis, design synthesis, and cost estimation. An improved process for AoA is developed in this paper based on a multi-objective decision-making method, which is intended to be applied in the design concept refinement and material solution analysis stage for the acquisition of naval surface ships. The presentation of the proposed AoA approach is then followed by a case study for the next generation multi-purpose training ship based on the principles of systems engineering and also using the models of the effectiveness measure, cost estimation, and risk assessments.

• The Journal of the Korea Contents Association
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• v.11 no.12
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• pp.122-135
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• 2011

Mobile spam message is a harmful factor which makes receivers to be annoyed and leads to unnecessary social cost. Unwanted junk messages flowing to a smart phone ruin main purpose of the smart work system to enhance the productivity, so we need to study on this area. In this paper, we proposed a novel spam filter on the smartphone in order to reduce computing process and improve the accuracy rate by feedback of error results to a training sample set. As the spam classifier operates on the smartphone independently with training on only user's received data, it could reflect user preference. The authorized personal computer takes on heavy works, such as preprocessing, feature selecting and training process, and the smartphone takes on light works to block junk messages. Experimental results showed reasonable accuracy rate of over 95%, and we found that the application occupied constant computing resources while running on the phone.

• The Journal of the Korea Contents Association
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• v.13 no.8
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• pp.386-395
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• 2013

This study examined social relation of cyber sports supporter's community and social capital as time passes. This study selected spectator sports supporters of cyber sports community based on number of number and history of cyber sports supporter. This community is a representative supporter's club of spectator sports. This study utilized 1,848 members accumulated during three month. To analyze data, Netminer 4.0 and social network analysis were used. The conclusion is following: First, social relation of cyber sports supporter's community showed up dynamic change. Second, social capital of cyber sports supporter's community shows Sports events and training schedules, player transfer, manager, record, game watching and TV watching, cheering, cheering uniform and tools, players, teams and clubs, game photos and video, etc. This is the poor-get-poorer and the rich-get-richer phenomenon.

• Convergence Security Journal
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• v.20 no.2
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• pp.123-135
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• 2020

Since AlphaGo's Match in 2016, there has been a growing calls for artificial intelligence applications in various industries, and research related to it has been actively conducted. The same is true in the military field, and since there has been no weapon system with artificial intelligence so far, effort to implement it are posing a challenge. Meanwhile, AlphaGo Zero, which beat AlphaGo, showed that artificial intelligence's self-training data-based approach can lead to better results than the knowledge-based approach by humans. Taking this point into consideration, this paper proposes to apply Reinforcement Learning, which is the basis of AlphaGo Zero, to the Shipboard Combat System or Combat Management System. This is how an artificial intelligence application to the Shipboard Combat System or Combat Management System that allows the optimal tactical assist with a constant win rate to be recommended to the user, that is, the commanding officer and operation personnel. To this end, the definition of the combat performance of the system, the design plan for the Shipboard Combat System, the mapping with the real system, and the training system are presented to smoothly apply the current operations.

• Journal of IKEEE
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• v.23 no.4
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• pp.1328-1336
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• 2019

To maintain the safe and optimal performance of batteries, accurate estimation of state of charge (SOC) is critical. In this paper, Long short-term memory network (LSTM) based on the artificial intelligence algorithm is applied to address the problem of the conventional coulomb-counting method. Different discharge cycles are concatenated to form the dataset for training and verification. In oder to improve the quality of input data for learning, preprocessing was performed. In addition, we compared learning ability and SOC estimation performance according to the structure of LSTM model and hyperparameter setup. The trained model was verified with a UDDS profile and achieved estimated accuracy of RMSE 0.82% and MAX 2.54%.

• Current Industrial and Technological Trends in Aerospace
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• v.5 no.2
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• pp.33-42
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• 2007

위성체 총조립 및 시험(AIT ; Assembly, Integration & Test)을 위한 전기지상지원장비(EGSE ; Electrical Ground Support Equipment)와 위성 임무 준비 및 운용을 위한 관제시스템(MCS ; Mission Control System)의 공동 개발은 미국과 유럽의 위성사업 기관 및 업체에서 지금까지 많은 연구가 되어 왔다. 비록 두 시스템이 다른 목적으로 사용되고 있지만 기술적으로 유사한 기능을 갖는 시스템으로서 많은 공통점과 호환 가능성을 갖고 있다. 두 시스템의 공동 개발은 시스템 개발과 위성 운용 교육 및 준비에 필요한 비용 절감뿐만 아니라 AIT 단계에서 위성운용단계로의 자연스러운 전환이 가능하다. 이는 AIT 단계에서 공통지상시스템 하드웨어 및 운영시스템, 시험/운용 절차서, 위성 데이터베이스의 사전 검증이 이루어지기 때문이다. 또한 위성 운용 요원의 AIT 참여를 통해 공통지상시스템 운용 훈련과 위성 관제 지식 습득이 자연스럽게 이루어 질 수 있다. 이로서 사업 일정과 개발 위험도를 최소화 할 수 있다. 이러한 두 시스템의 공통성과 호환성 및 공통시스템 개발 장점이 있기에 EGSE와 MCS의 공통 기능에 대한 표준화 작업은 1986년 만들어진 COES(Committee for Operations and EGSE Standard)에서 공식적으로 논의되기 시작하여 1994년 CNES와 ESA의 발의로 제정된 ECSS(European Cooperation for Space Standards)를 통해 국제 표준(ISO, CCSDS 등)을 바탕으로 한 지상시스템에 대한 유럽 표준화 작업이 ECSS-E-70 Working Group에서 진행되고 있다. 또한 검증된 지상시스템의 핵심 운영시스템의 소프트웨어 모듈의 재사용을 통해 최근에서 다양한 공통지상시스템이 개발되어 운용되고 있다. 이러한 배경으로 국내에서도 저궤도 위성 개발에서 EGSE 핵심 모듈인 TM/TC 처리 및 Database 관리 모듈을 AIT 단계에서 개발 및 검증 후에 MCS에서의 재사용을 적극적으로 고려하고 있다. 앞으로 국제적인 추세에 따라 AIT 및 지상국간의 기술 및 인력 교류와 핵심모듈 개발을 통한 공통지상시스템 개발의 활발한 전개가 예상된다.

• Journal of KIISE:Software and Applications
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• v.35 no.5
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• pp.306-312
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• 2008

In a goal-oriented dialogue, speaker's intention can be approximated by a semantic structure that consists of a pair of a speech act and a concept sequence. Therefore, it is very important to correctly identify the semantic structure of an utterance for implementing an intelligent dialogue system. In this paper, we propose a model to efficiently analyze the semantic structures based on an active teaming method. To reduce the burdens of high-level linguistic analysis, the proposed model only uses morphological features and previous semantic structures as input features. To improve the precisions of semantic structure analysis, the proposed model adopts CRFs(Conditional Random Fields), which show high performances in natural language processing, as an underlying statistical model. In the experiments in a schedule arrangement domain, we found that the proposed model shows similar performances(92.4% in speech act analysis and 89.8% in concept sequence analysis) to the previous models although it uses about a third of training data.