• 대기
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• 제28권3호
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• pp.233-245
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• 2018

This study explores the Subseasonal-to-Seasonal (S2S) prediction skills of the Northern Hemisphere mid-latitude geopotential height in the Global Seasonal forecasting model version 5 (GloSea5) hindcast experiment. The prediction skills are quantitatively verified for the period of 1991~2010 by computing the Anomaly Correlation Coefficient (ACC) and Mean Square Skill Score (MSSS). GloSea5 model shows a higher prediction skill in winter than in summer at most levels regardless of verification methods. Quantitatively, the prediction limit diagnosed with ACC skill of 500 hPa geopotential height, averaged over $30^{\circ}N{\sim}90^{\circ}N$, is 11.0 days in winter, but only 9.1 days in summer. These prediction limits are primarily set by the planetary-scale eddy phase errors. The stratospheric prediction skills are typically higher than the tropospheric skills except in the summer upper-stratosphere where prediction skills are substantially lower than upper-troposphere. The lack of the summer upper-stratospheric prediction skill is caused by zonal mean error, perhaps strongly related to model mean bias in the stratosphere.

• 대기
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• 제34권2호
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• pp.83-95
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• 2024

Atmospheric rivers (ARs) are closely related to local precipitation which can be both beneficial and destructive. Although several studies have evaluated their predictability, there is a lack of studies on East Asian ARs. This study evaluates the prediction skill of East Asian ARs in the Korean Integrated Model (KIM) for 2020~2022 summer. The spatial distribution of AR frequency in KIM is qualitatively similar to the observation but overestimated. In particular, the model errors greatly increase along the boundary of the western North Pacific subtropical high as the forecast lead time increases. When the prediction skills are quantitatively verified by computing the Anomaly Correlation Coefficient and Mean Square Skill Score, the useful prediction skill of daily AR around the Korean Peninsula is found up to 5 days. Such prediction limit is primarily set by the wind field errors with a minor contribution of moisture distribution errors. This result suggests that the improved prediction of atmospheric circulation field can improve the prediction of East Asian summer ARs and the associated precipitation.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2018년도 학술발표회
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• pp.150-150
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• 2018

The Numerical Weather Prediction (NWP) models provide information for weather forecasts. The highly nonlinear and complex interactions in the atmosphere are simplified in meteorological models through approximations and parameterization. Therefore, the simplifications may lead to biases and errors in model results. Although the models have improved over time, the biased outputs of these models are still a matter of concern in meteorological and hydrological studies. Thus, bias removal is an essential step prior to using outputs of atmospheric models. The main idea of statistical bias correction methods is to develop a statistical relationship between modeled and observed variables over the same historical period. The Model Output Statistics (MOS) would be desirable to better match the real time forecast data with observation records. Statistical post-processing methods relate model outputs to the observed values at the sites of interest. In this study three methods are used to remove the possible biases of the real-time outputs of the Weather Research and Forecast (WRF) model in Imjin basin (North and South Korea). The post-processing techniques include the Linear Regression (LR), Linear Scaling (LS) and Power Scaling (PS) methods. The MOS techniques used in this study include three main steps: preprocessing of the historical data in training set, development of the equations, and application of the equations for the validation set. The expected results show the accuracy improvement of the real-time forecast data before and after bias correction. The comparison of the different methods will clarify the best method for the purpose of the forecast skill enhancement in a real-time case study.

• 국제학술발표논문집
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• The 9th International Conference on Construction Engineering and Project Management
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• pp.319-327
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• 2022

Robots for construction sites, although not deeply widespread, are finding applications in the duties of project monitoring, material movement, documentation, security, and simple repetitive construction-related tasks. A significant shortcoming in the use of robots is the complexity involved in programming and re-programming an automation routine. Robotic programming is not an expected skill set of the traditional construction industry professional. Therefore, this research seeks to deliver a low-cost approach toward re-programming that does not involve a programmer's skill set. The researchers in this study examined an approach toward programming a terrestrial-based drone so that it follows a taped path. By doing so, if an alternative path is required, programmers would not be needed to re-program any part of the automated routine. Changing the path of the drone simply requires removing the tape and placing a different path - ideally simplifying the process and quickly allowing practitioners to implement a new automated routine. Python programming scripts were used with a DJI Robomaster EP Core drone, and a terrain navigation assessment was conducted. The study examined the pass/fail rates for a series of trial run over different terrains. The analysis of this data along with video recording for each trial run allowed the researchers to conclude that the accuracy of the tape follow technique was predictable on each of the terrain surfaces. The accuracy and predictability inform a non-coding construction practitioner of the optimal placement of the taped path. This paper further presents limitations and suggestions for some possible extended research options for this study.

• 중소기업융합학회논문지
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• 제2권1호
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• pp.59-67
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• 2012

최근 소프트웨어 산업분야가 높은 부가가치를 창출할 수 있는 분야임을 인식하면서, 회사의 규모를 막론하고 대부분의 소프트웨어 개발 조직에서 전문 인력을 확보에 고민하고 있다. 그러나 조직의 장기적인 비즈니스를 고려하지 않는 소프트웨어 개발 인력의 채용은 추후 또 다시 인력의 부족현상을 초래할 것이며, 채용 인력에 대한 장기적인 인력 관리에 대한 전략적 설계가 없다면 많은 소프트웨어 개발 인력을 확보하고도 높은 성과를 달성하기 어려울 것이다. 본 논문에서는 조직에서의 소프트웨어 개발 역량을 강화하기 위하여 소프트웨어 직무를 세부적으로 도출하고, 직무별 프로파일을 정의하기 위한 방안을 제시한다. 또한 제시된 프로파일을 근간으로 직원의 Career Path를 어떻게 관리할 것인가에 대하여 제시한다. 제시하는 직무 프로파일 기반 인력관리는 조직에서 적정 규모의 효율적 인력 운영과 비즈니스 성과 달성을 가능하게 하는 기반이 될 것으로 판다한다.

• 한국항공운항학회지
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• 제28권3호
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• pp.27-40
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• 2020

Flight safety in modern commercial aircraft depends on the ability of pilots to manage overall flight operations. ICAO has made it mandatory for airlines to adhere to Crew Resource Management(CRM) policies to reduce operational safety threats. CRM is a set of techniques designed to effectively manage the human resources, aircraft, and environmental factors in order to promote safety and enhance efficient air operations. When looking at the career backgrounds of new pilots joining the Republic of Korea's commercial airlines, discharged military fighter pilots represent the largest demographic. Fighter pilots are experienced in empowering leadership and directive leadership from their military training and culture. New commercial airline pilots with military fighter pilot training should effectively acquire the required civil aviation CRM skills. The present study has been carried out to determine how the leadership experience of this demographic affects the acquisition of CRM skills for commercial airlines, and it confirms that there is a positive correlation.

• Communications for Statistical Applications and Methods
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• 제19권1호
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• pp.97-105
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• 2012

일반화 정준상관 행렬도(generalized canonical correlation biplot)는 정준상관분석에서 세 변수군 이상에 의해서 측정된 다변량 자료에서 변수 집단 간의 관계와 개체들의 관계를 탐색하기 위한 2차원 그림이다. 최근에 이를 활용하여 최태훈과 최용석 (2010)은 2004년 대한테니스협회(KTA)에 등록된 남자선수들 중 상위 50명을 대상으로 세 변수군인 체격요인변수군, 체력요인변수군 그리고 기초기술요인변수군의 상호 연관성을 살펴보았다. 그러나 이들 분석에서 체격요인변수군이 나머지 두 변수군과 독립적이지 못하고 선형적 영향을 미치는 것으로 판단되어 이를 공변량변수군으로 고려하였다. 이와같이 세 변수군에서 한 변수군이 공변량(covariate)으로 영향을 주는 경우 이를 제거한 정준상관분석을 편(partial)정준상관분석이라 하며 이와 관련된 편정준상관 행렬도를 염아림과 최용석 (2011)은 제안하였다. 본 연구에서는 최태훈과 최용석(2010)의 분석에서 체격요인변수군의 영향을 제거하고 체력요인변수군과 기초기술요인변수군의 관계를 살펴보는 편정준상관 행렬도의 활용의 예를 보이고 기존 연구의 일반화 정준상관 행렬도, 편정준상관 행렬도, 정준상관 행렬도의 결과를 서로 비교하고자 한다. 덧붙여 이들 행렬도간의 형상변동 차이를 프로크러스티즈 분석을 활용하여 비교하고자 한다.

• 한국CDE학회지
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• 제11권2호
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• pp.15-22
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• 2005

Presented in the paper is an approach to developing an intelligent mold shop as a means to overcome the difficulties faced by mold-makers due to skill shortages and increased global competition. A machine shop where as much as of the human skills are replaced by a set of intelligent systems is called an intelligent machine shop, and an intelligent mold-making machine shop is called an intelligent mold shop(MS). By analyzing the contents of operator's skill. three intelligent S/W stations have been designed: Technical Data Processing(TDP) Station, Loading Schedule Station, and Real-time Monitoring Station. A detailed architecture of the TDP station is described, and measures of effectiveness of IMS are elaborated.

• 교육녹색환경연구
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• 제5권1호
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• pp.1-10
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• 2006

The purpose of this study is to clarify the actual conditions of the use and the plan of lifelong education facilities in national university of industry. This article discuses about the basic characteristics of the plan composition and the education programs of 8 lifelong education facilities in national university of industry. The results of this study are summarized as follows; 1) Needed spaces should functionally designed considering that basic and culture lecture, occupation skill and expert education, hobby/amusement/leisure, health/sanitation/sports, tradition culture understanding education among education programs of lifelong education facilities in universities are mainly constituted and occupation skill and expert education among theses are occupied with the most ratio. 2) Expansion of facilities is agent considering the number of students and lectures to be 3.0% from 1.7% of average ratio of continuous dimensions lifelong education facilities of each universities and composition following scale of the lecture room is set by organizing the number of students per lecture to small groups.

• 한국경영과학회지
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• 제22권4호
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• pp.115-131
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• 1997

The problem addressed in this paper is to minimize the deviations of workloads assigned to worker and to maximize the total utilizations(degree of skill) between workers and machines simultaneously. Each worker can handle the set of machines with the different degree of skill and each machine has the workloads needed to be processed. Also, each worker has to be assigned to at least one machine with the minimum workload deviation. This problem can be formulated as a preemptive goal programming with generalized assignment constraints. The proposed algorithm consists of two phases. First, a capacitated circulation network is constructed to assign the workers to machines with the maximum total utilizations while considering workloads balance. Then, a refinement process is applied to the split machines to satisfy the feasibility condition. The real industrial application in a plastic extrusion manufacturer is included along with several computational experiments.