• 기록학연구
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• 제55호
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• pp.97-133
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• 2018

국방기록물관리기관은 총 133개이며 개별 기록관의 고유문제 뿐만 아니라 공통문제를 점검하고 이를 해결하기 위한 전략이 필요하다. 국방기록물관리기관의 전략적 운영모형은 기록관의 운영문제를 점검하고 전략적으로 해결하기 위해 개발한 툴이다. 국방기록물관리기관의 문제를 점검하고 업무개선을 위해 지휘관의 전략적 판단을 획득하고자 할 때 도움을 주고자 하였다. 그리고 기록관리 정책을 수립하고자 하는 국방부 등의 정책기관과 중장기 발전계획을 수립하여 기록관의 개선을 도모하는 개별 국방기록물관리기관에서 사용할 수 있도록 제안되었다. 문헌연구를 기반으로 전문가의 검증, 통계적 분석, 국방기록관의 특성을 반영하여 7개 영역 67개 항목으로 개발되었다. 그리고 국방부가 전략적 운영모형을 활용한 실증사례를 통해 기록관의 개선전략수립과 활용을 제안하고자 한다.

• 산업경영시스템학회지
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• 제43권4호
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• pp.93-106
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• 2020

This research explores how imported automobile companies can develop their strategies to improve the outcome of their recalls. For this, the researchers analyzed patterns of recall demand, classified recall types based on the demand patterns and examined response strategies, considering plans on how to procure parts and induce customers to visit workshops, recall execution capacity and costs. As a result, recalls are classified into four types: U-type, reverse U-type, L- type and reverse L-type. Also, as determinants of the types, the following factors are further categorized into four types and 12 sub-types of recalls: the height of maximum demand, which indicates the volatility of recall demand; the number of peaks, which are the patterns of demand variations; and the tail length of the demand curve, which indicates the speed of recalls. The classification resulted in the following: L-type, or customer-driven recall, is the most common type of recalls, taking up 25 out of the total 36 cases, followed by five U-type, four reverse L-type, and two reverse U-type cases. Prior studies show that the types of recalls are determined by factors influencing recall execution rates: severity, the number of cars to be recalled, recall execution rate, government policies, time since model launch, and recall costs, etc. As a component demand forecast model for automobile recalls, this study estimated the ARIMA model. ARIMA models were shown in three models: ARIMA (1,0,0), ARIMA (0,0,1) and ARIMA (0,0,0). These all three ARIMA models appear to be significant for all recall patterns, indicating that the ARIMA model is very valid as a predictive model for car recall patterns. Based on the classification of recall types, we drew some strategic implications for recall response according to types of recalls. The conclusion section of this research suggests the implications for several aspects: how to improve the recall outcome (execution rate), customer satisfaction, brand image, recall costs, and response to the regulatory authority.

• 한국정보전자통신기술학회논문지
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• 제16권1호
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• pp.33-40
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• 2023

슈퍼 컴퓨팅 기술 및 하드웨어 기술의 발달로 수치 연산 방식 또한 고도화되고 있다. 그에 따라 이전 대비 향상된 기상 예측 또한 가능해진다. 본 논문에서는 SCAM(Single-Columns Atmospheric Model, CESM(Community Earth System Model)을 간소화 한 버전)에 포함되어 있으며 대기 연산을 수행하는 적운 모수화 코드, Unicon(A Unified Convection Scheme)의 성능을 향상하기 위하여 소스 코드 내의 선형대수 수치적 연산 부분에 고밀도 선형대수 연산을 위한 라이브러리인 LAPACK(Linear Algebra PACKage) BLAS(Basic Linear Algebra Subprograms)의 level1 함수를 적용할 것을 제안한다. 이를 분석하기 위하여 SCAM의 전체적인 실행 구조도를 제시하고 해당 실행환경에서 테스트를 진행하였다. 기존 소스 코드 대비 SCOPY 함수는 0.4053%, DSCAL 함수는 0.7812%, DDOT 함수는 0.0469%의 성능 향상을 이끌어 내었으며 이를 모두 적용한 결과 기존 소스 코드 대비 0.8537%의 성능 향상을 보였다. 이는 본 논문에서 제안한 고밀도 선형대수 연산을 위한 라이브러리인 LAPACK BLAS 적용 방법이 동일한 CPU 환경에서 추가적인 하드웨어의 개입 없이 성능을 향상시킬 수 있음을 의미한다.

• 국제학술발표논문집
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• The 4th International Conference on Construction Engineering and Project Management Organized by the University of New South Wales
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• pp.149-156
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• 2011

The performance measurement of construction firms is considered as a competitive advantage to develop and improve their performance to have place in the market and stay able to face the continuous challenge. Egyptian construction firms (ECF) started recently to adopt quality management system (QMS) as a way to develop and improve their performance as previous studies showed. However, measuring that performance to include all the firm's aspects in a competitive way is a crucial process for the ECF's culture. The research is trying to indicate the role of the QMS implementation in measuring performance (MP) through developing a model for measuring performance on the organization level, and explore its impact on the organization that adopt quality management system. This model is based on specific elements and their related indicators which have been derived from national approaches and models of measuring performance (benchmarking, quality awards and six sigma).Elements determination and the status of their real practice has been investigated through a questionnaire to a representative sample of ECF. This model determines the performance level (PL) of the organization that measured by a mean of a point system. Weights of the elements in the point system considered both the elements' importance in the international models and its real practice in the Egyptian construction firms. So, the final outcome of the model reveals the level of firm performance that helps the firm to identify the weak points against the strong ones, Confirm the priorities and identify new opportunities for developing, and Check the position of the company in the market among the others. Another questionnaire has been developed to be distributed on a group of Experts on measuring performance for the purpose of model validation. The majority of surveyed experts agreed that the proposed model can be applied effectively.

• 여성건강간호학회지
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• 제29권4호
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• pp.302-316
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• 2023

Purpose: This study aimed to develop and validate a structural model for the quality of life (QoL) among high-risk pregnant women, based on Roy's adaptation model. Methods: This cross-sectional study collected data from 333 first-time mothers diagnosed with a high-risk pregnancy in two obstetrics and gynecology clinics in Cheonan, Korea, or participating in an online community, between October 20, 2021 and February 20, 2022. Structured questionnaires measured QoL, contextual stimuli (uncertainty), coping (adaptive or maladaptive), and adaptation mode (fatigue, state anxiety, antenatal depression, maternal identity, and marital adjustment). Results: The mean age of the respondents was 35.29±3.72 years, ranging from 26 to 45 years. The most common high-risk pregnancy diagnosis was gestational diabetes (26.1%). followed by preterm labor (21.6%). QoL was higher than average (18.63±3.80). Above-moderate mean scores were obtained for all domains (psychological/baby, 19.03; socioeconomic, 19.00; relational/spouse-partner, 20.99; relational/family-friends, 19.18; and health and functioning, 16.18). The final model explained 51% of variance in QoL in high-risk pregnant women, with acceptable overall model fit. Adaptation mode (β=-.81, p=.034) and maladaptive coping (β=.46 p=.043) directly affected QoL, and uncertainty (β=-. 21, p=.004), adaptive coping (β=.36 p=.026), and maladaptive coping (β=-.56 p=.023) indirectly affected QoL. Conclusion: It is essential to develop nursing interventions aimed at enhancing appropriate coping strategies to improve QoL in high-risk pregnant women. By reinforcing adaptive coping strategies and mitigating maladaptive coping, these interventions can contribute to better maternal and fetal outcomes and improve the overall well-being of high-risk pregnant women.

• 스마트미디어저널
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• 제13권1호
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• pp.9-17
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• 2024

본 연구는 농산물의 품질, 수익 및 의사결정 효율성을 향상시키기 위한 통합적인 농업 유통망 관리시스템을 개발하는 데 목적이 있다. 우리는 YOLOX 객체 탐지 알고리즘을 기반으로 한 농작물 성숙도 체크와 Prophet 모델을 기반으로 한 시장 가격 예측이라는 두 가지 핵심 기술을 채택하였다. 객체 탐지 모델을 훈련함으로써, 다양한 성숙도 단계의 농작물을 정확하게 식별할 수 있게 되어 출하 시기를 최적화할 수 있었다. 동시에, 과거 시장 가격 데이터를 수집하고 Prophet 모델을 사용하여 가격을 예측함으로써, 출하시기 결정권자들에게 신뢰할 수 있는 가격 추세 정보를 제공하였다. 연구 결과에 따르면, 휴일 요소를 고려한 모델의 성능이 그렇지 않은 모델보다 두드러지게 우수하다는 것이 밝혀져서 휴일이 가격에 미치는 영향이 강함을 증명하였다. 이 시스템은 농민 및 농산물 유통 관리자에게 강력한 도구 및 의사결정 지원을 제공하여, 다양한 계절과 휴일 기간 동안 현명한 의사결정을 내릴 수 있게 도와준다. 아울러, 농산물 유통망을 최적화하고 농산물의 품질과 수익을 향상시킬 수 있다.

• 산업경영시스템학회지
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• 제47권2호
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• pp.155-167
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• 2024

Distribution and logistics industries contribute some of the biggest GDP(gross domestic product) in South Korea and the number of related companies are quarter of the total number of industries in the country. The number of retail tech companies are quickly increased due to the acceleration of the online and untact shopping trend. Furthermore, major distribution and logistics companies try to achieve integrated data management with the fulfillment process. In contrast, small and medium distribution companies still lack of the capacity and ability to develop digital innovation and smartization. Therefore, in this paper, a deep learning-based demand forecasting & recommendation model is proposed to improve business competitiveness. The proposed model is developed based on real sales transaction data to predict future demand for each product. The proposed model consists of six deep learning models, which are MLP(multi-layers perception), CNN(convolution neural network), RNN(recurrent neural network), LSTM(long short term memory), Conv1D-BiLSTM(convolution-long short term memory) for demand forecasting and collaborative filtering for the recommendation. Each model provides the best prediction result for each product and recommendation model can recommend best sales product among companies own sales list as well as competitor's item list. The proposed demand forecasting model is expected to improve the competitiveness of the small and medium-sized distribution and logistics industry.

• Journal of Electrical Engineering and Technology
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• 제12권1호
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• pp.64-71
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• 2017

Considering the volatility, intermittent and random of photovoltaic (PV) generation systems, accurate forecasting of PV power output is important for the grid scheduling and energy management. In order to improve the accuracy of short-term power forecasting of PV systems, this paper proposes a prediction model based on environmental factors and support vector machine optimized by genetic algorithm (GA-SVM). In order to improve the prediction accuracy of this model, weather conditions are divided into three types, and the gray correlation coefficient algorithm is used to find out a similar day of the predicted day. To avoid parameters optimization into local optima, this paper uses genetic algorithm to optimize SVM parameters. Example verification shows that the prediction accuracy in three types of weather will remain at between 10% -15% and the short-term PV power forecasting model proposed is effective and promising.

• 대한기계학회논문집
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• 제17권5호
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• pp.1193-1201
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• 1993

본 연구에서는 통계학적 이론 및 희귀분석에 근거한 보정함수를 모델 수정에 도입하여 조업조건별로 예측오차 요인들을 제거함으로써 예측 모델의 정도를 향상시키 고자 하였다. 이를 위해 일반강에 비해 압연하중 모델의 예측정도가 상대적으로 낮은 극저탄소강을 대상으로 하여 압연조업에 따른 압연하중 예측모델의 오차요인을 조업인 자별로 분석하였고 적용시켜 모델의 적중도를 향상시켰다.

• 한국유체기계학회 논문집
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• 제16권1호
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• pp.40-46
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• 2013

Recently, the duct system with a cross flow fan was used to improve the ventilation in various industrial fields. For the efficient ventilation, it is necessary to design the duct system based on the flow characteristics around the cross flow fan. In the present study, the flow characteristics around a cross flow fan in the ventilation duct were predicted by using the moving mesh and sliding interface techniques for the rotation of blades. To design the duct system with the high performance of ventilation, the CFD simulations were repeated with the revised duct model based on the DOE. With the numerical results of flow rate through the ventilation duct with various geometric parameters, the optimized geometry of ventilation duct to maximize the flow rate was obtained by using the Kriging approximation method. From the performance curves of cross flow fan in the original and optimized models of ventilation duct, it was observed that the flow rate through the optimized model is about 16 percent larger than that through the original model.