• 대한교통학회지
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• 제10권3호
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• pp.21-42
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• 1992

As for the travel demand analysis of the past, forcasting has been conducted by the use of revealed preference(RP) informations about actual or observed choices made by individuals. Forcasting method using RP data needs implicit assumptions that there will be no remarkable changes in existing transport conditions. However in case of occuring the great changes in existing conditions or adding a new choice-set of hypothetical options, it is very difficult to predict future travel demand. Fortunately in recent years, especially in the mode choice analysis, it has been perceived that the importance of individual performance data using stated preference(SP) experiments as well as RP data. But the research reports has not been reported sufficiently from models estimated using SP data. Under this background, we analyze the factors affecting the mode choice behavior as a fundamental study against the modelling task with SP choice data. For this analysis, we assumed subway operations in the secondary cities where there are no subway lines until now, and set up a choice-set of hypothetical options based on Experimental Design Method.

• International Journal of Reliability and Applications
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• 제4권1호
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• pp.27-40
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• 2003

Maintenance models involving minimal imperfect repair frequently appear in the literature of reliability and operations research. Most of the literatures concerning the stochastic behavior of repairable systems assume that it takes negligible time to repair a failed system and so the length of repair time does not affect the maintenance strategy. It is more realistic to consider the length of repair times in developing maintenance model, however. In this paper, we consider an imperfect repair model with random repair time and investigate some stochastic properties of the number of perfect repairs and the number of minimal repairs. Also we derive the expressions for evaluating the expected numbers of perfect and minimal repairs in general and apply these formulas for certain parametric life distributions.

• Journal of Smart Tourism
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• 제1권2호
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• pp.19-25
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• 2021

Before COVID-19, tourist destinations have experienced problems with congestion of both famous tourist attractions and public transportation. Over-tourism is not an issue at this time, but it is likely to rekindle after the COVID-19 pandemic ends. One method of mitigating over-tourism is to estimate tourist behavior using a tourist transition model and consequently adjust public transportation operations. In this study, we propose a construction method for a model of tourist transitions among tourist attractions based on tourist GPS trajectory data. We construct tourist transition models using actual trajectory data for tourists staying in the vicinity of Kyoto City. The results verify the model performance.

• International Journal of Advanced Culture Technology
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• 제8권4호
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• pp.110-118
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• 2020

It is important to have an appropriate amount of inventory for effective operations. This study seeks to develop a sustainable newsvendor model by incorporating environment-related costs into the existing well-known (single-period) newsvendor model. Since leftovers do more harm to environments than stockouts, the optimal order amount tends to be lower than the traditional quantity. However, this is not the case when a second buy is allowed. A second order opportunity is prevalent in industries where it improves demand forecast despite incurring extra costs. In this study, we conduct an extensive numerical analysis for a newsvendor situation with a permitted second buy. The results show that we can reduce inventory costs by considering sustainability concerns. The research idea of including sustainability considerations into existing inventory models can be extended to a more general case and provides managerial insights for better inventory decisions.

• 반도체디스플레이기술학회지
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• 제21권3호
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• pp.7-11
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• 2022

Object detection technology is one of the main research topics in the field of computer vision and has established itself as an essential base technology for implementing various vision systems. Recent DNN (Deep Neural Networks)-based algorithms achieve much higher recognition accuracy than traditional algorithms. However, it is well-known that the DNN model inference operation requires a relatively high computational power. In this paper, we analyze the inference time complexity of the state-of-the-art object detection architecture Yolov7 in various environments. Specifically, we compare and analyze the time complexity of four types of the Yolov7 model, YOLOv7-tiny, YOLOv7, YOLOv7-X, and YOLOv7-E6 when performing inference operations using CPU and GPU. Furthermore, we analyze the time complexity variation when inferring the same models using the Pytorch framework and the Onnxruntime engine.

• 한국국방경영분석학회지
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• 제36권3호
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• pp.95-111
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• 2010

NCO(Network Centric Operation) 효과분석과 관련된 요소 및 이들 간 관계는 PCO(Platform Centric Operation)의 그것과 비교하여 복잡하다. 그러나 기존 효과분석모델은 단위 효과요소관점의 효과분석방법을 제시하여, 복잡한 NCO의 효과분석을 위해서는 엔터프라이즈 관점의 통합된 효과분석과 공통언어로 활용 가능한 효과분석모델 개발이 시급한 상태다. EA(Enterprise Architecture)는 공통언어 가능의 참조모델과 이에 순응하는 적용모델 개념을 도입하여 엔터프라이즈의 변화와 복잡도를 관리한다. 본 연구는 EA의 특성인 참조 및 적용모델 개념을 도입한 '참조모델기반 NCO 효과분석모델 개발방법'을 제시한다. 이를 위해 첫째 참조 및 적용모델 개념을 가진 EA를 연구하며, 둘째, NCO 및 C2 효과분석 절차 몇 모델 분석과 모델 구성요소 식별과 관계설정을 위한 방법을 연구하며, 셋째, 연구된 내용을 바탕으로 참조모델기반 NCO 효과분석모델 개발방법을 제시하고, 마지막으로 제시된 방법에 따라 사례를 개발하여 제시한 방법의 효과성을 입증한다.

• 한국경영과학회지
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• 제28권3호
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• pp.81-101
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• 2003

The financial statements purpose to provide useful information to decision-making process of business managers. The value-relevant information, however, embedded in the financial statement has been often overlooked in Korea. In fact, the financial statements in Korea have been utilized for nothing but account reports to Security Supervision Boards (SSB). The objective of this study is to develop earnings forecasting models through financial statement analysis using artificial intelligence (AI). AI methods are employed in forecasting earnings: artificial neural networks (ANN) for manufacturing industry and case~based reasoning (CBR) for banking industry. The experimental results using such AI methods are as follows. Using ANN for manufacturing industry records 63.2% of hit ratio for out-of-sample, which outperforms the logistic regression by around 4%. The experiment through CBR for banking industry shows 65.0% of hit ratio that beats the statistical method by 13.2% in holdout sample. Finally, the prediction results for manufacturing industry are validated through monitoring the shift in cumulative returns of portfolios based on the earning prediction. The portfolio with the firms whose earnings are predicted to increase is designated as best portfolio and the portfolio with the earnings-decreasing firms as worst portfolio. The difference between two portfolios is about 3% of cumulative abnormal return on average. Consequently, this result showed that the financial statements in Korea contain the value-relevant information that is not reflected in stock prices.

• 한국경영과학회지
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• 제35권1호
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• pp.19-45
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• 2010

Virtual Communities, which are formed on the Internet, are expected to serve the needs of members for e-collaboration, e-communication, information and knowledge sharing. The executives of organizations should consider virtual community as a new innovation or knowledge pool since members share knowledge. However, many virtual community have failed due to members' low willingness to engage and furthermore to share knowledge with other members. Thus, there is a need to understand and foster the determinants of members' sense of belonging behavior in virtual community. This study develops an integrated model designed to investigate and explain the relationships between contextual factors, personal perceptions of virtual community, usability, trust and sense of belonging in using a certain virtual community. Empirical data was collected from 201 and tested using structural equation modeling (SEM) to verify the fit of the hypothetical model. The results show that the perceived usability and community trust of members significantly influences sense of belonging in using the virtual community, and information quality, system quality, familiarity on the virtual community are significantly influence the usability but not reputation. And I confirmed that perceived shared vision and responsiveness play the role of determinants in making the member's trust, perceived risk influence the making community trust in directly. The results of the study can be used to identify the motivation underlying members' sense of belonging in a certain virtual community by investigating the impacts of contextual factors and personal perceptions on virtual community, the integrated model better explains behavior than other proposed models. This study might help executives of virtual communities and organizations to manage and promote these determinants of sense of belonging to stimulate members' willingness to engage the community and futhermore enhance their virtual community loyalty.

• 한국국방경영분석학회지
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• 제37권1호
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• pp.87-97
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• 2011

본 논문에서는 앞으로 개발되어 전력화 예정인 제병협동통합연동체계에서 모델간 연동으로 인해서 발생가능한 문제점 중의 하나인 전투 피해평가 차이를 극복할 수 있는 근접전투 피해평가 전문가시스템을 제안하였다. 제병협동통합연동체계에서 서로 다른 모델에 속한 부대간 교전이 발생할 때에 피해평가 결과가 많은 차이를 보이고 있었는데, 이러한 피해평가의 차이는 제병협동통합연동체계의 신뢰성 문제와 직관되는 중요한 부분으로 반드시 해결되어야 할 부분이다. 이러한 문제점을 해결하고 신뢰할 만한 근접전투 피해평가를 위해 전문가시스템을 의사결정나무를 이용해서 제안하였다. 제안하는 전문가시스템은 실험 결과를 통해서 신뢰할 만한 결과를 보였고, 별도의 시스템으로 운용하지 않고 기존 모델에 모듈형식으로 탑재되기 때문에 시스템 측면에서 제병협동통합연동체계를 보다 단순화 시킬 수 있고 예산 절감의 효과를 기대할 수 있다.

• 한국국방경영분석학회지
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• 제29권1호
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• pp.88-111
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• 2003

This paper is to suggest strategic options for improving the export performance of the plant and construction industry. The overall objective of this study is to explore the feasibility of a sustained export performance in the plant and overseas construction industry by an analysis of its international competitiveness and technological competence. The empirical work of this study relates to a chosen sample of Korean and non-Korean firms in the plant and construction industry sector. Primary data was collected through a comprehensive questionnaire survey administered to plant and construction firms in twelve countries, including Korea. The actual number of firms for which full information at a sufficient level of disaggregation was obtained was 62, a response rate of 44.6％. Of these, 42 firms were drawn from Korean plant and construction firms and the remaining 20 firms from 11 other countries. The structure of responding firms by industry shows a total of 29 plant exporters and 33 construction firms. Data analysis was carried out using SPSS statistical technique such as Multiple Regression in order to examine the linear relationship among variables. The findings of the study indicate that export success and failure in plant and construction export markets is determined by firm size and by various qualitative variables. The high export volume (export success) of Plant and construction exporters is more strongly influenced by mutual economic cooperation and number of employees than by sales volume and competent knowledge of the plant and construction markets. It was also found that weak political and diplomatic relation between countries, low sales volume and lack of bid experience have an adverse effect and represent serious barriers to exports.