• 한국기술혁신학회:학술대회논문집
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• 한국기술혁신학회 2014년도 추계 학술대회 논문집
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• pp.699-711
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• 2014

• 한국정보전자통신기술학회논문지
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• 제11권5호
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• pp.493-506
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• 2018

본 논문에서는 직무별로 취업에 필요한 역량을 나타내고, 구직자가 온라인상에서 포트폴리오를 효율적으로 작성하고 관리하는 OOPP(Optimized Online Portfolio Platform)를 제안한다. 제안하는 OOPP는 세 가지 모듈로 구성된다. 첫째, JDCM(Job Data Collection Module)은 직업정보 사이트의 구인 광고들을 수집하여 스프레드시트에 저장한다. 둘째, CSM(Competency Statistical Medel)은 수집한 구인 광고들을 텍스트 마이닝하여 직무별로 요구되는 핵심 역량을 분류한다. 셋째, OBBM(Optimize Browser Behavior Module)은 브라우저의 처리속도를 개선하여 사용자가 데이터를 빠르게 조회할 수 있게 한다. OBBM은 검색엔진의 연산을 최적화하는 PSES(Parallel Search Engine Sub-Module)과 이미지 텍스트 등의 로드를 최적화하는 OILS(Optimized Image Loading Sub-Module)로 구성된다. 제안하는 OOPP의 성능분석 결과 CSM로 분석된 데이터의 정확도는 최대 100%, 최소 99.4%로 실제 광고와 분석된 데이터의 차이가 거의 발생하지 않았으며, OBBM을 이용한 브라우저 최적화를 실행하면, 작업시간이 약 68.37%가 감소한다. 결과적으로 OOPP는 직현재 직업정보 사이트의 구인 광고를 정확하게 분석하여 사용자가 분석한 결과를 웹페이지에서 신속하게 조회할 수 있다.

• 한국산학기술학회논문지
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• 제12권5호
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• pp.2124-2132
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• 2011

이 연구의 목적은 u-Campus 환경에서 교수능력(teaching skill)을 향상시키기 위한 평가시스템을 설계 개발하는데 있다. 이러한 목적을 달성하기 위하여 수업효율성과 교수평가에 관한 이론을 고찰 분석하여 시스템에 포함되어야 할 효율적인 교수능력향상 평가 요소를 추출하였다. 추출된 평가요소를 바탕으로 u-Campus 환경에서 교수능력 향상을 위한 교수평가, 코칭, 자기성찰, 포트폴리오, 평가자 선정 및 포트폴리오 공유에 대한 교수자 권한, 유비쿼터스기술 등을 반영하여 시스템을 설계하고 프로토타입(prototype)을 개발하였다. 프로토타입의 개발은 기존의 평가 방법과 달리 교수 자신의 평가에서 시작하여 본인의 의지에 따라 평가자를 확대하기 때문에 평가에 대한 부담을 덜며 교수능력을 향상시킬 수 있다. 포트폴리오와 유비쿼터스 기술을 적용한 교수평가 시스템은 u-Campus 환경에서 진정한 교수능력 향상을 위한 새로운 평가 방법의 대안이 될 것이며 대학교육의 질적인 발전에 도움이 될 것이다.

• 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.

• 대한수학회지
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• 제47권1호
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• pp.17-28
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• 2010

In this paper we deal with linear chance-constrained optimization problems, a class of problems which naturally arise in practical applications in finance, engineering, transportation and scheduling, where decisions are made in presence of uncertainty. After giving the deterministic equivalent formulation of a linear chance-constrained optimization problem we construct a conjugate dual problem to it. Then we provide for this primal-dual pair weak sufficient conditions which ensure strong duality. In this way we generalize some results recently given in the literature. We also apply the general duality scheme to a portfolio optimization problem, a fact that allows us to derive necessary and sufficient optimality conditions for it.

• 대한수학회지
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• 제59권6호
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• pp.1153-1170
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• 2022

In this paper, we investigate the portfolio optimization problem under the SVCEV model, which is a hybrid model of constant elasticity of variance (CEV) and stochastic volatility, by taking into account of minimum-entropy robustness. The Hamilton-Jacobi-Bellman (HJB) equation is derived and the first two orders of optimal strategies are obtained by utilizing an asymptotic approximation approach. We also derive the first two orders of practical optimal strategies by knowing that the underlying Ornstein-Uhlenbeck process is not observable. Finally, we conduct numerical experiments and sensitivity analysis on the leading optimal strategy and the first correction term with respect to various values of the model parameters.

• ETRI Journal
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• 제43권2호
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• pp.246-259
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• 2021

Traditional wisdom on how late industrialized countries follow the technology trajectories of preceding economies is in need of reformation as these countries have attained industrial leadership in a growing number of fields. However, current understandings about these countries' development of their emerging technologies have yet to investigate the divergence of idiosyncratic technology trajectories. The aim of this paper was to explore how their knowledge production strategies in emerging technology sectors are diverging. Specifically, this research examines the changing patterns of knowledge production in quantum technology in South Korea and China by developing a knowledge portfolio and knowledge strategic diagram. According to the knowledge portfolio, the relative literature position differs. In the knowledge strategic diagram, there are diverging patterns in the emerging keywords sector. This paper contributes to the literature by demonstrating the diverging strategies of late industrialized countries in their transition from catch-up to post-catch-up paradigms and provides policy implications for countries developing an idiosyncratic trajectory in emerging technology sectors.

• 유통과학연구
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• 제17권3호
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• pp.69-83
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• 2019

Purpose - This paper investigates the long term impact of RFID investment on firm value in Korea. We wand to find out why the long term performance of some firm's RFID investment is better than others. To understand the dynamics of the long term returns from RFID investment announcements, we divide our events into groups for each of the independent firm characteristic variable such as investment time period, kind of markets, industries, solvency and growth potential. We composed portfolios based on the RFID investment announcement date for each group and evaluate the monthly abnormal excess returns. Research design, data, and methodology - Based on these calendar-time portfolios, we measure the long term returns from 86 RFID investment announcements of 46 firms from 2003 to 2017. We construct the calendar-time portfolio for 3, 6, 9, 12 months of holding periods. Using the weighted least squares method, we regress the raw monthly returns of the portfolios on the Fama-French model and Carhart(1997) model. As a result, we can get the estimated risk adjusted mean monthly abnormal excess return α_P for each of the calendar-time portfolio. Results - We found that early adopters, large firms, non-manufacturing firms have very significant excess returns. We also found modestly significant excess returns for financially stable firms and slow growing firms. Put together, top managers of the firms which plan to invest RFID should understand the strategic role of RFID adoption and the generalized business process of distribution information technology investment in Korea. Moreover, the findings of this paper provide useful trading strategies to the managers of large funds who are considering on investing in RFID adopting firms. Conclusions - Put together, the results of this paper give us a new insight into how the RFID and IT technology in general and other characteristic factors' interactions affect the long term performance of firms. Using the unbiased estimates of long term returns of the calendar-time portfolios, this paper extends the understandings on short term impact of RFID adoption of existing studies. This paper also extends the current understandings of firm characteristics that affect the long term performance of RFID adopting firms.

• 한국경영과학회:학술대회논문집
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• 한국경영과학회 1987년도 추계학술발표회 발표논문초록집; 중소기업협동조합중앙회, 서울; 31 Oct. 1987
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• pp.28-29
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• 1987

• 한국연소학회:학술대회논문집
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• 대한연소학회 2003년도 제27회 KOSCO SYMPOSIUM 논문집
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• pp.309-328
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• 2003

Catalytic combustion is the cleanest emissions technology that has been demonstrated for the gas turbine. It has been a primary part of the research portfolio for the Combustor and Heat Transfer Technology Group at Cranfield University since 1989. The Paper describes the background to studies in the Group, their evolution and presents some results for specific study areas and themes.