선주와 운영사 분리의 시장위험 분할효과 분석

윤희성(Hee-Sung Yun),조성순(Seong-Soon Cho) 한국무역연구원 2021 무역연구 Vol.17 No.5

Purpose - There are three different business models in shipping: owner-operators, operators, and owners. This paper analyzes the effect of separating owner-operators into tonnage providers and operators, and considers this effect from the perspective of risks and returns. Design/Methodology/Approach - A historical simulation was performed to measure realized operating profits and the volatility of each type of player. Time series data from 1992 was adopted from Clarkson Research and Drewry Maritime Research to simulate revenues, capital costs, and operating costs for 229 investment cases. A bootstrap sampling enhances the robustness of the results. Findings - The results show that the operating profits of owner-operators are divided into those of two separate players. The same, however, cannot be said for market risk. Against general expectations, operator market risk was not significantly reduced by separation; in the case of Panamax, it even increased. This can be explained by a negative correlation between spot rates and actually-applied time charter rates. Research Implication - Most papers on market risk have so far focused on the measurement and forecast of return volatility. This paper, on the other hand, is a novel attempt to analyze the effect of business model separation on market risk. The public-sector owner model is widely discussed in Korean shipping circles, and this paper is expected to provide meaningful insight to policymakers. Additionally, the risk-return profile of the pure owner model provides a good basis to develop the model for the balanced growth of the Korean shipping industry.

성능 모니터링 이벤트들의 통계적 분석에 기반한 모바일 프로세서의 전력 예측

윤희성(Hee-Sung Yun),이상정(Sang-Jeong Lee) 한국정보과학회 2009 정보과학회 컴퓨팅의 실제 논문지 Vol.15 No.7

제한된 용량의 배터리로 동작해야 하는 모바일 시스템에서는 소프트웨어 설계 시 성능뿐만 아니라 전력소모도 고려해야 한다. 따라서 소프트웨어의 실행 중에 전력소모를 정확하게 예측할 수 있으면 전력과 성능을 고려한 효율적인 소프트웨어의 설계가 가능해진다. 본 논문에서는 모바일 프로세서의 전력소모 예측을 위해 정량적으로 프로세서의 동작을 분석하고 모델링 하는 통계적인 분석 방법을 제안한다. 제안된 방식은 다양한 벤치마크 프로그램들을 실행하여 프로세서의 성능 모니터링 이벤트들과 전력소모 데이터를 수집한 후 계층적 클러스터링(hierarchical clustering)분석 등을 적용하여 서로 중복되지 않으면서 전력소모에 크게 기여하는 대표적인 성능 모니터링 이벤트들을 추출한다. 전력 예측 모델은 선택된 성능 모니터링 이벤트들이 독립변수가 되고 전력소모가 종속변수가 되는 회귀분석(regression analysis)을 수행하여 개발한다. 전력 예측 모델은 Intel XScale 아키텍처 기반의 PXA320 모바일 프로세서에 적용하여 평균 4% 이내의 에러율로 전력소모를 예측할 수 있음을 보인다. In mobile systems, energy efficiency is critical to extend battery life. Therefore, power consumption should be taken into account to develop software in addition to performance. Efficient software design in power and performance is possible if accurate power prediction is accomplished during the execution of software. In this paper, power estimation model is developed using statistical analysis. The proposed model analyzes processor behavior quantitatively using the data of performance monitoring events and power consumption collected by executing various benchmark programs. And then representative hardware events on power consumption are selected using hierarchical clustering. The power prediction model is established by regression analysis in which the selected events are independent variables and power is a response variable. The proposed model is applied to a PXA320 mobile processor based on Intel XScale architecture and shows average estimation error within 4% of the actual measured power consumption of the processor.

반응표면법을 이용한 DC솔레노이드 밸브의 형상 최적화

윤희성(Hee Sung Yoon),황인성(In Sung Hwang),고창섭(Chang Seop Koh),김동수(Dong Soo Kim),윤소남(So Nam Yun) 대한전기학회 2006 대한전기학회 학술대회 논문집 Vol.2006 No.7

DC솔레노이드 밸브의 성능을 나타내기 위해 여러 가지 중요한 파라메터들이 존재한다. 최소 혹은 최대 스트로크 시의 흡입력, 온도상승, 소비전력 그리고 동작시간 등이 있다. 본 논문에서는 동작시간을 최소화시키기 위해 반응표면법을 이용하여 DC솔레노이드 밸브의 형상 최적화를 수행하였고 그 결과를 유한요소법을 이용하여 검증한다.

반응표면법을 이용한 최소동작시간을 갖는 DC 솔레노이드 밸브의 형상 최적 설계

尹熙盛(Hee Sung Yoon),黃仁聖(In Sung Hwang),金東洙(Dong Soo Kim),尹蘇南(So Nam Yun),高彰燮(Chang Seop Koh) 대한전기학회 2006 전기학회논문지 B Vol.55 No.9

In general, a DC solenoid valve is evaluated by the performances such as the attraction force at maximum and minimum strokes, temperature rising, power consumption and time of action. The importance of each performance may be different according to the specific application purpose. When the temperature rising and power consumption are fixed, however, the performance of DC solenoid valve is usually evaluated by the attraction force at maximum and minimum strokes and time of action. In this paper, the shape of the pole face of plunger and core is optimized to increase the attraction force at maximum stroke, and thereby to minimize the time of action. For the shape optimization, (1+1) evolution strategy is incorporated with the response surface method(RSM) and finite element method(FEM).

현훈(眩暈) 치험(治驗) 2례(例)

김규석,윤희성,박외숙,김희정,김윤범,Kim, Keoo-Seok,Yun, Hui-Sung,Park, Owe-Suk,Kim, Hee-Jeong,Kim, Yoon-Bum 대한한방안이비인후피부과학회 2005 한방안이비인후피부과학회지 Vol.18 No.3

Damum(痰飮) is a kind of pathologic secretion products that excessive water is accumulated in a part of body. Damhun(痰暈) is the vertigo induved by Damum(痰飮). We experienced two clinical cases treated vertigo by orietal medicine(herbal medication, acupuncture). 33-years old male and 63-years old female patients had Damhun(痰暈), vertigo by Damum(痰飮). We administered Banhabaechulcheoma-tang(Pansiabaichutienma-tang) and Yeonggyechulgam-tang(Lingguishugna-tang) to each Patient, and two Patients improved vertigo and referred symptoms. In other words, this study is that We did not limited peripheral vertigo to vestibular system, made a diagnosis of Damum(痰飮) and treated vertigo by orietal medicine(herbal medication, acupuncture) referred to many medical practitioner of many generations. We suggest that digestive sypmtom(related to Damum(痰飮), abdominal examination and stool frequency are closely associated with vertigo and could be estimated prognosis of vertigo.

Supramax Bulk Carrier Market Forecasting with Technical Indicators and Neural Networks

임상섭(Sang-Seop Lim),윤희성(Hee-Sung Yun) 한국항해항만학회 2018 한국항해항만학회지 Vol.42 No.5

Supramax bulk carriers cover a wide range of ocean transportation requirements, from major to minor bulk cargoes. Market forecasting for this segment has posed a challenge to researchers, due to complexity involved, on the demand side of the forecasting model. This paper addresses this issue by using technical indicators as input features, instead of complicated supply-demand variables. Artificial neural networks (ANN), one of the most popular machine-learning tools, were used to replace classical time-series models. Results revealed that ANN outperformed the benchmark binomial logistic regression model, and predicted direction of the spot market with more than 70% accuracy. Results obtained in this paper, can enable chartering desks to make better short-term chartering decisions.

순환신경망 모델을 활용한 벌크 운임지수 예측

임상섭(Sang Seop Lim),윤희성(Hee Sung Yun) 한국해양비즈니스학회 2018 해양비즈니스 Vol.- No.40

One of the characteristics of the shipping market is extreme volatility. The play in the volatile market requires players to make cautious decisions based on scientific analysis. Market risk management is of utmost importance in the shipping market and market forecasting is an important element in the management process. This paper deals with forecasting issues in the dry bulk shipping market. Despite the fact that bulk shipping is dominated by spot trading, there are few papers that apply scientific models to short-term forecasting. This paper employs recurrent neural networks that currently draws attention in time-series forecasting. More specifically, Elman neural networks and Jordan neural networks were applied to improve the forecasting performance over traditional econometric models and simple multi-layer perceptron models. Monthly observations of the BDI, BCI and BPI were used for spot forecasting. The result showed that the proposed two models outperformed the ARIMA model and the MLP model. The Elman model performed better for the time series with high volatility and the Jordan model demonstrated better performance for the time series with a modest volatility. The BDI is composed of sub-indices with varying levels of volatility. Hence in the case of the BDI forecast, the Jordan networks performed better than the Elman networks. The results will provide scientific grounds for chartering managers to make better decisions concerning the most active spot transactions.

케이프선 시장 운임의 결정요인 및 운임예측 모형 분석

임상섭(Sang Seop Lim),윤희성(Hee Sung Yun) 한국항해항만학회 2018 한국항해항만학회지 Vol.42 No.6

운임시장의 심한 변동성과 시계열 데이터의 불안정성으로 해운시황 예측에 대한 연구가 큰 성과를 내지 못하고 있지만 최근 대표적인 비선형 모델인 기계학습모델을 적용한 연구들이 활발히 진행되고 있다. 대부분의 기존 연구가 계량모델의 설계단계에서 입력변수에 해당하는 요인들을 기존 문헌연구와 연구자의 직관에 의존하여 선정했기 때문에 요인선정에 대한 체계적인 연구가 필요하다. 본 연구에서는 케이프선 운임을 대상으로 단계적 회귀모형과 랜덤포레스트모델을 이용하여 중요 영향요인을 분석하였다. 해운시장에서 비교적 단순한 수급구조를 가져 요인파악이 용이한 케이프선 운임을 대상으로 하였으며 총 16개의 수급요인들을 사전 추출하였다. 요인간의 상호관련성을 파악하여 단계적 회귀는 8개 요인, 랜덤포레스트는 10개 요인을 분석대상으로 선정하였으며 선정된 변수를 입력변수로 하여 예측한 결과를 비교하였다. 랜덤포레스트의 예측성능이 아주 우수하였는데 수요요인이 주로 선정된 단계적 회귀분석과는 달리 공급요인이 비중 있게 선정되었기 때문인 것으로 판단된다. 본 연구는 운임예측 연구에 있어 운임결정요인에 대한 과학적인 근거를 마련하였으며 이를 위해 기계학습 기반의 모델을 활용하였다는데 연구적 의의가 있다. 또한 시장정보의 분석에 있어 실무자들이 어떤 변수에 중점을 두어야 하는지에 대해 합리적 근거를 제시한 측면에서 해운기업의 의사결정에 실질적 도움이 될 것으로 기대된다. In recent years, research on shipping market forecasting with the employment of non-linear AI models has attracted significant interest. In previous studies, input variables were selected with reference to past papers or by relying on the intuitions of the researchers. This paper attempts to address this issue by applying the stepwise regression model and the random forest model to the Cape-size bulk carrier market. The Cape market was selected due to the simplicity of its supply and demand structure. The preliminary selection of the determinants resulted in 16 variables. In the next stage, 8 features from the stepwise regression model and 10 features from the random forest model were screened as important determinants. The chosen variables were used to test both models. Based on the analysis of the models, it was observed that the random forest model outperforms the stepwise regression model. This research is significant because it provides a scientific basis which can be used to find the determinants in shipping market forecasting, and utilize a machine-learning model in the process. The results of this research can be used to enhance the decisions of chartering desks by offering a guideline for market analysis.

UPnP 기반 RFID 서비스 발견

김동균 ( Dong-kyun Kim ),윤희성 ( Hee-sung Yun ),이상정 ( Sang-jung Lee ) 한국정보처리학회 2007 한국정보처리학회 학술대회논문집 Vol.14 No.2

RFID 인식 기술을 이용한 출입 통제 시스템은 RFID 태그가 개인의 신분을 나타내고 개별 인식을 통해 출입을 통제 관리한다. 시스템은 관리자의 휴대용 기기(PDA)나 PC 등과 같은 다양한 사무기기를 통한 모니터링 기능의 지원이 필요하다. 본 논문에서는 RFID 를 이용한 출입 통제 시스템을 구축하고 이상 징후 시 자동 알림 기능 지원 및 오피스 네트워크 애플리케이션들과 상호 운용이 용이한 UPnP 미들웨어를 적용한 UPnP 기반의 RFID 시스템을 설계 구현한다. 설계 구현된 시스템은 UPnP 기반의 RFID 서비스 발견 기술을 지원한다.

보안USB 시스템 환경에서의 안전한 사용자 인증 방안에 관한 연구

이선호(Sun-Ho Lee),윤희성(Hee-Sung Yun),강경호(Kang Kyung Ho),홍민(Min Hong),곽진(Jin Kwak),이임영(Im-Yeong Lee) 한국통신학회 2009 한국통신학회 학술대회논문집 Vol.2009 No.6