The paper produced an application that used Doppler radar sensor to prevent bicycle related accidents. Doppler radar sensor detects any approaching object and gives warning to the user through the danger detection algorithm of the application. The danger detection algorithm determines danger by comparing relative speed using the sensed approaching object and Doppler frequency. It also sends SMS to the preset contact to let him/her be informed of the critical situation in which the user lies when an accident happens. The experiment result showed that the algorithm judged danger by detecting the approach status and speed as well as sent out SMS to the set contact under the assumption that there was an accident.

요 약 동적 델타 헤징(Dynamic Delta Hedging)이란 옵션 발행자가 옵션의 만기정산금액(payoff)을 지급하기 위해 주기적으로 델타에 근거한 헤지 포지션을 조절함으로써 옵션의 payoff를 복제하고 옵션 가치변화에 따른 위험을 회피 하는 방법이다. 본 연구에서는 헤지에 있어서 주요 변수인 블랙-숄즈의 모형에 의해 산출된 델타의 대체 값을 찾기 위해 기계학습의 일종인 인공신경망 학습을 적용하여 옵션의 만기 시 헤지 비용의 최소화 및 차익 실현을 위한 방법 론을 제시하고자 한다. 기초자산의 현재가격, 변동성, 무위험이자율, 만기 등의 시장 상황 변화에 따른 다양한 시나리 오에 대한 실험을 통해 본 연구에서 제시하는 방법론의 성능을 분석하고 그 우수성을 보인다.Abstract Option issuers generally utilize Dynamic Delta Hedging(DDH) technique to avoid the risk resulting from continuously changing option value. DDH duplicates payoff of option position by adjusting hedge position according to the delta value from Black-Scholes(BS) model in order to maintain risk neutral state. DDH, however, is not able to guarantee optimal hedging performance because of the weaknesses caused by impractical assumptions inherent in BS model. Therefore, this study presents a methodology for dynamic option hedge using artificial neural network(ANN) to enhance hedging performance and show the superiority of the proposed method using various computational experiments.

Recently, with oil price jumping and environmental issues, Green ship is paid deep attention to by ship owner, operator, builder, class and government. Fuel efficiency and reduction of CO 2 emissions are expected to have a strong influence on the design and operation of merchant ships. Many ship owners and operators are seeking the more economic method by the best operating route and the application of reliable and effective energy saving devices. With the Energy Efficiency Design Index (EEDI) in 2013 attention will more than ever be focused at achieving maximum fuel economy in the hydrodynamic design of hull forms, their appendages and propellers. IMO requirements for CO 2 emission for ships will now be implemented for vessels ordered from 1st January 2013. So far, a lot of new idea and patents have been proposed, tested, claimed and applied for various kinds of ship type. This paper shows numerical and experimental work related to a study on a energy saving devices particularly for fuller ship such as merchant vessel of Tanker and Bulker. From the bare hull wake measurements, typical upper/lower asymmetry of hull wake at the propeller disk was found. The pre-swirl duct have been designed and reviewed to recover the loss of propeller running in that condition. The general function of the pre-swirl duct was set to work against this asymmetry of wake and generate pre-swirled flow into the propeller against the propeller rotating direction.

This study solves the decision making problems for TFT-LCD manufacturing supply chain with demand and price uncertainties by establishing robust production and distribution strategies. In order to control the decisions regarding production graded by quality, inventory level and distribution, this study develop scenario model based stochastic mixed integer linear programs (SMILPs) that consider demand and price uncertainties as well as realistic constraints such as capacities etc. The performance of the solution obtained from the SMILPs using robust algorithms will be evaluated through various scenarios.

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