The purpose of this study was to optimize dough properties using response surface methodology (RSM) and to demonstrate the performances of dough prepared under optimized conditions. Dough mixed with yeast, margarine, salt, sugar and wheat flour was prepared by fermentation process. Hardness, cohesiveness and springiness of dough were selected as critical quality attributes. The critical formulations (yeast and water) and process (fermentation time) variables were selected as critical input variables based on preliminary experiment. Box-Behnken design (BBD) was used as RSM. As a result, the quardratic, the squared and the linear model respectively provided the most appropriate fit (R2>90) and had no significant lack of fit (p>0.05) on critical quality attributes (hardness, cohesiveness and springiness). The accurate prediction of dough characteristics was possible from the selected models. It was confirmed by validation that a good correlation was obtained between the actual and predicted values. In conclusion, the methodologies using RSM in this study might be applicable to the optimization of fermented foods containing various wheat flour and yeast.

Airline schedules are highly dependent on various factors of uncertainties such as unfavorable weather conditions, mechanical problems, natural disaster, airport congestion, and strikes. If the schedules are not properly managed to cope with such disturbances, the operational cost and performance are severely affected by the delays, cancelations, and so forth. This is described as a disruption. When the disruption occurs, the airline requires the feasible recovery plan returning to the normal operations in a timely manner so as to minimize the cost and impact of disruptions. In this research, an Ant Colony Optimization (ACO) algorithm with re-timing strategy is developed to solve the recovery problem for both aircraft and passenger. The problem consists of creating new aircraft routes and passenger itineraries to produce a feasible schedule during a recovery period. The suggested algorithm is based on an existing ACO algorithm that aims to reflect all the downstream effects by considering the passenger recovery cost as a part of the objective function value. This algorithm is complemented by re-timing strategy to effectively manage the disrupted passengers by allowing delays even on some of undisrupted flights. The delays no more than 15 minutes are accepted, which does not influence on the on-time performance of the airlines. The suggested method is tested on the real data sets from 2009 ROADEF Challenge, and the computational results are compared with the existing ones on the same data sets. The method generates the solution for most of problem set in 10 minutes, and the result generated by re-timing strategy is discussed for its impact.

PURPOSES: Pavement Management System contains the data that describe the condition of the road. Under limited budget, the data can be utilized for efficient plans. The objective of this research is to develop a mixed integer program model that maximizes remaining durable years (or Lane-Kilometer-Years) in road maintenance planning. METHODS: An optimization model based on a mixed integer program is developed. The model selects a cluster of sectors that are adjacent to each other according to the road condition. The model also considers constraints required by the Seoul Metropolitan Facilities Management Corporation. They select two lanes at most not to block the traffic and limit the number of sectors for one-time construction to finish the work in given time. We incorporate variable cost constraints. As the model selects more sectors, the unit cost of the construction becomes smaller. The optimal choice of the number of sectors is implemented using piecewise linear constraints. RESULTS: Data (SPI) collected from Pavement Management System managed by Seoul Metropolitan City are fed into the model. Based on the data and the model, the optimal maintenance plans are established. Some of the optimal plans cannot be generated directly in existing heuristic approach or by human intuition. CONCLUSIONS: The mathematical model using actual data generates the optimal maintenance plans.

흰목이(Tremella fuciformis)는 전 세계적으로 약 40여종이 있으며, 아열대, 열대, 온대지방 등에서 폭넓게 분포하고 있다. 흰목이는 중국고전에서 양귀비가 즐겨먹었다고 나올 정도로 예로부터 미의 상징으로 여겨지기도 하였다. 실제로 흰목이 추출물이 세포의 멜라닌형성 억제를 유도하여 피부미백효과가 있고, UV 자극 손상으로 유발되는 주름을 예방하여 주름개선 효과를 나타낸다고 알려져 있다. 또한 흰목이는 미용에 관련 된 효과 뿐 아니라 당뇨병과 고혈압에서도 효능을 가지고 있고, 면역력을 높여주어 항암효과가 있다고 밝혀져 있다. 흰목이는 중국 사천성에서 최초로 재배했다고 기록되어 있으며, 현재는 중국과 동남아시아에서 생산되고 있다. 중국에서는 이미 흰목이 대량인공재배에 성공하였으나, 국내에서는 대량인공재배에 관한 연구가 많이 이루어지지 않고있다. 따라서 대량인공재배에 관한 연구를 하기 전 단계로, 흰목이의 표준 재 배법 확립을 위한 최적 배양조건을 구명하기 위해, 농과원에서 분양받은 흰목이 균주를 이용하여 실험을 진행하였다. 배지 종류로는 PDA, MCM, YM, CDA 등 4종류를 이용하였고, 배양실(25°C)에서 흰목이 균주의 최적 배양조건을 탐색하였다.

In this study, we propose a method of optimal placement technique of artificial reef considering characteristics of sea areas and provide basic data for efficient budget execution. In addition, we will contribute to increasing the economic efficiency by improving the fisheries productivity by suggesting the scientific basis for the policy data and the increase of the catch through the resource creation based on the ecological information about the biology. Especially, in order to establish the effective disposition (optimum separation distance) of artificial reef considering characteristics of biological and engineering factors, it is necessary to review the artificial reef installation management regulations and investigate the biological effects of artificial reef facilities, is needed. Through this, it is expected that the ground data of the direction of the policy promotion will be derived by suggesting the placement condition of the artificial reef complex which can maximize the resource composition effect according to the target fish species.