본 연구에서 흰목이버섯의 추출조건별 추출수율과 기능성 성분의 함량을 비교하여 최적 추출조건을 분석하였으며, 모든 분석에서 R²이 0.9331~0.9462로 유의성을 보이는 것을 확인하였다. 각 독립변수에 따른 추출수율과 ergothioneine, β-glucan 성분을 분석한 결과 추출수율은 추출온도와 추출시료농도에 반비례했으며, 추출시간에는 큰 영향이 없었다. Ergothioneine 성분은 온도가 증가할수록 증가하며, 추출시간은 4.33 h가 가장 높았고 시료량에 큰 영향이 없었다. β-glucan 성분은 온도가 증가할수록 감소했으며, 추출시간에 큰 영향이 없었고 시료량이 21.2 mg/mL에서 가장 높았다. 모든 종속변수의 최대 독립변수는 온도 60 o C, 추출시간 4.33 h, 추출시료농도 16.6 mg/mL에서 추출수율 24.9%, ergothioneine 성분함량 66.8 ug/g, β-glucan 성분함량 34.9 g/100 g으로 나타났다.

생강의 기능성 소재화를 위해 흑생강을 제조함에 있어 숙성 조건 최적화를 위한 숙성 온도(75.0~90.0℃, X1)와 시간(18.0~72.0 hr, X2)을 독립변수로 하고 중심합성계획에 따른 11구간의 조건에서 제조된 흑생강의 이화학적 특성 및 항산화 활성을 측정하였다. 흑생강의 수율은 모든 조건에서 60% 이상이었다. 흑생강의 명도와 황색도, 6-shogaol, 총 페놀 및 플라보노이드 함량은 숙성 온도가 높고 시간이 길어질수록 증가되는 경향이었다. 특히 흑생강의 6-shogaol, 총 페놀 함량 및 항산화 활성은 90℃에서 45 hr 숙성 시 최대값을 보였다. 반응표면분석법에 의한 흑생강의 제조 시 예측된 최적 조건은 89.97℃ 및 21.60 시간이었으며, 실측값은 예측값의 92.7~101.6%의 범위였다.

Investors aim to maximize the return rate for their own investment, utilizing various information as possible as they can access. However those investors, especially individual investors, have limitations of interpretation of the domain-specific information or even the acquisition of the information itself. Thus, individual investors tend to make decision affectively and frequently, which may cause a loss in returns. This study aims to analyze analysts’ target price and to suggest the strategy that could maximize individual’s return rate. Most previous literature revealed that the optimistic bias exists in the analysts’ target price and it is also confirmed in this study. In this context, this study suggests the upper limit of target rate of returns and the optimal value named ‘alpha(α)’ which performs the adjustment of proposed target rate to maximize excess earning returns eventually. To achieve this goal, this study developed an optimization problem using linear programming. Specifically, when the analysts’ proposed target rate exceeds 30%, it could be adjusted to the extent of 59% of its own target rate. As apply this strategy, the investors could achieve 1.2% of excess earning rate on average. The result of this study has significance in that the individual investors could utilize analysts’ target price practically.

With the spread of smart manufacturing, one of the key topics of the 4th industrial revolution, manufacturing systems are moving beyond automation to smartization using artificial intelligence. In particular, in the existing automatic machining, a number of machining defects and non-processing occur due to tool damage or severe wear, resulting in a decrease in productivity and an increase in quality defect rates. Therefore, it is important to measure and predict tool life. In this paper, v-ASVR (v-Asymmetric Support Vector Regression), which considers the asymmetry of є-tube and the asymmetry of penalties for data out of є-tube, was proposed and applied to the tool wear prediction problem. In the case of tool wear, if the predicted value of the tool wear amount is smaller than the actual value (under-estimation), product failure may occur due to tool damage or wear. Therefore, it can be said that v-ASVR is suitable because it is necessary to overestimate. It is shown that even when adjusting the asymmetry of є-tube and the asymmetry of penalties for data out of є-tube, the ratio of the number of data belonging to є-tube can be adjusted with v. Experiments are performed to compare the accuracy of various kernel functions such as linear, polynomial. RBF (radialbasis function), sigmoid, The best result isthe use of the RBF kernel in all cases

This paper proposes a methodology for gantry route optimization in order to maximize the productivity of a odd-type surface mount device (SMD). A odd-type SMD is a machine that uses a gantry to mount electronic components on the placement point of a printed circuit board (PCB). The gantry needs a nozzle to move its electronic components. There is a suitability between the nozzle and the electronic component, and the mounting speed varies depending on the suitability. When it is difficult for the nozzle to adsorb electronic components, nozzle exchange is performed, and nozzle exchange takes a certain amount of time. The gantry route optimization problem is divided into the mounting order on PCB and the allocation of nozzles and electronic components to the gantry. Nozzle and electronic component allocation minimized the time incurred by nozzle exchange and nozzle-to-electronic component compatibility by using an mixed integer programming method. Sequence of mounting points on PCB minimizes travel time by using the branch-and-price method. Experimental data was made by randomly picking the location of the mounting point on a PCB of 800mm in width and 800mm in length. The number of mounting points is divided into 25, 50, 75, and 100, and experiments are conducted according to the number of types of electronic components, number of nozzle types, and suitability between nozzles and electronic components, respectively. Because the experimental data are random, the calculation time is not constant, but it is confirmed that the gantry route is found within a reasonable time.

In this study, a model to optimize residual chlorine concentrations in a water supply system was developed using a multi-objective genetic algorithm. Moreover, to quantify the effects of optimized residual chlorine concentration management and to consider customer service requirements, this study developed indices to quantify the spatial and temporal distributions of residual chlorine concentration. Based on the results, the most economical operational method to manage booster chlorination was derived, which would supply water that satisfies the service level required by consumers, as well as the cost-effectiveness and operation requirements relevant to the service providers. A simulation model was then created based on an actual water supply system (i.e., the Multi-regional Water Supply W in Korea). Simulated optimizations were successful, evidencing that it is possible to meet the residual chlorine concentration demanded by consumers at a low cost.

This study analyzed the appropriate placement method by floor for evacuating all occupants during the nighttime through evacuation simulation. The analysis results are as follows. First, when non-self evacuating patients were placed on the first floor, 266 patients and 6 workers were found to be evacuated after 460 seconds. This result shows that it is meaningful to place non-self evacuating patients on the lower floor with a time that is faster than 540 seconds, which is an evaluation criterion set using life Safety standards for human. This result is a time faster than the evaluation criteria of 540 seconds, which is set using the life safety standards, and it can be confirmed that it is meaningful to place non-self evacuating patients on the lower floor. Next, as a result of placing non-self evacuating patients from the first floor to the fourth floor, it was found that evacuation of all occupants required 460 seconds for the first floor, 834 seconds for the second floor, 1,508 seconds for the third floor, and 1,915 seconds for the fourth floor. These results indicate that the placement of non-self evacuating patients on the rest of the floors, except for the first floor, can lead to dangerous results in excess of 540 seconds, which is a flashover time. As a result, it is necessary to place non-self evacuating patients on a lower floor for safe evacuation. The study has limitations except for comparative analysis of changes in evacuation time due to changes in the number of workers at eldery care hospitals and situations in which fire-fighting facilities such as sprinkler facilities operated. It is necessary to study the evacuation time linked to the operation of the fire-fighting facilities and the evacuation time according to the change in the number of workers in the future.

The estimation of heat source model is very important for heat transfer analysis with finite element method. Part I of this study used adaptive simulated annealing which is one of the global optimization algorithm for anticipating the parameters of the Goldak model. Although the analysis with 3D model which depicted the real situation produced the correct answer, that took too much time with moving heat source model based on Fortran and Abaqus. This research suggests the procedure which can reduce time with maintaining quality of analysis. The lead time with 2D model is reduced by 90% comparing that of 3D model, the temperature distribution is similar to each other. That is based on the saturation of heat transfer among the direction of heat source movement. Adaptive simulated annealing with 2D model can be used to estimate more proper heat source model and which could enhance to reduce the resources and time for experiments.