본 연구의 목적은 식품 중 안나토색소를 검출하기 위하여 주성분인 cis-bixin과 cis-norbixin의 동시분석법을 개발 하는 것이다. 최적 시험법 확립을 위해 국내외 기관 중 유럽식품안전청, 일본 후생노동성, 우리나라 식품의약품안전 평가원의 HPLC분석법들을 비교 및 검토하였다. 그리고 직선성, 검출한계, 정량한계 및 분석시간을 고려하여 최적 HPLC 동시분석조건을 선택 후 여러 식품에 적용가능한 최적 전처리법을 개발하였다. 식품의약품안전평가원 HPLC 분석법이 가장 우수한 직선성(R2≥0.999)을 보였으며, cisnorbixin 및 cis-bixin에 대한 검출한계와 정령한계가 각각 0.03과 0.05 μg/mL 그리고 0.097과 0.16 μg/mL로 낮게 나타났다. 모든 보고된 전처리방법은 여러 식품적용에 한계가 있었으며, 어육 및 육가공품, 가공치즈, 음료의 주요 세 식품군 모두에 대해서 높은 회수율을 보이는 최적 전처리법이 새롭게 확립되었다. 이 전처리 방법은 cis-norbixin과 cis-bixin에 대해서 98% 이상의 우수한 동시 회수율을 나 타냈었다. 새로운 전처리방법이 적용된 분석법은 두 성분에 대해 모두 결정계수(R2) 1로서 높은 직선성을 나타냈으며, 정확도(회수율)와 정밀도(%RSD)가 각각 평균 98% 및 0.4-7.9 이었다. 이러한 결과로부터 최적화된 분석시험법은 식품 중 안나토색소의 cis-norbixin과 cis-bixin 두 성분 동시분석에 매우 적합한 것으로 판단되었다.

This study explored the usefulness and implications of the Bayesian hyperparameter optimization in developing species distribution models (SDMs). A variety of machine learning (ML) algorithms, namely, support vector machine (SVM), random forest (RF), boosted regression tree (BRT), XGBoost (XGB), and Multilayer perceptron (MLP) were used for predicting the occurrence of four benthic macroinvertebrate species. The Bayesian optimization method successfully tuned model hyperparameters, with all ML models resulting an area under the curve (AUC) > 0.7. Also, hyperparameter search ranges that generally clustered around the optimal values suggest the efficiency of the Bayesian optimization in finding optimal sets of hyperparameters. Tree based ensemble algorithms (BRT, RF, and XGB) tended to show higher performances than SVM and MLP. Important hyperparameters and optimal values differed by species and ML model, indicating the necessity of hyperparameter tuning for improving individual model performances. The optimization results demonstrate that for all macroinvertebrate species SVM and RF required fewer numbers of trials until obtaining optimal hyperparameter sets, leading to reduced computational cost compared to other ML algorithms. The results of this study suggest that the Bayesian optimization is an efficient method for hyperparameter optimization of machine learning algorithms.

가거초 해양과학기지 자켓 구조물 내 콘크리트를 배제하고 강재로만 이루어진 최적설계를 제시한다. 50년 재현주기 극한하중조건에서 허용응력 및 허용응력비 조건을 모두 만족하는 안전한 경량 설계를 목표하였다. 역할에 따라 부재를 세 그룹으로 나눈 설계 조건 (Case-1)과 보다 세분화한 설계 조건(Case-2)에 대해 각 부재그룹별 현재 단면 두께 대비 두께 변화율을 설계변수로 설정한 유전 알고 리즘을 통해 최적설계를 탐색하였다. 그 결과 Case-1의 결과로 현재 가거초 해양과학기지보다 약 217톤 더 가벼운 설계(OPT-1)를 찾았고, Case-2에서는 추가적으로 약 84톤을 경량화하여 현재 대비 약 45%의 무게를 절감한 설계(OPT-2)를 얻을 수 있었다. 결론적으로 레그 내 콘크리트 보강 없이도 극한조건에서 허용응력 및 허용응력비를 모두 만족시킬 수 있는 경량화된 가거초 해양과학기지 설계를 제시하였다.

Spirulina platensis is a unique photosynthetic cyanobacterium that is used as a commercial feed for animals and a dietary supplement for humans. S. platensis has significant auto-flotation activity due to its gas vesicles. The natural flotation activity of these cells provides an effective method for harvesting of Spirulina biomass. The present research found that hydrodynamic pressure, light level and bicarbonate concentration affected the natural flotation of S. platensis. In particular, auto-flotation increased as light level decreased (5.5-times greater at no supplemental light than at 300 μ㏖ photons/㎡/s), as bicarbonate level increased (5-times higher at 0.6 than 0.2 M) and as hydrodynamic pressure decreased (indicated by depth of the culture). These results should be considered when designing photobioreactors for direct harvesting by auto-flotation.

Roridin E, produced by Podostroma cornu-damae, is a mycotoxin with anticancer activity. To increase the content of roridin E, submerged culture conditions were optimized using response surface methodology. Three factors, namely, medium initial pH, incubation time and agitation speed were optimized using a Box–Behnken design. The optimum submerged culture conditions to increase the content of roridin E included a medium with an initial pH of 4.0, an incubation time of 12.90 days, and an agitation speed of 63.03 rpm. The roridin E content in the submerged culture, under the aforementioned conditions, was 40.26 mg/L. The findings of this study can help lower the current price of roridin E and promote its related research.

This paper deals with a vehicle routing problem with resource repositioning (VRPRR) which is a variation of well-known vehicle routing problem with pickup and delivery (VRPPD). VRPRR in which static repositioning of public bikes is a representative case, can be defined as a multi-objective optimization problem aiming at minimizing both transportation cost and the amount of unmet demand. To obtain Pareto sets for the problem, famous multi-objective optimization algorithms such as Strength Pareto Evolutionary Algorithm 2 (SPEA2) can be applied. In addition, a linear combination of two objective functions with weights can be exploited to generate Pareto sets. By varying weight values in the combined single objective function, a set of solutions is created. Experiments accomplished with a standard benchmark problem sets show that Variable Neighborhood Search (VNS) applied to solve a number of single objective function outperforms SPEA2. All generated solutions from SPEA2 are completely dominated by a set of VNS solutions. It seems that local optimization technique inherent in VNS makes it possible to generate near optimal solutions for the single objective function. Also, it shows that trade-off between the number of solutions in Pareto set and the computation time should be considered to obtain good solutions effectively in case of linearly combined single objective function.

This paper describes an adaptive hybrid evolutionary firefly algorithm for a topology optimization of truss structures. The truss topology optimization problems begins with a ground structure which is composed of all possible nodes and members. The optimization process aims to find the optimum layout of the truss members. The hybrid metaheuristics are then used to minimize the objective functions subjected to static or dynamic constraints. Several numerical examples are examined for the validity of the present method. The performance results are compared with those of other metaheuristic algorithms.

본 연구에서는 복분자 콤부차의 최적 배합비를 찾고 이화학적 특성과 항산화 활성을 알아보았다. 반응표면분석법을 통해 복분자 콤부차의 최적 배합비는 홍차 농도 10% (w/v), 복분자 농도 8.09% (w/v)로 나타났고 이 배합비로 홍차 발효 주정에 복분자 당침액과 균을 첨가하여 14일간 초산 발효와 젖산 발효 과정을 통해서 산도 4%와 pH 2.77인 콤부차를 만들 수 있었다. 복분자 콤부차의 주요 유기산은 acetic acid, lactic acid, oxalic acid로 나타났으 며 그 중에서 acetic acid가 3,705.34 mg/100 mL로 가장 높았다. 발효 후 총 폴리페놀의 함량은 763.33 μg CE/mL 로 발효 전보다 증가하였으나 콤부차 발효 후 DPPH, ABTS 라디칼 소거활성을 측정한 결과 항산화활성은 각각 46.09%, 89.81%로 발효 전보다 감소하는 것을 확인할 수 있었다. 또한 반응표면분석법을 통해 얻은 최적 배합비의 종속변수 예측값과 최적 배합비 콤부차 실험값의 산도의 평균차는 0.065, 유기산의 평균차는 0.041, ABTS 라디칼 소거활성의 평균차는 0.061이므로 예측값과 실험값은 유사 하다.

A60 급 갑판 관통 관은 선박과 해양플랜트에서 화재사고가 발생할 경우 화염의 확산을 방지하고 인명을 보호하기 위해 수평구조에 설치되는 방화장치이다. 본 연구에서는 다양한 대리모델과 다중 섬유전자 알고리즘을 이용하여 A60 급 갑판 관통 관의 방화설계에 대한 이산변수 근사최적화를 수행하였다. A60 급 갑판 관통 관의 방화설계는 과도 열전달해석을 통해 평가하였다. 근사최적화에서 관통 관의 길이, 지름, 재질, 그리고 단열재의 밀도는 이산설계변수로 적용하였고, 제한조건은 온도, 생산성 및 가격을 고려하였다. 대리모델 기반의 근사최적설계 문제는 제한조건을 만족하면서 A60 급 갑판 관통 관의 중량을 최소화할 수 있는 이산설계변수를 결정하도록 정식화 하였다. 반응표면모델, 크리깅, 그리고 방사기저함수 신경망과 같은 다양한 대리모델이 근사최적화에 사용되었다. 근사최적화의 정확도를 검토하기 위해 최적해의 결과는 실제 계산 결과와 비교하였다. 근사최적화에 사용된 대리모델 중 방사기저함수 신경망 모델이 A60 급 갑판 관통 관의 방화설계에 대해 가장 정확한 최적설계 결과를 나타내었다.

The most important factor in the processing of composite materials is the creation of burrs. In order to minimize the generation of burrs, the preceding researchers changed the shape and processing conditions of the tool. The developed composite material using carbon and aramid fibers has limitations in reducing the formation of burrs. In this study, in order to solve this problem, by applying a jig under the test piece during drilling, it was possible to perform high-quality hole processing with minimal burr generation.

This study wanted to optimize the radiator tank's deformation assembled on the automotive engine block. Among the experimental planning methods, the Taguchi method was used to find optimal molding conditions to minimize plastic covers' deformation. The four main factors used in the Taguchi method were selected as the main factors: resin temperature, pressure time, coolant temperature, and cooling time. The number of cycles for each factor was divided into five stages, and a total of 25 experiments were conducted. The experiment used the Moldflow program, an injection molding analysis program. The maximum deformation obtained under the existing molding conditions was about 1.318mm. Still, the deformation of the mold applied with the optimal molding conditions obtained using the Taguchi method was approximately 1.273mm, which showed that the maximum deformation was reduced by 3.4% compared to the existing molding conditions.

In this study, a welding heat source model was presented and verified during fiber laser welding. The multi-layered heat source model is a model that can cover most of existing studies and can be defined with a simple formula. It consists of a total of 12 parameters, and an optimization algorithm was used to find them. As optimization algorithms, adaptive simulated annealing, multi island genetic algorithm, and Hooke-Jeeves technique were applied for comparative analysis. The parameters were found by comparing the temperature distribution when the STS304L was bead on plate welding and the temperature distribution derived through finite element analysis, and all three models were able to derive a model with similar trends. However, there was a deviation between parameters, which was attributed to the many variables. It is expected that a more clear welding heat source model can be derived in subsequent studies by giving a guide to the relational expression and range between variables and increasing the temperature measurement point, which is the target value.

Weight-based exercise equipment is unreasonable because of its large weight or volume and has limitations in use at home. On top of that, it is not easy to control the weight of domestic muscular exercise devices such as dumbbells and latex bands. This study proposes a new type of exercise equipment that can be used at home by modifying the exercise equipment used in fitness centers. Home training exercise equipment has been optimized by replacing the weight of strength training equipment, which is the core of weight control, with electric motors. For optimal design, process integration and design optimization (PIANO), a commercial PIDO tool, was analyzed in conjunction with DAFUL, a multi-body dynamics analysis program. When formulating the optimal design, the objective function was to minimize the weight, and the shape of the pinwheel and pulley used in exercise equipment was proposed considering the stress of cables as design constraints. As a result of optimization, design proposals were derived while meeting the design requirements and reduced by 5% compared to the initial model. In this work, we have miniaturized the shape of exercise equipment compared to conventional exercise equipment by optimizing its shape.

Welding is the most widely used technology for manufacturing in the automobile, and shipbuilding industries. Fiber laser welding is rapidly introduced into the field to minimize welding distortion and fast welding speed. Although it is advantageous to use finite element analysis to predict welding distortion and find optimized welding conditions, there are various heat source model for fiber laser welding. In this study, a welding heat source was proposed using a multi-layered heat source model that encompasses most of the existing various welding heat source models: conical shape, curved model, exponential model, conical-cylindrical model, and conical-conical model. A case study was performed through finite element analysis using the radius of each layer and the ratio of heat energy of the layer as variables, and the variables were found by comparing them with the actual experimental results. For case study, by applying Adaptive simulated annealing, one of the global optimization algorithms, we were able to find the heat source model more efficiently.