In this study, domestic soybean cultivars were extracted using water, 70% ethanol, and 100% ethanol. The contents of polyphenols, flavonoids, and antioxidant activities of these extracts were measured. For the water extracts, the polyphenol content was significantly higher in the Daewon cultivar compared to the others. Ethanol extracts contained lower levels than the water extracts, and, unlike the water extracts, there was no significant difference between the cultivars. The flavonoid content in the Jinpung cultivar was the highest among the water extracts, and this content was greater in the water extract than in the ethanol extract. In terms of ABTS radical scavenging activity, Daewon and Taekwang exhibited significantly higher activity in the water extracts. The Jinpung cultivar showed the highest activity in the 70% ethanol extract, which was slightly lower than that of the water extract. DPPH radical scavenging activity was found to be higher in Taekwang than in the other cultivars. In the 70% ethanol extract, Taekwang demonstrated high antioxidant activity, similar to that of the water extract. A correlation analysis of antioxidant components and antioxidant activity in soybean cultivars revealed the highest r value of 0.9326 between the contents of flavonoid compounds and polyphenol compounds.

Phellinus linteus, a medicinal mushroom with potent antioxidant properties, contains bioactive compounds, such as polyphenols and flavonoids. To optimize the extraction of skin-whitening compounds, ultrasound-assisted extraction combined with statistically based optimization was used to simultaneously extract total polyphenol content (TPC), radical scavenging activity (RSA), and tyrosinase activity inhibition (TAI). Extraction variables, including extraction time (X1:4.8 ~ 55.2 min), extraction temperature (X2:26.4 ~ 93.6oC), and ethanol concentration (X3:13.0 ~ 97.0%), were varied in 17 experimental cycles based on a central composite design. Quadratic regression models for TPC, RSA, and TAI had coefficients of determination (R2) greater than 0.92, demonstrating well-fitted models and statistical significance. Analysis of variance revealed that all three variables significantly influenced extraction efficiency (p < 0.0041), with ethanol concentration (X3) having the most pronounced effect. The optimal extraction conditions were 80.0 min, 82.5oC, and 64.8% ethanol, yielding predicted values of 6.42 mg GAE/g DM for TPC, 73.71% for RSA, and 85.04% for TAI. These results suggest that a moderate ethanol concentration combined with adequate thermal input maximizes the extraction of antioxidant and tyrosinase inhibitory activities specifically associated with skin-whitening effects.

Synthesis of high-purity magnesium hydroxide using dolomite and bittern is important for use in various applications. We synthesized magnesium hydroxide using bittern and dolomite, which are domestic resources. In Bittern, there is a high concentration of Mg2+ ions, but the impurity Ca2+ ion content is also significant, requiring a purification process to remove it. There are two main methods for this purification. Firstly, there is a separation method that utilizes the difference in solubility between Mg2+ ions and Ca2+ ions by using sulfuric acid on dolomite. Adding MgSO4 solution from dolomite to Bittern removes Ca2+ ions as CaSO4. This process simultaneously purifies Ca impurities and increases the Mg/Ca ratio by adding extra Mg2+ ions. In this study, purified bittern was obtained by using dolomite and sulfuric acid to extract MgSO4, which was then used to purify Ca2+ ions. High-purity Mg(OH)2 was synthesized by optimizing the NaOH and NH4OH ratio as an alkaline precipitant. Mg(OH)2 synthesis technology made by effectively removing Ca ions from dolomite and bittern can contribute to domestic pilot production.

결빙되거나 적설이 있는 도로와 같이 마찰이 작은 노면에서는 일반 노면과 비교했을 때 제동거리가 크게 증가하기 때문에 심각한 교통사고로 이어질 수 있다. 이에 블랙 아이스(Black ice)와 같은 노면 위험을 감지 하기 위한 노면 분류 기술에 대한 연구가 지금까지 지속적으로 이루어지고 있다. ESC(Electronic Stability Control) 시스템은 차량 자세 제어를 통해 마찰이 작은 노면에서 차량의 미끄러짐 및 전복을 방지하는 능동 안전시스템(Active safety system)이다. ESC 시스템의 성능을 위해서는 정확한 노면 마찰 계수(Road friction coefficient) 추정을 통한 노면 분류가 중요하다. 최근의 노면 분류 기술은 카메라, LiDAR 등의 이미 지 기반의 방법에 중점을 두고 연구가 진행되고 있다. 그러나 이러한 이미지 기반의 방법들은 정확도가 낮을 뿐만 아니라 높은 계산 복잡도의 문제를 가지고 있다. 이뿐만 아니라 높은 비용으로 인해 상용화 측면에서도 단점을 드러내고 있다. 본 연구에서는 그림1처럼 센서 융합 기술을 활용하여 이미지 기반 방법의 문제점을 해결하고자 한다. 차량 횡방향 동역학 모델(Vehicle lateral dynamic model)을 선형화하여 칼만 필터(Kalman filter)를 적용한 노면 마찰 계수 추정 알고리즘을 설계하고, 기계학습(Machine learning) 모델을 적용하여 블랙 아이스 검출 알고 리즘을 설계한다. 전기차 CAN 버스로부터 얻을 수 있는 차량 종방향 가속도(Vehicle longitudinal acceleration)를 제어 입력으로 하고, 요 레이트(Yaw rate)를 측정값으로 하여 칼만 필터에 적용하여 차량 종 방향 속도(Vehicle longitudinal velocity)와 차량 횡방향 속도(Vehicle lateral velocity), 요 레이트, 차량 횡방 향 힘(Vehicle lateral force)을 추정한다. 이때 전통적인 칼만 필터 대신 EKF-UI(Extended kalman filter with unknown input)를 적용하여 시스템 행렬의 크기를 줄여 계산 복잡도를 감소시키고 차량의 거동 변화 를 보다 정확하게 반영할 수 있도록 하였다. 추정된 차량 종방향 속도, 차량 횡방향 속도, 요 레이트를 통해 사이드 슬립 각(Side slip angle)을 구해 사이드 슬립 각과 차량 횡방향 힘의 관계를 이용해 특징들을 찾아 기계학습 모델(e.g. 앙상블 기법, SVM 등)을 적용하여 블랙 아이스를 검출할 수 있다. MATLAB/Simulink SW 및 CarSim을 사용하여 개발한 알고리즘의 성능을 검증하였으며, 본 연구의 결과는 ESC 시스템의 성능 을 개선시켜 차량의 미끄러짐으로 인한 교통사고의 예방에 도움이 될 것으로 예상한다. 여기에 스마트 타이 어(Smart tire)의 센서도 추가해 노면과 타이어 사이의 직접적인 데이터를 추가해 검출 성능을 높일 것이다.

상수도 배관에서 누수 또는 이상을 감지하는 기계학습 및 인공신경망 분류 모델에 대한 연구가 활발히 진행되어 왔다. 그러나 누수음 데이터는 시간과 환경에 따라 계속 변동하기 때문에, 입력 데이터의 변화에도 일정 수준 이상의 분류 성능을 유지하는 분류 모델을 찾는 데 어려움이 있다. 본 연구에서는 모델 선택과 초매개변수 조정보다 데이터 전처리 방법이 분류 성능 향상에 더 큰 영향을 미친다는 점에 주목했다. 변동성이 큰 누수음의 특징을 효과적으로 추출하기 위해 푸리에 변환 및 MFCC(Mel-Frequency Cepstral Coefficients)를 사용하였으며, 일부 정보가 중복될 가능성을 고려하여 다중공선성에 덜 민감한 트리 기반 모델을 사용해 누수음의 분류 성능을 평가했다. 연구 결과, 푸리에 변환과 MFCC를 결합한 데이터 세트를 사용했을 때 LightGBM 모델의 분류 정확도가 84.62%로 나타났으며, 각각의 전처리 방법을 단독으로 사용했을 때보다 더 높은 성능을 달성하였다. 이 결과는 두 전처리 방법의 상호 보완적 특성이 분류 성능 향상에 기여했음을 입증하며, 상수도 관망 누수 탐지 시스템 개발에 중요한 기여를 할 것으로 기대된다.

This paper introduces a simple and reliable photometric calibration method to extract Hα line flux from narrowband images. The equivalent width of the Hα line (EWHα) is derived using two- and simplified three-filter methods. Synthetic photometry of CALSPEC stars demonstrates the dependency of EWHα on the V − R color, described by a skewed Gaussian function within −0.1 < V − R < 0.7. Systematic errors of the two- and three-filter methods are analyzed under 0%–10% R-band flux contamination. Although the three-filter method underestimates EWHα by 10%, it exhibits less scatter compared to the two-filter method. The simplified three-filter method was validated with the Landolt SA 107 field and surpasses the two-filter method in terms of precision and accuracy. Additionally, applying our method to V960 Mon yields EWHα consistent with high-resolution spectroscopic results.

In order support the design support system of small and medium-sized shipbuilding companies that carry out designs using 2D CAD, this study developed a system that automatically calculates the cable length by extracting the Y-axis value expressed as text data in 2D CAD. By setting the equipment where the cable starts and ends, the essential route and the installation rate were checked so that the optimal route of the cable could be calculated. As a result, the value calculated based on the optimal route and length of the cable by extracting the data of 2D CAD through this study was the same as the value previously calculated by the actual user, and the installation rate was less than 130% so there was no problem with the on-site installation. In addition, it was confirmed that the cable length calculated through this was reduced by about 7% compared to the existing work.

Nanoparticles, especially those derived from plant extracts, are becoming increasingly popular as a bio-based, environmentally friendly alternative to conventional technologies. The Maui rose, a flowering plant with medicinal and therapeutic properties, is one of the most important of these materials because its extract component has antibacterial, antioxidant and anti-inflammatory biological activity. In this work, we report on synthesizing and characterizing iron oxide nanoparticles (Fe2O3) extracted from flower plants (Borago), to create persistent and environmentally friendly antibacterial agents. As part of the chemical formation process, Fe2O3 nanoparticles were extracted from specific flower plants utilizing a series of carefully regulated chemical reactions. X-ray diffraction (XRD), scanning electron microscopy (SEM), Fourier transform infrared spectroscopy (FTIR), and atomic force microscopy (AFM) of the samples were studied. The nanoparticles produced were analyzed using common microbiological methods and studies (EDS). The antibacterial activity of the Fe2O3 nanoparticles and their effect on a range of microorganisms were evaluated. The results demonstrated that Fe2O3 nanoparticles were successfully synthesized with a specific crystal structure and good anti-bacterial activities.

Sage (Salvia officinalis) contains various active compounds, including flavonoids and terpenes. In this study, the terpenes content, including camphor, borneol, and eucalyptol, was analyzed. Both subcritical water and conventional solvent extraction methods were used. Using subcritical water extraction, the optimal extraction conditions were determined based on temperature and time to selectively extract the desired components from the sage. These optimal extraction conditions were as follows: camphor (130°C for 5 min, 2.73±0.39 mg/g), borneol (130°C for 5 min, 0.72±0.07 mg/g), and eucalyptol (150°C for 5 min, 0.51±0.03 mg/g). A comparison of extracts obtained via subcritical water extraction technology and various solvents revealed that the extracts obtained using subcritical water extraction had higher levels of all three components. This indicates that subcritical water extraction is more efficient and faster than traditional solvent extraction methods. Moreover, these results suggest that subcritical water extraction technology has the potential to be applied as an eco-friendly alternative to traditional extraction methods for obtaining active compounds like terpenoids.

다알리아(Dahlia pinnata Cav.)는 멕시코 아즈텍인들이 식용으로 재배하여 꽃잎은 샐러드로, 뿌 리는 식용이나 약재로 사용하였다. 그러나 현재는 대부분 화훼용으로 사용되고 있으며, 식용이나 약재로서 의 연구는 부족한 실정이다. 본 연구에서는 다알리아 꽃을 차로 제조하여 다양한 침출 조건과 제다법을 사 용하여 항산화 활성 및 생리활성 성분 함량을 평가하였다. 항산화 활성은 DPPH radial 소거 활성으로 평 가하였으며, 생리활성 성분은 총 폴리페놀 함량(TPC)과 총 플라보노이드 함량(TFC)을 분석하였다. 건조된 다알리아 꽃차는 90℃에서 침출하였을 때 가장 높은 생리활성물질을 추출할 수 있었으며, 적절한 침출 시 간은 8분, 침출 횟수는 3회가 적합하였다. 다양한 제다 방법 중에서 증제법이 가장 높은 항산화 활성을 보 였으며, 그 다음으로 생화, 건조, 덖기 순으로 나타났다. 증제된 다알리아 꽃차의 총 폴리페놀 함량과 플라 보노이드 함량은 각각 50.9 mg/g과 80.6 mg/g으로 건조된 녹차와 비교했을 때 폴리페놀 함량은 낮지만 플라보노이드 함량은 약 3배 높게 나타났다. 이러한 결과는 다알리아 꽃이 우수한 생리활성물질을 함유하 고 있으며, 항산화제로서 식품 및 의약품, 화장품 등에서 높은 활용 가능성을 가지고 있음을 시사한다.

This study aims to develop a deep learning model to monitor rice serving amounts in institutional foodservice, enhancing personalized nutrition management. The goal is to identify the best convolutional neural network (CNN) for detecting rice quantities on serving trays, addressing balanced dietary intake challenges. Both a vanilla CNN and 12 pre-trained CNNs were tested, using features extracted from images of varying rice quantities on white trays. Configurations included optimizers, image generation, dropout, feature extraction, and fine-tuning, with top-1 validation accuracy as the evaluation metric. The vanilla CNN achieved 60% top-1 validation accuracy, while pre-trained CNNs significantly improved performance, reaching up to 90% accuracy. MobileNetV2, suitable for mobile devices, achieved a minimum 76% accuracy. These results suggest the model can effectively monitor rice servings, with potential for improvement through ongoing data collection and training. This development represents a significant advancement in personalized nutrition management, with high validation accuracy indicating its potential utility in dietary management. Continuous improvement based on expanding datasets promises enhanced precision and reliability, contributing to better health outcomes.

Rehmannia glutinosa root and Saururus chinensis plant have been widely used in natural traditional medicines. This study was conducted to investigate the effect of the content of the main components of R. glutinosa root and S. chinensis plant by extraction method. The results of comparative analysis of extraction yield, total flavonoid, and polyphenol content by extraction method indicated that extraction yield had the best performance with hot water extraction for R. glutinosa and ultrasound-assisted extraction for S. chinensis. The total flavonoid and polyphenol content had the best performance with maceration extraction for R. glutinosa and ultrasound-assisted extraction for S. chinensis. ABTS and DPPH activity was excellent with maceration extraction for both R. glutinosa and S. chinensis. The analysis of the main components showed that maceration extraction was most effective for both S. chinensis and R. glutinosa. Specifically, maceration extraction of R. glutinosa yielded 1.5 times more than conventional ultrasound-assisted extraction.

The separation of zirconium and hafnium using tributyl phosphate (TBP)-Dodecane extractants in nitric acid medium was performed. Zirconium oxychloride, used as extraction feed, was obtained from the synthesis of Kalimantan zircon sand concentrate smelted using NaOH. The extraction process was carried out by dissolving chloride-based metals in nitric acid media in the presence of sodium nitrate using TBP-Dodecane as an extractant. Some of the extraction parameters carried out in this study include variations in organic phase and aqueous phase (O/A), variations in contact time, and variations in nitric acid concentration. Extraction was carried out using a mechanical shaker according to the parameter conditions. X-ray fluorescence (XRF) was used for elemental (Zr and Hf) composition analysis of the aqueous solution. The results showed that zirconium was separated from hafnium at optimum conditions with an organic/aqueous ratio of 1:5, contact time of 75 min, and an HNO3 concentration of 7 M. The resulting separation factor of zirconium and hafnium using TBP-Dodecane was 14.4887.