Earticle

최근 들어 개인, 기업, 국가 등 사회 전반에 랜섬웨어에 의한 피해가 급증하고 있으며 그 규모도 점차 커지고 있다. 랜섬웨어는 사용자 컴퓨터 시스템에 침입하여 사용자의 중요 파일들을 암호화하여 사용자가 해당 파일들을 사용하지 못하게 하고 그 댓가로 금품을 요구하는 악의적인 소프트웨어이다. 랜섬웨어는 기타 다른 악의적인 코드들에 비해 공격기법이 다양 하고 정교하여 탐지가 어렵고 피해 규모가 크기 때문에 정확한 탐지와 해결 방법이 필요하다. 정확한 랜섬웨어를 탐지하기 위 해서는 랜섬웨어의 특성들로 학습한 탐지 시스템의 추론엔진이 요구된다. 따라서 본 논문에서는 랜섬웨어의 정확한 탐지를 위해 랜섬웨어가 가지는 특성을 추출하여 분류하는 모델을 제안하고 추출된 특성들의 유사성을 계산하여 특성의 차원을 축소 한 다음 축소된 특성들을 그룹화하여 랜섬웨어의 특성으로 공격 도구, 유입경로, 설치파일, command and control, 실행파 일, 획득권한, 우회기법, 수집정보, 유출기법, 목표 시스템의 상태 변경으로 분류하였다. 분류된 특성을 기존 랜섬웨어에 적용 하여 분류의 타당성을 증명하였고, 차후에 이 분류기법을 이용해 학습한 추론엔진을 탐지시스템에 장착하면 새롭게 등장하는 신종과 변종 랜섬웨어도 대부분 탐지할 수 있다.

Recently, there has been a sharp increase in the damages caused by ransomware across various sectors of society, including individuals, businesses, and nations. Ransomware is a malicious software that infiltrates user computer systems, encrypts important files, and demands a ransom in exchange for restoring access to the files. Due to its diverse and sophisticated attack techniques, ransomware is more challenging to detect than other types of malware, and its impact is significant. Therefore, there is a critical need for accurate detection and mitigation methods. To achieve precise ransomware detection, an inference engine of a detection system must possess knowledge of ransomware features. In this paper, we propose a model to extract and classify the characteristics of ransomware for accurate detection of ransomware, calculate the similarity of the extracted characteristics, reduce the dimension of the characteristics, group the reduced characteristics, and classify the characteristics of ransomware into attack tools, inflow paths, installation files, command and control, executable files, acquisition rights, circumvention techniques, collected information, leakage techniques, and state changes of the target system. The classified characteristics were applied to the existing ransomware to prove the validity of the classification, and later, if the inference engine learned using this classification technique is installed in the detection system, most of the newly emerging and variant ransomware can be detected.

최근에는 발전하는 정보통신 기술을 이용하여 악의적인 코드들이 제작되고 있고 이를 기존 탐지 시스템으로는 탐지하는게 역부족인 실정이다. 이러한 지능적이고 악의적인 코드를 정확하고 효율성 있게 탐지하고 대응하기 위해서는 지능적 탐지 모델이 필요하다. 그리고, 탐지 성능을 최대로 높이기 위해서는 악의적인 코드의 주요 특징 정보 집합으로 훈련하는 것이 중요하다. 본 논문에서는 지능적 탐지 모델을 설계하고 모델 훈련에 필요한 데이터를 변환, 차원축소, 특징 선택 단계를 거쳐 주요 특징 정보 집합으로 생성하는 기법을 제안하였다. 그리고 이를 기반으로 악의적인 코드별로 주요 특징 정보를 분류하였다. 또한, 분류된 특징 정보들을 기반으로 변형되거나 새로 등장하는 악의적인 코드를 분석하 고 탐지하는데 사용할 수 있는 공통 특징 정보를 도출하였다. 제안된 탐지 모델은 제한된 수의 특성 정보로 학습하여 악의적인 코드를 탐지하기에 탐지 시간과 대응이 빨리 이루어져 피해를 크게 줄일 수 있다. 그리고, 성능 평가 결과 값은 학습 알고리즘에 따라 약간 차이가 나지만 악의적인 코드 대부분을 탐지할 수 있음을 평가로 알 수 있었다.

In recent years, malicious codes are being produced using the developing information and communication technology, and it is insufficient to detect them with the existing detection system. In order to accurately and efficiently detect and respond to such intelligent malicious code, an intelligent detection model is required, and in order to maximize detection performance, it is important to train with the main characteristic information set of the malicious code. In this paper, we proposed a technique for designing an intelligent detection model and generating the data required for model training as a set of key feature information through transformation, dimensionality reduction, and feature selection steps. And based on this, the main characteristic information was classified by malicious code. In addition, based on the classified characteristic information, we derived common characteristic information that can be used to analyze and detect modified or newly emerging malicious codes. Since the proposed detection model detects malicious codes by learning with a limited number of characteristic information, the detection time and response are fast, so damage can be greatly reduced and Although the performance evaluation result value is slightly different depending on the learning algorithm, it was found through evaluation that most malicious codes can be detected.

본 연구는 2013-2015년도에 질병관리본부에서 실시한 국민건강영양조사 자료를 활용하여 만 65세 이 상의 발거가 필요한 치아를 보유한 음주노인 1,865명을 대상으로 했다. 치아발거필요 관련요인을 결과변수로 한 분석결과, 음주노인의 남성에서, 소득이 더 낮을수록, 흡연자에서, 본인인지구강건강상태 나쁨에서, 구강위 생용품 사용안함에서 치아를 발거해야 할 위험도가 높았으며, 통계적으로 유의한 차이를 보였다. 음주노인의 치아발거 위험요인을 미리 파악하여 치아상실을 조기에 예방하고 잔존치아의 수명을 최대한 연장하기 위해서 는 음주문화를 개선하고 현재가 아닌 이전 생애주기에서 음주자의 구강건강관리 전략을 모색하고, 국가차원의 통합적 구강보건정책이 추진되어야 할 것이다.

This study was conducted on 1,865 drunk elderly people who had teeth that were over 65 years old. As a result of analysis of factors related to tooth extraction, the higher the income, the lower the income, the higher the risk of having to remove teeth from smokers, poorer oral health status, and no oral hygiene products. The difference was statistically significant. In order to identify the risk factors of tooth extraction for the elderly and prevent tooth loss early and to extend the life of residual teeth as much as possible, it is necessary to improve the drinking culture and seek oral health care strategies in the previous life cycle, not the present, Oral health policy should be pursued.

미선나무 잎과 줄기 중 유효성분의 최적 추출조건을 평가하기 위해 다양한 비율의 물과 에탄올 혼합물(0, 20, 40, 60, 80, 100% ethanol(v/v))을 추출용매로 사용하여 환류냉각, 초음파 및 침지법을 적용하여 추출을 진행하였 다. 추출물의 총 폴리페놀과 플라보노이드 함량을 분석한 결과 80% 에탄올로 2시간 동안 환류냉각 추출하였을 때 가장 높은 값을 나타내었으며 미선나무 줄기의 DPPH free radical 소거능을 평가한 결과 침지 추출 시 71.3%로 가장 높았다. 미선나무 잎의 DPPH free radical 소거능은 용매별로 분획하여 측정한 결과 용매별로 다른 값을 나타내었으 며 부탄올 층에서 103.3%로 가장 높게 나타났다. 이러한 결과로써 미선나무의 잎과 줄기를 생리활성을 보유한 천연 물 소재로써 활용이 가능하다는 것을 확인하였다.

To evaluate optimum conditions of extract active components, extraction of Abeliophyllum distichum Nakai was performed with various ethanol and water mixture at ethanol concentration of 0, 20, 40, 60, 80 and 100%(v/v) and extraction methods. Higher polyphenol and flavonoids contents of extract achieved at 2 hours of reflux extraction in 80% ethanol. The highest DPPH free radical scavenging activity of the stem extracts by soaking method and butanol fractions of leaf extracts are 71.3% and 103.3% respectively. The results suggested that Abeliophyllum distichum Nakai can be used for valuable natural resource.

본 연구에서는 생강나무 꽃 발효 추출물의 항산화능 및 항염능을 확인하였다. 항산화능 측정을 위해 DPPH 실험, ABTS 실험을 실시하였다. 동시에 폴리페놀 농도 측정, 플라보노이드 농도 측정을 통해 항산화 물질 의 정량을 실시하였다. 플라보노이드, DPPH, ABTS에서는 발효 후의 항산화능이 증가한 것을 확인하였다. 이 때 플라보노이드 농도는 5.0%, DPPH 실험에서는 33.27%, ABTS 실험에서는 29.82%의 항산화능 개선 효과가 나타 났다. 항염능 실험에서는 세포 독성 실험과 LPS로 유도된 염증에 대한 항염능을 알아보기 위한 NO 생성 억제능 실험을 실시하였다. 세포독성의 경우 대조군과 발효군 모두 낮은 세포독성을 보였지만 발효군에서 더 낮은 세포독 성을 보였다. NO 생성 억제능의 경우 발효군이 대조군에 비해 50% 이상의 항염능 증가를 보여 발효 생강나무 꽃이 기존 생강나무 꽃에 비해 더 개선된 화장품 원료로서 사용가능함을 보였다.

In this study, the antioxidant activity and anti-inflammatory activity of Lindera obtusiloba flower fermentation extracts were identified. To evulate antioxidant activity and antioxidant concentration, polyphenol concentration measurements, flavonoid concentrations measurements, DPPH experiments, and ABTS experiments were conducted. In Flavonoids, DPPH and ABTS assay, antioxidant activity were increased after fermentation. At this time, the flavonoid concentration was 5.0%, the DPPH experiment showed 33.27% and the ABTS experiment showed 29.82% antioxidant increase. In the anti-inflammatory experiment, we conducted a cytotoxicity experiment and an anti-inflammatory experiment for LPS-induced inflammation. Cytotoxicity showed low cytotoxicity in both control and fermentation groups, but lower cytotoxicity in fermentation groups. In the case of NO production inhibition, fermented Lindera obtusiloba flowers showed an increase in anti-inflammatory activity by more than 50% compared to the control group, showing that they can be used as a cosmetic ingredient with anti-inflammatory function.

현대사회에서는 차량을 소유하는 사람들이 증가하면서 교통문제가 발생하고 있다. 특히 고속도로 교통사고 문 제는 발생률이 낮지만 치사율은 높다. 따라서 차량의 이상을 탐지하는 기술이 연구되고 있다. 이 중에는 딥러닝을 이용 한 차량 이상탐지 기술이 있다. 이는 사고 및 엔진고장으로 인한 정차차량 등의 차량 이상을 탐지한다. 그러나 도로에 서 이상이 발생할 경우 운전자의 위치를 파악할 수 있어야 빠른 대처가 가능하다. 따라서 본 연구에서는 도로 CCTV 데이터를 활용한 딥러닝 기반 차량 이상 감지 방법을 제안한다. 제안하는 방법은 먼저 도로 CCTV 데이터를 전처리한 다. 전처리는 배경 추출 알고리즘인 MOG2를 이용하여 배경과 전경을 분리한다. 전경은 변위가 존재하는 차량을 의미 하며 도로 위에서 이상이 존재하는 차는 변위가 없어 배경으로 판단된다. 배경이 추출된 이미지는 이상을 탐지하기 위해 YOLOv4를 이용하여 객체를 탐지한다. 해당 차량은 이상이 있음으로 판단한다.

In the modern society, traffic problems are occurring as vehicle ownership increases. In particular, the incidence of highway traffic accidents is low, but the fatality rate is high. Therefore, a technology for detecting an abnormality in a vehicle is being studied. Among them, there is a vehicle anomaly detection technology using deep learning. This detects vehicle abnormalities such as a stopped vehicle due to an accident or engine failure. However, if an abnormality occurs on the road, it is possible to quickly respond to the driver's location. In this study, we propose a deep learning-based vehicle anomaly detection using road CCTV data. The proposed method preprocesses the road CCTV data. The pre-processing uses the background extraction algorithm MOG2 to separate the background and the foreground. The foreground refers to a vehicle with displacement, and a vehicle with an abnormality on the road is judged as a background because there is no displacement. The image that the background is extracted detects an object using YOLOv4. It is determined that the vehicle is abnormal.

Termitomyces albuminosus has been recognized to have the best mushrooms in China, in terms of taste and aroma. The efficacy of these mushrooms has been recorded in the botanical list. However, research on the development of their artificial culture methods is necessary. In this study, we prepared an organic solvent extract and a hot water extract to understand the development of compounds and functional foods with antioxidant and anti-inflammatory activities. The IC50 value of DPPH radical scavenging activity of the hot water extract (TA4) was 1.5 mg/mL and the IC50 value of the MeOH fraction (TA2) was 1.93 mg/mL. The anti-inflammatory activity was investigated by the inhibition of NO production. EtOAc fraction (TA1) is a crude extract, but 79% of NO production was inhibited at 100 μg/mL. NO was not produced at 200 μg/mL. TA1-5-6, from TA1 inhibited NO production by 15% as compared to the positive control at 15 μg/mL, and completely inhibited NO production at 30 μg/mL. No cytotoxicity was observed at 50 μg/mL. TA2-1-5 from the MeOH fraction (TA2) inhibited more than 75% of NO production at 30 μg/mL; cytotoxicity was very low even at 50 μg/mL. In conclusion, by selective solvent selection, it was possible to manufacture an extract with no cytotoxicity and excellent biological activities. Furthermore, the extracts showed potential for developing various functional foods and drugs.

The purpose of this study was to investigate the flavor characteristics of Gondre (Cirsium setidens Nakai) essential oil. The essential oil was isolated from the aerial parts of the plant by the hydrodistillation extraction method and analyzed by gas chromatography (GC) and GC-mass spectroscopy (MS). Seventy-eight (90.28%) volatile flavor components were identified in the essential oil from Gondre harvested in May. The major compounds were hexadecanoic acid (44.84%), phytol (15.57%), 6,10,14-trimethyl-2-pentadecanone (5.62%), and tertadecanoic acid (4.77%). Seventy (90.72%) volatile flavor components were identified in the essential oil from Gondre harvested in September. The major compounds were phytol (24.18%), 6,10,14-trimethyl-2-pentadecanone (15.59%), tetracosane (8.87%), 2-methyl eicosane (3.55%), 6,10,14-trimethyl-5,9,13-pentadecatrien-2-one (3.12%), dibuthyl phthalate (2.35%), and viridiflorol (2.33%). The flavor components of the essential oil from Gondre harvested in May and September were characterized by higher proportions of aliphatic fatty acids and terpene compounds, respectively.

본 연구에서는 한국 차례 및 제사에 이용되는 식단의 엽산 함량을 분석하기 위하여 trienzyme 추출과 Lactobacillus casei를 이용한 microplate assay법을 검증하고, 이를 적용하여 분석하는 동안 분석 품질관리를 수행하여 분석 결과의 신뢰도를 확보하였다. 인증표준물질을 이용한 정확성 검증으로 분석값이 인증값의 상대표준 오차 범위 안에 포함되는 값을 얻었으며 식품군을 대표하는 시료를 선정하여 엽산 표준용액을 첨가한 시료와 첨가하지 않은 시료를 함께 분석하여 엽산 회수율을 측정 시 96.0~106.2%를 얻어 정확성이 높은 분석법임을 확인하였다. Repeatability와 reproducibility로 측정한 미생물학적 분석법의 정밀성 모두 5% 미만의 값을 얻어 정밀성이 우수함을 확인하였다. 제사 음식 중의 엽산 함량은 국 및 탕류($4.62{\sim}18.84{\mu}g/100g$)에서는 토란국이 가장 높은 함량을 나타내었으며, 나물류($6.13{\sim}48.40{\mu}g/100g$)에서는 미나리나물, 적 및 전류($5.49{\sim}49.50{\mu}g/100g$)는 홍합산적, 찜류($10.34{\sim}38.88{\mu}g/100g$)에서는 도미찜, 후식류($3.33{\sim}49.55{\mu}g/100g$)에서는 송화다식이 엽산 함량이 가장 높은 것으로 나타났다. 이러한 한국 의례 음식의 섭취는 1회 100g 섭취 시 성인 일일 권장 섭취량의 0.8~12.4%의 수준까지 엽산을 섭취할 수 있으며, 한상차림으로 섭취 시 평균 약 28.1%의 엽산을 섭취할 수 있는 것으로 보인다. 본 연구가 진행된 약 10개월 동안 분석 품질관리를 수행하였으며 품질관리도표(quality control chart)의 관리를 통하여 본 연구에서 진행된 모든 분석이 관리 하에 진행되었음을 확인할 수 있었으며 이는 본 논문에서 보고하는 총 59종의 한국 차례 및 제사 음식의 엽산 함량이 신뢰도 높게 분석되어 국가 엽산 함량 데이터로 활용될 수 있을 것으로 사료된다.

Trienzyme extraction coupled with microplate assay (Lactobacillus casei subsp. rhamnosus) was validated and applied for the determination of folate (vitamin B9) in Korean ancestral rite foods. Foods included five Guk (Tang), eleven Sookchaes, eight Jeoks, nine Jeons, six Jjims, and twenty desserts. Folate was detected in all samples: Guk (Tang) 4.62~18.84, Sookchae 6.13~48.40, Jeok 5.49~49.50, Jeon 6.96~30.77, Jjim 10.34~38.88, and desserts $3.33{\sim}49.55{\mu}g/100g$. The lowest folate content was observed in Sikhye ($3.33{\mu}g/100g$), whereas the highest was observed in Songhwa-dasik ($49.55{\mu}g/100g$). Folate analyses of certified reference materials, BCR-121 (whole meal flour) and BCR-487 (pig liver), showed good recoveries of 90.0% (0.45 mg/kg) and 92.4% (12.3 mg/kg), respectively. The recoveries (96.0 to 106.2%) obtained by analyzing eight spiked samples with different matrices also showed good accuracy. Both repeatability and reproducibility were less than 5%, indicating good precision. The quality control chart (n>30) obtained by running commercial folate fortified-wheat flour once a week for about 10 months showed that all assays were under control. All validation method and analytical quality control results showed that folate contents in Korean ancestral rite foods produced by microplate assay were reliable enough to be used for the construction of a national folate database.

Test of the optimum condition of solid phase micro extraction(SPME) was performed by use of 5 vol-atile components in dilute aqueous solution. Volatile components of Sancho(Zanthoxylum schinifolium) were isolated by SPME method and were analyzed by GC/MSD and compared with volatile compone-nts isolated by simultaneous distillation extraction (SDE) method. Total 31 components were identified by comparing gas chromatography retention time and mass spectral data. The major compounds were limonene geranyl acetate $\beta$-phellandrene phellandral mycene linalool rose oxide caproic acid and caprylic acid SPME sampling procedure was found to be a good method for qualitative analysis of the volatile components.

현재 상업적으로 회수되고 있는 리튬 공급량은 이미 한계에 도달하였고 이를 극복하기 위해 지열수, 유전염호 등과 같은 리튬을 함유한 저농도 염호로부터 리튬을 회수하는 연구가 활발히 진행되고 있다. 고품위 염호를 대상으로 적용되는 자연증발/농축 기반의 상용화 공정의 경우 저농도 염호에 적용하기에는 한계를 지녀, 이 를 대체 할 수 있는 DLE(Direct Li Extraction) 기술이 제시되고 있다. DLE 기술은 저품위 염호( Li conc.<1000 ppm)으로부터 리튬을 회수할 수 있는 침전법, 용매추출법, 흡착법 등과 같은 비증발 리튬추출기술을 적용해 리튬을 회수하는 방법으로 기존 자연증발농축법의 단점인 긴 공정시간, 생산량 한계를 극복할 수 있는 기술로써 중요성이 확대되고 있다. 본논문에서는 리튬회수기술 현황 및 최근 활발히 진행되고 있는 DLE 기술 개발 동향분석을 통해 환경성/경제성을 확보할 수 있는 DLE 기술 개발 방향성을 제시하고자 한다.

The commercial supply of lithium has recently reached its limit, prompting active research into the recovery of lithium from low-grade brines, such as geothermal water and oil field brine, which contain lithium. The commercialized process that relies on natural evaporation and concentration, typically applied to high-grade brine, has limitations when applied to low-grade brine. As an alternative, direct lithium extraction (DLE) technology is being proposed. DLE technology employs non-evaporative lithium extraction methods, including precipitation, solvent extraction, and adsorption, to recover lithium from low-grade brines (with lithium concentrations less than 1000 ppm). This technology is gaining importance, because it can overcome the drawbacks of conventional methods, such as lengthy processing time and production limits. This paper discusses the development direction of DLE technology that can ensure environmental and economic feasibility, using an analysis of the current status and trends of lithium recovery technology.

In order to improve the market competitiveness of the processed products of Undaria pinnatifida, various extraction conditions of Undaria pinnatifida were examined to determine the optimal conditions for the extraction of its valuable components. The highest level of alginic acid content was detected after 90 min of typical extraction or after 20 min of pressure extraction, after which the levels decreased slightly. The concentrations of reducing sugar and crude protein were also high after 90 min of typical extraction. Both alginic acid and reducing sugar were extracted in greater amounts using pressure extraction. The reducing sugar content was $2.8{\sim}3.2$ times higher using pressure extraction rather than typical extraction. Furthermore, the extraction results were superior with the, pressure extraction method. The appropriate temperature and duration of extraction were found to be $120^{\circ}C$ for 20 min. The use of a single enzyme yielded better results during extraction compared to the use of a mixture of enzymes. 20 min of pressure extraction followed by the addition of 0.1% pectinase and 2 hr of further extraction at $50^{\circ}C$ yielded high contents of alginic acid and reducing sugar from Undaria pinnatifida.

Selective catalytic reduction (SCR) has been a promising technology to reduce the air pollution caused by nitrogen oxides (NOx) in several industries. The consumption of SCR catalysts increases every year as technology evolves, however those have a limited lifespan and usually end up in landfills after they deactivate. Currently, the most widely used catalyst for and stationary applications is V2O5-WO3/TiO2 which can contain around 50% wt V2O5 and 7-10% wt of WO3. The vast uses for both vanadium and tungsten and the worldwide interest in recycling methods that allow for the extraction of metals from secondary sources represent the major motivation for this research. The extraction time, pH dependency, extraction concentration studies were carried out using Aliquat 336 in exxol D80 as the extractant. It was determined that to optimize the extraction of both metals 30min of contact time with an organic phase containing 0.5mol/L of Aliquat 336 are needed at a slightly acidic pH (~5.0). In addition, counter McCabe-Thiele studies allowed us to determine that one stage is necessary for the removal of 99% of vanadium while 2 stages are necessary for the extraction of tungsten and counter current simulations proved that the theoretical approach was correct.

This paper aims to extract an ObjectProperty-UsageMethod relation, in particular the HerbalMedicinalProperty-UsageMethod relation of the herb-plant object, as a semantic relation between two related sets, a herbal-medicinal-property concept set and a usage-method concept set from several web documents. This HerbalMedicinalProperty-UsageMethod relation benefits people by providing an alternative treatment/solution knowledge to health problems. The research includes three main problems: how to determine EDU (where EDU is an elementary discourse unit or a simple sentence/clause) with a medicinal-property/usage-method concept; how to determine the usage-method boundary; and how to determine the HerbalMedicinalProperty-UsageMethod relation between the two related sets. We propose using N-Word-Co on the verb phrase with the medicinal-property/usage-method concept to solve the first and second problems where the N-Word-Co size is determined by the learning of maximum entropy, support vector machine, and naïve Bayes. We also apply naïve Bayes to solve the third problem of determining the HerbalMedicinalProperty-UsageMethod relation with N-Word-Co elements as features. The research results can provide high precision in the HerbalMedicinalProperty-UsageMethod relation extraction.

Rice proteins were extracted from brown and milled rice of five varieties: Kwanganbyeo, Daeanbyeo, Daejinbyeo, Surabyeo, Hwaseongbyeo; and their electrophoretic patterns were analyzed by SDS-PAGE. Albumin was extracted with water, globulin with 5% NaCl, prolamin with 70% ethanol, and glutelin with 0.2 M sodium borate buffer (pH 10.0) containing 0.5% SDS, 0.6% $\beta$-mercaptoethanol. The ratios of albumin : globulin : prolamin : glutelin in the brown rice were 10.8~14.1 : 12.4~16.4 : 3.6~5.3 : 68.6~72.8, and in milled rice were 4.4~5.6 : 10.6~12.0 : 3.9~5.4 : 75.7~79.8. In albumin seven major bands were observed with molecular weights ranging from 14.g~96.8 kDa, in globulin four bands with molecular weights in the range of 14.4~56.9 kDa, prolamin had only one band with a molecular weight of 14.4 kDa, and glutelin had four bands with molecular weights of 14.4 ~ 57.4 kDa. There were no differences in electrophoretic patterns between rice varieties or between brown and milled rice.

In this study, we investigated maximum yield of radical scavenging activity (RSA) using each of various extraction solvents and procedure from noni friut (Morinda citrifolia). Noni fruits were either sun-dried (FS) or hot-air dried (FO) at 60℃ after steam blanching. For optimum aqueous extraction, noni fruits should be sun dried and autoclave extraction time should not be over 30 min to produce extraction with high RSA with low cost. In case of 50% ethanol extraction,reflux extracts of FS and FO resulted in IC_50 of 1.92 ㎎/mL and 3.06 ㎎/mL at 8 hr. When IC_50 values were lower than 5 ㎎/mL, coefficient of correlation was 0.71 indicating that 71% of the phenolic antioxidants in noni fruits were accounted for the activity by scavenging free DPPH. However, coefficient of correlation significantly decreased to 0.63 over IC_50 values of 5 ㎎/mL. Autoclave extraction contained chlorogenic acid of 14.69 ㎍/mL and scopoletin of 3.86 ㎍/mL. Reflux extraction showed all three compounds, chlorogenic acid (26.19 ㎍/mL), quercetin (19.59 ㎍/mL), and scopoletin (17.4 ㎍/mL). Therefore,the result of this study indicated that the potential antioxidant activities and functional values were obtained significantly with reflux extraction from noni fruit.

Non-proliferative diabetic retinopathy is a representative complication of diabetic patients and is known to be a major cause of impaired vision and blindness. There has been ongoing research on automatic detection of diabetic retinopathy, however, there is also a growing need for research on an automatic severity classification system. This study proposes an automatic detection system for pathological symptoms of diabetic retinopathy such as microaneurysms, retinal hemorrhage, and hard exudate by applying the Faster R-CNN technique. An automatic severity classification system was devised by training and testing a Random Forest classifier based on the data obtained through preprocessing of detected features. An experiment of classifying 228 test fundus images with the proposed classification system showed 97.8% accuracy.