대한민국의 해양레저산업은 세일링을 비롯한 다양한 형태의 수상레저 활동이 증가하는 추세에 따라 세계적으로 신흥시장으로 주목받고 있어 세일링 요트에 대한 수요가 높아질 것으로 추정된다. 이에 따라 2022년 현재 우리나라 요트 문화의 부흥과 보급을 위해 해 양수산부의 지원을 받아 28피트 세일 요트의 설계 및 개발이 착수되었다. 개발 초기 단계에서의 성능을 확인하고 이를 통해 설계 인자를 결정하기 위하여 속도 예측 프로그램 VPP(Velocity Prediction Program) 분석이 수행되었다. 본 연구에서 사용된 소프트웨어는 University of Southampton의 Wolfson Unit社의 WinDesign으로, 속도 예측에 적용된 유체역학적 데이터 모델은 Wolfson Unit社자체적인 조선공학 및 요트 연구 분야에서 수십 년간의 예인 수조 시험 데이터를 회귀 분석한 방법으로 대부분의 현대식 요트에 대해 신뢰할 수 있는 추정치를 제공 하는 것으로 여겨진다. 하지만 예인 수조 시험이나 CFD 수치해석 등을 통한 실험 결과적인 유체역학적 정보가 없기 때문에 소프트웨어에 서 제공하는 유체역학적 데이터 회귀 모델의 저항 값은 다소 차이가 있을 것으로 예상된다. 또한, 아직 미완료된 무게 중심 추정에 의한 VCG 값은 속도 예측의 입력 변수 중 하나로, 성능 결과에 어느 정도 영향을 미칠 수 있을 것으로 예상된다. 개발 세일 요트에 대한 최적 화된 보트 속도는 풍속 4, 8, 12, 16 및 20노트의 집세일 조합(최대 120° TWA) 및 스피네커 세일 조합(80° TWA부터) 모두에서 확인되었으 며, VPP를 활용하여 얻어진 최적화된 속도는 국제적으로 유사한 등급의 요트와 견줄수 있는 수준으로 확인되었다.

Distractive marking, as conceptualized by Abbott H. Thayer, refers to diminutive patterns of contrasting colors on an animal’s body. Thayer hypothesized that these patterns augment camouflage by diverting predatory focus from the outline of the prey, however, the evidence was insufficient. In this study, we verified the hypothesis that the presence of distractive markings confers a survival advantage under specific conditions. Specifically, the experiment aimed to ascertain whether the existence of lichens on trees hinders the visual detection of prey, given that lichens resemble distractive markings. The experimental design involved human subjects as predators and artificial moth images on a monitor as prey. The survival of moths with and without distractive markings was compared, also considering the influence of the presence of lichens in the background. As an analysis result, the survival likelihood of moths was statistically significantly hindered when the distractive marking was present. This result contradicts Thayer‘s hypothesis and implies the presence of a function distinct other than the enhancement of camouflage.

Degenerative arthritis is a common joint disease that affects many elderly people and is typically diagnosed through radiography. However, the need for remote diagnosis is increasing because knee pain and walking disorders caused by degenerative arthritis make face-to-face treatment difficult. This study collects three-dimensional joint coordinates in real time using Azure Kinect DK and calculates 6 gait features through visualization and one-way ANOVA verification. The random forest classifier, trained with these characteristics, classified degenerative arthritis with an accuracy of 97.52%, and the model's basis for classification was identified through classification algorithm by features. Overall, this study not only compensated for the shortcomings of existing diagnostic methods, but also constructed a high-accuracy prediction model using statistically verified gait features and provided detailed prediction results.

Maintaining fuel sheath integrity during dry storage is important. Intact sheath acts as the primary containment barrier for both fuel pellets and fission products over the dry storage periods and during subsequent fuel handling operations. In KNF, in-house fuel performance code was developed to predict the overall behavior of a fuel rod under normal operating conditions. It includes the analysis modules to predict temperature, pellet cracking and deformation, sheath stress and strain at the mid-plane of the pellet and pellet-pellet interfaces, fission gas release and internal gas pressure. The main focus of the code is to provide information on initial conditions prior to dry storage, such as fission gas inventory and its distribution within the fuel pellet, initial volumes of storage spaces and their locations, radial profile of heat generation within the pellet, etc. To upgrade the developed code that address all the damage mechanisms, the first step was a review of the available technical information on phenomena relevant to fuel integrity. Potential degradation mechanisms that may affect sheath integrity of CANDU spent fuel during dry storage are: creep rupture under internal gas pressure, sheath oxidation in air environment, stress corrosion cracking (SCC), delayed hydride cracking (DHC), and sheath splitting due to UO2 oxidation for a defective fuel. The failure by creep rupture, SCC or DHC is in the form of small cracks or punctures. The failure by sheath oxidation or sheath splitting due to UO2 oxidation results in a gross sheath rupture. The second step was to examine the technical bases of all modules of the in-house code, identify and extend the ranges of all modules to required operating ranges. This step assessed the degradation mechanisms for the fuel integrity. The objective of this assessment is to predict the probability of sheath through-wall failure by a degradation mechanisms as a function of the sheath temperature during dry storage. Further improvements being considered include upgrades of the analysis module to achieve sufficient accuracy in key output parameters. The emphasis in the near future will be on validation of the inhouse code according to a rigorous and formal methodology. The developed models provide a platform for research and industrial applications, including the design of fuel behavior experiments and prediction of safe operating margins for CANDU spent fuel.

농촌진흥청 국립원예특작과학원에서는 2018년 오리엔탈-트럼펫(OT) 종간잡종나리 ‘Pink Bella’를 개발하였다. 2008년 연노란색 OT 종간잡종나리 ‘Valparadiso’와 붉은색의 오리엔탈나리 ‘Scalini’를 각각 모본과 부본으로 화주 절단 수분법과 주 두교배법으로 각 3화를 인공교배하였고, 교배 후 미숙한 3개의 꼬투리를 수확하여 배가 형성된 배주를 기내에서 배양하여 잡종을 획득한 후 재배하였다. 육묘한 배양묘로부터 2011년 분홍색의 OT 종간잡종 나리 ‘OTO-11-43’ 계통을 개체 선발하였다. 2012년부터 2017년까지 선발된 계통은 자구와 인편번식, 조직배양을 이용하여 번식 및 양구한 후 1, 2차 생육특성 검정을 실시하였다. 2018년 3차 생육특성검정 및 소비자 기호도 평가를 수행한 결과 화색 및 화형에 대한 기호도가 높은 분홍색(RHS, RP62C)의 조기개화성 절화용 OT 종간잡종 나리 ‘Pink Bella’를 육성하였다. 3배체의 OT 종간잡종 나리로 초장은 131.7cm로 초장신장성이 우수하였다. ‘Pink Bella’의 화폭은 18.6cm이며 대조품종 ‘Table Dance’의 18.4cm와 유사한 크기였으며, 내화피의 폭, 길이 역시 대조품종과 통계적인 차이가 없었다. ‘Pink Bella’의 개화기는 6월 15일로 대조품종 ‘Table Dance’의 6월 28일에 비교하여 개화기가 13일 단축된 것으로 나타났으며 통계적으로 유의하였다.

This study explores multiple variables of an OTT service for discovering hidden relationship between rating and the other variables of each successful and failed content, respectively. In order to extract key variables that are strongly correlated to the rating across the contents, this work analyzes 170 Netflix original dramas and 419 movies. These contents are classified as success and failure by using the rating site IMDb, respectively. The correlation between the contents, which are classified via rating, and variables such as violence, lewdness and running time are analyzed to determine whether a certain variable appears or not in each successful and failure content. This study employs a regression analysis to discover correlations across the variables as a main analysis method. Since the correlation between independent variables should be low, check multicollinearity and select the variable. Cook's distance is used to detect and remove outliers. To improve the accuracy of the model, a variable selection based on AIC(Akaike Information Criterion) is performed. Finally, the basic assumptions of regression analysis are identified by residual diagnosis and Dubin Watson test. According to the whole analysis process, it is concluded that the more director awards exist and the less immatatable tend to be successful in movies. On the contrary, lower fear tend to be failure in movies. In case of dramas, there are close correlations between failure dramas and lower violence, higher fear, higher drugs.