운량은 천체 관측을 지속하는 데에 중요한 요소 중 하나이다. 과거에는 관측자가 날씨를 직접 판단할 수밖에 없 었으나, 원격 및 자동 관측 시스템의 개발로 관측자의 역할이 상대적으로 줄어들었다. 또한 구름의 다양한 형태와 빠른 이동 때문에 자동으로 운량을 판단하는 것은 쉽지 않다. 이 연구에서는 기계학습 기반의 파이썬 모듈인 “cloudynight” 을 밀양아리랑우주천문대의 전천 영상에 적용하여 운량을 모니터링하는 프로그램을 개발하였다. 전천 영상을 하위 영역 으로 나누어 각 39,996개 영역의 16개의 특징을 학습하여 기계학습 모델을 생성하였다. 검증 표본에서 얻은 F1 점수는 0.97로, 기계학습 모델이 우수한 성능을 가짐을 보여준다. 운량(“Cloudiness”)은 전체 하위 영역 개수 중 구름으로 식별 된 하위 영역 개수의 비율로 계산하며, 운량이 지난 30분 동안 0.6을 초과할 때 관측을 중단하도록 자동 관측 프로그 램 규칙을 정하였다. 이 규칙을 따를 때, 기계학습 모델이 운량을 오판하여 관측에 영향을 미치는 경우는 거의 발생하 지 않았다. 본 기계학습 모델을 통하여, 밀양아리랑우주천문대 0.7 m 망원경의 성공적인 자동 관측을 기대한다.

본 연구는 동물매개 치유농장을 방문한 방문객의 특성을 분석하고, 이들 방문객을 대상으로 동물매개 치유농업의 활성화를 위한 속성별 중요도와 성취도를 조사하였다. 결과를 토대로 동물매개 치유농업 관련 전문가, 공무원, 연구원 등에게 정책수립과 연구 기초자료를 제공하고, 치유농장 품질인증제에 따른 수요자 맞춤 자료를 제공하고자 연구를 수행하였으며, 분석기법은 Importance-Performance Analysis (IPA)를 활용하였다. 분석결과 1사분면에서는 편의시설, 2사분면은 직원의 전문성, 3사분면은 동물 수의 적정성, 4사분면은 직원의 친절성이 도출되었다. 본 연구의 결과를 통해 도출된 속성에 적합한 방안을 적용하고 원활한 동물매개 치유농업 정책이 이루어지길 기대한다.

PURPOSES : This study investigates the effects of three different three-color arrow traffic light operations on right-turn vehicles at intersections in Busan Metropolitan City. METHODS : Intersections in this study were categorized as general intersections (Type 1), intersections with right-turn pockets (Type 2), and intersections with scramble crosswalks (Type 3), and were investigated in terms of the efficiency (i.e., control delay) and safety (i.e., number of conflicts) of right-turn vehicles by employing VISSIM 2023 and SSAM3. RESULTS : From a mobility perspective (i.e., control delay), the protected/permitted operation outperformed the other two methods at the three types of intersections. The protected operation, similar to the results of the protected/permitted operation, was also superior to the permitted operation in terms of safety (i.e., number of conflicts). CONCLUSIONS : Protected/permitted operation has been proven to be a more efficient and safer measure than other operation methods for alleviating the problems of protected right-turn operation, which is currently implemented without three-color arrow traffic lights.

In this study, we investigated the time signal devices of Deungnu (circa 1270) and Gungnu (1354), the water clocks produced during the Yuan Dynasty (1271–1368). These clocks influenced Heumgyeonggaknu (1438) of the Joseon Dynasty (1392–1910), exemplifying the automatic water clocks of the Yuan Dynasty. Deungnu, Gungnu, and Heumgyeonggaknu can be considered as automatic mechanical clocks capable of performances. The Jega-Yeoksang-Jip (Collection of Calendrical and Astronomical Theories of Various Chinese Masters) contains records of Deungnu extracted from the History of the Yuan Dynasty. We interpreted these records and analyzed reproduction models and technical data previously produced in China. The time signal device of Deungnu featured a four-story structure, with the top floor displaying the four divine constellations, the third floor showcasing models of these divinities, the second floor holding 12-h jacks and a 100-Mark ring, and the first floor with four musicians and a 100-Mark Time-Signal Puppet providing a variety of visual attractions. We developed a 3D model of Deungnu, proposing two possible mechanical devices to ensure that the Time-Signal Puppet simultaneously pointed to the 100-Mark graduations in the east, west, south, and north windows: one model reduced the rotation ratio of the 100-Mark ring to 1/4, whereas the other model maintained the rotation ratio using four separate 100-Mark rings. The power system of Deungnu was influenced by Suunuisangdae (the water-driven astronomical clock tower) of the Northern Song Dynasty (960–1127); this method was also applied to Heumgyeonggaknu in the Joseon Dynasty. In conclusion, these automatic water clocks of East Asia from the 13th to 15th centuries symbolized creativity and excellence, representing scientific devices that were the epitome of clock-making technology in their times.

건축물은 사용자의 부주의, 전기적, 기계적 요인 등에 의해 화재가 발생할 수 있고, 화재 발생 시 각 재료의 특성에 따라 강성 및 강도가 감소하여 구조 성능이 저하될 수 있다. 이러한 상황에서 적절 한 성능 복구가 되지 않으면 후에 지진 등의 큰 하중이 가해질 때 건축물 붕괴 등 치명적인 피해가 발생할 수 있다. 현재 내화성능을 높이는 방법으로 내화피복을 사용하는 등 수동적인 방법에 머물러 있으며, 꾸준한 유지관리 등이 필요하다는 단점이 있다. 따라서 변형 후 열을 가하면 원래의 형상으로 돌아가는 성질을 가진 형상기억합금을 사용하여 콘크리트 보를 보강하고, 화재 시, 화재 후에 프리스 트레스트 콘크리트와 유사한 방식으로 콘크리트에 압축응력을 발생시켜 구조 성능을 향상시킬 수 있 는지 ANSYS 구조해석 프로그램을 통해 그 효과를 확인해보고자 한다.

Clover cyst nematode (Heterodera trifolii, CCN) is one of the important plantparasitic nematodes in the Republic of Korea, causing serious damage to Kimchi-cabbage in Gangwon province since 2017. Soil fumigants are the preferred choice for managing CCN. However, cabbage fields in Gangwon province have a slope, making it challenging to apply soil fumigants and use plastic mulch. Consequently, alternative materials should be developed for managing CCN. Nematicidal cover crops and resistant cultivars are among the alternatives. We conducted resistance screening of 82 white mustard (Sinapis alba) resources from a genebank at RDA against CCN for use as nematicidal cover crops or breeding materials. In the first assay (1st, 2nd, and 3rd pot experiments), 15 white mustard resources were selected, while others were susceptible to CCN. To confirm the reproducibility of resistance to CCN for 13 selected resources, the second assay was performed. As a result, five white mustard resource (IT297309, IT297312, IT302951, IT302953, IT302954) demonstrated resistance to CCN. These findings indicate the potential use of these five white mustard resources as nematicidal cover crops or for breeding cultivars of Kimchi-cabbage in Republic of Korea.

Existing reinforced concrete buildings with seismically deficient column details affect the overall behavior depending on the failure type of column. This study aims to develop and validate a machine learning-based prediction model for the column failure modes (shear, flexure-shear, and flexure failure modes). For this purpose, artificial neural network (ANN), K-nearest neighbor (KNN), decision tree (DT), and random forest (RF) models were used, considering previously collected experimental data. Using four machine learning methodologies, we developed a classification learning model that can predict the column failure modes in terms of the input variables using concrete compressive strength, steel yield strength, axial load ratio, height-to-dept aspect ratio, longitudinal reinforcement ratio, and transverse reinforcement ratio. The performance of each machine learning model was compared and verified by calculating accuracy, precision, recall, F1-Score, and ROC. Based on the performance measurements of the classification model, the RF model represents the highest average value of the classification model performance measurements among the considered learning methods, and it can conservatively predict the shear failure mode. Thus, the RF model can rapidly predict the column failure modes with simple column details.

Non-uniform reinforced concrete brace facade systems are newly considered to improve seismic performance of reinforced concrete frame buildings under lateral load. For normal and high strength concrete of 30MPa, 80MPa, and 120MPa, the cross-sections of reinforced concrete brace facade systems were designed as different size with same amount of reinforcements. The strengthened frame systems were analyzed by a non-linear two-dimensional finite element technique which was considering material non-linearities of concrete and reinforcing bars under monotonic and cyclic loadings. From the study of non-linear analysis of the systems, therefore, it was provided that the proposed braced facade systems were reliable to improve laterally load-carrying capacity and minimize damages of concrete members through comparisons of load-displacement curves, crack patterns, and stress distributions of reinforcing bars predicted by current non-linear finite element analysis of frame specimens.

In ecosystems within limited resources, interspecific competition is inevitable, often leading to the competitive exclusion of inferior species. This study aims to provide foundational information for the conservation and restoration management of Microphysogobio rapidus by evaluating species’ ecological response to biological factors within its habitat. To understand this relationship, we collected food web organisms from site where M. rapidus coexist with Microphysogobio yaluensis, a specie ecologically similar to M. rapidus, and evaluated the trophic levels (TL), isotopic niche space (INS), and the overlap of INS among fishes within the habitat using stable isotope analysis. Our analysis revealed that the M. rapidus exhibited a higher TL than M. yaluensis, with TL of 2.6 and 2.4, respectively. M. yaluensis exhibited a broad INS, significantly influencing the feeding characteristics of most fish. Conversely, M. rapidus showed a narrow INS and asymmetric feeding relationships with other species, in habitats with high competition levels. This feeding characteristics of M. rapidus indicate that the increase in competitors sharing the similar resources lead to a decrease in available resources and, consequently, is expected to result in a decrease in their density.

The paper presents the experimental investigation of RC beams retrofitted with Textile Reinforced Mortar (TRM), featuring enhanced bond capacity. Anchoring systems, including an extension of retrofitting length and the use of chemical anchors, are newly employed to improve the structural performance of the RC beam retrofitted with TRM. For the experimental investigation, a total of seven shear-critical RC beams, with and without stirrups, were designed and constructed. The structural behaviors of specimens retrofitted with the proposed TRM methods were compared to those of non-retrofitted specimens or specimens strengthened with conventional TRM methods. Crack pattern, force-displacement relationship, and absorbed energy were evaluated for each specimen. The experimental results indicate a significant improvement in the shear capacity of the RC beam with the proposed retrofitting method. Therefore, it is concluded that the application of an extended retrofitting length and chemical anchors to the TRM retrofitting method can effectively enhance the bond capacity of TRM, thereby improving the shear performance of RC beams.

In this study, the expression of genes related to fruit ripening was investigated using realtime PCR. The study aimed to determine the effective conditions of calcium compounds (Calcium citrate, calcium chloride, calcium nitrate, GH-Ca, OS-Ca) and chitosan treatment to extend the shelf-life in the ‘Kumhong’ nectarine and ‘Madoka’ peach fruits. In this study, in the ‘Kumhong’ and ‘Madoka’ fruits, the expression of genes related to cell wall degradation, pectin lyase (PL), polygalacturonase (PG), and pectin methylesterase (PME), was inhibited by calcium, chitosan, or a mixture (Chitosan+CaCl2) treatment. In ‘Madoka’ peach, although the expression of the PG gene was suppressed at pre-harvest Ca and chitosan treatment, the expression of the PL gene was induced at pre- and post-harvest Ca and chitosan treatment compared to the control. The spray of calcium, chitosan itself, or a mixture (Chitosan+ CaCl2) on the trees at the ripening stage and harvested fruits can extend the shelf-life by suppressing the expression of cell wall degrading enzymes genes (PL, PG, PME) in ‘Kumhong’ nectarine and ‘Madoka’ peach tree. These results provide valuable information for the development of technology for the extension of the shelf-life of peach and nectarine fruits.

본 연구의 목적은 고독과 외로움에 관한 한국어 단어 도구를 개발하는 것이다. 적합한 단어를 수집하는 것이 매우 중요하므로, 3종의 국어사전에서 두 정서를 나타내는 것으로 판단되는 어휘를 선별하였다. 이때, 자발적 고독을 추구 하는 사람들의 증가 현상을 특별히 반영하여 관련 단어를 수집하였다. 그 결과, 총 1,768개의 단어로 구성된 총집을 마련하였다. 이어서 모든 사람이 이해하고 사용할 수 있는 구체적 기준에 근거해 총 684개의 단어로 선별한 후 6회의 반복적 선별 절차를 통해 총 243개의 단어를 선정하였다. 연구 특성상, 수집된 단어의 의미는 명확해야 하고 고독과 외로움의 전체적인 양상을 총체적으로 나타낼 수 있어야 한다. 이에 총 243개 단어에 대한 친숙성과 적절성의 평정치 가 공통으로 가장 높게 나타난 단어들을 중심으로 최종 선별하였다. 본 연구가 고독과 외로움에 대한 명확한 개념 정립과 한국인의 실제적이고 보편적인 인식을 발달적 관점에서 파악하는 데 활용 가능한 기초자료를 제공할 수 있을 것으로 기대한다.