• Korean Journal of Agricultural Science
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• v.48 no.4
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• pp.753-760
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• 2021

This study was carried out to discover suitable packaging methods during the cold or frozen storage of sawtooth oak and Japanese larch seedlings, which are major afforestation tree species in Korea. The weight loss rate of sawtooth oak was lower under frozen storage at -2℃ (maximum, 33.7%) than under cold storage at 2℃ (maximum, 61.0%). A film liner treatment inside the packaging box effectively suppressed the increase in the weight loss rate. For the sawtooth oak containerized seedlings, when stored at -2℃, the rate of weight loss was 17.9 to 25.4% in the untreated group and less than 1% in the film liner treatment group. Similar results were observed with Japanese larch. After two months of freezing at -2℃, both species maintained a low index of 1.0 - 1.1 with regard to the degree of shoot desiccation of containerized seedlings, and there was no significant difference between the treatments. On the other hand, the chlorine dioxide treatment could more effectively reduce the occurrence of mold and shoot desiccation than a PE single treatment in bare-root seedlings. According to these results, it was concluded that frozen storage is generally suitable as a means of long-term storage compared to cold storage of sawtooth oak and Japanese larch. A chlorine dioxide treatment at 20 ppm was effective for maintaining seedling quality levels during storage, demonstrating the good effect of suppressing the occurrence of shoot desiccation and the occurrence of mold.

• Geomechanics and Engineering
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• v.33 no.3
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• pp.279-289
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• 2023

Brittleness index (BI) is an important property of rocks because it is a good index to predict rockburst. Due to its importance, several empirical and soft computing (SC) models have been proposed in the literature based on the punch penetration test (PPT) results. These models are very important as there is no clear-cut experimental means for measuring BI asides the PPT which is very costly and time consuming to perform. This study used a novel Multivariate Adaptive regression spline (MARS), M5P, and white-box ANN to predict the BI of rocks using the available data in the literature for an improved BI prediction. The rock density, uniaxial compressive strength (σ_c) and tensile strength (σ_t) were used as the input parameters into the models while the BI was the targeted output. The models were implemented in the MATLAB software. The results of the proposed models were compared with those from existing multilinear regression, linear and nonlinear particle swarm optimization (PSO) and genetic algorithm (GA) based models using similar datasets. The coefficient of determination (R²), adjusted R² (Adj R²), root-mean squared error (RMSE) and mean absolute percentage error (MAPE) were the indices used for the comparison. The outcomes of the comparison revealed that the proposed ANN and MARS models performed better than the other models with R² and Adj R² values above 0.9 and least error values while the M5P gave similar performance to those of the existing models. Weight partitioning method was also used to examine the percentage contribution of model predictors to the predicted BI and tensile strength was found to have the highest influence on the predicted BI.

• Journal of Veterinary Science
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• v.23 no.1
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• pp.17.1-17.10
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• 2022

Background: Inspection of livestock farms using surveillance cameras is emerging as a means of early detection of transboundary animal disease such as African swine fever (ASF). Object tracking, a developing technology derived from object detection aims to the consistent identification of individual objects in farms. Objectives: This study was conducted as a preliminary investigation for practical application to livestock farms. With the use of a high-performance artificial intelligence (AI)-based 3D depth camera, the aim is to establish a pathway for utilizing AI models to perform advanced object tracking. Methods: Multiple crossovers by two humans will be simulated to investigate the potential of object tracking. Inspection of consistent identification will be the evidence of object tracking after crossing over. Two AI models, a fast model and an accurate model, were tested and compared with regard to their object tracking performance in 3D. Finally, the recording of pig pen was also processed with aforementioned AI model to test the possibility of 3D object detection. Results: Both AI successfully processed and provided a 3D bounding box, identification number, and distance away from camera for each individual human. The accurate detection model had better evidence than the fast detection model on 3D object tracking and showed the potential application onto pigs as a livestock. Conclusions: Preparing a custom dataset to train AI models in an appropriate farm is required for proper 3D object detection to operate object tracking for pigs at an ideal level. This will allow the farm to smoothly transit traditional methods to ASF-preventing precision livestock farming.

• Design Convergence Study
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• v.14 no.1
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• pp.83-98
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• 2015

This study will examine the visual composition by which Secretly Greatly, in a circumstance that even the good original Manhwas or Webtoon have not made a hit on the market until now, could attract the spectator, in other word, illustrate the analogousness of the images through analysing visual texts. The study draw, first of all, a meaning of the box office performance caused by analogousness of image, that is similarity between the webtoon and film. In addition, the study will come up with an answer to the question that the webtoon, not in a temporary trend but in a sustainable form, can make itself develop. For this, the study suggests a meaning, worth and importance of the transformation, analysing visual components of a webtoon to film adaptation, Secretly Greatly. It primarily ranges over visual components, mise-en-scène identified with its expression formula, frame to frame changes and colour and tone. The examination sets the cinema's visual expression manner against the webtoon's on their concrete components: the size of scene, movement, color and tone, narrative condition and its background, spatial composition and depth, contrast, expression manner and disposition manner.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.7 no.11
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• pp.235-244
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• 2017

This paper aims to design a system for psychological diagnosis in sandbox play by applying rule based expert system. Sandbox play is one of play therapy and it is a technique that can be combined with psychological diagnosis and treatment using sand and various kinds of figures. In this technique, we focus on psychological diagnostic factors and try to implement a system that automatically diagnoses psychological types when input values are given. Therefore, six kinds of language objects are set and the rules are created according to the types of figures, arrangement of figures, and production time in the sand box used as a reference element in the diagnosis method. In this system, it is assumed that the client recognizes the finished sandbox as a sensor device. Then, when the recognized state enters the input value, the rules based on the language object are ignited in order. Through this, the client is diagnosed with one of 26 types of psychology. As a result, the diagnostic process is simplified and automated. Accordingly, a more detailed psychological diagnosis and treatments are provided.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.240-240
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• 2020

강우 시 우수관로 내부의 수리 거동(유속, 수위)에 영향을 미치는 대표적인 매개변수는 관로의 조도계수와 손실계수 등이 있다. 이 중 조도계수는 관로 내부의 퇴적 및 협잡물로 인한 조도높이 변화에 따른 관로 내의 수리학적 거동을 평가할 수 있는 매개변수이며 손실계수는 관로의 확대, 축소, 만곡 등에 의한 에너지 감쇄 효과에 따른 관로 내 수리학적 변화를 평가할 수 있는 매개변수이다. 본 연구에서는 서울시 주요 배수구역에 대해 관로 조도계수 및 손실계수 변화에 따른 수위, 유속 변동성을 SWMM으로 분석하였다. 연구에 적용한 대상 배수구역은 반포 02 (방배1), 안양천 13 (봉천1), 성내 05 (길동), 안양천 11(신림4), 반포 03 (방배2), 안양천 01 (오류1), 성내 03 (천호)로 총 7개 배수구역이다. 모형수행을 위한 조건으로 조도계수는 0.015 ~ 0.120 구간에 대해 0.003 단위로 증가시키며 총 12개 CASE를 적용하였으며 손실계수는 0.0 ~ 0.5 구간에 대해 0.1 단위로 총 6개 CASE를 적용하였다. 관로 수리특성에 따른 수심, 유속의 변화량 분석 결과는 관로 및 유역의 크기별로 변화의 폭이 매우 크므로 상자-수염그림(Box-whisker plot) 이용하여 중간값의 변화 정도를 검토하였다. 조도계수 증가에 따른 수심증가, 유속 감소치의 중간값을 분석한 결과 조도계수가 0.013에서 0.034로 증가 시 수심은 40.6% 증가하고 유속은 47.4% 감소하는 것으로 검토되었다(그림 1, 2). 한편, 손실계수 증가에 따른 수심증가, 유속 감소치의 중간값을 분석한 결과 조도계수가 0.0에서 1.6으로 증가시 수심은 15.7% 증가하고 유속은 15.0% 감소하는 것으로 검토되었다. 이상과 같은 연구의 성과는 우수관로 내부의 다양한 여건 변화가 강우 시 관로 내 수리특성에 미치는 영향을 판단하기 위한 기초 자료로 활용할 수 있으며 향후, 우수관로 모니터링 결과와 연계하여 유지관리 방안 수립에 활용할 수 있을 것으로 판단된다.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.128-128
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• 2020

최근 농업환경의 변화와 기후변화에 대응하기 위해 농업용수 관리 정보화 및 과학화의 필요성이 증대되어 실시간으로 저수지 저수량과 농업용수 공급량을 파악하기 위해 자동 수위계측시설이 도입되었다. 농림축산식품부의 저수지 자동수위측정기 설치 및 운영지침에 따라 현재 농어촌공사 관리 저수지 1,734개소 및 수로부 1,880개소에 자동수위계가 설치되어 있으며, 저수지와 수로에서 10분 간격으로 수위자료가 생성되고 있다. 농업용 저수지 수문자료의 공인지점은 2016년 6개소에서 2019년 49개소로 증대되고 있으며, 데이터 품질 저하의 최소화 및 신뢰성 있는 수문자료 생성의 필요성이 증가함에 따라 농업용 저수지의 특성을 반영한 저수지 수위 오결측 데이터 보정 방안 및 수문 자료 품질관리 방안이 요구된다. 농업용 저수지의 수위 변화 및 강우-유출 현상은 물리적 모형을 구축하여 기상, 지형 등 영향 인자와 수위(또는 유출)와의 상관관계를 분석하는 것은 무적으로 불가능하였지만, 최근 인공신경망 (Artificial Neural Network, ANN) 등과 같이 black-box 형태의 모형을 이용하여 비선형적인 수문해석이 가능해졌다. 본 연구에서는 빅데이터와 인공신경망을 결합시킨 알고리즘인 딥러닝 (Deep Learning) 기반의 LSTM (Long Short-Term Memory) 모형을 활용하여 농업용 저수지 수위자료를 검토하여 자동계측기에서 발생하는 오류 보정을 위해 품질관리 방안을 제시하고자 한다.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.338-338
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• 2020

강우-유출 모형에 의한 유출해석은 하천의 기후변화 및 재난대응, 수자원확보, 유역개발 등의 정책수립을 위한 가장 기본적인 과정이다. 이를 위해 다양한 물리적 강우-유출모형이 개발되었으며 많은 연구들에 의해 유용성이 증명되었다. 그러나 메콩강 유역과 같이 물리적 데이터의 양적, 질적 신뢰도가 부족한 지역을 대상으로 하는 경우 모형의 기본적인 불확실성 외에 다양한 기초자료 및 매개변수의 결정 또는 추정에 의한 추가적인 불확실성이 포함된다. 본 연구에서는 물리적 강우-유출모형에 대한 대안으로 데이터 기반의 black-box 모형인 LSTM 모형을 이용하여 메콩강 본류 Kratie지점을 대상으로 강우-유출해석시스템을 구축하였다. 이후 기후변화시나리오를 적용하여 미래유출변화를 모의를 수행하였다. 도출된 결과는 물리적 강우-유출모형인 SWAT 모형의 유출해석결과의 비교를 수행하고 이를 통해 LSTM 모형의 적용성을 판단하였다. 관측유량 및 기온자료를 제외한 모형에서 요구되는 기초자료는 범용 입력자료를 이용하고 미래기간의 예측을 위해 편의보정 된 RCP 4.5 및 8.5 기후변화시나리오가 적용되었다. 두 모형의 Kratie 지점에 대한 미래 유출예측결과는 경향성 분석결과 두 모형 모두 시나리오 별 통계적으로 유의한 수준의 경향은 도출되지 않았으나 RCP 4.5 시나리오에 대비 RCP 8.5 시나리오에서 연평균 유량의 변동성이 크게 나타나는 것으로 분석되는 등 결과의 유사성을 보이고 있는 것으로 분석되었다. 이를 통해 LSTM 모형에 의한 유출예측결과가 단순 시계열 변화에 따른 유출변화 모의에 있어서 SWAT의 결과에 비해 높은 재현성을 보이는 것을 확인하였다. 본 연구와 같이 유출량의 시 계열 변화만을 필요로 하는 경우 적은 데이터만으로 비교적 정확한 결과를 도출하는 LSTM 모형은 매우 효과적으로 사용될 수 있다고 판단된다.

• ALGAE
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• v.38 no.2
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• pp.93-110
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• 2023

Progress in phylogenomic analysis has led to a considerable re-evaluation of former cyanobacterial system, with many new taxa being established at different nomenclatural levels. The family Geminocystaceae is among cyanobacterial taxa recently described on the basis of polyphasic approach. Within this family, there are six genera: Geminocystis, Cyanobacterium, Geminobacterium, Annamia, Picocyanobacterium, and Microcrocis. The genus Geminocystis previously encompassed two species: G. herdmanii and G. papuanica. Herein, a new species G. urbisnovae was proposed under the provision of the International Code of Nomenclature for algae, fungi, and plants (ICN). Polyphasic analysis was performed for five strains from the CALU culture collection (St. Petersburg State University, Russian Federation), and they were assigned to the genus Geminocystis in accordance with high 16S rRNA gene similarity to existing species, as well as because of proximity to these species on the phylogenetic trees reconstructed with RaxML and Bayes methods. Plausibility of their assignment to a separate species of the genus Geminocystis was substantiated with smaller cell size; stenohaline freshwater ecotype; capability to complementary chromatic adaptation of second type (CA2); distinct 16S rRNA gene clustering; sequences and folding of D1-D1' and B box domains of the 16S-23S internal transcribed spacer region. The second objective pursued by this communication was to provide a survey of the family Geminocystaceae. The overall assessment was that, despite attention of many researchers, this cyanobacterial family has been understudied and, especially in the case of the crucially important genus Cyanobacterium, taxonomically problematic.

• Journal of the Korea Fashion and Costume Design Association
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• v.25 no.2
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• pp.1-16
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• 2023

Due to the current seriousness of environmental pollution and the eco-friendly movement of the fashion industry, research on sustainable fashion design is being actively conducted. In this study, consumer perception of upcycling products, are divided into image, function, and meaning; and image is further divided into shape, color, and material. It was redefined as pattern, and image recognition was evaluated among men and women in their 20s and 30s, and men and women in their 40s and 50s used as subjects. First, factors that determine each image were extracted based on qualitative analysis of the precedent cases of upcycling bags, and quantitative analysis of the subjects was induced through a questionnaire. As a result of the analysis of evaluation items related to image association, the average frequency analysis of all subjects for each stimuli and the cognitive variance of the frequency analysis by generation by gender were found to be similar. However, awareness of some stimuli by generation showed a significant difference. Overall, in the three stimuli with high overall preference, common features, such as the basic box-shaped symmetrical structure, the monochromatic color of the Munsell system, solid and practical texture, and appropriate use of patterns were identified. In addition, it was confirmed that there was a difference with factors such as femininity, simplicity, touch, and splendor in the measurement factors. In conclusion, it is considered that the main significance of this study is that it excluded the recognition and meaning of upcycling products and explored the original design and image elements of products. Therefore, it is expected that this study will be used as a basic data for responding to the gender image of each generation as an alternative method of sustainable fashion design, and it will be an opportunity to expand the scope of the study to a detailed study beyond the biased topic.