• Title/Summary/Keyword: 성 판별

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Yield Comparison Simulation between Seasonal Climatic Scenarios for Italian Ryegrass (Lolium Multiflorum Lam.) in Southern Coastal Regions of Korea (우리나라 남부해안지역에서 이탈리안 라이그라스에 대한 계절적 기후시나리오 간 수량비교 시뮬레이션)

  • Kim, Moonju;Sung, Kyung Il
    • Journal of The Korean Society of Grassland and Forage Science
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    • v.42 no.1
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    • pp.1-9
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    • 2022
  • This study was carried out to compare the DMY (dry matter yield) of IRG (Italian ryegrass) in the southern coastal regions of Korea due to seasonal climate scenarios such as the Kaul-Changma (late monsoon) in autumn, extreme winter cold, and drought in the next spring. The IRG data (n = 203) were collected from various Reports for Collaborative Research Program to Develop New Cultivars of Summer Crops in Jeju, 203 Namwon, and Yeungam from the Rural Development Administration - (en DASH). In order to define the seasonal climate scenarios, climate variables including temperature, humidity, wind, sunshine were used by collected from the Korean Meteorological Administration. The discriminant analysis based on 5% significance level was performed to distinguish normal and abnormal climate scenarios. Furthermore, the DMY comparison was simulated based on the information of sample distribution of IRG. As a result, in the southern coastal regions, only the impact of next spring drought on DMY of IRG was critical. Although the severe winter cold was clearly classified from the normal, there was no difference in DMY. Thus, the DMY comparison was simulated only for the next spring drought. Under the yield comparison simulation, DMY (kg/ha) in the normal and drought was 14,743.83 and 12,707.97 respectively. It implies that the expected damage caused by the spring drought was about 2,000 kg/ha. Furthermore, the predicted DMY of spring drought was wider and slower than that of normal, indicating on high variability. This study is meaningful in confirming the predictive DMY damage and its possibility by spring drought for IRG via statistical simulation considering seasonal climate scenarios.

Violation Detection of Application Network QoS using Ontology in SDN Environment (SDN 환경에서 온톨로지를 활용한 애플리케이션 네트워크의 품질 위반상황 식별 방법)

  • Hwang, Jeseung;Kim, Ungsoo;Park, Joonseok;Yeom, Keunhyuk
    • The Journal of Korean Institute of Next Generation Computing
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    • v.13 no.6
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    • pp.7-20
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    • 2017
  • The advancement of cloud and big data and the considerable growth of traffic have increased the complexity and problems in the management inefficiency of existing networks. The software-defined networking (SDN) environment has been developed to solve this problem. SDN enables us to control network equipment through programming by separating the transmission and control functions of the equipment. Accordingly, several studies have been conducted to improve the performance of SDN controllers, such as the method of connecting existing legacy equipment with SDN, the packet management method for efficient data communication, and the method of distributing controller load in a centralized architecture. However, there is insufficient research on the control of SDN in terms of the quality of network-using applications. To support the establishment and change of the routing paths that meet the required network service quality, we require a mechanism to identify network requirements based on a contract for application network service quality and to collect information about the current network status and identify the violations of network service quality. This study proposes a method of identifying the quality violations of network paths through ontology to ensure the network service quality of applications and provide efficient services in an SDN environment.

Improvement and Operation of Urban Inundation Forecasting System in Seoul (서울시 도시침수 예측시스템의 개선 및 운영)

  • Shim, Jea Bum;Kim, Ho Soung;Gang, Tae hun;Lee, Byong Ju
    • Proceedings of the Korea Water Resources Association Conference
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    • 2021.06a
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    • pp.481-481
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    • 2021
  • 서울시는 '10년, '11년, '18년의 기록적인 호우로 인해 막대한 재산피해를 기록하였다. 이로 인해 서울시는 수재해 최소화 대책의 필요성을 인지하여 방재시설물 확충 등의 구조적 대책과 함께 침수지역 예측, 호우 영향 예보와 관련된 비구조적 대책 수립을 위해 노력하고 있다. 그 일환으로 2018~2019년 『서울시 강한 비구름 유입경로 및 침수위험도 예측 용역』 수행을 통해 레이더 실황강우 기반의 강한 비구름 이동경로 추정 기술, 강우시나리오 기반의 침수위험지역추정 기술이 적용된 서울시 도시침수 예측시스템을 개발하였다. 또한, 침수피해에 선제적으로 대응하기 위해 2019~2020년 『서울시 내수침수 위험지역 실시간 예측기술 개발』을 통하여 이류모델 기반의 예측강우정보 추정 기술, 예측강우정보 기반의 실시간 침수위험지역 추정기술을 적용하였다. 현재 서울시 도시침수 예측시스템은 서울시 전역의 강우 및 침수정보를 제공하며, 관로 113,286개(전체 385,768개), 맨홀 106,097개(전체 272,133개), 빗물펌프장 117개소(전체 121개소)가 반영되어 있다. 서울시 도시침수 예측시스템에서는 서울시 25개 자치구를 대상으로 실황 및 예측 강우정보, 강한 비구름에 대한 이동경로정보, 시나리오 및 실시간 침수정보를 제공하고 있다. 강우정보는 10분 및 1시간 단위 AWS 실황정보와 10분 단위 이류모델 기반 예측정보, 1시간 단위 LDAPS 기반 예측정보를 제공한다. 또한, 레이더 실황정보를 통해 판별된 강한 비구름에 대해 10분 단위 1시간 예측경로를 제공한다. 침수정보는 총강우량, 강우지속기간, 빗물받이효율 조건을 반영한 강우시나리오 기반의 6m 고해상도 격자단위 침수시나리오 정보와 자치구별 침수위험정보를 제공한다. 또한, 이류모델 기반의 레이더 예측정보를 이용하여 실시간 침수 예측정보를 제공한다. 향후 서울시 내 모든 수방시설물의 적용, 관로 유출구별 기점수위 반영, 관측자료를 이용한 도시유출 및 도시침수 모델 최적화 등 지속적으로 고도화를 수행하고자 하며, 서울시 도시침수 예측시스템을 통해 서울시 및 자치구 풍수해 담당자가 침수피해를 대비, 대응할 수 있을 것으로 기대된다.

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Trace element analysis of korean car windshield using LA-ICP-MS (LA-ICP-MS를 이용한 한국 자동차 유리의 미량원소 분석)

  • Min, Ji-Sook;Choi, Man-Sik;Heo, Sang-Cheol;Kim, Jae-Kyun
    • Analytical Science and Technology
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    • v.22 no.3
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    • pp.235-246
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    • 2009
  • The analyses of minor and trace elements in glass debris were performed using LA-ICP-MS in order to identify manufacturers using real commercial samples. At first, a calibration curve was made using standard glass samples of NIST 610, 612, 614 and 616. $^{29}Si$ was used as an internal standard, and the ratios of metal/Si for each metal were compared with their concentrations. Based on elements in each sample and standard materials, 24 metals were quantified and the LOD in analysis, according to the blank sample, was in the range of 0.11 mg/kg (Ti)-4.91 mg/kg (Ca). Eleven samples from two manufacturers were collected and five sub-samples were taken from each sample for analysis. 15 elements (Co, Ce, Ca, Mn, Sr, Ba, Li, Rb, U, La, Th, Na, Al, Zr and Hf) were selected to identify manufacturers because some elements (Cu, Cr, Cd and Ni) were below the detection limit and some elements (Ti, Pr, Mg, Nb, Nd) were absent in the analysis of standards and others (Pb and Sn) had a problem of homogeneity. The attempts to identify manufacturers and the manufacturing period were performed through a triangular diagram. In the manufacturer discrimination by discriminant analysis, a canonical discriminant function was made based on Mn, Ce and Rb, and each sample could be identified.

Logo Renewal Design according to Strategy for Renewal based on Brand Life Cycle Focused on Cases for brands in Food and beverages (브랜드 수명 주기별 리뉴얼 전략에 따른 로고 리뉴얼 디자인 - 식음료 브랜드 사례를 중심으로 -)

  • Lee Yerim;Han Jiae
    • Smart Media Journal
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    • v.12 no.5
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    • pp.111-121
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    • 2023
  • The purpose of this study is to find methods for logo renewal design according to the brand life cycle, considering the logo as an important visual tool that represents the brand identity in terms of brand management. This study was conducted through literature study on brand life cycle and brand renewal strategy, an expert survey on logo renewal design, and logo analysis of 35 food and beverage brands with statistical data to determine brand life cycle. The results of the study are three. First, the four stages(introduction, growth, maturity, and decline) of brand life cycle characteristics and renewal strategies were derived. Second, four brand renewal strategies(partial change, total change, repositioning, new image creation) and methods for logo renewal design were proposed based on the life cycle of the brand. Based on this, renewal characteristics for each life cycle were proposed. Third, visual elements of identity that are important depending on the brand life cycle and brand renewal strategy were found. It was found that the addition and subtraction of graphic elements and change of color tone are important in the partial change strategy of the growth period and maturity period, and that the change of signature color is important in the repositioning strategy and the creation of the new image.

Validity of the Happiness-Enhancing Activities and Positive Practices Inventory(HAPPI) Scale in Physical Activities Participation in Korean Old Adults (신체활동참여 한국 노인을 위한 행복증진활동(HAPPI)척도의 구인타당도)

  • Kim, Woo-Kyung
    • Journal of Korea Entertainment Industry Association
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    • v.13 no.7
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    • pp.285-294
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    • 2019
  • The purpose of this study is to assess construct validity and verify the concept of the Happiness-enhancing Activities and Positive Practices Inventory(HAPPI) developed by Henricksen & Stephens(2013), for Korean old adults who participating physical activities with measuring happiness-related propensity. In this study, the research model was confirmed by evidenced based on the content validity, EFA, construct validity of the latent structure analysis with CFA, reliability as internal consistency. Using self-reported questionnaire conducted among 370 participants who physical activities. Total of 344 data were selected. As a result, internal consistency α was acceptable. Evidence-based on convergent and discriminant of the CFA as GFI=.925, CFI .962, TLI .953, and RMSEA .062 appeared significantly. Model goodness-of-fit, C.R. ratio(Critical ratio: estimates/SE) and Squared Multiple Correlations(SMC), and average variance extracted(AVE) was verified with the hypothesis of the model. Therefore, HAPPI validity evidence for the model fit was confirmed. In conclusion, the HAPPI 4 factors and 16 items(Other-focused, Personal recreation and interests, Achievement, Self-Concordant Work, Spiritual and thought-related) has reliable evidence to apply for Korean old adults and applicable assessment of happiness.

International Case Study and Strategy Proposal for IUCN Red List of Ecosystem(RLE) Assessment in South Korea (국내 IUCN Red List of Ecosystem(생태계 적색목록) 평가를 위한 국제 사례 연구와 전략 제시)

  • Sang-Hak Han;Sung-Ryong Kang
    • Journal of Wetlands Research
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    • v.25 no.4
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    • pp.408-416
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    • 2023
  • The IUCN Red List of Ecosystems serves as a global standard for assessing and identifying ecosystems at high risk of biodiversity loss, providing scientific evidence necessary for effective ecosystem management and conservation policy formulation. The IUCN Red List of Ecosystems has been designated as a key indicator (A.1) for Goal A of the Kunming-Montreal Global Biodiversity Framework. The assessment of the Red List of Ecosystems discerns signs of ecosystem collapse through specific criteria: reduction in distribution (Criterion A), restricted distribution (Criterion B), environmental degradation (Criterion C), changes in biological interaction (Criterion D), and quantitative estimation of the risk of ecosystem collapse (Criterion E). Since 2014, the IUCN Red List of Ecosystems has been evaluated in over 110 countries, with more than 80% of the assessments conducted in terrestrial and inland water ecosystems, among which tropical and subtropical forests are distributed ecosystems under threat. The assessment criteria are concentrated on spatial signs (Criteria A and B), accounting for 68.8%. There are three main considerations for applying the Red List of Ecosystems assessment domestically: First, it is necessary to compile applicable terrestrial ecosystem types within the country. Second, it must be determined whether the spatial sign assessment among the Red List of Ecosystems categories can be applied to the various small-scale ecosystems found domestically. Lastly, the collection of usable time series data (50 years) for assessment must be considered. Based on these considerations, applying the IUCN Red List of Ecosystems assessment domestically would enable an accurate understanding of the current state of the country's unique ecosystem types, contributing to global efforts in ecosystem conservation and restoration.

Establishment of a deep learning-based defect classification system for optimizing textile manufacturing equipment

  • YuLim Kim;Jaeil Kim
    • Journal of the Korea Society of Computer and Information
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    • v.28 no.10
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    • pp.27-35
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    • 2023
  • In this paper, we propose a process of increasing productivity by applying a deep learning-based defect detection and classification system to the prepreg fiber manufacturing process, which is in high demand in the field of producing composite materials. In order to apply it to toe prepreg manufacturing equipment that requires a solution due to the occurrence of a large amount of defects in various conditions, the optimal environment was first established by selecting cameras and lights necessary for defect detection and classification model production. In addition, data necessary for the production of multiple classification models were collected and labeled according to normal and defective conditions. The multi-classification model is made based on CNN and applies pre-learning models such as VGGNet, MobileNet, ResNet, etc. to compare performance and identify improvement directions with accuracy and loss graphs. Data augmentation and dropout techniques were applied to identify and improve overfitting problems as major problems. In order to evaluate the performance of the model, a performance evaluation was conducted using the confusion matrix as a performance indicator, and the performance of more than 99% was confirmed. In addition, it checks the classification results for images acquired in real time by applying them to the actual process to check whether the discrimination values are accurately derived.

Implementation and Evaluation of Optimal Dose Control for Portable Detectors with SiPM (SiPM을 통한 휴대용 검출기의 최적 선량 제어에 대한 구현 및 평가)

  • Byung-Wuk Kang;Sun-Kook Yoo
    • Journal of the Korean Society of Radiology
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    • v.17 no.7
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    • pp.1139-1147
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    • 2023
  • The purpose of this paper is to present and evaluate the performance of a method for controlling the dose for optimal image acquisition while minimizing patient exposure by applying a small-sized Photomultiplier(SiPM) sensor inside a portable detector. Portable detectors have the advantage of being able to quickly access the patient's location for rapid diagnosis, but this mobility comes with the challenge of dose control. This paper presents a method to identify the dose that can have the DQE and optimal image quality of the detector through image evaluation based on IEC62220-1-1, an international standard for X-ray imaging devices, and to identify the optimal dose by matching the ADU of the image and the output of the SiPM Sensor. The Skull AP image was acquired by implementing the detector manufacturer's reference dose. The optimal dose was 342.8 µGy, and the optimal controlled dose was 148.3 µGy, which is 57 % of the manufacturer's reference dose. The Chest AP image was 81.9 µGy and the optimal controlled dose was 27.9 µGy, which is a high dose reduction effect of 66 %. In addition, the two images were analyzed by five radiologists and found to have no clinically significant difference in anatomical delineation.

Analysis of Microbial Community Change in Ganjang According to the Size of Meju (메주의 크기에 따른 간장의 미생물 군집 변화 양상 분석)

  • Ho Jin Jeong;Gwangsu Ha;Ranhee Lee;Do-Youn Jeong;Hee-Jong Yang
    • Journal of Life Science
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    • v.34 no.7
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    • pp.453-464
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    • 2024
  • The fermentation of ganjang is known to be greatly influenced by the microbial communities derived from its primary ingredients, meju and sea salt. This study investigated the effects of changes in meju size on the distribution and correlation of microbial communities in ganjang fermentation, to enhance its fermentation process. Ganjang was prepared using whole meju and meju divided into thirds, and samples were collected at 7-day intervals over a period of 28 days for microbial community analysis based on 16S rRNA gene sequencing. At the genus level, during fermentation, ganjang made with whole meju exhibited a dominance of Chromohalobacter (day 7), Pediococcus (day 14), Bacillus (day 21), and Pediococcus (day 28), whereas ganjang made with meju divided into thirds consistently showed a Pediococcus predominance over the 28 days. Beta-diversity analysis of microbial communities in ganjang with different meju sizes revealed significant separation of microbial communities at fermentation days 7 and 14 but not at days 21 and 28 across all experimental groups. The linear discriminant analysis effect size (LEfSe) was determined to identify biomarkers contributing to microbial community differences at days 7 and 14, showing that on day 7, potentially halophilic microbes such as Gammaproteobacteria, Firmicutes, Oceanospirillales, Halomonadaceae, Bacilli, and Chromohalobacter were prominent, whereas on day 14, lactic acid bacteria such as Pediococcus acidilactici, Lactobacillaceae, Pediococcus, Bacilli, Leuconostocaceae, and Weissella were predominant. Furthermore, correlation analysis of microbial communities at the genus and species levels revealed differences in correlation patterns between meju sizes, suggesting that meju size may influence microbial interactions within ganjang.