• Title/Summary/Keyword: Cover ratio

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Estimation of Surplus Solar Energy in Greenhouse Based on Region (지역별 온실내의 잉여 태양에너지 산정)

  • Yoon, Yong-Cheol;Im, Jae-Un;Kim, Hyeon-Tae;Kim, Young-Joo;Suh, Won-Myung
    • Journal of agriculture & life science
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    • v.45 no.4
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    • pp.135-141
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    • 2011
  • This research was conducted to provide basic data of surplus heat for designing solar heat-storage systems. The surplus heat is defined as the heat exhausted by forced ventilations from the greenhouses to control the greenhouse temperature within setting limits. Various simulations were performed to compare the differences of thermal behaviors among greenhouse types as well as among several domestic areas by using pseudo-TMY (Typical Meteorological Year) data manipulated based both on the weather data supplied from Korean Meteorological Administration and the TMY data supplied from The Korean Solar Energy Society. Additional analyses were carried out to examine the required heating energy together with some others such as the energy balances in greenhouses to be considered. The results of those researches are summarized as follows. Regional surplus solar heats for the nine regions with 4-type were analyzed. The results showed that the ratio of surplus solar energy compared to heating energy was the highest in Jeju (about 212.0~228.0%) for each greenhouse type. And followed by Busan, Kwangju, Jinju, Daegu, Daejeon, Jeonju, Suwon and Daekwanryung. And irrespective of greenhouse types, surplus solar energy alone could cover up nearly all of the required supplemental heating energy except for a few areas.

Development of Risk Evaluation Checklist for In-Situ Production of Precast Concrete Members (기성콘크리트 부재의 현장생산 리스크 평가를 위한 체크리스트 개발)

  • Lim, Jeeyoung;Jeong, Hee Woong;Kim, Dae Young
    • Journal of the Korea Institute of Building Construction
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    • v.21 no.5
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    • pp.445-457
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    • 2021
  • In previous studies, it was confirmed that through the in-situ production of precast concrete members, costs could be reduced by 14.5-39.4% compared to in-plant production. In particular, it was confirmed that the factory owner did not make a contract if it did not earn more than 20% of the production cost. If precast concrete members are produced in-situ under the same conditions, the quality equivalent to that of factory production can be secured. As it is advantageous in terms of cost and quality, precast concrete members must be produced in-situ. However, it is difficult to produce all quantities in-situ due to time and various other constraints. This is because in-situ production is avoided due to anticipated risks during the project management process. However, if the risk factors are analyzed before performing in-situ production of precast concrete members, it will increase the opportunity for in-situ production. Therefore, this study develops a checklist for evaluating the risk of in-situ production of precast concrete members. By applying the checklist to one case site, it was verified that risk factors can be evaluated easily and quickly. As a result, it was analyzed that sites with a high building coverage ratio are classified as high-risk sites because it is difficult to secure usable area for production and storage. The developed checklist efficiently evaluates the risk factors of in-site production, and makes it possible for the operator to determine the risk factors, which can change frequently during project execution, and respond according to the situation.

Prediction of Potential Habitat and Damage Amount of Rare·Endemic Plants (Sophora Koreensis Nakai) Using NBR and MaxEnt Model Analysis - For the Forest Fire Area of Bibongsan (Mt.) in Yanggu - (NBR과 MaxEnt 모델 분석을 활용한 희귀특산식물(개느삼) 분포 및 피해량 예측 - 양구 비봉산 산불피해지를 대상으로-)

  • Yun, Ho-Geun;Lee, Jong-Won;An, Jong-Bin;Yu, Seung-Bong;Bak, Gi-Ppeum;Shin, Hyun-Tak;Park, Wan-Geun;Kim, Sang-Jun
    • Korean Journal of Plant Resources
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    • v.35 no.2
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    • pp.169-182
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    • 2022
  • This study was conducted to predict the distribution of rare·endemic plants (Sophora koreensis Nakai) in the border forests where wildfire damage occurred and to quantify the damage. For this purpose, we tried to derive more accurate results through forest area damage (NBR) according to the Burn severity of wildfires, damage by tree species type (Vegetation map), and MaxEnt model. For Burn severity analysis, satellite imagery (Landsat-8) was used to analyze Burn severity (ΔNBR2016-2015) and to derive the extent of damage. To prepare the Vegetation map, the land cover map prepared by the Ministry of Environment, the Vegetation map prepared by the Korea Forest Service, and the vegetation survey conducted by itself were conducted to prepare the clinical map before and after the forest fire. Lastly, for MaxEnt model analysis, the AUC value was derived by using the habitat coordinates of Sophora koreensis Nakai based on the related literature and self-report data. As a result of combining the Maxent model analysis data with the Burn severity data, it was confirmed that 45.9% of the 44,760 m2 of habitat (predicted) area of Sophora koreensis Nakai in the wildfire damaged area or 20,552 m2, was damaged.

Analysis Study on the Detection and Classification of COVID-19 in Chest X-ray Images using Artificial Intelligence (인공지능을 활용한 흉부 엑스선 영상의 코로나19 검출 및 분류에 대한 분석 연구)

  • Yoon, Myeong-Seong;Kwon, Chae-Rim;Kim, Sung-Min;Kim, Su-In;Jo, Sung-Jun;Choi, Yu-Chan;Kim, Sang-Hyun
    • Journal of the Korean Society of Radiology
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    • v.16 no.5
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    • pp.661-672
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    • 2022
  • After the outbreak of the SARS-CoV2 virus that causes COVID-19, it spreads around the world with the number of infections and deaths rising rapidly caused a shortage of medical resources. As a way to solve this problem, chest X-ray diagnosis using Artificial Intelligence(AI) received attention as a primary diagnostic method. The purpose of this study is to comprehensively analyze the detection of COVID-19 via AI. To achieve this purpose, 292 studies were collected through a series of Classification methods. Based on these data, performance measurement information including Accuracy, Precision, Area Under Cover(AUC), Sensitivity, Specificity, F1-score, Recall, K-fold, Architecture and Class were analyzed. As a result, the average Accuracy, Precision, AUC, Sensitivity and Specificity were achieved as 95.2%, 94.81%, 94.01%, 93.5%, and 93.92%, respectively. Although the performance measurement information on a year-on-year basis gradually increased, furthermore, we conducted a study on the rate of change according to the number of Class and image data, the ratio of use of Architecture and about the K-fold. Currently, diagnosis of COVID-19 using AI has several problems to be used independently, however, it is expected that it will be sufficient to be used as a doctor's assistant.

Exposure Assessment of Dust, Ultra Fine Dust(Particulate Matter 2.5, PM2.5) and Black Carbon among Aircraft Cabin Cleaners (항공기 기내 청소노동자의 분진, 초미세먼지(PM2.5) 및 블랙카본 노출수준 평가)

  • Hyunhee Park;Sedong Kim;Sungho Kim;Seung-Hyun Park
    • Journal of Korean Society of Occupational and Environmental Hygiene
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    • v.33 no.2
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    • pp.171-187
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    • 2023
  • Objectives: Aircraft cabin cleaning work is characterized by being performed within a limited time in a narrow and enclosed space. The objective of this study was to evaluate the exposure levels to dust, ultra fine dust(PM2.5) and black carbon(BC) among aircraft cabin cleaners. Methods: Active personal air sampling for respirable dust(n=73) and BC(n=47) was conducted during quick transit cleaning(cabin general and vacuum-specific) and seat cover replacement and total dust and PM2.5 were area-air-sampled as well. Also, size distribution of particle was identified with the cleaning workers targeted. Dusts were collected with PVC filters using gravimetric analysis. The concentration of PM2.5 and the particle size distribution were measured with real-time direct reading portable equipment using light scattering analysis. The concentration of BC was measured by aethalometer(filter-based real-time light absorption analysis instrument). Results: The geometric mean of respirable dust was the highest at vacuum cleaning as 74.4 ㎍/m3, following by replacing seat covers as 49.3 ㎍/m3 and cabin general cleaning as 47.8 ㎍/m3 . The arithmetic mean of PM2.5 was 4.83 ~ 9.89 ㎍/m3 inside the cabin, and 28.5~44.5 ㎍/m3 outside the cabin(from bus and outdoor waiting space). From size distribution, PM2.5/PM10 ratio was 0.54 at quick transit cleaning and 0.41 at replacing seat covers. The average concentration of BC was 2~7 ㎍/m3, showing a high correlation with the PM2.5 concentration. Conclusions: The hazards concentration levels of aircraft cabin cleaners were very similar to those of roadside outdoor workers. As the main source of pollution is estimated to be diesel vehicles operating at airports, and it is necessary to replace older vehicles, strengthen pollutant emission control regulations, and introduce electric vehicles. In addition, it is necessary to provide as part of airport-inftastructure a stable standby waiting space for aircraft cabin cleaners and introduce a systematic safety and health management system for all workers in the aviation industry.

A Study on the Care Policy for the Elderly in Super-aged Society (초고령 사회의 노인 돌봄 정책에 관한 융복합 연구)

  • Dong-Gun Kim
    • Journal of Digital Convergence
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    • v.22 no.2
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    • pp.21-28
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    • 2024
  • This study analyzed the current status of care policies and senior citizen issues in Korea, which has entered a super-aging society, and attempted to suggest improvement measures for desirable convergence policies. The problems of the elderly in Korea have emerged as health problems, poverty problems, loss of roles, and care problems due to changes in the concept of family, values, and socioeconomic structure. In addition, poor seniors need jobs and employment policies, and healthy middle-class seniors need policy development to enable leisure activities and volunteer activities. In particular, it is necessary to establish policies to enable people to spend the rest of their lives in elderly care facilities and elderly care hospitals through community care policies. The super-aging society accounts for more than 20% of the total population among those aged 65 or older, and according to the National Statistical Office, it is expected to become a super-aging society by 2025. Elderly welfare policies must provide various programs and the needs and services of elderly care, and in the future, a super-aging society will need to secure a lot of financial resources and maintain a productive population to cover the financial resources. In other words, the human life cycle is from birth to death, and when the ratio of natural deaths of the elderly and infants born is appropriate, the society and the country can be seen as stable, vibrant, and healthy societies.

LIM Implementation Method for Planning Biotope Area Ratio in Apartment Complex - Focused on Terrain and Pavement Modeling - (공동주택단지의 생태면적률 계획을 위한 LIM 활용방법 - 지형 및 포장재 모델링을 중심으로 -)

  • Kim, Bok-Young;Son, Yong-Hoon;Lee, Soon-Ji
    • Journal of the Korean Institute of Landscape Architecture
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    • v.46 no.3
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    • pp.14-26
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    • 2018
  • The Biotope Area Ratio (BAR) is a quantitative pre-planning index for sustainable development and an integrated indicator for the balanced development of buildings and outdoor spaces. However, it has been pointed out that there are problems in operations management: errors in area calculation, insufficiency in the underground soil condition and depth, reduction in biotope area after construction, and functional failure as a pre-planning index. To address these problems, this study proposes implementing LIM. Since the weights of the BAR are mainly decided by the underground soil condition and depth with land cover types, the study focused on the terrain and pavements. The model should conform to BIM guidelines and standards provided by government agencies and professional organizations. Thus, the scope and Level Of Detail (LOD) of the model were defined, and the method to build a model with BIM software was developed. An apartment complex on sloping ground was selected as a case study, a 3D terrain modeled, paving libraries created with property information on the BAR, and a LIM model completed for the site. Then the BAR was calculated and construction documents were created with the BAR table and pavement details. As results of the study, it was found that the application of the criteria on the BAR and calculation became accurate, and the efficiency of design tasks was improved by LIM. It also enabled the performance of evidence-based design on the terrain and underground structures. To adopt LIM, it is necessary to create and distribute LIM library manuals or templates, and build library content that comply with KBIMS standards. The government policy must also have practitioners submit BIM models in the certification system. Since it is expected that the criteria on planting types in the BAR will be expanded, further research is needed to build and utilize the information model for planting materials.

Estimation of Rice and Soybean Growth Stage Using a Microwave Scatterometer (마이크로파 산란계를 이용한 벼, 콩 생육단계 추정)

  • Kim, Yi-Hyun;Hong, Suk-Young;Lee, Hoon-Yol;Lee, Jae-Eun;Lee, Kyung-Do
    • Korean Journal of Soil Science and Fertilizer
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    • v.45 no.4
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    • pp.503-510
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    • 2012
  • Microwave radar can penetrate cloud cover regardless of weather conditions and can be used day and night. Especially a A ground-based polarimetric scatterometer operating at multiple frequencies can continuously monitor the crop conditions. We analyzed scattering characteristics of rice and soybean using pauli decomposition method. Surface scattering (${\alpha}$) is the dominant component over the entire stages for all bands and pauli decomposition value was the highest for L-band. Double bounce scattering (${\beta}$) and volume scattering (${\gamma}$) were approximately equal for C-band and volume scattering was higher than double bounce scattering for X-band in rice field. In soybean, double bounce scattering becomes higher than volume scattering during the R2 stage (DOY 224) and there was a significant difference between the two components after the R4 stage (DOY 242) for L-band. The maximum growth stage of soybean can also be detected using L-band double bounce scattering. The peak of double bounce effect coincides with the peak of growth biophysical variables on DOY 271. We found that pauli decomposition can provide insight on the relative magnitude of different scattering mechanisms during the rice and soybean growth cycle.

Design Evaluation Model Based on Consumer Values: Three-step Approach from Product Attributes, Perceived Attributes, to Consumer Values (소비자 가치기반 디자인 평가 모형: 제품 속성, 인지 속성, 소비자 가치의 3단계 접근)

  • Kim, Keon-Woo;Park, Do-Hyung
    • Journal of Intelligence and Information Systems
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    • v.23 no.4
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    • pp.57-76
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    • 2017
  • Recently, consumer needs are diversifying as information technologies are evolving rapidly. A lot of IT devices such as smart phones and tablet PCs are launching following the trend of information technology. While IT devices focused on the technical advance and improvement a few years ago, the situation is changed now. There is no difference in functional aspects, so companies are trying to differentiate IT devices in terms of appearance design. Consumers also consider design as being a more important factor in the decision-making of smart phones. Smart phones have become a fashion items, revealing consumers' own characteristics and personality. As the design and appearance of the smartphone become important things, it is necessary to examine consumer values from the design and appearance of IT devices. Furthermore, it is crucial to clarify the mechanisms of consumers' design evaluation and develop the design evaluation model based on the mechanism. Since the influence of design gets continuously strong, various and many studies related to design were carried out. These studies can classify three main streams. The first stream focuses on the role of design from the perspective of marketing and communication. The second one is the studies to find out an effective and appealing design from the perspective of industrial design. The last one is to examine the consumer values created by a product design, which means consumers' perception or feeling when they look and feel it. These numerous studies somewhat have dealt with consumer values, but they do not include product attributes, or do not cover the whole process and mechanism from product attributes to consumer values. In this study, we try to develop the holistic design evaluation model based on consumer values based on three-step approach from product attributes, perceived attributes, to consumer values. Product attributes means the real and physical characteristics each smart phone has. They consist of bezel, length, width, thickness, weight and curvature. Perceived attributes are derived from consumers' perception on product attributes. We consider perceived size of device, perceived size of display, perceived thickness, perceived weight, perceived bezel (top - bottom / left - right side), perceived curvature of edge, perceived curvature of back side, gap of each part, perceived gloss and perceived screen ratio. They are factorized into six clusters named as 'Size,' 'Slimness,' 'No-Frame,' 'Roundness,' 'Screen Ratio,' and 'Looseness.' We conducted qualitative research to find out consumer values, which are categorized into two: look and feel values. We identified the values named as 'Silhouette,' 'Neatness,' 'Attractiveness,' 'Polishing,' 'Innovativeness,' 'Professionalism,' 'Intellectualness,' 'Individuality,' and 'Distinctiveness' in terms of look values. Also, we identifies 'Stability,' 'Comfortableness,' 'Grip,' 'Solidity,' 'Non-fragility,' and 'Smoothness' in terms of feel values. They are factorized into five key values: 'Sleek Value,' 'Professional Value,' 'Unique Value,' 'Comfortable Value,' and 'Solid Value.' Finally, we developed the holistic design evaluation model by analyzing each relationship from product attributes, perceived attributes, to consumer values. This study has several theoretical and practical contributions. First, we found consumer values in terms of design evaluation and implicit chain relationship from the objective and physical characteristics to the subjective and mental evaluation. That is, the model explains the mechanism of design evaluation in consumer minds. Second, we suggest a general design evaluation process from product attributes, perceived attributes to consumer values. It is an adaptable methodology not only smart phone but also other IT products. Practically, this model can support the decision-making when companies initiative new product development. It can help product designers focus on their capacities with limited resources. Moreover, if its model combined with machine learning collecting consumers' purchasing data, most preferred values, sales data, etc., it will be able to evolve intelligent design decision support system.

Wildfire Severity Mapping Using Sentinel Satellite Data Based on Machine Learning Approaches (Sentinel 위성영상과 기계학습을 이용한 국내산불 피해강도 탐지)

  • Sim, Seongmun;Kim, Woohyeok;Lee, Jaese;Kang, Yoojin;Im, Jungho;Kwon, Chunguen;Kim, Sungyong
    • Korean Journal of Remote Sensing
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    • v.36 no.5_3
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    • pp.1109-1123
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    • 2020
  • In South Korea with forest as a major land cover class (over 60% of the country), many wildfires occur every year. Wildfires weaken the shear strength of the soil, forming a layer of soil that is vulnerable to landslides. It is important to identify the severity of a wildfire as well as the burned area to sustainably manage the forest. Although satellite remote sensing has been widely used to map wildfire severity, it is often difficult to determine the severity using only the temporal change of satellite-derived indices such as Normalized Difference Vegetation Index (NDVI) and Normalized Burn Ratio (NBR). In this study, we proposed an approach for determining wildfire severity based on machine learning through the synergistic use of Sentinel-1A Synthetic Aperture Radar-C data and Sentinel-2A Multi Spectral Instrument data. Three wildfire cases-Samcheok in May 2017, Gangreung·Donghae in April 2019, and Gosung·Sokcho in April 2019-were used for developing wildfire severity mapping models with three machine learning algorithms (i.e., Random Forest, Logistic Regression, and Support Vector Machine). The results showed that the random forest model yielded the best performance, resulting in an overall accuracy of 82.3%. The cross-site validation to examine the spatiotemporal transferability of the machine learning models showed that the models were highly sensitive to temporal differences between the training and validation sites, especially in the early growing season. This implies that a more robust model with high spatiotemporal transferability can be developed when more wildfire cases with different seasons and areas are added in the future.