South Korea is pushing for the advancement of crop production technology to achieve food self-sufficiency and meet the demand for safe food. A medium-sized satellite for agriculture is being launched in 2023 with the aim of collecting and providing information on agriculture, not only in Korea but also in neighboring countries. The satellite is to be equipped with various sensors, though reference data for ground information are lacking. Hyperspectral remote sensing combined with 1st derivative is an efficient tool for the identification of agricultural crops. In our study, we develop a system for hyperspectral analysis of the ground-based reflectance spectrum, which is monitored seven times during the cultivation period of three soybean crops using a PSR-2500 hyperspectral sensor. In the reflection spectrum of soybean canopy, wavelength variations correspond with stages of soybean growths. The spectral reflection characteristics of soybeans can be divided according to growth into the vegetative (V)stage and the reproductive (R)stage. As a result of the first derivative analysis of the spectral reflection characteristics, it is possible to identify the characteristics of each wavelength band. Using our developed monitoring system, we observed that the near-infrared (NIR) variation was largest during the vegetative (V1-V3) stage, followed by a similar variation pattern in the order of red-edge and visible. In the reproductive stage (R1-R8), the effect of the shape and color of the soybean leaf was reflected, and the pattern is different from that in the vegetative (V) stage. At the R1 to R6 stages, the variation in NIR was the largest, and red-edge and green showed similar variation patterns, but red showed little change. In particular, the reflectance characteristics of the R1 stage provides information that could help us distinguish between the three varieties of soybean that were studied. In the R7-R8 stage, close to the harvest period, the red-edge and NIR variation patterns and the visible variation patterns changed. These results are interpreted as a result of the large effects of pigments such as chlorophyll for each of the three soybean varieties, as well as from the formation and color of the leaf and stem. The results obtained in this study provide useful information that helps us to determine the wavelength width and range of the optimal band for monitoring and acquiring vegetation information on crops using satellites and unmanned aerial vehicles (UAVs)
In this study, a method for an integrated flood risk mapping was proposed that simultaneously considers the flood inundation map indicating the degree of risk and the disaster vulnerability index. This method creates a new disaster map that can be used in actual situations by providing various and specific information on a single map. In order to consider the human, social and economic factors in the disaster map, the study area was divided into exposure, vulnerability, responsiveness, and recovery factors. Then, 7 indicators for each factor were extracted using the GIS tool. The data extracted by each indicator was classified into grades 1 to 5, and the data was selected as a disaster vulnerability index and used for integrated risk mapping by factor. The risk map for each factor, which overlaps the flood inundatoin map and the disaster vulnerability index factor, was used to establish an evacuation plan by considering regional conditions including population, assets, and buildings. In addition, an integrated risk analysis method that considers risks while converting to a single vulnerability through standardization of the disaster vulnerability index was proposed. This is expected to contribute to the establishment of preparedness, response and recovery plans for providing detailed and diverse information that simultaneously considers the flood risk including social, humanistic, and economic factors.
Journal of the Korea Society of Computer and Information
/
v.27
no.3
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pp.53-61
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2022
Recent years have drawn a great attention to generation MZ and Metaverse, due to 4th industrial revolution and the development of digital environment that blurs the boundary between reality and virtual reality. Generation MZ approaches the information very differently from the existing generations and uses distinguished communication methods. In terms of learning, they have different motivations, types, skills and build relationships differently. Meanwhile, Metaverse is drawing a great attention as a teaching method that fits traits of gen MZ. Thus, the current research aimed to investigate how to increase the use of Metaverse in Educational Technology. Specifically, this research examined the antecedents of popularity of Gather Town, a platform of Metaverse. Big data of news articles have been collected and analyzed using the Bigkinds system provided by Korea Press Foundation. The analysis revealed, first, a rapid increasing trend of media exposure of Gather Town since July 2021. This suggests a greater utilization of Gather Town in the field of education after the COVID-19 pandemic. Second, Word Association Analysis and Word Cloud Analysis showed high weights on education related words such as 'remote', 'university', and 'freshman', while words like 'Metaverse', 'Metaverse platform', 'Covid19', and 'Avatar' were also emphasized. Third, Network Analysis extracted 'COVID19', 'Avatar', 'University student', 'career', 'YouTube' as keywords. The findings also suggest potential value of Gather Town as an educational tool under COVID19 pandemic. Therefore, this research will contribute to the application and utilization of Gather Town in the field of education.
Journal of the Korean Society of Marine Environment & Safety
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v.28
no.4
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pp.542-548
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2022
In order to reduce marine accidents, each contracting Government needs to implement the instruments enacted and amended by the International Maritime Organization (IMO). The III Code requires each administration of the government to have a system for improvement through periodic review and evaluation and to include performance indicators in its evaluation methods. Thus, each IMO Member State needs to develop its own performance indicators. The purpose of this paper is to develop and present an evaluation model using the Balanced Scorecard (BSC) and Key Performance Indicators (KPI) in order to quantify and evaluate the level of implementation of the instruments by the administrations. From the perspective of 'III-BSC', which applies the BSC concept to the III code requirements, the Critical Success Factors (CSF) that must be secured to achieve the established vision were drawn up, and candidate KPIs for each evaluation area were developed to measure the derived key success factors and an initial study model was designed composed of four levels. The validity of the KPIs was verified and the study model was finalized using the survey design using the SMART technique. Furthermore, based on the developed study model, an evaluation model for the implementation of the BSC-based IMO instruments was developed by deriving the weights of elements for each level through AHP analysis. The developed evaluation model is expected to contribute toward improving the administrations' level of implementation of the IMO instruments as a tool for quantitatively grasping the level of performance of the implementation.
Korean Journal of Construction Engineering and Management
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v.23
no.4
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pp.15-25
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2022
As the incidence and mortality of serious disasters in the construction industry are the highest, various efforts are being made in Korea to reduce them. Among them, risk assessment is used as data for disaster reduction measures and evaluation of risk factors at the construction stage. However, the existing risk assessment involves the subjectivity of the performer and is vulnerable to the domestic construction site. This study established a DB classification system for risk assessment with the aim of early identification and pre-removal of risks by quantitatively deriving risk factors using BIM in the risk assessment field and presents a methodology for risk assessment using BIM. Through this, prior removal of risks increases the safety of construction workers and reduces additional costs in the field of safety management. In addition, since it can be applied to new construction methods, it improves the understanding of project participants and becomes a tool for communication. This study proposes a framework for deriving quantitative risks based on BIM, and will be used as a base technology in the field of risk assessment using BIM in the future.
This study was attempted to suggest a direction for future research on good death by analyzing and synthesizing research trends on good death. For this purpose, 66 articles related to good death published in academic journals in Korea from 2011 to 2021 were analyzed based on the analysis frame of references. As a result, the year with the most good death studies was 2019 (18.2%). In the analysis by research design, 52 articles (78.8%) were the most quantitative studies, and 36 studies (54.5%) were survey studies. In the field of research, nursing studies were the most researched with 47 articles (71.2%), but multidisciplinary studies were three articles (4.5%). The subjects of the good death study were mainly the aged in the community and nursing students, each of which was 13 (19.7%), but the studies for patients were published only four articles (6.1%). The most used tool was the perception of a good death and conducted in in 38 articles (73.1%). The main research variables were the the perception of good death and hospice palliative and end-of-life care, and family support was used as mediating variables. Therefore, not only multidisciplinary research but also development research for vaious good death instruments may be suggested to comprehensively understand good death.
Drone and sensor technologies are enabling digitalization of agricultural crop's growth information and accelerating the development of the precision agriculture. These technologies could be able to assess damage of crops when natural disaster occurs, and contribute to the scientification of the crop insurance assessment method, which is being conducted through field survey. This study was aimed to calculate lodged damage rate from the vegetation indices extracted by drone based RGB images for soybean. Support Vector Classifier (SVC) models were considered by adding vegetation indices to the Crop Surface Model (CSM) based lodged damage rate. Visible Atmospherically Resistant Index (VARI) and Green Red Vegetation Index (GRVI) based lodged damage rate classification were shown the highest accuracy score as 0.709 and 0.705 each. As a result of this study, it was confirmed that drone based RGB images can be used as a useful tool for estimating the rate of lodged damage. The result acquired from this study can be used to the satellite imagery like Sentinel-2 and RapidEye when the damages from the natural disasters occurred.
In modern society, human and social damages caused by natural disasters and frequent disaster accidents have been increased year by year. Prompt access to dangerous disaster sites that are inaccessible or inaccessible using state-of-the-art Earth observation equipment such as satellites, drones, and survey robots, and timely collection and analysis of meaningful disaster information. It can play an important role in protecting people's property and life throughout the entire disaster management cycle, such as responding to disaster sites and establishing mid-to long-term recovery plans. This special issue introduces the National Disaster Management Research Institute (NDMI)'s disaster management technology that utilizes various Earth observation platforms, such as mobile survey vehicles equipped with close-range disaster site survey sensors, drones, and survey robots, as well as satellite technology, which is a tool of remote earth observation. Major research achievements include detection of damage from water disasters using Google Earth Engine, mid- and long-term time series observation, detection of reservoir water bodies using Sentinel-1 Synthetic Aperture Radar (SAR) images and artificial intelligence, analysis of resident movement patterns in case of forest fire disasters, and data analysis of disaster safety research. Efficient integrated management and utilization plan research results are summarized. In addition, research results on scientific investigation activities on the causes of disasters using drones and survey robots during the investigation of inaccessible and dangerous disaster sites were described.
The Japanese eel Anguilla japonica is a highly valued research object that is important for aquaculture in Asia, including the Republic of Korea. However, few studies have been conducted analyzing parentage using microsatellite markers derived from the Japanese eel. We acquired Japanese eel genome data using next generation sequencing technology, and constructed a draft genome comprising 1,087 Mbp. Using the Simple Sequence Repeat Identification Tool program, 444,724 microsatellites were identified. Of these, 1,842 microsatellites located in the 3' untranslated region, which are stably inherited, were finally selected. Ninety-six primers were selected to validate polymorphism at these microsatellites, and 9 primers were finally identified for multiplex analysis. Using multiplex polymerase chain reaction with three different fluorescence chemistries, we performed parentage analysis of an artificial Japanese eel population. CERVUS software was used to calculate the logarithm of the odds (LOD) scores and the confidence of the parentage assignments. The results presented here show that 83 out of 85 paternity cases were assigned at 95% confidence to a candidate father and mother with LOD scores ranging from 4.79 to 28.2. This study provided a microsatellite marker-based assay for parentage analysis of Japanese eels, which will be useful for selective breeding and genetic diversity studies.
In this study, we tried to present a method for calculating the amount of regression using a watershed modeling method that can simulate the hydrological mechanism of water balance analysis and agricultural water based on watershed unit. Using the soil water assessment tool (SWAT), a watershed water balance analysis was conducted considering the simulation of paddy fields for the Manbongcheon Standard Basin (97.34 km2), which is a representative agricultural area of the Yeongsan river basin. Before evaluating return flow, the SWAT was calibrated and validated using the daily streamflow observation data at Naju streamflow gauge station (NJ). The coefficient of determination (R2), Nash-Sutcliffe Efficiency (NSE), Root-Mean-Square Error (RMSE) of NJ were 0.73, 0.70, 0.64 mm/day. Based on the calibration results for three years (2015-2017), the quick return flow and the return rate compared to the water supply amount for the irrigation period (April 1 to September 30) were calculated, and the average return flow rate was 53.4%. The proposed method of this study may be used as foundation data to optimal agricultural water supply plan for rational watershed management.
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