Miguel Enrico L. Robles;Franz Kevin F. Geronimo;Chiny C. Vispo;Haque Md Tashdedul;Minsu Jeon;Lee-Hyung Kim
Journal of Wetlands Research
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v.25
no.4
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pp.353-365
/
2023
The effects of climate change on green infrastructure and environmental media remain uncertain and context-specific despite numerous climate projections globally. In this study, the extreme weather conditions in seven major cities in South Korea were characterized through statistical analysis of 20-year daily meteorological data extracted fro m the Korea Meteorological Administration (KMA). Additionally, the impacts of extreme weather on Nature-based Solutions (NbS) were determined through a comprehensive review. The results of the statistical analysis and comprehensive review revealed the studied cities are potentially vulnerable to varying extreme weather conditions, depending on geographic location, surface imperviousness, and local weather patterns. Temperature extremes were seen as potential threats to the resilience of NbS in Seoul, as both the highest maximum and lowest minimum temperatures were observed in the mentioned city. Moreover, extreme values for precipitation and maximum wind speed were observed in cities from the southern part of South Korea, particularly Busan, Ulsan, and Jeju. It was also found that extremely low temperatures induce the most impact on the resilience of NbS and environmental media. Extremely cold conditions were identified to reduce the pollutant removal efficiency of biochar, sand, gravel, and woodchip, as well as the nutrient uptake capabilities of constructed wetlands (CWs). In response to the negative impacts of extreme weather on the effectiveness of NbS, several adaptation strategies, such as the addition of shading and insulation systems, were also identified in this study. The results of this study are seen as beneficial to improving the resilience of NbS in South Korea and other locations with similar climate characteristics.
Journal of the Korean Society of Earth Science Education
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v.16
no.3
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pp.340-350
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2023
This study analyzed the difficulty level of class on the seasonal change unit for 84 students at a university of education. The conclusions of this study are as follows. First, if we first present the four topics that make up the seasonal changes in elementary science, the subjects that have the greatest difficulty in teaching for prospective elementary school teachers are 'Why do seasonal changes occur?' (Teaching difficulty level 4.05), 'The sun changes depending on the season' What is the difference between the southern altitude and the length of day and night?' (difficulty level of class, 3.12), 'What is the relationship between the altitude of the sun, length of shadow, and temperature during the day?' (difficulty level of class, 2.85), 'How does the temperature change depending on the season?' (class difficulty level 2.80). As a result, in the elementary science season change unit, the class on the four topics 'Why do seasons change?', which is classified as a class topic that requires the concept of spatial perception, showed a higher level of class difficulty than other units. Second, in the seasonal change unit, various factors of class difficulty appeared depending on the class topic. When pre-service elementary school teachers look at the factors that make class difficult when teaching a lesson on seasonal changes in order of frequency, 42 (50%) said 'Experimental instruction for comparing the altitude of solar masculine according to the tilt of the axis of rotation', followed by 'Solar masculine'. 38 people (45%) answered 'Difficulty in explaining mid-high altitude and the length of day and night', 27 people (32%) answered 'Difficulty in explaining the concept of mid-high altitude', and 24 people (32%) answered 'Difficulty in explaining seasonal changes in the sun's position.' 29%), 20 people (24%) said 'Explain the reasonable reason why the height of the light should be adjusted when measuring the solar altitude', and 16 people (19%) said 'It is difficult to explain the reason for the discrepancy between the solar altitude and the maximum temperature'. ), 'difficulties in measuring sand (ground) temperature' were mentioned by 12 people (14%). Third, when analyzing the factors of class difficulty, there were more curriculum factors than teacher factors. In this context, the exploratory activities on 'Why do seasonal changes occur?', the fourth topic of the seasonal change unit in which elementary school pre-service teachers showed the greatest difficulty in teaching, need improvement in terms of the curriculum.
Minju Kim;Jeong U Park;Juhyeon Park;Jisoo Park;Chang-Uk Hyun
Korean Journal of Remote Sensing
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v.39
no.5_1
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pp.481-493
/
2023
In high-density urban areas, the urban heat island effect increases urban temperatures, leading to negative impacts such as worsened air pollution, increased cooling energy consumption, and increased greenhouse gas emissions. In urban environments where it is difficult to secure additional green spaces, rooftop greening is an efficient greenhouse gas reduction strategy. In this study, we not only analyzed the current status of the urban heat island effect but also utilized high-resolution satellite data and spatial information to estimate the available rooftop greening area within the study area. We evaluated the mitigation effect of the urban heat island phenomenon and carbon sequestration capacity through temperature predictions resulting from rooftop greening. To achieve this, we utilized WorldView-2 satellite data to classify land cover in the urban heat island areas of Busan city. We developed a prediction model for temperature changes before and after rooftop greening using machine learning techniques. To assess the degree of urban heat island mitigation due to changes in rooftop greening areas, we constructed a temperature change prediction model with temperature as the dependent variable using the random forest technique. In this process, we built a multiple regression model to derive high-resolution land surface temperatures for training data using Google Earth Engine, combining Landsat-8 and Sentinel-2 satellite data. Additionally, we evaluated carbon sequestration based on rooftop greening areas using a carbon absorption capacity per plant. The results of this study suggest that the developed satellite-based urban heat island assessment and temperature change prediction technology using Random Forest models can be applied to urban heat island-vulnerable areas with potential for expansion.
Han-bit Lee;Ju-Eun Kim;Moon-Seon Kim;Dong-Su Kim;Seung-Hwan Min;Tae-Ho Kim
Korean Journal of Remote Sensing
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v.39
no.6_2
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pp.1615-1633
/
2023
Sargassum horneri is one of the floating algae in the sea, which breeds in large quantities in the Yellow Sea and East China Sea and then flows into the coast of Republic of Korea, causing various problems such as destroying the environment and damaging fish farms. In order to effectively prevent damage and preserve the coastal environment, the development of Sargassum horneri detection algorithms using satellite-based remote sensing technology has been actively developed. However, incorrect detection information causes an increase in the moving distance of ships collecting Sargassum horneri and confusion in the response of related local governments or institutions,so it is very important to minimize false detections when producing Sargassum horneri spatial information. This study applied technology to automatically remove false detection results using the GOCI-II-based Sargassum horneri detection algorithm of the National Ocean Satellite Center (NOSC) of the Korea Hydrographic and Oceanography Agency (KHOA). Based on the results of analyzing the causes of major false detection results, it includes a process of removing linear and sporadic false detections and green algae that occurs in large quantities along the coast of China in spring and summer by considering them as false detections. The technology to automatically remove false detection was applied to the dates when Sargassum horneri occurred from February 24 to June 25, 2022. Visual assessment results were generated using mid-resolution satellite images, qualitative and quantitative evaluations were performed. Linear false detection results were completely removed, and most of the sporadic and green algae false detection results that affected the distribution were removed. Even after the automatic false detection removal process, it was possible to confirm the distribution area of Sargassum horneri compared to the visual assessment results, and the accuracy and precision calculated using the binary classification model averaged 97.73% and 95.4%, respectively. Recall value was very low at 29.03%, which is presumed to be due to the effect of Sargassum horneri movement due to the observation time discrepancy between GOCI-II and mid-resolution satellite images, differences in spatial resolution, location deviation by orthocorrection, and cloud masking. The results of this study's removal of false detections of Sargassum horneri can determine the spatial distribution status in near real-time, but there are limitations in accurately estimating biomass. Therefore, continuous research on upgrading the Sargassum horneri monitoring system must be conducted to use it as data for establishing future Sargassum horneri response plans.
This study examines the customer value factors affecting the intention to continue using the mobile app of department stores, which are traditional offline retailers, in the retail industry that is rapidly digitalizing and becoming mobile. This study clarifies multidimensional customer value in three dimensions; functional, convenience, and social. Functional value refers to the integrated channel, and consistent customer experience provided between channels in the omnichannel retail environment, while convenience value is the convenience of saving time and effort save while customers use a mobile app. Social value refers to the improvement of social approval or social self-concept occurring due to the use of products or services related to green marketing within the mobile app of the department store. The influence of each on the dependent variable, the mobile app's continuous use intention, was analyzed by using the three dimensions of customer value as independent variables. Data was collected from customers who have a history of using the mobile app of Shinsegae Department Store in Korea, and a confirmatory analysis was conducted using Smart PLS 4.0. The analysis results showed that all three dimensions of customer value; functional value, convenience value, and social value, had a positive (+) influence on customers' intention to continue using the mobile app, and the influence of functional value had the greatest impact. As functional value appears to be the most important influencing factor due to the omnichannel retail trend by advancement of technology, it suggests that it is important for department stores, and offline retailers, to provide integrated channels. This provides insights into the direction of customer-centered strategy formulation for activating department store mobile apps and suggests basic analytical data for customized services and marketing activities that department stores can effectively meet the changing expectations and demands of customers through new mobile channels rather than existing offline channels.
Urban is an area where small-scale changes to individual buildings occur frequently. An existing urban building database requires periodic updating to increase its usability. However, there are limitations in data collection for building changes over a wide urban. In this study, we check the possibility of detecting building changes and updating a building database by using satellite images that can capture a wide urban region by a single image. For this purpose, building areas in a satellite image are first extracted by projecting 3D coordinates of building corners available in a building database onto the image. Building areas are then divided into roof and facade areas. By comparing textures of the roof areas projected, building changes such as height change or building removal can be detected. New height values are estimated by adjusting building heights until projected roofs align to actual roofs observed in the image. If the projected image appeared in the image while no building is observed, it corresponds to a demolished building. By checking buildings in the original image whose roofs and facades areas are not projected, new buildings are identified. Based on these results, the building database is updated by the three categories of height update, building deletion, or new building creation. This method was tested with a KOMPSAT-3A image over Incheon Metropolitan City and Incheon building database available in public. Building change detection and building database update was carried out. Updated building corners were then projected to another KOMPSAT-3 image. It was confirmed that building areas projected by updated building information agreed with actual buildings in the image very well. Through this study, the possibility of semi-automatic building change detection and building database update based on single satellite image was confirmed. In the future, follow-up research is needed on technology to enhance computational automation of the proposed method.
Infectious bursal disease (IBD) is an acute, highly contagious, and immunosuppressive disease in young chickens, and causes considerable economic losses to the poultry industry. More than 30 years ago, an antigenic variant IBDV (avIBDV) was reported in chicken farms in the United States. Recently, a novel avIBDV exhibited clear differences in molecular characteristics compared with previous variant strains. This study investigated the molecular characteristics of recently isolated avIBDV strains in Korea. Strains of avIBDV were confirmed by reverse transcription PCR (RT-PCR) and were propagated in 10-day-old specific-pathogen-free (SPF) embryonated chicken eggs through chorioallantoic membrane (CAM) inoculation. Multiple sequence alignment and phylogenetic analyses of hypervariable regions VP2 gene revealed that the strains originated from two different avIBDV lineages (G2a and G2d). In our results, we confirmed the co-existence and prevalence of avIBDV genogroup G2a and G2d in chicken farms. It is necessary to study the protective efficacy of current vaccines against avIBDVs.
Korean Journal of Construction Engineering and Management
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v.25
no.2
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pp.23-35
/
2024
This study analyzed the correlation between each of the 12 influencing factors in FAR 16.04 and the decision-making process for construction contract types, using data from a total of 2,406 DoD Construction Acquisitions spanning from 2008 to 2022. The study considered 12 independent variables, grouped into 4 Characteristics with 3 factors each. Meanwhile, all other contract types were categorized into two types: Firm-Fixed-Price (FFP) and Cost-Reimbursement Contract (CRC), which served as the dependent variables. The findings revealed that FFP contracts significantly dominated in terms of acquisition volume. In line with prevailing beliefs, logistic data analysis and Analytical Hierarchy Process (AHP) analysis of Relative Weights from Experts' Survey demonstrated that independent variables like Uncertainty of the Scope of Work and Complexity found out to be increasing the likelihood of selecting CRC. The number of contractors in the market does indeed influence the possibilities of contract decision-making between CRC and FFP. Meanwhile, the p-values of the top 3 influencing factors on CRC from the AHP analysis-namely, Appropriateness of CAS, Project Urgency, and Cost Analysis-exceeded 0.05 in the binominal regression results, rendering it inconclusive whether they significantly influenced the construction contract type decision, particularly with respect to payment methods. This outcome partly results from the fact that a majority of respondents possessed specific experiences related to the USFK relocation project. Furthermore, influencing factors in construction projects behave differently than common beliefs suggest. As a result, it is imperative to consider the 12 influencing factors categorized into 4 Characteristics areas before establishing acquisition strategies for targeted construction projects.
Types of innovation can be categorized into simplification, information, automation, and intelligence. Intelligence is the highest level of innovation, and RPA can be seen as one of intelligence. Robotic Process Automation(RPA), a software robot with artificial intelligence, is an example of intelligence that is suited for simple, repetitive, large-scale transaction processing tasks. The RPA, which is already in operation in many companies in Korea, shows what needs to be done to naturally focus on the core tasks in a situation where the need for a strong organizational culture is increasing and the emphasis is on voluntary leadership, strong teamwork and execution, and a professional working culture. The introduction was considered naturally according to the need to find. Robotic Process Automation, or RPA, is a technology that replaces human tasks with the goal of quickly and efficiently handling structural tasks. RPA is implemented through software robots that mimic humans using software such as ERP systems or productivity tools. RPA robots are software installed on a computer and are called robots by the principle of operation. RPA is integrated throughout the IT system through the front end, unlike traditional software that communicates with other IT systems through the back end. In practice, this means that software robots use IT systems in the same way as humans, repeat the correct steps, and respond to events on the computer screen instead of communicating with the system's application programming interface(API). Designing software that mimics humans to communicate with other software can be less intuitive, but there are many advantages to this approach. First, you can integrate RPA with virtually any software you use, regardless of your openness to third-party applications. Many enterprise IT systems are proprietary because they do not have many common APIs, and their ability to communicate with other systems is severely limited, but RPA solves this problem. Second, RPA can be implemented in a very short time. Traditional software development methods, such as enterprise software integration, are relatively time consuming, but RPAs can be implemented in a relatively short period of two to four weeks. Third, automated processes through software robots can be easily modified by system users. While traditional approaches require advanced coding techniques to drastically modify how they work, RPA can be instructed by modifying relatively simple logical statements, or by modifying screen captures or graphical process charts of human-run processes. This makes RPA very versatile and flexible. This RPA is a good example of the application of digital to intelligence(D2I).
This study was carried out to examine agronomic characteristics and seed qualities of 827 Korean soybean landraces according to the collecting areas. Agronomic characteristics and seed qualities was examined according to the localities by weather characteristics. Days to flowering was the longest (mean 70.9 days) in the northwest seashore, and the most short in the south inland (mean 63.8 days). Growth days was the longest in the Gyeongbuk inland (mean 136.0 days), and the most short in the mountain-high (mean 132.8 days). The stem height was the most short in the north-west seashore (mean 81.3 cm), and in the south seashore (mean 58.8 cm). The seed weight of 100 seeds was the lightest in the north-west seashore (mean 17.1 g), and the heaviest in the south-west seashore (mean 21.5 g). The crude protein contents was the lowest in the north-west seashore (mean 40.1%), the highest in the south seashore (mean 42.8%), and vice versa in the crude oil. The contents of sucrose and oligo-saccharide was the highest 5.8% and 8.6%, respectively, in the mountain-high, and the lowest 4.8% and 7.6% in the Gyeongbuk inland and south seashore, respectively. Among the iso-flavone contests, the contents of genistein and total was the highest, $635.6\;{\mu}g/g$ and $1258.1\;{\mu}g/g$, respectively, in the mountain inland, and the lowest $319.2\;{\mu}g/g$ and $835.3\;{\mu}g/g$ in the south-west seashore. The contents of glycitein was the highest $124.3\;{\mu}g/g$ in the south seashore.
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