• Korea Trade Review
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• v.48 no.1
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• pp.243-261
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• 2023

This study was conducted with the goal of analyzing the needs of Truckers, who are the main users of the cargo transportation platform, to find a development direction for the improvement and activation of the cargo transportation platform service. For this purpose, this study conducted an empirical analysis through IPA analysis targeting Truckers using domestic cargo transportation platforms. As a result of the IPA analysis, in the case of importance, fair fare presentation, unfair trade prevention measures, transportation payment deadline accuracy, transportation section information provision accuracy, quick interaction, application system quality, ease of use, user-customized service, settlement service support function, Variety of transportation sections, brand image, and additional services were shown in order. In the case of satisfaction, ease of use, settlement service support function, transport section information provision accuracy, application system quality, brand image, additional services, user-customized service, transport section diversity, quick interaction, transport payment deadline accuracy, unfair transaction prevention Measures and fair fares were presented in that order. The analysis results show high satisfaction with the ease of use related to the platform quality and the function to support the settlement work. These results can be seen as the result of a significant investment in system quality improvement for the convenience of users by suppliers in the domestic cargo transportation platform industry, where competition has become fierce. As the factors most urgently needed for improvement, 'observance of payment deadlines', 'prevention of unfair trade', and 'provision of fair fares' were selected, and these are related to chronic problems in the domestic freight transportation industry.

• Journal of the Korea institute for structural maintenance and inspection
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• v.27 no.6
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• pp.120-129
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• 2023

To evaluate the vertical loads on railway bridges, conventional load tests are typically conducted. However, these tests often entail significant costs and procedural challenges. Railway conditions involve nearly identical load profiles due to standardized rail systems, which may appear straightforward in terms of load conditions. Nevertheless, this study aims to validate load tests conducted under operational train conditions by comparing the results with those obtained from conventional load tests. Additionally, static and dynamic structural behaviors are extracted from the measurement data for evaluation. To ensure the reliability of load testing, this research demonstrates feasibility through comparisons of existing measurement data with sensor attachment locations, train speeds, responses between different rail lines, tendency analysis, selection of impact coefficients, and analysis of natural frequencies. This study applies to the Dongho Railway Bridge and verifies the applicability of the proposed method. Ten operational trains and 44 sensors were deployed on the bridge to measure deformations and deflections during load test intervals, which were then compared with theoretical values. The analysis results indicate good symmetry and overlap of loads, as well as a favorable comparison between static and dynamic load test results. The maximum measured impact coefficient (0.092) was found to be lower than the theoretical impact coefficient (0.327), and the impact influence from live loads was deemed acceptable. The measured natural frequencies approximated the theoretical values, with an average of 2.393Hz compared to the calculated value of 2.415Hz. Based on these results, this paper demonstrates that for evaluating vertical loads, it is possible to measure deformations and deflections of truss railway bridges through load tests under operational train conditions without traffic control, enabling the calculation of response factors for stress adjustments.

• Journal of Korean Society of Forest Science
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• v.112 no.4
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• pp.426-441
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• 2023

This study investigated the predictive accuracy of a model of landslide displacement in Jecheon-si, where a great number of landslides were triggered by heavy rain on both natural (non-clear-cut) and clear-cut slopes during August 2020. This was accomplished by applying three flow direction methods (single flow direction, SFD; multiple flow direction, MFD; infinite flow direction, IFD) and the degree of root cohesion to an infinite slope stability equation. The application assumed that the soil saturation and any changes in root cohesion occurred following the timber harvest (clear-cutting). In the study area, 830 landslide locations were identified via landslide inventory mapping from satellite images and 25 cm resolution aerial photographs. The results of the landslide modeling comparison showed the accuracy of the models that considered changes in the root cohesion following clear-cutting to be improved by 1.3% to 2.6% when compared with those not considered in the area under the receiver operating characteristics (AUROC) analysis. Furthermore, the accuracy of the models that used the MFD algorithm improved by up to 1.3% when compared with the models that used the other algorithms in the AUROC analysis. These results suggest that the discriminatory application of the root cohesion, which considers changes in the vegetation condition, and the selection of the flow direction method may influence the accuracy of landslide predictive modeling. In the future, the results of this study should be verified by examining the root cohesion and its dynamic changes according to the tree species using the field hydrological monitoring technique.

• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1321-1330
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• 2023

Normalized Difference Vegetation Index (NDVI) is the most widely used remote sensing data in the agricultural field and is currently provided by most optical satellites. In particular, as high-resolution optical satellite images become available, the selection of optimal optical satellite images according to agricultural applications has become a very important issue. In this study, we aim to define the most optimal optical satellite image when monitoring NDVI in rice fields in Korea and derive the resolution-related requirements necessary for this. For this purpose, we compared and analyzed the spatial distribution and time series patterns of the Dangjin rice paddy in Korea from 2019 to 2022 using NDVI images from MOD13, Landsat-8, Sentinel-2A/B, and PlanetScope satellites, which are widely used around the world. Each data is provided with a spatial resolution of 3 m to 250 m and various periods, and the area of the spectral band used to calculate NDVI also has slight differences. As a result of the analysis, Landsat-8 showed the lowest NDVI value and had very low spatial variation. In comparison, the MOD13 NDVI image showed similar spatial distribution and time series patterns as the PlanetScope data but was affected by the area surrounding the rice field due to low spatial resolution. Sentinel-2A/B showed relatively low NDVI values due to the wide near-infrared band area, and this feature was especially noticeable in the early stages of growth. PlanetScope's NDVI provides detailed spatial variation and stable time series patterns, but considering its high purchase price, it is considered to be more useful in small field areas than in spatially uniform rice paddy. Accordingly, for rice field areas, 250 m MOD13 NDVI or 10 m Sentinel-2A/B are considered to be the most efficient, but high-resolution satellite images can be used to estimate detailed physical quantities of individual crops.

• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1413-1425
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• 2023

The increasing frequency of wildfires due to climate change is causing extreme loss of life and property. They cause loss of vegetation and affect ecosystem changes depending on their intensity and occurrence. Ecosystem changes, in turn, affect wildfire occurrence, causing secondary damage. Thus, accurate estimation of the areas affected by wildfires is fundamental. Satellite remote sensing is used for forest fire detection because it can rapidly acquire topographic and meteorological information about the affected area after forest fires. In addition, deep learning algorithms such as convolutional neural networks (CNN) and transformer models show high performance for more accurate monitoring of fire-burnt regions. To date, the application of deep learning models has been limited, and there is a scarcity of reports providing quantitative performance evaluations for practical field utilization. Hence, this study emphasizes a comparative analysis, exploring performance enhancements achieved through both model selection and data design. This study examined deep learning models for detecting wildfire-damaged areas using Landsat 8 satellite images in California. Also, we conducted a comprehensive comparison and analysis of the detection performance of multiple models, such as U-Net and High-Resolution Network-Object Contextual Representation (HRNet-OCR). Wildfire-related spectral indices such as normalized difference vegetation index (NDVI) and normalized burn ratio (NBR) were used as input channels for the deep learning models to reflect the degree of vegetation cover and surface moisture content. As a result, the mean intersection over union (mIoU) was 0.831 for U-Net and 0.848 for HRNet-OCR, showing high segmentation performance. The inclusion of spectral indices alongside the base wavelength bands resulted in increased metric values for all combinations, affirming that the augmentation of input data with spectral indices contributes to the refinement of pixels. This study can be applied to other satellite images to build a recovery strategy for fire-burnt areas.

• Land and Housing Review
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• v.14 no.4
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• pp.77-93
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• 2023

The COVID-19 pandemic has brought about significant social changes through government prevention and control measures, changes in people's risk perceptions, and lifestyle changes. In response, urban inhabitants changed their behaviors significantly, including their preferences for transportation modes and urban spaces in response to government quarantine policies and concerns over the potential risk of infection in urban spaces. These changes may have long-lasting effects on urban spaces beyond the COVID-19 pandemic or they may evolve and develop new forms. Therefore, this study aims to explore the potential for urban spaces to adapt to the present and future pandemics by examining changes in urban residents' preferences in travel modes and urban space use due to the COVID-19 pandemic. This study found that overall preferences for travel modes and urban spaces significantly differ between the pre-pandemic, pandemic, and post-pandemic periods. During the pandemic, preferences for travel modes and urban spaces has decreased, except for privately owned vehicles and green spaces, which are perceived to be safe from transmission, show more favorable than others. Post-pandemic preferences for travel modes and urban spaces are less favorable than pre-pandemic with urban spaces being five times less favorable than transportation. Although green spaces and medical facilities that were positively perceived during the pandemic are expected to return to the pre-pandemic preference level, other factors of urban spaces are facing a new-normal. The findings suggest that the COVID-19 pandemic has had a significant impact on urban residents' preferences for travel modes and urban space use. Understanding these changes is crucial for developing strategies to adapt to present and future pandemics and improve urban resilience.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.68 no.3
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• pp.114-120
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• 2023

Soybean is the one of the most important crops for providing quality vegetable protein to umans and livestock. Soybean cultivars with a brown seed coat have a wide range of antioxidant benefits because of the flavonoid components. However, they also contain lectin, 7S α′ subunit, lipoxygenase, and Kunitz trypsin inhibitor (KTI) proteins that can be allergenic and digestive inhibitors and reduce processing aptitude. Genetic removal of these four proteins is necessary in soybean breeding. Therefore, this study was conducted to select a new line with brown seed coat, green cotyledon, and tetra-null genotype (lecgy1lox1lox2lox3ti) for lectin, 7S α′ subunit, lipoxygenase, and KTI proteins in the mature seed. Five germplasms were used to create breeding population. From a total of 58 F₂ plants, F₂ plants with lele genotype were selected using a DNA marker, and F₃ seeds with a brown seed coat, green cotyledon, and the absence of 7S α′ subunit protein were selected. Three lines (S1, S2, and S3) were developed. Genetic absence of lectin, 7S α′ subunit, lipoxygenase, and KTI proteins was confirmed in F₆ seeds of the three lines, which had a brown seed coat, green cotyledons, and a white hilum. The 100 seed weights of the three lines were 26.4-30.9 g, which were lower than 36 g of the check cultivar - 'Chungja#3'. The new S2 line with 30.9 g hundred seed weight can be used as a parent to improve colored soybean cultivars without antinutritional factors such as lectin, 7S α′ subunit, lipoxygenase, and KTI proteins.

• Korea Trade Review
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• v.48 no.4
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• pp.303-320
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• 2023

Recently, import and export companies have been using T/T remittance and Surrender B/L more frequently than L/C when selecting the process and method of trade payment settlement. The new trade and logistics environment is thriving in the era of the Fourth Industrial Revolution (4IR). Document-based trade transactions are undergoing a digitalization as bills of lading or smart contracts are being developed. The purpose of this study is to verify whether exporters choose export payment types based on negotiating factors. In addition, we would like to discuss the application of the characteristics of the new trade and logistics environment. Data for analysis was collected through surveys. The collection method consisted of direct visits to the company, e-mail, fax, and online surveys. The survey distribution period is from February 1, 2023, to April 30, 2023. The questionnaire was distributed in 2,000 copies, and 447 copies were collected. The final 336 copies were used for analysis, excluding 111 copies that were deemed inappropriate for the purpose of this study. The results of the study are shown below. First, among the negotiating factors, the product differentiation of exporters did not significantly affect the selection of export payment types. Second, among the negotiating factors, the greater the purchasing advantage recognized by exporters, the higher the possibility of using the post-transfer method. In addition to analyzing the results, this study suggests that exporters should consider adopting new payment methods, such as blockchain technology-based bills of lading and trade finance platforms, to adapt to the characteristics of the evolving trade and logistics environment. Therefore, exporters should continue to show interest in initiatives aimed at digitizing trade documents as a response to the challenges posed by bills of lading. In future studies, it is necessary to address the lack of social awareness in Korea by conducting advanced research abroad.

• The Journal of Korean Academy of Sensory Integration
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• v.21 no.2
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• pp.69-83
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• 2023

Objective : This study sought to systematically examine the intervention effect of social stories when applied in relation to children with sleep disorders. Methods : Studies available in the SCOPUS, ScienceDirect, PsycArticles, and PubMed databases that were published from 2001 to 2022 were searched. The keywords used for the search were as follows: ("social story" OR "social stories") AND ("sleep" OR "sleep disorders" OR "sleep wake disorder bedtimes" OR "sleep initiation and maintenance disorders" OR "sleep wake disorder" OR "sleep arousal disorders"). Based on the selection criteria, six experimental studies were selected and analyzed. Results : The selected studies were two randomized controlled trials, three individual trials, and one case study. The subjects were mostly children diagnosed with autism spectrum disorder who were school-aged or adolescent. The intervention types were often complex interventions, including social stories and other interventions, while the durations of the interventions varied from one day to more than 40 days. The interventions had a positive effect on the subjects' sleep quality, with night wakings, sleep onset delay, and sleep anxiety all being improved. As standardized assessment tools to evaluate the effectiveness of social stories, the Child Sleep Habits Questionnaire and the Child Behavior Checklist were used in two papers each, and were the most commonly used. As non-standardized assessment tools, each of the four papers used turbulence and sleep diaries as assessment tools. Conclusion : The effect of social story mediation can be divided into sleep quality and sleep-related behavior. In terms of sleep quality, studies showing improvements in night wakings, sleep onset delay, and sleep anxiety accounted for a large proportion of the sample. The detailed effect area of sleep quality showed a significant improvement after the interventions in most studies, and in all six studies analyzed in the present study, the continuation of the effect after the intervention was confirmed via follow-up tests. Thus, the findings of this study are expected to be helpful when applying social stories in children with sleep disorders in clinical practice due to presenting the intervention effects, outcome evaluation tools, and intervention periods in children with sleep disorders in prior investigations involving social stories.

• Journal of agricultural medicine and community health
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• v.48 no.4
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• pp.239-250
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• 2023

Objective: This study was a preliminary study for the prevention programs for farmers' occupational diseases. It selected the priorities recognized by farmers, such as occupational diseases, and also identifies the effectiveness and feasibility of prevention programs among diseases recognized by farmers. Therefore, we plan to use it as basis data for future farmer safety and health programs. Method: The subjects of the study were farmers living in the region, selected through a snowball recruitment method, and a total of 671 people were targeted. The priority selection method was the Basic Priority Rating System (BPRS) method, and among the occupational diseases, programs to prevent musculoskeletal diseases, cardiovascular and respiratory diseases, and pesticide poisoning were surveyed on the effectiveness and feasibility of farmers. Results: Among occupational diseases, the highest priority was musculo-skeletal disease, followed by respiratory disease and pesticide poisoning. Among the programs for musculoskeletal disease, 'use of agricultural work convenience equipment and auxiliary tools' had the highest perceived effectiveness and feasibility. Among the five programs for pesticide poisoning, 'equipment of protective equipment such as pesticide protective clothing/glove' had the highest effectiveness at 67.4%, and 'compliance with pesticide use instructions' had the highest level of feasibility at 64.3%. Among the four programs to prevent respiratory diseases, 'wearing a dust mask or gas mask' was the highest at 65.5% in terms of both effectiveness and feasibility. Conclusion: When carrying out safety and health programs for farmers, the priorities recognized by farmers should be taken into consideration, and the program contents should also be developed taking into account the size of effect and feasibility recognized by farmers.