• Journal of the Korean Society of Radiology
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• v.17 no.3
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• pp.315-325
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• 2023

The purpose of this study was to predict abdominal obesity with 3-Dimensional computed tomography (3D CT) measurements of kidneys by analyzing the correlation between kidney sizes and abdominal obesity level. The subjects were 178 healthy adults without underlying diseases who had a comprehensive health examination at the Health Medical Center of Jesus Hospital in Jeonju. Abdominal obesity was measured by CT cross-sectional image at the level of the umbilicus and divided into visceral fat area, subcutaneous fat area, visceral fat/total fat ratio. The average comparison of kidney sizes classified according to abdominal obesity were performed through one-way analysis of variance (ANOVA) and Scheffe test. Pearson correlation analysis was performed to correlate all measurement values. The results of kidney size ANOVA analysis according to abdominal obesity were as follows. The means of kidney measurements according to visceral fat classification were significantly different in all kidney measurements (p<0.05). And in case of subcutaneous fat classification, the means of kidney measurements by 3D CT of the severe obesity group were significantly different in the right kidney width (p<0.05). In case of visceral fat area/total fat area ratio, the means of kidney measurements by 3D CT of the severe obesity group were significantly different in both kidneys width (p<0.05). Pearson correlation between kidneys measurements and CT abdominal obesity showed that visceral fat area had the highest correlation with the left kidney width measured by 3D CT (r=0.467) and subcutaneous fat area had correlation with the right kidney width measured by 3D CT (r=0.249). The visceral fat area/total fat area ratio had correlation with the left kidney width measured by 3D CT (r=0.291).

• Journal of The Korean Association For Science Education
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• v.43 no.3
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• pp.253-263
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• 2023

This study explored the discrepancy between the text of a teacher's guide about straight and reflective light and the content knowledge of pre-service elementary teachers. A total of 455 questions and 543 answers generated by 279 pre-service elementary teachers after reading a 'Shadow and Mirror' unit in the teacher's guide were analyzed. The questions were classified according to the types of concepts and discrepancies, and the answers were analyzed for accuracy. The results of analyzing the concepts of questions revealed that the pre-service elementary teachers were most curious about the shadow in the straight concept, the mirror image in the reflection concept, and the light source in other concepts. The questions with a low correct answer rate due to incorrect- or non-answers, such as those concerning the superposition principle of light by reflection, the principle of experimental tools, and images by lenses, were only partially or not included in the teacher's guide. When the questions were classified according to the type of discrepancy, the frequency of questions due to knowledge deficit was higher than that due to knowledge clash. This demonstrates that the concepts that teachers need to know must be supplemented with the contents of the teacher's guide. Discrepancies due to knowledge clashes are often caused by conflicts between what is experienced in everyday life and what is presented in textbooks. Therefore, it is necessary to reduce the discrepancy between the texts of the teacher's guide and the knowledge of pre-service elementary teachers by including the differences between the actual context of everyday life and the context of the textbook in the teacher's guide.

• Korean Journal of Heritage: History & Science
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• v.56 no.1
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• pp.22-43
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• 2023

This paper deals with the stone standing Avalokitesvara statue in Jeonghyesa Temple that was created by Mangong in 1924. The stone standing Avalokitesvara statue of Jeonghyesa Temple is the earliest extant Buddha statue produced by Mangong, and symbolism was given to Jeonghyesa in the process of its reconstruction. So far, there has been no study that has approached ideas and beliefs through Buddhist studies led by Mangong and specific relics. In order to proceed with this study, Mangong's legal words and anecdotes and newspaper articles during the Japanese colonial era were used to trace the dynamics of Jeonghyesa and Sudeoksa during Mangong's reign, and to investigate the effects obtained from the creation of the large Bodhisattva statue and the meaning of its location. In addition, an interview was attempted with the descendants of master, who were in charge of the sculpture at the time, to confirm the exact construction period and the list of craftsmen. It is judged that the stone standing Bodhisattva statue of Gwanchoksa Temple has been influenced by the double covering and square crown seen in the standing stone statue of Avalokitesvara Bodhisattva of Jeonghyesa Temple, the large hands compared to the body, the proportion between the head and the body, and the sense of enormity felt in the body like a stone pillar. Therefore, we looked at how the standing stone Bodhisattva statue of Gwanchoksa Temple, which was produced in the early Goryeo Dynasty, could have influenced the creation of the Bodhisattva statue in the modern period. A multilateral analysis was attempted on how the image of the Gwanchoksa Bodhisattva statue, which was used as a symbol representing Chungcheongnam-do in the Chosun Exposition held in 1929 and the visit to Gwanchoksa Temple, which began with the laying of the railroad during the Japanese colonial period, was used from the viewpoint of the succession and transformation of the style. With this study as an opportunity, it is hoped that the understanding of the prehistoric Mangong representing the modern period and the horizon of Korean Buddhist sculpture research in the modern period will be broadened.

• Korean Journal of Remote Sensing
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• v.39 no.2
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• pp.193-205
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• 2023

A large amount of floating debris from land-based sources during heavy rainfall has negative social, economic, and environmental impacts, but there is a lack of monitoring systems for floating debris accumulation areas and amounts. With the recent development of artificial intelligence technology, there is a need to quickly and efficiently study large areas of water systems using drone imagery and deep learning-based object detection models. In this study, we acquired various images as well as drone images and trained with You Only Look Once (YOLO)v5s and the recently developed YOLO7 and YOLOv8s to compare the performance of each model to propose an efficient detection technique for land-based floating debris. The qualitative performance evaluation of each model showed that all three models are good at detecting floating debris under normal circumstances, but the YOLOv8s model missed or duplicated objects when the image was overexposed or the water surface was highly reflective of sunlight. The quantitative performance evaluation showed that YOLOv7 had the best performance with a mean Average Precision (intersection over union, IoU 0.5) of 0.940, which was better than YOLOv5s (0.922) and YOLOv8s (0.922). As a result of generating distortion in the color and high-frequency components to compare the performance of models according to data quality, the performance degradation of the YOLOv8s model was the most obvious, and the YOLOv7 model showed the lowest performance degradation. This study confirms that the YOLOv7 model is more robust than the YOLOv5s and YOLOv8s models in detecting land-based floating debris. The deep learning-based floating debris detection technique proposed in this study can identify the spatial distribution of floating debris by category, which can contribute to the planning of future cleanup work.

• Journal of the Korean Institute of Landscape Architecture
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• v.51 no.3
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• pp.83-94
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• 2023

This study analyzed the satisfaction of green infrastructure around 39 dams, including multi-purpose dams, water dams, and flood control reservoir dams, to induce space improvement in terms of sustainability, and the results of the study are as follows. First, the satisfaction level based on the Likert scale of 5 points for the currently created dam green infrastructure was 3.76, and there were differences depending on the respondents' gender, age, residence, number of dam visits, and the need to pursue sustainability, and it was analyzed to be statistically significant. In the case of gender, p<.05, age, residence, number of dam visits, and the need to pursue sustainability were found to be p<.01. Regression analysis was conducted to confirm the effect of these respondents' characteristics on satisfaction, and it was analyzed that only the number of dam visits and the need to pursue sustainability had a statistically significant effect, and other characteristic variables had no significant effect. Second, in terms of satisfaction with the conceptual image of public bridge, view place and play space, which are the main spaces of dam green infrastructure considering sustainability, view place was the highest at 4.43, the play space was 4.35 and public bridge was analyzed as 4.21. The t-test result for the satisfaction of each space was found to be p<.01, and the difference in values was analyzed to be significant. The difference from the current satisfaction with green infrastructure was also analyzed as p<.00, showing a statistically significant difference. Third, as a way to revitalize green infrastructure around the dam through the results of satisfaction analysis, it is necessary to identify needs for major visitors in their 40s and 50s and create a space considering them. It was proposed to derive facilities and programs that can be introduced to other regions through the analysis of green infrastructure status around dams in Chungbuk, Jeonju, and Ulsan, where there are relatively many dams. Furthermore, satisfaction analysis by space showed that green infrastructure around the dam could be activated in terms of sustainability when selecting packaging materials considering the structure and shape of the dam, arranging observation facilities considering lake prospects, and introducing amusement facilities using local environmental resources. This study differs from previous studies in that it presented space improvement measures in consideration of sustainability for green infrastructure around dams for non-urban areas, and space improvement can contribute to improving it connectivity in urban and non-urban areas, which can also contribute to improving the sustainability of green infrastructure in Korea.

• Journal of the Korea Knowledge Information Technology Society
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• v.13 no.1
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• pp.11-23
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• 2018

This paper empirically investigates the factors that influence the consumer choice of an app market based on the rational choice theory. The app market is the only channel where a consumer can buy smartphone apps, which give various functional convenience and are considered to be a major contributor to the proliferation of smartphones. Analyses of 281 questionnaires show that usability and structural guarantees as benefit factors significantly influence the app market choice. From the cost perspectives, both monetary and non-monetary conversion costs are found to significantly influence the app market choice. On the other hand, customer trust, information quality, and market image were found to have no significant effect on app market selection. In particular, Korean app market platform providers (KT, LG U +) seem to be superior in terms of structural guarantees, such as customer center operation and damage compensation regulations, compared to overseas app market platform operators (Google). However, in the case of the Google App Market, it is pre-installed on all Android phones, so it is not inconvenient to install additional apps to use other app market. This is disadvantageous to domestic app market platform operators, and it is necessary to establish a policy solution point. In terms of operator costs, both monetary and non-monetary conversion costs have a significant impact on app market choice. In particular, non-monetary conversion costs have a negative impact on Korean app market platform operators. It can be explained that the service expectation level of the domestic app market is low and it is recognized that the time cost factor such as membership is large for new users to use. It seems to be necessary to improve the domestic app market business. Meanwhile, extant research on smartphone apps focuses on the purchase of apps themselves, but not on the selection of the app market itself. In order to fill in this gap, this study focuses on the determinants of app market selection, including the characteristics of an app market and the switching costs.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.4
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• pp.387-397
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• 2023

Plant height is a growth parameter that provides visible insights into the plant's growth status and has a high correlation with yield, so it is widely used in crop breeding and cultivation research. Investigation of the growth characteristics of crops such as plant height has generally been conducted directly by humans using a ruler, but with the recent development of sensing and image analysis technology, research is being attempted to digitally convert growth measurement technology to efficiently investigate crop growth. In this study, the canopy height of rice grown at various nitrogen fertilization levels was measured using a laser scanner capable of precise measurement over a wide range, and a comparative analysis was performed with the actual plant height. As a result of comparing the point cloud data collected with a laser scanner and the actual plant height, it was confirmed that the estimated plant height measured based on the average height of the top 1% points showed the highest correlation with the actual plant height (R² = 0.93, RMSE = 2.73). Based on this, a linear regression equation was derived and used to convert the canopy height measured with a laser scanner to the actual plant height. The rice growth curve drawn by combining the actual and estimated plant height collected by various nitrogen fertilization conditions and growth period shows that the laser scanner-based canopy height measurement technology can be effectively utilized for assessing the plant height and growth of rice. In the future, 3D images derived from laser scanners are expected to be applicable to crop biomass estimation, plant shape analysis, etc., and can be used as a technology for digital conversion of conventional crop growth assessment methods.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.4
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• pp.258-266
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• 2023

This study analyzed methodologies for estimating carbon stocks of perennial woody crops and the research cases in overseas countries. As a result, we found that Australia, Bulgaria, Canada, and Japan are using the stock-difference method, while Austria, Denmark, and Germany are estimating the change in the carbon stock based on the gain-loss method. In some overseas countries, the researches were conducted on estimating the carbon stock change using image data as tier 3 phase beyond the research developing country-specific factors as tier 2 phase. In South Korea, convergence studies as the third stage were conducted in forestry field, but advanced research in the agricultural field is at the beginning stage. Based on these results, we suggest directions for the following four future researches: 1) securing national-specific factors related to emissions and removals in the agricultural field through the development of allometric equation and carbon conversion factors for perennial woody crops to improve the completeness of emission and removals statistics, 2) implementing policy studies on the cultivation area calculation refinement with fruit tree-biomass-based maturity, 3) developing a more advanced estimation technique for perennial woody crops in the agricultural sector using allometric equation and remote sensing techniques based on the agricultural and forestry satellite scheduled to be launched in 2025, and to establish a matrix and monitoring system for perennial woody crop cultivation areas in the agricultural sector, Lastly, 4) estimating soil carbon stocks change, which is currently estimated by treating all agricultural areas as one, by sub-land classification to implement a dynamic carbon cycle model. This study suggests a detailed guideline and advanced methods of carbon stock change calculation for perennial woody crops, which supports 2050 Carbon Neutral Strategy of Ministry of Agriculture, Food, and Rural Affairs and activate related research in agricultural sector.

• Korean Journal of Remote Sensing
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• v.39 no.5_1
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• pp.521-535
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• 2023

When converting rice fields into fields,sorghum (sorghum bicolor L. Moench) has excellent moisture resistance, enabling stable production along with soybeans. Therefore, it is a crop that is expected to improve the self-sufficiency rate of domestic food crops and solve the rice supply-demand imbalance problem. However, there is a lack of fundamental statistics,such as cultivation fields required for estimating yields, due to the traditional survey method, which takes a long time even with a large manpower. In this study, U-Net was applied to RGB images based on unmanned aerial vehicle to confirm the possibility of non-destructive segmentation of sorghum cultivation fields. RGB images were acquired on July 28, August 13, and August 25, 2022. On each image acquisition date, datasets were divided into 6,000 training datasets and 1,000 validation datasets with a size of 512 × 512 images. Classification models were developed based on three classes consisting of Sorghum fields(sorghum), rice and soybean fields(others), and non-agricultural fields(background), and two classes consisting of sorghum and non-sorghum (others+background). The classification accuracy of sorghum cultivation fields was higher than 0.91 in the three class-based models at all acquisition dates, but learning confusion occurred in the other classes in the August dataset. In contrast, the two-class-based model showed an accuracy of 0.95 or better in all classes, with stable learning on the August dataset. As a result, two class-based models in August will be advantageous for calculating the cultivation fields of sorghum.

• Korean Journal of Remote Sensing
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• v.39 no.5_1
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• pp.669-681
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• 2023

Studies have tried to apply remote sensing technology, a non-destructive survey method, instead of the existing destructive survey, which requires relatively large labor input and a long time to estimate chlorophyll content, which is an important indicator for evaluating the growth of fruit trees. This study was conducted to non-destructively evaluate the chlorophyll content of pear tree leaves using unmanned aerial vehicle-based hyperspectral imagery for two years(2021, 2022). The reflectance of the single bands of the pear tree canopy extracted through image processing was band rationed to minimize unstable radiation effects depending on time changes. The estimation (calibration and validation) models were developed using machine learning algorithms of elastic-net, k-nearest neighbors(KNN), and support vector machine with band ratios as input variables. By comparing the performance of estimation models based on full band ratios, key band ratios that are advantageous for reducing computational costs and improving reproducibility were selected. As a result, for all machine learning models, when calibration of coefficient of determination (R²)≥0.67, root mean squared error (RMSE)≤1.22 ㎍/cm², relative error (RE)≤17.9% and validation of R²≥0.56, RMSE≤1.41 ㎍/cm², RE≤20.7% using full band ratios were compared, four key band ratios were selected. There was relatively no significant difference in validation performance between machine learning models. Therefore, the KNN model with the highest calibration performance was used as the standard, and its key band ratios were 710/714, 718/722, 754/758, and 758/762 nm. The performance of calibration showed R²=0.80, RMSE=0.94 ㎍/cm², RE=13.9%, and validation showed R²=0.57, RMSE=1.40 ㎍/cm², RE=20.5%. Although the performance results based on validation were not sufficient to estimate the chlorophyll content of pear tree leaves, it is meaningful that key band ratios were selected as a standard for future research. To improve estimation performance, it is necessary to continuously secure additional datasets and improve the estimation model by reproducing it in actual orchards. In future research, it is necessary to continuously secure additional datasets to improve estimation performance, verify the reliability of the selected key band ratios, and upgrade the estimation model to be reproducible in actual orchards.