• Korean Journal of Remote Sensing
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• v.39 no.6_3
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• pp.1779-1790
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• 2023

Satellite-based fog detection algorithms are being developed to detect fog in real-time over a wide area, with a focus on the Korean Peninsula (KorPen). The GEO-KOMPSAT-2A/Advanced Meteorological Imager (GK2A/AMI, GK2A) satellite offers an excellent temporal resolution (10 min) and a spatial resolution (500 m), while GEO-KOMPSAT-2B/Geostationary Ocean Color Imager-II (GK2B/GOCI-II, GK2B) provides an excellent spatial resolution (250 m) but poor temporal resolution (1 h) with only visible channels. To enhance the fog detection level (10 min, 250 m), we developed a fused GK2AB fog detection algorithm (FDA) of GK2A and GK2B. The GK2AB FDA comprises three main steps. First, the Korea Meteorological Satellite Center's GK2A daytime fog detection algorithm is utilized to detect fog, considering various optical and physical characteristics. In the second step, GK2B data is extrapolated to 10-min intervals by matching GK2A pixels based on the closest time and location when GK2B observes the KorPen. For reflectance, GK2B normalized visible (NVIS) is corrected using GK2A NVIS of the same time, considering the difference in wavelength range and observation geometry. GK2B NVIS is extrapolated at 10-min intervals using the 10-min changes in GK2A NVIS. In the final step, the extrapolated GK2B NVIS, solar zenith angle, and outputs of GK2A FDA are utilized as input data for machine learning (decision tree) to develop the GK2AB FDA, which detects fog at a resolution of 250 m and a 10-min interval based on geographical locations. Six and four cases were used for the training and validation of GK2AB FDA, respectively. Quantitative verification of GK2AB FDA utilized ground observation data on visibility, wind speed, and relative humidity. Compared to GK2A FDA, GK2AB FDA exhibited a fourfold increase in spatial resolution, resulting in more detailed discrimination between fog and non-fog pixels. In general, irrespective of the validation method, the probability of detection (POD) and the Hanssen-Kuiper Skill score (KSS) are high or similar, indicating that it better detects previously undetected fog pixels. However, GK2AB FDA, compared to GK2A FDA, tends to over-detect fog with a higher false alarm ratio and bias.

• Journal of the Korean Society of Radiology
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• v.83 no.2
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• pp.344-359
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• 2022

Purpose To develop a denoising convolutional neural network-based image processing technique and investigate its efficacy in diagnosing breast cancer using low-dose mammography imaging. Materials and Methods A total of 6 breast radiologists were included in this prospective study. All radiologists independently evaluated low-dose images for lesion detection and rated them for diagnostic quality using a qualitative scale. After application of the denoising network, the same radiologists evaluated lesion detectability and image quality. For clinical application, a consensus on lesion type and localization on preoperative mammographic examinations of breast cancer patients was reached after discussion. Thereafter, coded low-dose, reconstructed full-dose, and full-dose images were presented and assessed in a random order. Results Lesions on 40% reconstructed full-dose images were better perceived when compared with low-dose images of mastectomy specimens as a reference. In clinical application, as compared to 40% reconstructed images, higher values were given on full-dose images for resolution (p < 0.001); diagnostic quality for calcifications (p < 0.001); and for masses, asymmetry, or architectural distortion (p = 0.037). The 40% reconstructed images showed comparable values to 100% full-dose images for overall quality (p = 0.547), lesion visibility (p = 0.120), and contrast (p = 0.083), without significant differences. Conclusion Effective denoising and image reconstruction processing techniques can enable breast cancer diagnosis with substantial radiation dose reduction.

• Journal of Korean Library and Information Science Society
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• v.7
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• pp.1-55
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• 1980

It has been observed that the purpose of education is poorly coordinated with the school library. Consequently a healthy growth of the library has been very rare, and educational process has been rather inefficient. Therefore this study attempts to define the role of a school library and the necessasity of its growth, examine principals' concepts of the library, find out the adverse causes for its growth, and make some suggestions to rectify them. A questionnaire was designed to get information on the principals' conceptions about the nature and the role of a school library, a librarian, and adverse causes for the growth of the library. This study is largely based on the analysis of this questionnaire. The results of this study may be summarized as. follows: 1) The school library is not generally considered as the center of educational activities. It is rather variously regarded as a subsidiary organization for education, a place where reading materials are offered, a place where books are kept, or a reading room. 2) This was largely due to the misconceptions of the principals as to the true nature and the role of the school library. 3) The degrees of their misconceptions varied depending on the amount of their exposure to the library science. Those principals who studied library science more hours had better understanding of the library. 4) Although the principals showed rather much concern for the library, the school library was not up to the expectation largely due to their misconception of it. 5) Most of the principals felt that they needed more knowledge on library science to carry out their job. This feeling was stronger for those who spent more hours in a library science course. 6) Most of the principals wanted to offer a position for a dual function: a librarian and a teacher. This was largely due to their lack of knowledge as to the duties of a librarian-which were considered as secondary to the duties of a teacher. 7) The majority of the principals thought the librarians were not paid well enough, but some of the principals o n.0, pposed their pay raise. The former generally took more courses in library science than the latter. 8) Many principals agreed that the adverse causes for the growth of the school library originated from the regional or governmental school authorities. This seemed to indicate that the legal requirements for the library were inadequate and that there was no administrative organization to take care of the library. 9) Most of the principals considered the insufficient funds as the major reason for the present poor condition of the library. But considering the fact that some libraries are better equi n.0, pped that others, financial matter cannot be the deciding factor. It rather seemed that there is some serious problems in the current educational system. For further studies in this field and for the libraries to function properly, the following suggestions are made here: 1) The major adverse cause for the healthy growth of the school library was found in the misconceptions on the school library by the principals, and these misconceptions were largely due to their lack of knowledge. Therefore they should be given more o n.0, pportunities to take courses in library science. 2) The librarian should not be overburdened with other duties than what his job duly calls for, and they should be properly compensated for their own job. They should also be encouraged to grow as librarians. 3) Education itself should be improved so that the library becomes the center of learning. 4) An administrative department should be created to oversee the school libraries, and legal measures should be enacted for better school libraries. 5) Financial su n.0, pport should be provided for a period of time in order to upgrade the school library to a certain level. Finally it is strongly felt that more detailed and inclusive studies in this field should be carried on and further experimental studies should be done.

• Journal of The Korean Association For Science Education
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• v.19 no.1
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• pp.41-61
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• 1999

In this study I defined the direction Integrated Science Education(ISE) should take. So that I groped for the direction ISE should take in the inherent nature of science and education, analyzing their respective validity from philosophical and psychological angles. Based upon these researches, I formulated the three directions for ISE to take; knowledge-centered, social problem-centered, and individual interest-centered. The results of this thesis may be summed up as follows: 1. The knowledge-centered ISE that thinks the inherent nature of science is in the scientific knowledge is based upon Hirst's integrated logic which is built on discipline-centered educational viewpoint. Now, the focus of interdisciplinary integration consists in clarifying the meanings of knowledge and the logical relations between one knowledge and another according to the respective form of exploration. The knowledge-centered ISE, therefore, was analyzed to find its justification in the educational philosophy of idealism, realism, neo-scholasticism; in the educational theories of essentialism, behaviorism, perennial ism; in the scientific philosophy of empiricism. positivism; in the educational psychology of developmental psychology and constructivism. 2. The social problem-centered ISE that thinks the inherent nature of science is the process of social concord is based upon Dewey's integrated logic which is built on experience-centered educational viewpoint. Now, the focus of interdisciplinary integration consists in the methodological aspect facilitating the process of experience. The social problem-centered ISE, therefore, was analyzed to find its theoretical justification in the educational philosophy of pragmatism; in the educational theory of progressivism; in the scientific philosophy of relativism and rationalism; and in the educational psychology of developmental psychology and constructivism. 3. The individual interest-centered ISE is based upon Patterson's integrated logic which is built on human-centered educational viewpoint. The focus of education here is self-realization. Therefore, rather than provide in learning conditions from outside, one is made to choose them oneself and the process of satisfying one's motive is emphasized. The individual interest-centered ISE, therefore, was analyzed to find its theoretical justification in the educational philosophy of existentialism; in the educational theory of humanism; in the scientific philosophy of relativism; and in Gestalt psychology.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.1
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• pp.15-33
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• 2021

In this study, the possibility of discriminating Fire blight (FB) infection tested using the hyperspectral imagery. The reflectance of healthy and infected leaves and branches was acquired with 5 nm of full width at high maximum (FWHM) and then it was standardized to 10 nm, 25 nm, 50 nm, and 80 nm of FWHM. The standardized samples were divided into training and test sets at ratios of 7:3, 5:5 and 3:7 to find the optimal bands of FWHM by the decision tree analysis. Classification accuracy was evaluated using overall accuracy (OA) and kappa coefficient (KC). The hyperspectral reflectance of infected leaves and branches was significantly lower than those of healthy green, red-edge (RE) and near infrared (NIR) regions. The bands selected for the first node were generally 750 and 800 nm; these were used to identify the infection of leaves and branches, respectively. The accuracy of the classifier was higher in the 7:3 ratio. Four bands with 50 nm of FWHM (450, 650, 750, and 950 nm) might be reasonable because the difference in the recalculated accuracy between 8 bands with 10 nm of FWHM (440, 580, 640, 660, 680, 710, 730, and 740 nm) and 4 bands was only 1.8% for OA and 4.1% for KC, respectively. Finally, adding two bands (550 nm and 800 nm with 25 nm of FWHM) in four bands with 50 nm of FWHM have been proposed to improve the usability of multispectral image sensors with performing various roles in agriculture as well as detecting FB with other combinations of spectral bands.

• Korean Journal of Remote Sensing
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• v.39 no.5_3
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• pp.949-965
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• 2023

In this study, we propose a method to monitor the surface area of agricultural reservoirs in South Korea using Sentinel-1 synthetic aperture radar images and the deep learning model, Swin Transformer. Utilizing the Google Earth Engine platform, datasets from 2017 to 2021 were constructed for seven agricultural reservoirs, categorized into 700 K-ton, 900 K-ton, and 1.5 M-ton capacities. For four of the reservoirs, a total of 1,283 images were used for model training through shuffling and 5-fold cross-validation techniques. Upon evaluation, the Swin Transformer Large model, configured with a window size of 12, demonstrated superior semantic segmentation performance, showing an average accuracy of 99.54% and a mean intersection over union (mIoU) of 95.15% for all folds. When the best-performing model was applied to the datasets of the remaining three reservoirsfor validation, it achieved an accuracy of over 99% and mIoU of over 94% for all reservoirs. These results indicate that the Swin Transformer model can effectively monitor the surface area of agricultural reservoirs in South Korea.

• Korean Journal of Remote Sensing
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• v.39 no.5_3
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• pp.997-1008
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• 2023

Ship detection at sea can be performed in various ways. In particular, satellites can provide wide-area surveillance, and Synthetic Aperture Radar (SAR) imagery can be utilized day and night and in all weather conditions. To propose an efficient ship detection method from SAR images, this study aimed to apply the You Only Look Once Version 5 (YOLOv5) model to Sentinel-1 images and to analyze the difference between individual vs. integrated models and the accuracy characteristics by polarization. YOLOv5s, which has fewer and lighter parameters, and YOLOv5x, which has more parameters but higher accuracy, were used for the performance tests (1) by dividing each polarization into HH, HV, VH, and VV, and (2) by using images from all polarizations. All four experiments showed very similar and high accuracy of 0.977 ≤ AP@0.5 ≤ 0.998. This result suggests that the polarization integration model using lightweight YOLO models can be the most effective in terms of real-time system deployment. 19,582 images were used in this experiment. However, if other SAR images,such as Capella and ICEYE, are included in addition to Sentinel-1 images, a more flexible and accurate model for ship detection can be built.

• Journal of Science Education
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• v.33 no.1
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• pp.12-30
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• 2009

The purpose of this study was to analyze recognition characteristics of science gifted students on the earth system based on their thinking style. The subjects were 24 science gifted students at the Science Institute for Gifted Students of a university located in metropolitan city in Korea. The students' thinking styles were firstly examined on the basis of the Sternberg's theory of mental self-government. And then, the students were divided into two groups: Type I group(legislative, judicial, global, liberal) and Type II group(executive, local, conservative) based on Sternberg's theory. Data was collected from three different type of questionnaires(A, B, C types), interview, word association method, drawing analyses, concept map, hidden dimension inventory, and in-depth interviews. The findings of analysis indicated that their thinking styles were characterized by 'Legislative', 'Executive', 'Anarchic', 'Global', 'External', 'Liberal' styles. Their preference were conducting new projects and using creative problem solving processes. The results of students' recognition characteristics on earth system were as follows: First, though the two groups' quantitative value on 'System Understanding' was very similar, there were considerable distinctions in details. Second, 'Understanding the Relationship in the System' was closely connected to thinking styles. Type I group was more advantageous with multiple, dynamic, and recursive approach. Third, in the relation to 'System Generalization' both of the groups had similar simple interpretational ability of the system, but Type I group was better on generalization when 'hidden dimension inventory' factor was added. On the system prediction factor, however, students' ability was weak regardless of the type. Consequently, more specific development strategies on various objects are needed for the development and application of the system learning program. Furthermore, it is expected that this study could be practically and effectively used on various fields related to system recognition.

• Journal of the Korean earth science society
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• v.43 no.2
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• pp.312-323
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• 2022

This study began with the hypothesis of whether "solar radiation" and "terrestrial radiation" can be replaced by "visible radiation" and "infrared radiation", respectively. To this end, we investigated the perceptions of high school students who completed the Earth Science I course through a questionnaire to reveal how they perceived each concept. We also analyzed the descriptions and illustrations of textbooks that may have affected their perceptions. All of the students who participated in the questionnaire recognized solar radiation as radiation emitted only in the visible light region. About 35% of the students recognized convection, conduction, and latent heat as energy transfer by radiation in the Earth's heat budget. By analyzing six types of Earth Science I textbooks in the 2015 revised curriculum, we observed that two types introduced the terms "shortwave radiation" and "longwave radiation" but had no explanation for them, while the other two described solar radiation as "radiation mainly in the visible light region" or "radiation in short wavelengths". Regarding solar and terrestrial radiation in the last two types, there was no explanation for the wavelength regions, or ambiguous terms such as "short wavelength" and "long wavelength" were used. In addition, the two textbooks contained some errors in the illustration of the energy budget. Considering that textbooks described solar and terrestrial radiation without defining the exact terms for shortwave and longwave radiation, learners are likely to recognize solar and terrestrial radiation as visible and infrared radiation, respectively. This finding implies that vague statements or errors in textbooks can cause or reproduce students' misconceptions. The discussion in this study is expected to be used as a helpful reference material for teaching and learning processes regarding the Earth's radiation equilibrium and heat budget, and thereby contribute to proposing reasonable description plans for future textbook writing.

• Korean Journal of Remote Sensing
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• v.39 no.5_1
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• pp.695-713
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• 2023

In coastal waters, phytoplankton,suspended particulate matter, and dissolved organic matter intricately and nonlinearly alter the reflectivity of seawater. Neural network technology, which has been rapidly advancing recently, offers the advantage of effectively representing complex nonlinear relationships. In previous studies, a three-stage neural network was constructed to extract the inherent optical properties of each component. However, this study proposes an algorithm that directly employs a deep neural network. The dataset used in this study consists of synthetic data provided by the International Ocean Color Coordination Group, with the input data comprising above-surface remote-sensing reflectance at nine different wavelengths. We derived inherent optical properties using this dataset based on a deep neural network. To evaluate performance, we compared it with a quasi-analytical algorithm and analyzed the impact of log transformation on the performance of the deep neural network algorithm in relation to data distribution. As a result, we found that the deep neural network algorithm accurately estimated the inherent optical properties except for the absorption coefficient of suspended particulate matter (R² greater than or equal to 0.9) and successfully separated the sum of the absorption coefficient of suspended particulate matter and dissolved organic matter into the absorption coefficient of suspended particulate matter and dissolved organic matter, respectively. We also observed that the algorithm, when directly applied without log transformation of the data, showed little difference in performance. To effectively apply the findings of this study to ocean color data processing, further research is needed to perform learning using field data and additional datasets from various marine regions, compare and analyze empirical and semi-analytical methods, and appropriately assess the strengths and weaknesses of each algorithm.