• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1407-1422
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• 2022

This study was conducted to classify tree species and assess the classification accuracy, using SE-Inception, a classification-based deep learning model. The input images of the dataset used Worldview-3 and GeoEye-1 images, and the size of the input images was divided into 10 × 10 m, 30 × 30 m, and 50 × 50 m to compare and evaluate the accuracy of classification of tree species. The label data was divided into five tree species (Pinus densiflora, Pinus koraiensis, Larix kaempferi, Abies holophylla Maxim. and Quercus) by visually interpreting the divided image, and then labeling was performed manually. The dataset constructed a total of 2,429 images, of which about 85% was used as learning data and about 15% as verification data. As a result of classification using the deep learning model, the overall accuracy of up to 78% was achieved when using the Worldview-3 image, the accuracy of up to 84% when using the GeoEye-1 image, and the classification accuracy was high performance. In particular, Quercus showed high accuracy of more than 85% in F₁ regardless of the input image size, but trees with similar spectral characteristics such as Pinus densiflora and Pinus koraiensis had many errors. Therefore, there may be limitations in extracting feature amount only with spectral information of satellite images, and classification accuracy may be improved by using images containing various pattern information such as vegetation index and Gray-Level Co-occurrence Matrix (GLCM).

• Korean Journal of Remote Sensing
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• v.38 no.5_1
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• pp.523-533
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• 2022

This paper presents a two-stage spatio-spectral fusion method (2SSFM) based on area-to-point regression kriging (ATPRK) to enhance spatial and spectral resolutions using multi-sensor satellite images with complementary spatial and spectral resolutions. 2SSFM combines ATPRK and random forest regression to predict spectral bands at high spatial resolution from multi-sensor satellite images. In the first stage, ATPRK-based spatial down scaling is performed to reduce the differences in spatial resolution between multi-sensor satellite images. In the second stage, regression modeling using random forest is then applied to quantify the relationship of spectral bands between multi-sensor satellite images. The prediction performance of 2SSFM was evaluated through a case study of the generation of red-edge and short-wave infrared bands. The red-edge and short-wave infrared bands of PlanetScope images were predicted from Sentinel-2 images using 2SSFM. From the case study, 2SSFM could generate red-edge and short-wave infrared bands with improved spatial resolution and similar spectral patterns to the actual spectral bands, which confirms the feasibility of 2SSFM for the generation of spectral bands not provided in high spatial resolution satellite images. Thus, 2SSFM can be applied to generate various spectral indices using the predicted spectral bands that are actually unavailable but effective for environmental monitoring.

• Journal of the Korean Institute of Landscape Architecture
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• v.51 no.4
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• pp.16-30
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• 2023

As the concept of metaverse has received great attention, interest in metaverse related to landscape architecture is also increasing. The aim of this research is to understand the potential and tasks of applying metaverse in the field of landscape architecture by analyzing the user experience of a metaverse platform. The object of the research is Meta-Everland built in the Roblox platform, which has the most users among landscape architectural metaverses in Korea. NPS of 30 users who have been to Everalnd was investigated after using Meta-Everland with interviews. NPS before the metaverse experience was -16 and NPS after the experience was -24. This result means that the promotion level was lowered after the experience of the metaverse. There were three causes of lowered NPS: lack of users, low-quality graphics and interface, and lack of content. The factor of lack of users was the result of the other two problems. The factor of low technical quality is hard to be improved in a short period of time. Therefore, the main task to improve the metaverse is developing better metaverse content related to landscape architecture. It is more appropriate to develop metaverse-specific content rather than improve reality issues. Applying AR and VR devices, enhancing communication function, and developing potential as a simulation device are needed to be considered.

• The Korean Journal of Applied Statistics
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• v.37 no.2
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• pp.119-138
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• 2024

Text indicators are increasingly valuable in economic forecasting, but are often hindered by noise and high dimensionality. This study aims to explore post-processing techniques, specifically noise filtering and dimensionality reduction, to normalize text indicators and enhance their utility through empirical analysis. Predictive target variables for the empirical analysis include monthly leading index cyclical variations, BSI (business survey index) All industry sales performance, BSI All industry sales outlook, as well as quarterly real GDP SA (seasonally adjusted) growth rate and real GDP YoY (year-on-year) growth rate. This study explores the Hodrick and Prescott filter, which is widely used in econometrics for noise filtering, and employs sufficient dimension reduction, a nonparametric dimensionality reduction methodology, in conjunction with unstructured text data. The analysis results reveal that noise filtering of text indicators significantly improves predictive accuracy for both monthly and quarterly variables, particularly when the dataset is large. Moreover, this study demonstrated that applying dimensionality reduction further enhances predictive performance. These findings imply that post-processing techniques, such as noise filtering and dimensionality reduction, are crucial for enhancing the utility of text indicators and can contribute to improving the accuracy of economic forecasts.

• Journal of Korean Library and Information Science Society
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• v.54 no.4
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• pp.359-392
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• 2023

Digital citizenship includes an evolving set of knowledge and skills related to effectively and ethically using technology, especially when interacting with other people, information, and media in the online context. As public libraries have long provided access to and training with a variety of technologies, this study explores how digital citizenship has been covered in public library programming to identify potential trends and best practices. A purposive sampling of public library recipients of the American Library Association (ALA) and Information Today Inc.'s Library of the Future Award over the past 11 years (2013-2023) identified 7 case libraries to review. The titles and descriptions of 337 relevant library programs for audiences of school-aged children (5 years old and up) to seniors were collected for a 2-month period from each library's website and analyzed using Ribble & Parks (2019) 9 elements of digital citizenship. The findings suggest that programming related to digital citizenship most often addresses themes connected to digital access and digital fluency through coverage of topics related to computer and technology use. Based on themes and examples from the findings, public libraries are encouraged to expand upon existing programs to integrate all elements of digital citizenship, strive for inclusive and accessible digital citizenship education for all ages, and leverage resources and expertise from relevant stakeholders and community partnerships.

• The Journal of the Acoustical Society of Korea
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• v.43 no.1
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• pp.39-48
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• 2024

A car horn serves a crucial safety role as a means of communication between drivers and a part that alerts pedestrians in advance. While previous studies have utilized finite element method and electric circuit model to simulate and analyze characteristics of the car horns, there remains a lack of research on design methods of a trumpet horn. This paper presents a design approach that predicts the operating frequency based on the acoustic reactance at the throat of the horn, once the vibrating part is determined. We deal with a horn combining both an exponential horn and a waveguide in the acoustic section, and confirm that the acoustic reactance at the horn throat measured by impedance tube experiment agrees well compared with the numerical result obtained using the finite element method. The resonance frequency of the car horn is predicted using the COMSOL Multiphysics finite element numerical analysis model, and the proposed design method is validated by measuring the operating frequency of the designed horn in a sound pressure experiment. As a result, the resonance measured in a semi-anechoic chamber environment by applying a DC voltage of 12 [V] excluding the holder occurs accurately within a few [Hz] of the design operating frequency. This paper discuss the design method of a trumpet horn from the perspective of the horn's acoustic reactance, and is expected to be useful for designing horn systems.

• Journal of Korea Water Resources Association
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• v.57 no.2
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• pp.73-85
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• 2024

Predicting water quality of rivers and reservoirs is necessary for the management of water resources. Artificial Neural Networks (ANNs) have been used in many studies to predict water quality with high accuracy. Previous studies have used Gradient Descent (GD)-based optimizers as an optimizer, an operator of ANN that searches parameters. However, GD-based optimizers have the disadvantages of the possibility of local optimal convergence and absence of a solution storage and comparison structure. This study developed improved optimizers to overcome the disadvantages of GD-based optimizers. Proposed optimizers are optimizers that combine adaptive moments (Adam) and Nesterov-accelerated adaptive moments (Nadam), which have low learning errors among GD-based optimizers, with Harmony Search (HS) or Novel Self-adaptive Harmony Search (NSHS). To evaluate the performance of Long Short-Term Memory (LSTM) using improved optimizers, the water quality data from the Dasan water quality monitoring station were used for training and prediction. Comparing the learning results, Mean Squared Error (MSE) of LSTM using Nadam combined with NSHS (NadamNSHS) was the lowest at 0.002921. In addition, the prediction rankings according to MSE and R² for the four water quality indices for each optimizer were compared. Comparing the average of ranking for each optimizer, it was confirmed that LSTM using NadamNSHS was the highest at 2.25.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.36 no.2
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• pp.50-60
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• 2024

To promote the application of reliability-based design within the Korean coastal engineering community, the author conducted reliability analyses and optimized the design of a vertical-type breakwater, considering multiple limit states in the seas off of Pusan and Gunsan - two representative ports in Korea. In this process, rather than relying on design waves of a specific return period, the author intentionally avoided such constraints. Instead, the author characterized the uncertainties associated with wave force, lift force, and overturning moment - key factors significantly influencing the integrity of a vertical-type breakwater. This characterization was achieved by employing a probabilistic model derived from the frequency analysis results of long-term in-situ wave data. The limit state of the vertical-type breakwater encompassed sliding, overturning, and collapse failure, with the close interrelation between wave force, lift force, and moment described using the Nataf joint probability distribution. Simulation results indicate, as expected, that considering only sliding failure underestimates the failure probability. Furthermore, it was shown that the failure probability of vertical-type breakwaters cannot be consistently secured using design waves with a specific return period. In contrast, breakwaters optimally designed to meet the reliability index requirement of 𝛽-3.5 to 4 consistently achieve a consistent failure probability across all sea areas.

• Journal of the Korean Academy of Child and Adolescent Psychiatry
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• v.7 no.1
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• pp.34-43
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• 1996

In adolescence, the symptoms of depression are more various and different from those of adult. Conduct behaviours are frequently represented in adolescent's depression. The patients who have the depression and conduct disorder are defined as depressive condor disorder in ICD-10. We hypothesized that there might be different parental rearing patterns between the patients with depression alone and the depressive conduct disorder. We applied children's depression inventory (CDI), parental rating form for conduct disorder based on DSM-III-R, and parental bonding instrument (PBI) to patients and normal control adolescent group. The results were as follows : 1) There were no significant differences in severity of depressive symptoms, maternal care, maternal overprotection, and paternal care. 2) Paternal overprotection showed significant higher scores in depressive conduct disorder group than depression group and normal control group. 3) There were positive correlations in the severity of depressive symptoms and behavior problems in all subjects. 4) There were no correlations in maternal care and overprotecion with conduct problems, but with depressive symptoms in all subject. 4) There were no correlations in paternal care with conduct problems and depressive symptoms in all subjects. 5) There were significant correlations in patienral overprotective, intrusive attitudes with conduct problems, not with depressive symptoms in all subjects.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.52 no.1
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• pp.69-80
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• 2007

Among the photoactive semiconductors such as $TiO_2,\;ZnO,\;Fe_2O_3,\;WO_3,\;and\;CdSe,\;TiO_2$ is the most widely used as photocatalyst in different media, because of its lack of toxicity and stability. In this study, the effects of titanium dioxide were investigated to obtain the information of physiological change in rice plant. Light-adapted Chlorophyll flourescence index decreased and relative electron transport rate of rice leaves was activated by titanium dioxide under $2,400\;{\mu}mol\;m^{-2}\;s^{-1}$ PAR (Photosynthetic active radiation). Relative electron transport rate of rice leaf treated with titanium dioxide 10 ppm was high in order of $2,400\;{\mu}mol\;m^{-2}\;s^{-1}\;PAR,\;2,200\;{\mu}mol\;m^{-2}\;s^{-1}\;PAR,\;450\;{\mu}mol\;m^{-2}\;s^{-1}\;PAR$ and titanium dioxide 10 ppm (45.1%), control (32.4%), diuron 10 ppm (15.3%) under $2,400\;{\mu}mol\;m^{-2}\;s^{-1}\;PAR$. Titanium dioxide increased photosynthesis of the rice leaf under $13.6\;KJ\;m^{-2}\;day^{-1}$ UV-B only. With titanium dioxide 20 ppm, reduced UV-B ($0.15\;KJ\;m^{-2}\;day^{-1}$) intensity changed the induction of proteins and twenty-five proteins were identified. Among them, seventy proteins were up-regulated, four proteins were down-regulated and four proteins were newly synthesized. Function of these proteins was related to photosynthesis (52%), carbohydrate metabolism (4%), stress/defense (8%), secondary metabolism (4%), energy/electron transport (4%), and miscellaneous (28%).