• The Journal of Korean Academy of Sensory Integration
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• v.19 no.3
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• pp.32-43
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• 2021

Objective : This study aimed to verify the construct validity of the Korean version of the Peabody Developmental Motor Scale-2 (K-PDMS-2) and its test-retest reliability for children with cerebral palsy (CP) and typical children. Method : To ascertain the construct validity, the K-PDMS-2 evaluation was conducted on 42 children with cerebral palsy and 42 typical children of similar age and gender. Construct validity was proved through comparison with standard scores. Ten of the children with CP were re-evaluated after two weeks to determine test-retest reliability. Results : There was a statistically significant difference in gross motor and fine motor development according to five subtests between the group of children with CP and the typical group (p = .000). For test-retest reliability, the correlation coefficient of the total frequency score was .989, representing very high temporal stability. Conclusion : This study confirmed that K-PDMS-2 is an evaluation tool of high reliability and validity, and a potentially useful future measure for domestic clinical sites and research.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1047-1056
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• 2022

Sea ice, frozen sea water, in the Artic is a primary indicator of global warming. Due to its importance to the climate system, shipping-route navigation, and fisheries, Arctic sea ice prediction has gained increased attention in various disciplines. Recent advances in artificial intelligence (AI), motivated by a desire to develop more autonomous and efficient future predictions, have led to the development of new sea ice prediction models as alternatives to conventional numerical and statistical prediction models. This study aims to evaluate the performance of the two-stream convolutional long-and short-term memory (TS-ConvLSTM) AI model, which is designed for learning both global and local characteristics of the Arctic sea ice changes, for the minimum September Arctic sea ice from 2001 to 2021, and to show the possibility for an operational prediction system. Although the TS-ConvLSTM model generally increased the prediction performance as training data increased, predictability for the marginal ice zone, 5-50% concentration, showed a negative trend due to increasing first-year sea ice and warming. Additionally, a comparison of sea ice extent predicted by the TS-ConvLSTM with the median Sea Ice Outlooks (SIOs) submitted to the Sea Ice Prediction Network has been carried out. Unlike the TS-ConvLSTM, the median SIOs did not show notable improvements as time passed (i.e., the amount of training data increased). Although the TS-ConvLSTM model has shown the potential for the operational sea ice prediction system, learning more spatio-temporal patterns in the difficult-to-predict natural environment for the robust prediction system should be considered in future work.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.40 no.4
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• pp.275-292
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• 2022

In order to detect climate changes using satellite imagery, the GCOS (Global Climate Observing System) defines requirements such as spatio-temporal resolution, stability by the time change, and uncertainty. Due to limitation of GK-2A sensor performance, the level-2 products can not satisfy the requirement, especially for spatial resolution. In this paper, we found the optimal pan-sharpening algorithm for GK-2A products. The six pan-sharpening methods included in CS (Component Substitution), MRA (Multi-Resolution Analysis), VO (Variational Optimization), and DL (Deep Learning) were used. In the case of DL, the synthesis property based method was used to generate training dataset. The process of synthesis property is that pan-sharpening model is applied with Pan (Panchromatic) and MS (Multispectral) images with reduced spatial resolution, and fused image is compared with the original MS image. In the synthesis property based method, fused image with desire level for user can be produced only when the geometric characteristics between the PAN with reduced spatial resolution and MS image are similar. However, since the dissimilarity exists, RD (Random Down-sampling) was additionally used as a way to minimize it. Among the pan-sharpening methods, PSGAN was applied with RD (PSGAN_RD). The fused images are qualitatively and quantitatively validated with consistency property and the synthesis property. As validation result, the GSA algorithm performs well in the evaluation index representing spatial characteristics. In the case of spectral characteristics, the PSGAN_RD has the best accuracy with the original MS image. Therefore, in consideration of spatial and spectral characteristics of fused image, we found that PSGAN_RD is suitable for GK-2A products.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.3
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• pp.125-132
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• 2023

In this study, we compared the performance of machine learning models for predicting Vapor Pressure Deficits (VPD) in greenhouses that affect pore function and photosynthesis as well as plant growth due to nutrient absorption of plants. For VPD prediction, the correlation between the environmental elements in and outside the greenhouse and the temporal elements of the time series data was confirmed, and how the highly correlated elements affect VPD was confirmed. Before analyzing the performance of the prediction model, the amount and interval of analysis time series data (1 day, 3 days, 7 days) and interval (20 minutes, 1 hour) were checked to adjust the amount and interval of data. Finally, four machine learning prediction models (XGB Regressor, LGBM Regressor, Random Forest Regressor, etc.) were applied to compare the prediction performance by model. As a result of the prediction of the model, when data of 1 day at 20 minute intervals were used, the highest prediction performance was 0.008 for MAE and 0.011 for RMSE in LGBM. In addition, it was confirmed that the factor that most influences VPD prediction after 20 minutes was VPD (VPD_y__71) from the past 20 minutes rather than environmental factors. Using the results of this study, it is possible to increase crop productivity through VPD prediction, condensation of greenhouses, and prevention of disease occurrence. In the future, it can be used not only in predicting environmental data of greenhouses, but also in various fields such as production prediction and smart farm control models.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.4
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• pp.446-454
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• 2023

The impact of climate change on agriculture is substantial, especially as global warming is projected to lead to varying temperature and humidity patterns in the future. These changes pose a higher risk for both crops and livestock, exposing them to environmental stressors under altered climatic conditions. Specifically, as temperatures are expected to rise, the risk of heat stress is assessable through the Temperature-Humidity Index (THI), derived from temperature and relative humidity data. This study involved the comparison of THI collected from 10 Korea Meteorological Administration ASOS stations spanning a 60-year period from 1961 to 2020. Moreover, high-resolution temperature and humidity distribution data from 1981 to 2020 were employed to generate high-resolution TH I distributions, analyzing temporal changes. Additionally, the number of days characterized by heat stress, derived from TH I, was compared over different time periods. Generally, TH I showed an upward trend over the past, albeit with varying rates across different locations. As TH I increased, the frequency of heat stress days also rose, indicating potential future cost increases in the livestock industry due to heat-related challenges. The findings emphasize the feasibility of evaluating heat stress risk in livestock using THI and underscore the need for research analyzing THI under future climate change scenarios.

• Korean Journal of Radiology
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• v.22 no.5
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• pp.725-734
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• 2021

Objective: To intraindividually compare hepatocellular carcinoma (HCC) washout between MRIs using hepatobiliary agent (HBA) and extracellular agent (ECA). Materials and Methods: This study included 114 prospectively enrolled patients with chronic liver disease (mean age, 55 ± 9 years; 94 men) who underwent both HBA-MRI and ECA-MRI before surgical resection for HCC between November 2016 and May 2019. For 114 HCCs, the lesion-to-liver visual signal intensity ratio (SIR) using a 5-point scale (-2 to +2) was evaluated in each phase. Washout was defined as negative visual SIR with temporal reduction of visual SIR from the arterial phase. Illusional washout (IW) was defined as a visual SIR of 0 with an enhancing capsule. The frequency of washout and MRI sensitivity for HCC using LR-5 or its modifications were compared between HBA-MRI and ECA-MRI. Subgroup analysis was performed according to lesion size (< 20 mm or ≥ 20 mm). Results: The frequency of portal venous phase (PP) washout with HBA-MRI was comparable to that of delayed phase (DP) washout with ECA-MRI (77.2% [88/114] vs. 68.4% [78/114]; p = 0.134). The frequencies were also comparable when IW was allowed (79.8% [91/114] for HBA-MRI vs. 81.6% [93/114] for ECA-MRI; p = 0.845). The sensitivities for HCC of LR-5 (using PP or DP washout) were comparable between HBA-MRI and ECA-MRI (78.1% [89/114] vs. 73.7% [84/114]; p = 0.458). In HCCs < 20 mm, the sensitivity of LR-5 was higher on HBA-MRI than on ECA-MRI (70.8% [34/48] vs. 50.0% [24/48]; p = 0.034). The sensitivity was similar to each other if IW was added to LR-5 (72.9% [35/48] for HBA-MRI vs. 70.8% [34/48] for ECA-MRI; p > 0.999). Conclusion: Extracellular phase washout for HCC diagnosis was comparable between MRIs with both contrast agents, except for tumors < 20 mm. Adding IW could improve the sensitivity for HCC on ECA-MRI in tumors < 20 mm.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.14 no.1
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• pp.10-21
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• 2009

Muan Bay has extensively undertaken artificial influences through a series of construction of dams and dykes nearby resulting in a substantial increase in highest high water level. To unravel sedimentary responses to the water level rise, we collected a number of surface sediment samples and hydrodynamic data from in-situ observations of tidal currents in Muan Bay in 1998 and 2007. Comparison of the data between 1998 and 2007 shows that the relative content of coarse fractions, sand and gravel, in the sediment samples has increased with a decreased mean size, on average, from 6.2 to 5.8${\phi}$ at the expense of silt contents. Such a coarsening trend, which is more evident around high water level, particularly on the tidal flats of Dongam-ri, Guro-ri and Aphae-do, is most likely attributable to rising water level. On the other hand, an increase of fine fractions locally in the western entrance of the bay can be explained with changes in characteristics of tidal currents imposed by construction of bridges therein, such as decreased velocities and varied direction and phase of the tidal currents.

• Journal of Environmental Impact Assessment
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• v.33 no.2
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• pp.53-63
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• 2024

Biodiversity holds significant importance within the framework of environmental impact assessment, being utilized in site selection for development, understanding the surrounding environment, and assessing the impact on species due to disturbances. The field of environmental impact assessment has seen substantial research exploring new technologies and models to evaluate and predict biodiversity more accurately. While current assessments rely on data from fieldwork and literature surveys to gauge species richness indices, limitations in spatial and temporal coverage underscore the need for high-resolution biodiversity assessments through species richness mapping. In this study, leveraging data from the 4th National Ecosystem Survey and environmental variables, we developed a species distribution model using Random Forest. This model yielded mapping results of 24 mammalian species' distribution, utilizing the species richness index to generate a 100-meter resolution map of species richness. The research findings exhibited a notably high predictive accuracy, with the species distribution model demonstrating an average AUC value of 0.82. In addition, the comparison with National Ecosystem Survey data reveals that the species richness distribution in the high-resolution species richness mapping results conforms to a normal distribution. Hence, it stands as highly reliable foundational data for environmental impact assessment. Such research and analytical outcomes could serve as pivotal new reference materials for future urban development projects, offering insights for biodiversity assessment and habitat preservation endeavors.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.27 no.2
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• pp.55-65
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• 2024

This study aimed to figure out diel activity patterns of water deer and wild boar, whose habitat is disturbed by human activity in a suburban area. Photographic data of water deer and wild boar collected by 18 camera traps from January 2021 to November 2022 was categorized into four diel periods (dawn, day, dusk, and night), and converted into frequencies per 100 CTD (Camera Trap-Days) for seasonal and spatial diel activity pattern analysis. Water deer exhibited intense nocturnality in fall, and wild boar did in fall and winter. During the fall, water deer's night-time capture rate was the highest (61.9%), and day-time photographic rate was the lowest (13.9%) among other seasons. During the fall and winter, wild boar's night-time photographic rate was relatively high (77.6%, 78.0%, respectively), and day-time photographic rate was relatively low (0.7%, 1.8%) in comparison with other seasons. In spatial diel activity analysis, both water deer and wild boar showed a tendency to avoid humans, especially near trails during day-time hours. The day-time photographic rate of water deer in trail-near group was 12.1% and trail-far group was 24.6%. The day-time photographic rate of wild boar was 3.4%, 5.7%, respectively. Because the diel activity patterns of wildlife reflect human disturbance, this study provides useful ecological information for developing appropriate management plans for the coexistence of water deer and wild boar in suburban areas.

• Korean Journal of Environmental Biology
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• v.42 no.1
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• pp.15-27
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• 2024

The goal of this study was to provide basic data necessary for managing fish in the Seomgang River by confirming diversity of fish species in the Seomgang River and determining the degree of change in fish species through a comparison with earlier related work. Growth rate, obesity level, and temporal and spatial reproductive capacities were analyzed to determine growth characteristics of dominant species. Fish fauna and structure of the fish community were surveyed at three different time points from October of 2020 to August of 2021 at eight sites. In addition, growth characteristics of Zacco platypus from June of 2021 to July of 2022 at four sites were determined. A total of 3,999 individuals, 43 species, and ten families of fish were identified. Among these species, 19 (44.19%) were Korean endemic species and four (9.30%) were endangered species. The dominant species was Z. platypus. Pungtungia herzi was identified as a subdominant species. An analysis of length-weight relationships and condition factor (k) of Z. platypus confirmed a good state of growth. As a result of a frequency analysis of the total length, the life cycle of the Z. platypus population living in the Seomgang River was found to be stable. According to gonadosomatic index (GSI) analysis, the spawning season of Z. platypus was estimated to occur after May, consistent with the literature.