• Journal of The Korean Astronomical Society
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• v.35 no.3
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• pp.143-149
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• 2002

In this paper we present a methodology to derive the temporal change of the magnetic shear angle from a series of vector magnetograms, with a high time cadence. This method looks for the minimum change of the shear angle between a pair of magnetograms, free from the $180^{\circ}$ ambiguity, and then accumulates this change over many successive pairs to derive the temporal change of magnetic shear. This methodology will work well if only the successive magnetograms occurred in an active region are well aligned and its helicity sign is reasonably determined. We have applied this methodology to a set of vector magnetograms of NOAA Active Region 9661 on October 19, 2001 by the new digital magnetograph at the Big Bear Solar Observatory (BBSO). For this work we considered well aligned magnetograms whose cross-correlation values are larger than 0.95. As a result, we have confirmed the recent report of Wang et al. that there was the abrupt shear change associated with the X1.6 flare. It is also demonstrated that the shear change map can be an useful tool to highlight the local areas that experienced the abrupt shear change. Finally, we suggest that this observation should be a direct support of the emergence of sheared magnetic fields.

• Korean Journal of Remote Sensing
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• v.25 no.1
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• pp.85-94
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• 2009

This paper presents the capability to use QuickBird imagery for effects of forest disturbance in Okgye burned area. Particular attention of this paper deals with the NBR-derived mapping burn severity on QuickBird imagery to locate reliable rehabilitation(namely, secondary succession) over postfire surface. Comparisons of the mapping forest disturbance derived from QuickBird NBR data and the mapping burn severity derived from Landsat ${\Delta}NBR$ data show substantial agreement (KHAT value =0.7886). The method calculated from the correlation between QuickBird wetness and Landsat ETM+ band7 may have application to forest harvest disturbance.

• Journal of the Optical Society of Korea
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• v.15 no.1
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• pp.68-73
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• 2011

This study investigated, using the Orbscan II topography system, the influence of age and sex related changes on the corneal thickness and anterior corneal curvature, more specifically the fine structure of the cornea, in a Korean young population. The Orbscan II topography system is a computer-assisted slit-beam scanning technology that can map the anterior section of the cornea. The mean central corneal thickness of all subjects was $547.532{\pm}44.529\;{\mu}m$. There was no statistical difference (p>0.5) in the mean central corneal thickness between males and females. Sex and age related changes in the mean central corneal thickness had no specific statistical difference (P>0.5). There was a negative correlation between the anterior corneal curvature and the central corneal thickness in all subjects, except for the twenty year olds. However, the thickness relationship between the mean central corneal and the eight paracentral corneal thicknesses had strong statistical differences in all subjects. Also age and sex related changes in the central corneal thickness and the anterior corneal curvature in all subjects had no statistically significant difference, except from 20-26 years old (p>0.05). This information could be a suitable reference basis for future studies in the young population of Asia and for the development of examination tools for corneal refractive surgery.

• Current Optics and Photonics
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• v.3 no.1
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• pp.54-65
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• 2019

To develop a biomarker predicting tumor treatment efficacy is helpful to reduce time, medical expenditure, and efforts in oncology therapy. In clinics, microvessel density using immunohistochemistry has been proposed as an indicator that correlates with both tumor size and metastasis of cancer. In the preclinical study, we hypothesized that vascular morphometrics using optical coherence tomography angiography (OCTA) could be potential indicators to estimate the treatment efficacy of breast cancer. To verify this hypothesis, a 13762-MAT-B-III rat breast tumor was grown in a dorsal skinfold window chamber which was applied to a nude mouse, and the change in vascular morphology was longitudinally monitored during tumor growth and metronomic cyclophosphamide treatment. Based on the daily OCTA maximum intensity projection map, multiple vessel parameters (vessel skeleton density, vessel diameter index, fractal dimension, and lacunarity) were compared with the tumor size in no tumor, treated tumor, and untreated tumor cases. Although each case has only one animal, we found that the vessel skeleton density (VSD), vessel diameter index and fractal dimension (FD) tended to be positively correlated with tumor size while lacunarity showed a partially negative correlation. Moreover, we observed that the changes in the VSD and FD are prior to the morphological change of the tumor. This feasibility study would be helpful in evaluating the tumor vascular response to treatment in preclinical settings.

• Korean Journal of Remote Sensing
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• v.35 no.1
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• pp.137-149
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• 2019

Traffic emissions are the main cause of environmental pollution in cities and respiratory problems amongst people. This study developed a model based on an integration of support vector regression (SVR) algorithm and geographic information system (GIS) to map traffic carbon monoxide (CO) concentrations and produce prediction maps from micro level to macro level at a particular time gap in a day in a very densely populated area (Utara-Selatan Expressway-NKVE, Kuala Lumpur, Malaysia). The proposed model comprised two models: the first model was implemented to estimate traffic CO concentrations using the SVR model, and the second model was applied to create prediction maps at different times a day using the GIS approach. The parameters for analysis were collected from field survey and remote sensing data sources such as very-high-resolution aerial photos and light detection and ranging point clouds. The correlation coefficient was 0.97, the mean absolute error was 1.401 ppm and the root mean square error was 2.45 ppm. The proposed models can be effectively implemented as decision-making tools to find a suitable solution for mitigating traffic jams near tollgates, highways and road networks.

• Advances in environmental research
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• v.9 no.4
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• pp.251-273
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• 2020

Soil degradation has become a major worldwide environmental problem, particularly in arid and semi-arid climate zones due to irregular rainfall and the intensity of storms that frequently generate heavy flooding. The main objective of this study is the use of geographic information system and remote sensing techniques to quantify and to map the soil losses in the Wadi Saida watershed (624 ㎢) through the revised universal soil loss equation model and a proposed model based on the surface erosive runoff. The results Analysis revealed that the Wadi Saida watershed showed moderate to moderately high soil loss, between 0 and 1000 t/㎢/year. In the northern part of the basin in the region of Sidi Boubkeur and the mountains of Daia; which are characterized by steep slopes, values can reach up to 3000 t/㎢/year. The two models in comparison showed a good correlation with R = 0.95 and RMSE = 0.43; the use of the erosive surface runoff parameter is effective to estimate the rate of soil loss in the watersheds. The problem of soil erosion requires serious interventions, particularly in basins with disturbances and aggressive climatic parameters. Good agricultural practices and forest preservation areas play an important role in soil conservation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.4
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• pp.1080-1099
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• 2023

Digital healthcare combined with telemedicine services in the form of convergence with digital technology and AI is developing rapidly. Digital healthcare research is being conducted on many conditions including shock. However, the causes of shock are diverse, and the treatment is very complicated, requiring a high level of medical knowledge. In this paper, we propose a shock detection method based on the correlation between shock and data extracted from hemodynamic monitoring equipment. From the various parameters expressed by this equipment, four parameters closely related to patient shock were used as the input data for a machine learning model in order to detect the shock. Using the four parameters as input data, that is, feature values, a random forest-based ensemble machine learning model was constructed. The value of the mean arterial pressure was used as the correct answer value, the so called label value, to detect the patient's shock state. The performance was then compared with the decision tree and logistic regression model using a confusion matrix. The average accuracy of the random forest model was 92.80%, which shows superior performance compared to other models. We look forward to our work playing a role in helping medical staff by making recommendations for the diagnosis and treatment of complex and difficult cases of shock.

• Fisheries and Aquatic Sciences
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• v.26 no.6
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• pp.393-405
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• 2023

The aim of this research was to enhance the flavor of visceral extracts from skipjack tuna. Flavor precursors and the optimum condition for the Maillard reaction were determined. The flavor extract was prepared from the tuna viscera using Endo/Exo Protease controlled in 3 factors; temperature, enzyme amounts and incubation time. The optimal condition for producing tuna viscera protein hydrolysate (TVPH) was 60℃, 0.5% enzyme (w/w) and 4-hour incubation time. TVPH were further processed to tuna viscera flavor enhancer (TVFE) with Maillard reaction. The Maillard reactions of TVFE were conducted with or without supplements such as xylose, yeast extract and methionine. The Maillard volatile components were analyzed with gas chromatography-mass spectrometry. Sixteen volatiles such as 2-methylpropanal, methylpyrazine, 2,5-dimethylpyrazine, dimethyl disulfide and 2-acetylthaizone were newly formed via Maillard reaction and the similarity of volatile contents from TVPH and TVFE were virtualized using Pearson's correlation integrated with heat-map and principal component analysis. To virtualize aromagram of TVPH and TVFE, odor activity value and odor impact spectrum (OIS) techniques were applied. According to OIS results, 3-methylbutanal, 2-methylbutanal, 1-octen-3-ol 2,5-dimethylpyrazine, methional and dimethyl trisulfide were the potent odorants contributed to the meaty, creamy, and toasted aroma in TVFE.

• Structural Engineering and Mechanics
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• v.89 no.5
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• pp.491-505
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• 2024

This study evaluates the seismic performance of a premodern six story reinforced concrete building typology designed during the communism period of Albania and build throughout the country. During the November 26, 2019 Earthquake in Albania, the most affected reinforced concrete buildings were among the old templates, lacking shear walls and inadequate reinforcement details which suffer from concrete aging. The mathematical model of the selected building is done in the environments of ZeusNL software, developed especially for earthquake engineering applications. The capacity curve of the structure is gained using the conventional static nonlinear analysis. On the other hand, the demand estimation is utilized using one of the recent methods known as Incremental Dynamic Analysis with a set of 18 ground motion records. The limit states in both curves are defined based on the modern guidelines. For the pushover, immediate occupancy (IO), life safety (LS) and collapse prevention (CP) are plotted in the same graph with capacity curve. Furthermore, on each IDA derived, the IO, CP and global instability (GI) are determined. Moreover, the IDA fractiles are generated as suggested by the literature, 16%, 50% (median) and 84%. In addition, the comparative assessment of the IDA median with capacity curve shows good correlation points. Lastly, this study shows the approach of determination of LS in IDA fractiles for further vulnerability assessment based on the local seismic hazard map with 95 and 475 return period.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.21 no.1
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• pp.1-10
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• 2016

Currently available surface seawater partial pressure carbon dioxide ($pCO_2$) data sets in the East Sea are not enough to quantify statistically the carbon dioxide flux through the air-sea interface. To complement the scarcity of the $pCO_2$ measurements, we construct a neural network (NN) model based on satellite data to map $pCO_2$ for the areas, which were not observed. The NN model is constructed for the Ulleung Basin, where $pCO_2$ data are best available, to map and estimate the variability of $pCO_2$ based on in situ $pCO_2$ for the years from 2003 to 2012, and the sea surface temperature (SST) and chlorophyll data from the MODIS (Moderate-resolution Imaging Spectroradiometer) sensor of the Aqua satellite along with geographic information. The NN model was trained to achieve higher than 95% of a correlation between in situ and predicted $pCO_2$ values. The RMSE (root mean square error) of the NN model output was $19.2{\mu}atm$ and much less than the variability of in situ $pCO_2$. The variability of $pCO_2$ with respect to SST and chlorophyll shows a strong negative correlation with SST than chlorophyll. As SST decreases the variability of $pCO_2$ increases. When SST is lower than $15^{\circ}C$, $pCO_2$ variability is clearly affected by both SST and chlorophyll. In contrast when SST is higher than $15^{\circ}C$, the variability of $pCO_2$ is less sensitive to changes in SST and chlorophyll. The mean rate of the annual $pCO_2$ increase estimated by the NN model output in the Ulleung Basin is $0.8{\mu}atm\;yr^{-1}$ from 2003 to 2014. As NN model can successfully map $pCO_2$ data for the whole study area with a higher resolution and less RMSE compared to the previous studies, the NN model can be a potentially useful tool for the understanding of the carbon cycle in the East Sea, where accessibility is limited by the international affairs.