• Atmosphere
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• v.29 no.1
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• pp.105-112
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• 2019

Measurements of vertical air motion and microphysics are essential for improving our understanding of convective clouds. In this paper, the author reviews the current research on the retrieval of vertical air motions using the cloud radar. At radar wavelengths of 3 mm (W-band radar; 94-GHz radar; cloud radar), the raindrop backscattering cross-section (${\sigma}b$) varies between successive maxima and minima as a function of the raindrop diameter (D) that are well described by Mie theory. The first Mie minimum in the backscattering cross-section occurs at D~1.68 mm, which translates to a raindrop terminal fall velocity of ${\sim}5.85m\;s^{-1}$ based on the Gunn and Kinzer relationship. Since raindrop diameters often exceed this size, the signal is captured in the radar Doppler spectrum, and thus, the location of the first Mie minimum can be used as a reference for retrieving the vertical air motion. The Mie technique is applied to radar Doppler spectra from the surface-based and airborne, upward pointing W-band radars. The contributions of aircraft motion to the vertical air motion are also described and further the first-order aircraft motion corrected equation is presented. The review also shows that the separate spectral peaks due to the cloud droplets can provide independent validation of the Mie technique retrieved vertical air motion using the cloud droplets as a tracer of vertical air motion.

• Yonsei Medical Journal
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• v.59 no.9
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• pp.1138-1142
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• 2018

This study aimed to analyze the impact of sleep deprivation (SD) on cardiac, hemodynamic, and endothelial parameters and to determine whether these are sustained with increased periods of SD. The study included 60 healthy men (mean: age $31.2{\pm}6.3years$; body mass index $24.6{\pm}2.6kg/m^2$). Hemodynamic parameters, parameters of myocardial contractility, spectral analysis of heart rate (HR) and blood pressure (BP) variability, and the sensitivity of arterial baroreflex function were evaluated. Biochemical tests were performed to assess L-arginine (L-Arg) and asymmetric dimethylarginine (ADMA) levels in reflection of endothelial nitric oxide synthase ability. Measurements of cardiovascular system parameters were obtained at 9 a.m. (baseline) on the first day of the study and 9 a.m. (24-h SD), 1 p.m. (28-h SD), and 5 p.m. (32-h SD) on the second day. Blood samples for evaluating biochemical parameters were obtained at baseline and after 24-h SD. ANOVA Friedman's test revealed a significant effect for time in relation to HR (${\chi}^2=26.04$, df=5, p=0.000), systolic BP (${\chi}^2=35.98$, df=5, p=0.000), diastolic BP (${\chi}^2=18.01$, df=5, p=0.003), and mean BP (${\chi}^2=28.32$, df=5, p=0.000). L-Arg and ADMA levels changed from $78.2{\pm}12.9$ and $0.3{\pm}0.1$ at baseline to $68.8{\pm}10.2$ and $0.4{\pm}0.1$ after 24-hr SD, respectively (p=0.001, p=0.004). SD in healthy men is associated with increases in BP, which appear to occur after 24 hours of SD and are maintained over increasing periods of SD. The observed hemodynamic changes may have resulted due to disordered vascular endothelial function, as reflected in alterations in L-Arg and ADMA levels.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.4
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• pp.245-257
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• 2023

The representative crop in the Republic of Korea, rice, is cultivated over extensive areas every year, which resulting in reduced resistance to pests and diseases. One of the major rice diseases, rice blast disease, can lead to a significant decrease in yields when it occurs on a large scale, necessitating early detection and effective control of rice blast disease. Drone-based crop monitoring techniques are valuable for detecting abnormal growth, but frequent image capture for potential rice blast disease occurrences can consume significant labor and resources. The purpose of this study is to early detect rice blast disease using remote sensing data, such as drone and satellite images, along with weather data. Satellite images was helpful in identifying rice cultivation fields. Effective detection of paddy fields was achieved by utilizing vegetation and water indices. Subsequently, air temperature, relative humidity, and number of rainy days were used to calculate the risk of rice blast disease occurrence. An increase in the risk of disease occurrence implies a higher likelihood of disease development, and drone measurements perform at this time. Spectral reflectance changes in the red and near-infrared wavelength regions were observed at the locations where rice blast disease occurred. Clusters with low vegetation index values were observed at locations where rice blast disease occurred, and the time series data for drone images allowed for tracking the spread of the disease from these points. Finally, drone images captured before harvesting was used to generate spatial information on the incidence of rice blast disease in each field.

• Nuclear Engineering and Technology
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• v.55 no.10
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• pp.3913-3923
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• 2023

Todays, medium energy resolution detectors are preferably used in radioisotope identification devices(RID) in nuclear and radioactive material categorization. However, there is still a need to develop or enhance « automated identifiers » for the useful RID algorithms. To decide whether any material is SNM or NORM, a key parameter is the better energy resolution of the detector. Although masking, shielding and gain shift/stabilization and other affecting parameters on site are also important for successful operations, the suitability of the RID algorithm is also a critical point to enhance the identification reliability while extracting the features from the spectral analysis. In this study, a RID algorithm based on Bayesian statistical method has been modified for medium energy resolution detectors and applied to the uranium gamma-ray spectra taken by a LaBr3:Ce detector. The present Bayesian RID algorithm covers up to 2000 keV energy range. It uses the peak centroids, the peak areas from the measured gamma-ray spectra. The extraction features are derived from the peak-based Bayesian classifiers to estimate a posterior probability for each isotope in the ANSI library. The program operations were tested under a MATLAB platform. The present peak based Bayesian RID algorithm was validated by using single isotopes(²⁴¹Am, ⁵⁷Co, ¹³⁷Cs, ⁵⁴Mn, ⁶⁰Co), and then applied to five standard nuclear materials(0.32-4.51% at.²³⁵U), as well as natural U- and Th-ores. The ID performance of the RID algorithm was quantified in terms of F-score for each isotope. The posterior probability is calculated to be 54.5-74.4% for ²³⁸U and 4.7-10.5% for ²³⁵U in EC-NRM171 uranium materials. For the case of the more complex gamma-ray spectra from CRMs, the total scoring (ST) method was preferred for its ID performance evaluation. It was shown that the present peak based Bayesian RID algorithm can be applied to identify ²³⁵U and ²³⁸U isotopes in LEU or natural U-Th samples if a medium energy resolution detector is was in the measurements.

• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1427-1435
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• 2023

Vegetation indices based on selected wavelength reflectance measurements are used to represent crop growth and physiological conditions. However, the anisotropic properties of the crop canopy surface can govern spectral reflectance and vegetation indices. In this study, we applied an ensemble of bidirectional reflectance distribution function (BRDF) models to high-resolution Sentinel-2 satellite imagery and compared the differences between correction results before and after reflectance. In the red and near-infrared (NIR) band reflectance images, BRDF-corrected outlier values appeared in certain urban and paddy fields of farmland areas and forest shadow areas. These effects were equally observed when calculating the normalized difference vegetation index (NDVI) and 2-band enhanced vegetation index (EVI2). Furthermore, the outlier values in corrected NIR band were shown in pixels shadowed by mountain terrain. These results are expected to contribute to the development and improvement of BRDF models in high-resolution satellite images.

• Korean Journal of Remote Sensing
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• v.40 no.4
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• pp.319-341
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• 2024

The utilization of multispectral imaging systems (MIS) in remote sensing has become crucial for large-scale agricultural operations, particularly for diagnosing plant health, monitoring crop growth, and estimating plant phenotypic traits through vegetation indices (VIs). However, environmental factors can significantly affect the accuracy of multispectral reflectance data, leading to potential errors in VIs and crop status assessments. This paper reviewed the complex interactions between environmental conditions and multispectral sensors emphasizing the importance of accounting for these factors to enhance the reliability of reflectance data in agricultural applications.An overview of the fundamentals of multispectral sensors and the operational principles behind vegetation index (VI) computation was reviewed. The review highlights the impact of environmental conditions, particularly solar zenith angle (SZA), on reflectance data quality. Higher SZA values increase cloud optical thickness and droplet concentration by 40-70%, affecting reflectance in the red (-0.01 to 0.02) and near-infrared (NIR) bands (-0.03 to 0.06), crucial for VI accuracy. An SZA of 45° is optimal for data collection, while atmospheric conditions, such as water vapor and aerosols, greatly influence reflectance data, affecting forest biomass estimates and agricultural assessments. During the COVID-19 lockdown,reduced atmospheric interference improved the accuracy of satellite image reflectance consistency. The NIR/Red edge ratio and water index emerged as the most stable indices, providing consistent measurements across different lighting conditions. Additionally, a simulated environment demonstrated that MIS surface reflectance can vary 10-20% with changes in aerosol optical thickness, 15-30% with water vapor levels, and up to 25% in NIR reflectance due to high wind speeds. Seasonal factors like temperature and humidity can cause up to a 15% change, highlighting the complexity of environmental impacts on remote sensing data. This review indicated the importance of precisely managing environmental factors to maintain the integrity of VIs calculations. Explaining the relationship between environmental variables and multispectral sensors offers valuable insights for optimizing the accuracy and reliability of remote sensing data in various agricultural applications.

• Journal of Korean Society of Environmental Engineers
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• v.29 no.3
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• pp.317-324
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• 2007

Fluorescence measurements of dissolved organic matter(DOM) have the superior advantages over other analysis tools for applying to water quality management. A preliminary study was conducted to test the feasibility of applying synchronous fluorescence measurements for tracing and monitoring pollution sources in a small stream located in an upstream area of the Sooyoung watershed in Busan. The water quality of the small stream is affected by leachate from sawdust pile and discharge of untreated sewage. The sampling sites included an upstream site, two pipes discharging untreated sewage, leachate from sawdust, and a downstream site. Of the five field samples, the leachate was distinguished from the other samples by a high peak at a lower wavelength range and a blunt peak at 350nm, suggesting that synchronous fluorescence can be used as a discrimination tool for monitoring the pollution. The efficacy of various indices derived from the spectral features to discriminate the pollution source was tested for well-defined mixture of the sawdust leachate and the upstream stream by comparing (1)the difference between measured values and those predicted based on mass balance and the characteristics of the two samples and (2)the linear correlations between index values and mass ratios of the sample mixtures. Of various discrimination indices selected, fluorescence intensities at 276 nm$({\Delta}\lambda=30nm)$and 347 nm$({\Delta}\lambda=60nm)$ were suggested as promising potential discrimination indices for the sawdust pollution source. Despite the limited number of samples and the study area, this study illustrates the evaluation process that should be followed to develop rapid, low-cost discrimination indices to monitor pollution sources based on end member mixing analyses.

• Korean Journal of Optics and Photonics
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• v.27 no.1
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• pp.18-24
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• 2016

To effectively utilize a flash and predict its effects on an infrared device, it is essential to know the infrared characteristics of the flash source. In this paper, a study of the IR characteristics of flash light sources is carried out. The IR characteristics of three flash sources, of which two are combustive and the other is explosive, are measured with an IR characteristic measurement system over the middle- and long-wavelength infrared ranges. From the measurements, the radiances over the two IR ranges and the radiative temperatures of the flashes are extracted. The IR radiance of flash A is found to be the strongest among the three, followed by those of sources C and B. It is also shown that the IR radiance of flash A is about 10 times stronger than that of flash B, even though these two sources are the same type of flash with the same powder. This means that the IR radiance intensity of a combustive flash source depends only on the amount of powder, not on the characteristics of the powder. From the measured radiance over MWIR and LWIR ranges for each flashes, the radiative temperatures of the flashes are extracted by fitting the measured data to blackbody radiance. The best-fit radiative temperatures (equivalent to black-body temperatures) of the three flash sources A, B, and C are 3300, 1120, and 1640 K respectively. From the radiance measurements and radiative temperatures of the three flash sources, it is shown that a combustive source radiates more IR energy than an explosive one; this mean, in turn, that the effects of a combustive flash on an IR device are more profound than those of an explosive flash source. The measured IR radiances and radiative temperatures of the flash sources in this study can be used to estimate the effects of flashes on various IR devices, and play a critical role for the modeling and simulation of the effects of a flash source on various IR devices.

• Journal of Korean Society of Environmental Engineers
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• v.27 no.3
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• pp.253-261
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• 2005

Catalytic wet oxidation of ppm levels of trichloroethylene (TCE) in water has been conducted using $TiO_2$-supported cobalt oxides at a given temperature and weight hourly space velocity. 5% $CoO_x/TiO_2$ might be the most promising catalyst for the wet oxidation at $36^{\circ}C$ although it exhibited a transient behavior in time on-stream activity. Not only could the bare support be inactive for the wet decomposition reaction, but no TCE removal also occurred by the process of adsorption on $TiO_2$ surface. The catalytic activity was independent of all particle sizes used, thereby representing no mass transfer limitation in intraparticle diffusion. Characterization of the $CoO_x$ catalyst by acquiring XPS spectra of both fresh and used Co surfaces gave different surface spectral features of each $CoO_x$. Co $2p_{3/2}$ binding energy of Co species exposed predominantly onto the outermost surface of the fresh catalyst appeared at 781.3 eV, which is very similar to the chemical states of $CoTiO_x$ such as $Co_2TiO_4$ and $CoTiO_3$. The spent catalyst possessed a 780.3 eV main peak with a satellite structure at 795.8 eV. Based on XPS spectra of reference Co compound, the TCE-exposed Co surfaces could be assigned to be in the form of mainly $Co_3O_4$. XRD measurements indicated that the phase structure of Co species in 5% $CoO_x/TiO_2$ catalyst even before reaction is quite comparable to the diffraction lines of external $Co_3O_4$ standard. A model structure of $CoO_x$ present on titania surfaces would be $Co_3O_4$, encapsulated in thin-film $CoTiO_x$ species consisting of $Co_2TiO_4$ and $CoTiO_3$, which may be active for the decomposition of TCE in a flow of water.

• Korean Journal of Soil Science and Fertilizer
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• v.42 no.2
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• pp.79-87
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• 2009

Pot experiments using sand culture were conducted in 2004 under greenhouse conditions to evaluate the effect of nitrogen deficiency on red pepper biomass. Nitrogen stress was imposed by implementing 6 levels (40% to 140%) of N in Hoagland's nutrient solution for red pepper. Canopy reflectance measurements were made with hand held spectral sensors including $GreenSeeker^{TM}$, $Crop\;Circle^{TM}$, and $Field\;Scout^{TM}$ Chlorophyll meter, and a spectroradiometer as well as Minolta SPAD-502 chlorophyll meter. Canopy reflectance and dry weight of red pepper were measured at five growth stages, the 30th, 40th, 50th, 80th and 120th day after planting(DAT). Dry weight of red pepper affected by nitrogen stress showed large differences between maximum and minimum values at the 120th DAT ranged from 48.2 to $196.6g\;plant^{-1}$, respectively. Several reflectance indices obtained from $GreenSeeker^{TM}$, $Crop\;Circle^{TM}$ and Spectroradiometer including chlorophyll readings were compared for evaluation of red pepper biomass. The reflectance indices such as rNDVI, aNDVI and gNDVI by the $Crop\;Circle^{TM}$ sensor showed the highest correlation coefficient with dry weight of red pepper at the 40th, 50th, and 80th DAT, respectively. Also these reflectance indices at the same growth station was closely correlated with dry weight, yield, and nitrogen uptake of red pepper at the 120th DAT, especially showing the best correlation coefficient at the 80th DAT. From these result, the aNDVI at the 80th DAT can significantly explain for dry weight of red pepper at the 120th DAT as well as for application level of nitrogen fertilizer. Consequently ground remote sensing as a non-destructive real-time assessment of plant nitrogen status was thought to be a useful tool for in season nitrogen management for red pepper providing both spatial and temporal information.