• Atmosphere
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• v.27 no.4
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• pp.385-398
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• 2017

Numerical weather prediction experiments were carried out by applying topographic effects to reduce or enhance the solar radiation by terrain. In this study, x and ${\kappa}({\phi}_o,\;{\theta}_o)$ are precalculated for topographic effect on high resolution numerical weather prediction (NWP) with 1 km spatial resolution, and meteorological variables are analyzed through the numerical experiments. For the numerical simulations, cases were selected in winter (CASE 1) and summer (CASE 2). In the CASE 2, topographic effect was observed on the southward surface to enhance the solar energy reaching the surface, and enhance surface temperature and temperature at 2 m. Especially, the surface temperature is changed sensitively due to the change of the solar energy on the surface, but the change of the precipitation is difficult to match of topographic effect. As a result of the verification using Korea Meteorological Administration (KMA) Automated Weather System (AWS) data on Seoul metropolitan area, the topographic effect is very weak in the winter case. In the CASE 1, the improvement of accuracy was numerically confirmed by decreasing the bias and RMSE (Root mean square error) of temperature at 2 m, wind speed at 10 m and relative humidity. However, the accuracy of rainfall prediction (Threat score (TS), BIAS, equitable threat score (ETS)) with topographic effect is decreased compared to without topographic effect. It is analyzed that the topographic effect improves the solar radiation on surface and affect the enhancements of surface temperature, 2 meter temperature, wind speed, and PBL height.

• Korean Journal of Optics and Photonics
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• v.19 no.1
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• pp.9-14
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• 2008

In this paper, a new type of Yagi-Uda antenna that operates in the terahertz frequencies is designed. The proposed Yagi-Uda antenna can obtain high input resistance of approximately $2000{\Omega}$ at the resonance frequency by using a full-wavelength dipole instead of a half-wavelength dipole as the driver element. The current leakage into the bias line was minimized by applying the photonic bandgap structure to the bias line. By designing the antenna on a thin substrate, the impedance lowering of an antenna caused by the relative dielectric constant of the substrate was prevented and the end-fire radiation pattern which is the original radiation characteristic of the Yagi-Uda antenna could be obtained. We expect that the proposed Yagi-Uda antenna can achieve increased terahertz output power by improving the impedance mismatching problem with the photomixer.

• Atmosphere
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• v.27 no.2
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• pp.235-249
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• 2017

This paper describes methodology verifying near-surface predictability of numerical weather prediction models against the surface synoptic weather station network (SYNOP) observation. As verification variables, temperature, wind, humidity-related variables, total cloud cover, and surface pressure are included in this tool. Quality controlled SYNOP observation through the pre-processing for data assimilation is used. To consider the difference of topographic height between observation and model grid points, vertical inter/extrapolation is applied for temperature, humidity, and surface pressure verification. This verification algorithm is applied for verifying medium-range forecasts by a global forecasting model developed by Korea Institute of Atmospheric Prediction Systems to measure the near-surface predictability of the model and to evaluate the capability of the developed verification tool. It is found that the verification of near-surface prediction against SYNOP observation shows consistency with verification of upper atmosphere against global radiosonde observation, suggesting reliability of those data and demonstrating importance of verification against in-situ measurement as well. Although verifying modeled total cloud cover with observation might have limitation due to the different definition between the model and observation, it is also capable to diagnose the relative bias of model predictability such as a regional reliability and diurnal evolution of the bias.

• Proceedings of the Korean Vacuum Society Conference
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• 2010.02a
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• pp.16-17
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• 2010

Molecular spintronics has attracted attentions, which combines molecular electronics with the spin degree of freedom in electron transport. Among various molecules as candidates of the molecular spintronics, single molecule magnet (SMM) is one of the most promising material. SMM molecules show a ferromagnetic behavior even as a single molecule and hold the spin information even after the magnetic field is turned off. Here in this report, we show the spin behavior of SMM molecules adsorbed on the Au surface by combining the observation of Kondo peak in the STS and ESR-STM measurement. Kondo resonance state is formed near the Fermi level when degenerated spin state interacts with conduction electrons. ESR-STM detects the Larmor frequency of the spin in the presence of a magnet field. The sample include $MPc_2$ and $M_2Pc_3$ molecules ($M\;=\;Tb^{3+}$, $Dy^{3+}$, and $Y^{3+}$ Pc=phthalocyanine) whose critical temperature as a ferromagnet reaches 40 K. A clear Kondo peak was observed which is originated from an unpaired electron in the ligand of the molecule, which is the first demonstration of the Kondo peak originated from electron observed in the STS measurement. We also observed corresponding peaks in ESR-STM spectra. [1] In addition we found that the Kondo peak intensity shows a clear variation with the conformational change of the molecule; namely the azimuthal rotational angle of the Pc planes. This indicates that the Kondo resonance is correlated with the molecule electronic state. We examined this phenomena by using STM manipulation technique, where pulse bias application can rotate the relative azimuthal angle of the Pc planes. The result indicates that an application of ~1V pulse to the bias voltage can rotate the Pc plane and the Kondo peaks shows a clear variation in intensity by the molecule's conformational change.

• Journal of the Korean Solar Energy Society
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• v.39 no.2
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• pp.71-80
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• 2019

Daily ahead forecast is necessary for the electricity balance between load and supply due to the variability renewable energy. Numerical weather prediction is usually employed to produce the solar irradiance as well as electric power forecast for more than 12 hours forecast horizon. UM-LDAPS model is the numerical weather prediction operated by Korea Meteorological Administration and it generates the 36 hours forecast of hourly total irradiance 4 times a day. This study attempts to evaluate the model performance against the in situ measurements at 37 ground stations from January to May, 2013. Relative mean bias error, mean absolute error and root mean square error of hourly total irradiance are averaged over all ground stations as being 8.2%, 21.2% and 29.6%, respectively. The behavior of mean bias error appears to be different; positively largest in Chupoongnyeong station but negatively largest in Daegu station. The distinct contrast might be attributed to the limitation of microphysics parameterization for thick and thin clouds in the model.

• The Journal of Churna Manual Medicine for Spine and Nerves
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• v.19 no.1
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• pp.73-82
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• 2024

Objectives This study aims to evaluate the effectiveness of cervical chuna manipulative treatment (CCMT) in patients with peripheral facial paralysis (PFP). Methods We conducted a comprehensive search of MEDLINE, CENTRAL, EMBASE, KMbase, OASIS and ScienceOn, and CNKI for randomized controlled trials (RCTs) comparing CCMT for PFP up to April 25, 2024. Risk of Bias was assessed using the Cochrane RoB tool. Results Among the 462 studies retrieved, 5 RCTs with a total of 340 patients were included in the systematic review. Of these, 4 RCTs that reported the total effectiveness rate as the primary outcome were included in the meta-analysis. CCMT combined with acupuncture showed significant improvement in total effectiveness rate compared to acupuncture alone (Relative Ratio [RR] 1.14, 95% CI 1.04 to 1.26, I²=49, P<0.008). However, the included studies had some limitations including uncertain risk of bias and short follow-up periods. Conclusions CCMT may be an effective treatment for PFP. Due to the low quality of evidence from the included studies, high-quality, well-designed RCTs are needed to further verify the effectiveness and safety of CCMT.

• Information Systems Review
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• v.20 no.3
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• pp.51-71
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• 2018

Many studies in the field of information security reveal the need to increase awareness. However, although awareness of information security has been raised to a considerable extent, actual security behavior has been shown to fall short of that. Therefore, we wanted to identify the role of psychological factors in making information security decisions by conducting a experimental study. The results show that there are differences in perception of information security risks according to the probabilistic distance and the degree of relative optimism due to social distance. In relation to their relative optimism and intention of information security, they reduced the level of perceived risk compared to those close to them and found that their influence varied according to their probabilistic distance. This study has made valuable attempt in terms of methodology and it is meaningful that the psychological factor is taken into consideration for the information protection behavior, so that the range of relative optimism that actually affects the perception of risk is narrowed. It is expected to contribute to the improvement of information security level of information technology users and protection of information assets by empirically identifying necessity of various approaches to decision making process for information security.

• Journal of Korea Water Resources Association
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• v.51 no.5
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• pp.439-449
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• 2018

Many potential sources of bias are used in several steps of the radar-rainfall estimation process because the hydrological and meteorological radars measure the rainfall amount indirectly. Previous studies on radar-rainfall uncertainties were performed to reduce the uncertainty of each step by using bias correction methods in the quantitative radar-rainfall estimation process. However, these studies do not provide comprehensive uncertainty for the entire process and the relative ratios of uncertainty between each step. Consequently, in this study, a suitable approach is proposed that can quantify the uncertainties at each step of the quantitative radar-rainfall estimation process and show the uncertainty propagation through the entire process. First, it is proposed that, in the suitable approach, the new concept can present the initial and final uncertainties, variation of the uncertainty as well as the relative ratio of uncertainty at each step. Second, the Maximum Entropy Method (MEM) and Uncertainty Delta Method (UDM) were applied to quantify the uncertainty and analyze the uncertainty propagation for the entire process. Third, for the uncertainty quantification of radar-rainfall estimation at each step, two quality control algorithms, two radar-rainfall estimation relations, and two bias correction methods as post-processing through the radar-rainfall estimation process in 18 rainfall cases in 2012. For the proposed approach, in the MEM results, the final uncertainty (from post-processing bias correction method step: ME = 3.81) was smaller than the initial uncertainty (from quality control step: ME = 4.28) and, in the UDM results, the initial uncertainty (UDM = 5.33) was greater than the final uncertainty (UDM = 4.75). However uncertainty of the radar-rainfall estimation step was greater because of the use of an unsuitable relation. Furthermore, it was also determined in this study that selecting the appropriate method for each stage would gradually reduce the uncertainty at each step. Therefore, the results indicate that this new approach can significantly quantify uncertainty in the radar-rainfall estimation process and contribute to more accurate estimates of radar rainfall.

• Nuclear Engineering and Technology
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• v.52 no.10
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• pp.2379-2386
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• 2020

This paper presents the results of the first intercomparison exercise performed by the Korea retrospective dosimetry (KREDOS) working group using electron paramagnetic resonance (EPR) spectroscopy. The intercomparison employed the alanine dosimeter, which is commonly used as the standard dosimeter in EPR methods. Four laboratories participated in the dose assessment of blind samples, and one laboratory carried out irradiation of blind samples. Two types of alanine dosimeters (Bruker and Magnettech) with different geometries were used. Both dosimeters were blindly irradiated at three dose levels (0.60, 2.70, and 8.00 Gy) and four samples per dose were distributed to the participating laboratories. Assessments of blind doses by the laboratories were performed using their own measurement protocols. One laboratory did not participate in the measurements of Magnettech alanine dosimeter samples. Intercomparison results were analyzed by calculating the relative bias, E_n value, and z-score. The results reported by participating laboratories were overall satisfactory for doses of 2.70 and 8.00 Gy but were considerably overestimated with a relative bias range of 10-95% for 0.60 Gy, which is lower than the minimum detectable dose (MDD) of the alanine dosimeter. After the first intercomparison, participating laboratories are working to improve their alanine-EPR dosimetry systems through continuous meetings and are preparing a second intercomparison exercise for other materials.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1141-1141
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• 2001

The aim of the study was to evaluate the performance of 3 calibration methods, modified partial least squares (MPLS), local PLS (LOCAL) and artificial neural network (ANN) on the prediction of chemical composition of forages, using a large NIR database. The study used forage samples (n=25,977) from Australia, Europe (Belgium, Germany, Italy and Sweden) and North America (Canada and U.S.A) with information relative to moisture, crude protein and neutral detergent fibre content. The spectra of the samples were collected with 10 different Foss NIR Systems instruments, which were either standardized or not standardized to one master instrument. The spectra were trimmed to a wavelength range between 1100 and 2498 nm. Two data sets, one standardized (IVAL) and the other not standardized (SVAL) were used as independent validation sets, but 10% of both sets were omitted and kept for later expansion of the calibration database. The remaining samples were combined into one database (n=21,696), which was split into 75% calibration (CALBASE) and 25% validation (VALBASE). The chemical components in the 3 validation data sets were predicted with each model derived from CALBASE using the calibration database before and after it was expanded with 10% of the samples from IVAL and SVAL data sets. Calibration performance was evaluated using standard error of prediction corrected for bias (SEP(C)), bias, slope and R2. None of the models appeared to be consistently better across all validation sets. VALBASE was predicted well by all models, with smaller SEP(C) and bias values than for IVAL and SVAL. This was not surprising as VALBASE was selected from the calibration database and it had a sample population similar to CALBASE, whereas IVAL and SVAL were completely independent validation sets. In most cases, Local and ANN models, but not modified PLS, showed considerable improvement in the prediction of IVAL and SVAL after the calibration database had been expanded with the 10% samples of IVAL and SVAL reserved for calibration expansion. The effects of sample processing, instrument standardization and differences in reference procedure were partially confounded in the validation sets, so it was not possible to determine which factors were most important. Further work on the development of large databases must address the problems of standardization of instruments, harmonization and standardization of laboratory procedures and even more importantly, the definition of the database population.