• Journal of the Korean Geographical Society
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• v.49 no.6
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• pp.833-848
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• 2014

The assessment of the current and future climate change-induced potential wind energy is an important issue in the planning and operations of wind farm. Here, the authors analyze spatiotemporal characteristics and variabilities of wind energy over Korean Peninsula in the near future (2006-2040) using Representative Concentration Pathway(RCP) scenarios data. In this study, National Institute of Meteorological Research (NIMR) regional climate model HadGEM3-RA based RCP 2.6 and 8.5 scenarios are analyzed. The comparison between ERA-interim and HadGEM3-RA during the period of 1981-2005 indicates that the historical simulation of HadGEM3-RA slightly overestimates (underestimates) the wind energy over the land (ocean). It also shows that interannual and intraseasonal variability of hindcast data is generally larger than those of reanalysis data. The investigation of RCP scenarios based future wind energy presents that future wind energy density will increase over the land and decrease over the ocean. The increase in the wind energy and its variability is particularly significant over the mountains and coastal areas, such as Jeju island in future global warming. More detailed analysis presents that the changes in synoptic conditions over East Asia in future decades can influence on the predicted wind energy abovementioned. It is also suggested that the uncertainty of the predicted future wind energy may increase because of the increase of interannual and intra-annual variability. In conclusion, our results can be used as a background data for devising a plan to develop and operate wind farm over the Korean Peninsula.

• Diabetes and Metabolism Journal
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• v.42 no.6
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• pp.496-512
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• 2018

Background: This study aimed to investigate the association between the presence and severity of cardiovascular autonomic neuropathy (CAN) and development of long-term glucose fluctuation in subjects with type 2 diabetes mellitus. Methods: In this retrospective cohort study, subjects with type 2 diabetes mellitus who received cardiovascular autonomic reflex tests (CARTs) at baseline and at least 4-year of follow-up with ${\geq}6$ measures of glycosylated hemoglobin (HbA1c) were included. The severity of CAN was categorized as normal, early, or severe CAN according to the CARTs score. HbA1c variability was measured as the standard deviation (SD), coefficient of variation, and adjusted SD of serial HbA1c measurements. Results: A total of 681 subjects were analyzed (294 normal, 318 early, and 69 severe CAN). The HbA1c variability index values showed a positive relationship with the severity of CAN. Multivariable logistic regression analysis showed that CAN was significantly associated with the risk of developing higher HbA1c variability (SD) after adjusting for age, sex, body mass index, diabetes duration, mean HbA1c, heart rate, glomerular filtration rate, diabetic retinopathy, coronary artery disease, insulin use, and anti-hypertensive medication (early CAN: odds ratio [OR], 1.65; 95% confidence interval [CI], 1.12 to 2.43) (severe CAN: OR, 2.86; 95% CI, 1.47 to 5.56). This association was more prominent in subjects who had a longer duration of diabetes (>10 years) and lower mean HbA1c (<7%). Conclusion: CAN is an independent risk factor for future higher HbA1c variability in subjects with type 2 diabetes mellitus. Tailored therapy for stabilizing glucose fluctuation should be emphasized in subjects with CAN.

• The Korean Journal of Nuclear Medicine Technology
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• v.23 no.2
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• pp.29-37
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• 2019

Purpose DMIDR(Discovery Molecular Imaging Digital Ready, General Electric Healthcare, USA) is a PET/CT scanner designed to allow application of PSF(Point Spread Function), TOF(Time of Flight) and Q.Clear algorithm. Especially, Q.Clear is a reconstruction algorithm which can overcome the limitation of OSEM(Ordered Subset Expectation Maximization) and reduce the image noise based on voxel unit. The aim of this paper is to evaluate the performance of reconstruction algorithms and optimize the algorithm combination to improve the accurate SUV(Standardized Uptake Value) measurement and lesion detectability. Materials and Methods PET phantom was filled with $^{18}F-FDG$ radioactivity concentration ratio of hot to background was in a ratio of 2:1, 4:1 and 8:1. Scan was performed using the NEMA protocols. Scan data was reconstructed using combination of (1)VPFX(VUE point FX(TOF)), (2)VPHD-S(VUE Point HD+PSF), (3)VPFX-S (TOF+PSF), (4)QCHD-S-400((VUE Point HD+Q.Clear(${\beta}-strength$ 400)+PSF), (5)QCFX-S-400(TOF +Q.Clear(${\beta}-strength$ 400)+PSF), (6)QCHD-S-50(VUE Point HD+Q.Clear(${\beta}-strength$ 50)+PSF) and (7)QCFX-S-50(TOF+Q.Clear(${\beta}-strength$ 50)+PSF). CR(Contrast Recovery) and BV(Background Variability) were compared. Also, SNR(Signal to Noise Ratio) and RC(Recovery Coefficient) of counts and SUV were compared respectively. Results VPFX-S showed the highest CR value in sphere size of 10 and 13 mm, and QCFX-S-50 showed the highest value in spheres greater than 17 mm. In comparison of BV and SNR, QCFX-S-400 and QCHD-S-400 showed good results. The results of SUV measurement were proportional to the H/B ratio. RC for SUV is in inverse proportion to the H/B ratio and QCFX-S-50 showed highest value. In addition, reconstruction algorithm of Q.Clear using 400 of ${\beta}-strength$ showed lower value. Conclusion When higher ${\beta}-strength$ was applied Q.Clear showed better image quality by reducing the noise. On the contrary, lower ${\beta}-strength$ was applied Q.Clear showed that sharpness increase and PVE(Partial Volume Effect) decrease, so it is possible to measure SUV based on high RC comparing to conventional reconstruction conditions. An appropriate choice of these reconstruction algorithm can improve the accuracy and lesion detectability. In this reason, it is necessary to optimize the algorithm parameter according to the purpose.

• Atmosphere
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• v.18 no.3
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• pp.225-235
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• 2008

Sulfur hexafluoride ($SF_6$), man-made compound, has been paid attention as a potent greenhouse gas. After Kyoto Pototcol on Climate Change in 1997, nations established the policy aimed at minimizing release of $SF_6$ to atmosphere. We have developed and operated an automatic analytical system for monitoring atmospheric $SF_6$ using gas chromatography with electron capture detector (GC-ECD) and packed separate-column. Here, we report and discuss 4-month record of atmospheric $SF_6$ concentrations monitored at Seoul National University (SNU) pilot station near the Kwanak Mountain, Seoul. Most of observed $SF_6$ concentrations were excessively high compared with Northern Hemisphere (NH) background trend obtained from National Oceanic and Atmospheric Administration (NOAA) Earth System Research Laboratory (ESRL) monitoring stations. And the observed $SF_6$ showed extremely wide variability ranging from 4.6 pptv to $1.1{\times}10^3$ pptv, which may be affected by local sources placed nearby. Simultaneous wind data with $SF_6$ measurements show that relatively high values of $SF_6$ correspond to weak wind as well as southerly. There are many engineering installations to the south of the station. The regional value of the atmospheric $SF_6$ estimated from the data selection by wind conditions is about 6.8 pptv. This value, which is similar to concentrations of urban areas, is higher than NH background concentration.

• Journal of the Ergonomics Society of Korea
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• v.35 no.5
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• pp.371-381
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• 2016

Objective:This study aims to evaluate the features of heart rate variability (HRV) and respiratory signals as indices for a driver's drowsiness and waking status in order to develop the classification model for a driver's drowsiness and waking status using those features. Background: Driver's drowsiness is one of the major causal factors for traffic accidents. This study hypothesized that the application of combined bio-signals to monitor the alertness level of drivers would improve the effectiveness of the classification techniques of driver's drowsiness. Method: The features of three heart rate variability (HRV) measurements including low frequency (LF), high frequency (HF), and LF/HF ratio and two respiratory measurements including peak and rate were acquired by the monotonous car driving simulation experiments using the photoplethysmogram (PPG) and respiration sensors. The experiments were repeated a total of 50 times on five healthy male participants in their 20s to 50s. The classification model was developed by selecting the optimal measurements, applying a binary logistic regression method and performing 3-fold cross validation. Results: The power of LF, HF, and LF/HF ratio, and the respiration peak of drowsiness status were reduced by 38%, 22%, 31%, and 7%, compared to those of waking status, while respiration rate was increased by 3%. The classification sensitivity of the model using both HRV and respiratory features (91.4%) was improved, compared to that of the model using only HRV feature (89.8%) and that using only respiratory feature (83.6%). Conclusion: This study suggests that the classification of driver's drowsiness and waking status may be improved by utilizing a combination of HRV and respiratory features. Application: The results of this study can be applied to the development of driver's drowsiness prevention systems.

• Journal of Korean Society for Atmospheric Environment
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• v.33 no.2
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• pp.174-183
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• 2017

The background level and timely variation characteristics of atmospheric $^{222}Rn$ concentrations have been evaluated by the real time monitoring at Gosan site of Jeju Island, Korea, during 2008~2015. The average concentration of atmospheric radon was $2,480mBq\;m^{-3}$ for the study period. The cyclic seasonality of radon was characterized such as winter maximum and summer minimum, consistent with the reduction in terrestrial fetch going to summer. On monthly variations of radon, the mean concentration in October was the highest as $3,041mBq\;m^{-3}$, almost twice as that in July ($1,481mBq\;m^{-3}$). The diurnal radon concentrations increased throughout the nighttime approaching to the maximum ($2,819mBq\;m^{-3}$) at around 7 a.m., and then gradually decreased throughout the daytime by the minimum ($2,069mBq\;m^{-3}$) at around 3 p.m. The diurnal radon cycle in winter showed comparatively small amplitude due to little variability in atmospheric mixing depth, conversely, large amplitude was observed in summer due to relatively a big change in atmospheric mixing depth. The cluster back-trajectories of air masses showed that the high radon events occurred by the predominant continental fetch over through Asia continent, and the radon concentrations from China continent were about 1.9 times higher on the whole than those from the North Pacific Ocean. The concentrations of $PM_{10}$ also increased in proportion to the high radon concentrations, showing a good linear correlation between $PM_{10}$ and radon concentrations.

• Korean Journal of Remote Sensing
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• v.31 no.6
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• pp.583-598
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• 2015

This paper presents derivation of background temperature from geostationary satellite and its validation based on ground measurements and Geographic Information System (GIS) for future use in weather and surface heat variability. This study only focuses on daily and monthly brightness temperature in 2012. From the analysis of COMS Meteorological Data Processing System (CMDPS) data, we have found an error in cloud distribution of model, which used as a background temperature field, and in examining the spatial homogeneity. Excessive cloudy pixels were reconstructed by statistical reanalysis based on consistency of temperature measurement. The derived Brightness temperature has correlation of 0.95, bias of 0.66 K and RMSE of 4.88 K with ground station measurements. The relation between brightness temperature and both elevation and vegetated land cover were highly anti-correlated during warm season and daytime, but marginally correlated during cold season and nighttime. This result suggests that time varying emissivity data is required to derive land surface temperature.

• The Journal of the Acoustical Society of Korea
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• v.21 no.1E
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• pp.3-11
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• 2002

Broadcast news transcription is one of the hardest tasks in speech recognition because broadcast speech signals have much variability in speech quality, channel and background conditions. We developed a Korean broadcast news speech recognizer. We used a morpheme-based dictionary and a language model to reduce the out-of·vocabulary (OOV) rate. We concatenated the original morpheme pairs of short length or high frequency in order to reduce insertion and deletion errors due to short morphemes. We used a lexicon with multiple pronunciations to reflect inter-morpheme pronunciation variations without severe modification of the search tree. By using the merged morpheme as recognition units, we achieved the OOV rate of 1.7% comparable to European languages with 64k vocabulary. We implemented a hidden Markov model-based recognizer with vocal tract length normalization and online speaker adaptation by maximum likelihood linear regression. Experimental results showed that the recognizer yielded 21.8% morpheme error rate for anchor speech and 31.6% for mostly noisy reporter speech.

• Language and Information
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• v.4 no.1
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• pp.21-42
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• 2000

In this paper, I explore the semantic interpretation of the English present perfect by arguing that the perfect is analogous to modals in its interpretation. The perfect produces several different readings, i.e., the resultative and the current relevant reading, to mention a few. Despite this, the meaning of the perfect remains invariable in sentences where it occurs. Instead, the semantic variability of the perfect is due to the nature of the conversational background. This indicates that just as modals are context-dependent, so is the perfect, which inspires a modal-based approach to the semantics of the perfect. By incorporating such an approach into its semantic analysis, we can present a unified account of the different meanings of the perfect.

• Proceedings of the IEEK Conference
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• 2003.11b
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• pp.195-198
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• 2003

The accuracy of automatic speech recognition system depends on the presence of background noise and speaker variability such as sex, intonation of speech, and speaking rate. Specially, the speaking rate of both inter-speaker and intra-speaker is a serious cause of mis-recognition. In this paper, we propose the compensation method of the speaking rate by the ratio of each vowel's length in a phrase. First the number of feature vectors in a phrase is estimated by the information of speaking rate. Second, the estimated number of feature vectors is assigned to each syllable of the phrase according to the ratio of its vowel length. Finally, the process of feature vector extraction is operated by the number that assigned to each syllable in the phrase. As a result the accuracy of automatic speech recognition was improved using the proposed compensation method of the speaking rate.