• Journal of Korean Society for Atmospheric Environment
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• v.28 no.1
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• pp.94-104
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• 2012

The purpose of this research is to quantify the compliance of on-road emission from a light duty diesel vehicle, based on a comparison to emission regulation standard. $NO_x$, CO and THC emissions were measured using a portable device on a selected real-world driving route with a length of approximately 22 km. On-road measurements were repeated by 10 times on a same route to reflect variability in traffic conditions. A test route was divided into 22 road links with length of 1 km to analyze emission results with higher spatial resolution. The average emissions of $NO_x$, CO and THC over total travel distance, which is approximately 220 km, were quantified to be in compliance with emission regulation standards. Under higher spatial resolution, $NO_x$ concentration exceeded a standard in 92 links out of 220 links. The extended time in stop period and the stop-and-go driving cycle were identified as two important reasons for increased $NO_x$ emissions in observed cases. Heavy traffics showed higher $NO_x$ emissions than free flow. These results indicate that the real-world vehicle emissions might exceed the compliance level associate with traffic conditions. Another interesting observation of this research is that the on-road emission characteristics can be independent to the average speed of road links with higher spatial resolution. Variability in on-road emission might not be fully described by solely relying on an average speed, because variability in traffic conditions and road conditions can influence on real-world vehicle emissions.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.42 no.1
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• pp.55-63
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• 2019

This paper develops an algorithm to determine the batch size of the batch process in real time for improving production and efficient control of production system with multiple processes and batch processes. It is so important to find the batch size of the batch process, because the variability arising from the batch process in the production system affects the capacity of the production. Specifically, batch size could change system efficiency such as throughput, WIP (Work In Process) in production system, batch formation time and so on. In order to improve the system variability and productivity, real time batch size determined by considering the preparation time and batch formation time according to the number of operation of the batch process. The purpose of the study is to control the WIP by applying CONWIP production system method in the production line and implements an algorithm for a real time batch size decision in a batch process that requires long work preparation time and affects system efficiency. In order to verify the efficiency of the developed algorithm that determine the batch size in a real time, an existed production system with fixed the batch size will be implemented first and determines that batch size in real time considering WIP in queue and average lead time in the current system. To comparing the efficiency of a system with a fixed batch size and a system that determines a batch size in real time, the results are analyzed using three evaluation indexes of lead time, throughput, and average WIP of the queue.

• Imaging Science in Dentistry
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• v.51 no.3
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• pp.299-306
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• 2021

Purpose: This study aimed to propose a fully automatic landmark identification model based on a deep learning algorithm using real clinical data and to verify its accuracy considering inter-examiner variability. Materials and Methods: In total, 950 lateral cephalometric images from Yonsei Dental Hospital were used. Two calibrated examiners manually identified the 13 most important landmarks to set as references. The proposed deep learning model has a 2-step structure-a region of interest machine and a detection machine-each consisting of 8 convolution layers, 5 pooling layers, and 2 fully connected layers. The distance errors of detection between 2 examiners were used as a clinically acceptable range for performance evaluation. Results: The 13 landmarks were automatically detected using the proposed model. Inter-examiner agreement for all landmarks indicated excellent reliability based on the 95% confidence interval. The average clinically acceptable range for all 13 landmarks was 1.24 mm. The mean radial error between the reference values assigned by 1 expert and the proposed model was 1.84 mm, exhibiting a successful detection rate of 36.1%. The A-point, the incisal tip of the maxillary and mandibular incisors, and ANS showed lower mean radial error than the calibrated expert variability. Conclusion: This experiment demonstrated that the proposed deep learning model can perform fully automatic identification of cephalometric landmarks and achieve better results than examiners for some landmarks. It is meaningful to consider between-examiner variability for clinical applicability when evaluating the performance of deep learning methods in cephalometric landmark identification.

• Journal of Korean Society of Transportation
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• v.22 no.3 s.74
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• pp.85-94
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• 2004

Loop detection systems have been used in real-time signal control system to collect traffic information for estimating queue lengths. The queue length algorithm uses speed as a key variable estimated from occupancy time and average vehicle length. The measurement of average vehicle length is affected from the lengths of feeder cable, but their effects have not yet been evaluated. In this study, the variability of average vehicle length due to the lengths of feeder cable is assessed through a field study, and a practical guidelines is proposed. By applying this result, the operational performance of real-time signal control system could be improved.

• The Journal of Korean Medicine
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• v.26 no.3 s.63
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• pp.228-238
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• 2005

Objectives : We conducted a randomized, double-blinded clinical trial to assess the anti-hypertensive effect of Ginseng and to know the difference of the effect according to it's growing districts md species by 24-hour ambulatory blood pressure measurement (ABPM). Methods : We allocated 96 hypertensive patients enrolled in this trial to Korean ginseng(KG), American ginseng (AG), Chinese ginseng (CG), and Korean red ginseng (KRG) groups by randomization. Each subject was administered 4.5mg/day of encapsulated ginseng for 4 weeks. We assessed anti-hypertensive effect, blood pressure variability using ABPM and toxicity by blood chemistry before and after treatment. We also evaluated changes of symptoms due to hypertension and adverse effect in all groups at the first visit, 2 weeks later and 4 weeks later. Results : Blood pressure after treatments showed significant decrease of systolic blood pressure (sBP) in the CG-group (p<0,05) and diastolic blood pressure (dBP) in the KRG-group (p<0.05). However, there were no significant changes of sBP (or dBP) after treatment in the other groups and no significant difference in changes of BP between before and after treatment among the 4 groups. Blood pressure variability in the CG-group showed significant decrease after treatment but not in the KRG-group. Symptoms such as headache or neck stiffness and heating sensation due to hypertension improved significantly in all groups, especially in the KRG-group. A3l patients had no adverse effect after treatment and there was no liver or kidney toxicity. Conclusions : CG and KRG seem to have anti-hypertensive effects, but there was no significantly different effect depending on growing district and species of Ginseng.

• Communications for Statistical Applications and Methods
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• v.15 no.6
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• pp.925-937
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• 2008

In this study, we considered the clustering analysis for stock return traded in the stock market. Most of financial time-series data, for instance, stock price and exchange rate have conditional heterogeneous variability depending on time, and, hence, are not properly applied to the autoregressive moving-average(ARMA) model with assumption of constant variance. Moreover, the variability is font and center for stock investors as well as academic researchers. So, this paper focuses on the generalized autoregressive conditional heteroscedastic(GARCH) model which is known as a solution for capturing the conditional variance(or volatility). We define the metrics for similarity of unconditional volatility and for homogeneity of model structure, and, then, evaluate the performances of the metrics. In real application, we do clustering analysis in terms of volatility and structure with stock return of the 11 Korean companies measured for the latest three years.

• The Journal of the Korea Contents Association
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• v.11 no.7
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• pp.234-238
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• 2011

This paper will evaluate the usefulness of 3D target of CBCT by comparing human body's posture and position when simulated treatment is being carried out as well as human phantom posture and position using CBCT which is applying OBI. From the Rando Phantom which is located in the datum point moved in parallel and rotationary direction using CBCT. Then the mean and standard deviation difference on images location difference that are acquired were compared with real the Rando Phantom' moved distance. To make a plan of simulated treatment with the same procedure of real radiation therapy, we are going to setup the Rando Phantom. With an assumption that the position is set in accurate place, we measured the setup errors accroding to the change of the translation and rotation. Tests are repeated 10 times to get the standard deviation of the error values. The variability in couch shift after positioning equivalent to average residual error showed lateral $0.2{\pm}0.2$mm, longitudinal $0.4{\pm}0.3$mm, vertical $-0.4{\pm}0.1$mm. The average rotation erroes target localization after simulated $0.4{\pm}0.2$ mm, $0.3{\pm}0.3$ mm, and $0.3{\pm}0.4$ mm. The detection error by rotation is $0{\sim}0.6^{\circ}$ CBCT 3D/3D matching using the Rando Phantom minimized the errors by realizing accurate matching during simulated treatment and patient caring.

• Journal of Biomedical Engineering Research
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• v.33 no.2
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• pp.59-64
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• 2012

With rapid increasing usage of smart phones, social concerns have arisen about the possible effects of electromagnetic fields emitted from wideband code division multiple access(WCDMA) mobile phones on human health. The number of people with self-reported electromagnetic hypersensitivity(EHS) who complain of various subjective symptoms such as headache, insomnia etc. has also recently increased. However, it is unclear whether EHS results from physiological or other origins. In this double-blinded study, we investigated physiological changes such as heart rate, respiration rate, and heart rate variability with real and sham exposures for 15 EHS and 17 non-EHS persons using a module inside a dummy phone. Experiment was conducted using a WCDMA module with average power of 24 dBm at 1950 MHz with the specific absorption rate of 1.57 W/kg using a headphone for 32 min. As a conclusion, WCDMA RF exposure did not have any effects on the physiological variables in either group.

• Imaging Science in Dentistry
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• v.47 no.1
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• pp.11-15
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• 2017

Purpose: This study was performed to investigate the intra- and inter-observer variability in linear measurements with axial images obtained by PreXion (PreXion Inc., San Mateo, USA) and i-CAT(Imaging Sciences International, Xoran Technologies Inc., Hatfield, USA) CBCT scanners, with different voxel sizes. Materials and Methods: A cylindrical object made from nylon with radiopaque markers (phantom) was scanned by i-CAT and PreXion 3D devices. For each axial image, measurements were taken twice in the horizontal(distance A-B) and vertical (distance C-D) directions, randomly, with a one-week interval between measurements, by four oral radiologists with five years or more experience in the use of these measuring tools. Results: All of the obtained linear measurements had lower values than those of the phantom. The statistical analysis showed high intra- and inter-observer reliability (p=0.297). Compared to the real measurements, the measurements obtained using the i-CAT device and PreXion tomography, on average, revealed absolute errors ranging from 0.22 to 0.59 mm and from 0.23 to 0.63 mm, respectively. Conclusion: It can be concluded that both scanners are accurate, although the linear measurements are underestimations, with no significant differences between the evaluators.

• 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.