• Korean Journal of Remote Sensing
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• v.26 no.4
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• pp.403-410
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• 2010

NDVI(Normalized Difference Vegetation Index), which is broadly used as short-term data composite, is an important parameter for climate change and long-term land surface monitoring. Although atmospheric correction is performed, NDVI dramatically appears several low peak noise in the long-term time series. They are related to various contaminated sources, such as cloud masking problem and wet ground condition. This study suggests a simple method through harmonic analysis for reducing NDVI noise using SPOT/VGT NDVI 10-day MVC data. The harmonic analysis method is compared with the polynomial regression method suggested previously. The polynomial regression method overestimates the NDVI values in the time series. The proposed method showed an improvement in NDVI correction of low peak and overestimation.

• The Journal of Korean Institute of Information Technology
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• v.16 no.11
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• pp.23-34
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• 2018

This paper presents the high efficiency and high power-factor power supply for LED lighting equipment. The proposed power supply is the single-stage power structure consisted of the full-bridge diode rectifier and flyback converter, and thus the power-factor correction and output voltage regulation are performed simultaneously using only one controller IC and one power semiconductor switch. Furthermore, the proposed power supply reduces the voltage stress and switching loss of main switch using the regenerative snubber, and it improves the system efficiency using the synchronous rectifier. The applied synchronous rectifier is the new voltage-driven type and its operation and construction are simple. In this paper, the operation principle of proposed power supply is explained through the operation analyses of its power-factor correction and main power conversion parts and the operation of synchronous rectifier is described, briefly. Also, a design example of the power circuit of 40W-class prototype is shown and the operation characteristics of proposed power supply are validated through the experimental results of the implemented prototype by the designed circuit parameter.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.6
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• pp.1-13
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• 2021

In this study, a time series analysis technique was applied to calibrate and predict traffic data for various purposes, such as planning, design, maintenance, and research. Existing algorithms have limitations in application to data such as traffic data because they show strong periodicity and seasonality or irregular data. To overcome and supplement these limitations, we applied the SARIMA model, an analytical technique that combines the autocorrelation model, the Seasonal Auto Regressive(SAR), and the seasonal Moving Average(SMA). According to the analysis, traffic volume prediction using the SARIMA(4,1,3)(4,0,3) 12 model, which is the optimal parameter combination, showed excellent performance of 85% on average. In addition to traffic data, this study is considered to be of great value in that it can contribute significantly to traffic correction and forecast improvement in the event of missing traffic data, and is also applicable to a variety of time series data recently collected.

• Journal of Korea Water Resources Association
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• v.47 no.2
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• pp.119-133
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• 2014

The study adopted extended Kalman filter technique in an effort to predict Z-R relationship parameter as a stable value in real-time. Toward this end, a parameter estimation model was established based on extended Kalman filter in consideration of non-linearity of Z-R relationship. A state-space model was established based on a study that was conducted by Adamowski and Muir (1989). Two parameters of Z-R relationship were set as state variables of the state-space model. As a result, a stable model where a divergence of Kalman gain and state variables are not generated was established. It is noteworthy that overestimated or underestimated parameters based on a conventional method were filtered and removed. As application of inappropriate parameters might cause physically unrealistic rain rate estimation, it can be more effective in terms of quantitative precipitation estimation. As a result of estimation on radar rainfall based on parameters predicted with the extended Kalman filter, the mean field bias correction factor turned out to be around 1.0 indicating that there was a minor difference from the gauge rain rate without the mean field bias correction. In addition, it turned out that it was possible to conduct more accurate estimation on radar rainfall compared to the conventional method.

• Journal of Environmental Health Sciences
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• v.22 no.2
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• pp.90-95
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• 1996

This study was performed to calculate the degration rate coefficient, operating parameters to meet the effluent standards, and the temperature adjustment coefficients to each parameter of pollution by seasonal variation of concentration and temperature of influent in livestock wastewater treatment by sequencing batch reactor process in field scale. The followings are the conclusions that were derived from this study. 1. In the field, temperature of livestock wastewater in reactor was 20.3$\circ$C in summer and 6.0$\circ$C in winter. The ratio of BOD:TKN: T-P in influent was 100:80:7. BOD loadings in winter and spring were 0.26 and 0.43 kg $BOD/m^3$ day, respectively. Those in summer and fall were 0.25 and 0.13 kg $BOD/m^3$ day, respectively. 2. The degradation rate coefficient for TKN was larger in summer and fall in which temperature was high than that in which temperature was high than that in winter and spring in which concentration was high. On the contrary, the phosphorus uptake rate was larger in winter and spring than that in summer and fall. 3. The hydraulic retention time in winter and spring was longer than that in summer and fall. Especially, in order to meet the standard for TKN of 120 mg/l in winter in which temperature of wastewater was 6.0$\circ$C, as the MLSS concentration was increased from 4, 000 to 7, 000 mg/l, the hydraulic retention time was increased from 212 to 121 hours. But, in order to shorten that less than 121 hours for the economical wastewater treatment, countermeasure to increase temperature of wastewater in the reactor should be considered. 4. the temperature adjustment coefficients for BOD, $COD_{Mn}$, TKN and T-P were 1.0241, 1.0225, 1.0541 and 1.0495, respectively. Namely, the treatment of TKN was most sensitively affected by temperature. For the purpose of the effective removal of nitrogen and phosphorus which are sensitive to temperature, it is necessary to keep the temperature of livestock wastewater more than 20$\circ$C which is the temperature of it in summer.

• Steel and Composite Structures
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• v.34 no.5
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• pp.643-655
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• 2020

In the present work, the buckling behavior of a single-layered graphene sheet (SLGS) embedded in visco-Pasternak's medium is studied using nonlocal four-unknown integral model. This model has a displacement field with integral terms which includes the effect of transverse shear deformation without using shear correction factors. The visco-Pasternak's medium is introduced by considering the damping effect to the classical foundation model which modeled by the linear Winkler's coefficient and Pasternak's (shear) foundation coefficient. The SLGS under consideration is subjected to compressive in- plane edge loads per unit length. The influences of many parameters such as nonlocal parameter, geometric ratio, the visco-Pasternak's coefficients, damping parameter, and mode numbers on the buckling response of the SLGSs are studied and discussed.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.15 no.2
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• pp.209-218
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• 2002

The Vector Random Decrement technique has been developed as an efficient method for transforming ambient responses into free decays of linear structures. It is shown that the VRD functions nay contain as much information about the modes as the really measured free decay responses. In this paper, the theory of the VRD technique is extended by applying the concept of the mode shape ratio into the Ibrahim Time Domain modal parameter identification algorithm. The VRD function is not shifted in the correction procedures for constant time shifts of the proposed VRD technique. Thus, a number of points equal to the largest of the time shifts used in the vector triggering condition are not deleted. In the VRD functions, any influence of the input to the system is averaged out. The proposed technique is compared with the traditional VRD technique by assessment of the modal parameters. The applicability of the VRD technique has been justified through a simulation study and a study of the response of a laboratory beam model subject to ambient loads.

• Journal of The Korean Society of Integrative Medicine
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• v.7 no.4
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• pp.265-272
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• 2019

Purpose : Excessive computer use frequently results in musculoskeletal disorders of the neck and shoulder such as forward head posture (FHP). The purpose of this study was to investigate effects of neck and shoulder exercise program on spino-pelvic alignment and the correlation between change in head and neck posture and spino-pelvic alignment in FHP. Methods : The study included 44 participants with FHP. The participants performed the exercise for correction of FHP 2-3 times a week for 4 weeks. We examined whole spine X-ray images in the lateral standing position with both arms crossed. We measured anterior head translation distance (AHT), craniovertebral angle (CVA), cervical lordosis (CL), thoracic kyphosis (TK), lumbosacral lordosis (LSL), sacral slope (SS), pelvic tilt (PT), and pelvic incidence (PI) of the subjects. The association between change in AHT and each spino-pelvic parameter was also subjected to Pearson's correlation coefficient analysis. Results : There were statistically significant differences before and after exercise in the parameters of AHT, CVA, and SS (p<.05). Significant negative correlation was observed between the change in AHT and CVA (r=-.768, p<.001), and CL (r=-.388, p<.05). There was significant positive correlation between the change in AHT and SS (r=.328, p<.05), and PI (r=.333, p<.05). However, no significant correlation was observed in change in AHT with that of TK, LSL, and PT. Conclusion : Based on the above results, we conclude that there is a relationship between change in AHT, which is a parameter associated with forward displacement of the head, and that of CVA, CL, SS, and PI after exercise in cases of FHP.

• Steel and Composite Structures
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• v.20 no.2
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• pp.227-249
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• 2016

The objective of this work is to present a zeroth-order shear deformation theory for free vibration analysis of functionally graded (FG) nanoscale plates resting on elastic foundation. The model takes into consideration the influences of small scale and the parabolic variation of the transverse shear strains across the thickness of the nanoscale plate and thus, it avoids the employ use of shear correction factors. Also, in this present theory, the effect of transverse shear deformation is included in the axial displacements by using the shear forces instead of rotational displacements as in available high order plate theories. The material properties are supposed to be graded only in the thickness direction and the effective properties for the FG nanoscale plate are calculated by considering Mori-Tanaka homogenization scheme. The equations of motion are obtained using the nonlocal differential constitutive expressions of Eringen in conjunction with the zeroth-order shear deformation theory via Hamilton's principle. Numerical results for vibration of FG nanoscale plates resting on elastic foundations are presented and compared with the existing solutions. The influences of small scale, shear deformation, gradient index, Winkler modulus parameter and Pasternak shear modulus parameter on the vibration responses of the FG nanoscale plates are investigated.

• The Korean Journal of Applied Statistics
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• v.29 no.4
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• pp.643-656
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• 2016

High dimensional data are frequently encountered in various fields where the number of variables is greater than the number of samples. It is usually necessary to select variables to estimate regression coefficients and avoid overfitting in high dimensional data. A penalized regression model simultaneously obtains variable selection and estimation of coefficients which makes them frequently used for high dimensional data. However, the penalized regression model also needs to select the optimal model by choosing a tuning parameter based on the model selection criterion. This study deals with the bias effect of LASSO regression for model selection criteria. We numerically describes the bias effect to the model selection criteria and apply the proposed correction to the identification of biomarkers for lung cancer based on gene expression data.