• Journal of the Korean earth science society
• /
• v.30 no.2
• /
• pp.234-246
• /
• 2009

Characteristics of speckle errors of Sea-viewing Wide Field-of-view Sensor (SeaWiFS) chlorophyll-${\alpha}$ concentration were analyzed, and its causes were investigated by using SeaWiFS data in the East Sea from September 1997 to December 2007. The speckles with anomalously high concentrations were randomly distributed and showed remarkably high bias of greater than $10mg/m^3$, compared with their neighboring pixels. The speckles tended to appear frequently in winter, which might be related to cloud distribution. Ten-year averaged cloudiness of winter was much higher over the southeastern part, with frequent speckles, than the northwestern part of the East Sea. Statistical analysis results showed that the number of the speckles was increased as cloudiness increased. Normalized water-leaving radiance of the speckle pixel was considerably low at the short wavelengths (443, 490, and 510 nm), whereas the radiance at 555 nm band was normal. These low measurements produced extraordinarily high concentration from the chlorophyll-${\alpha}$ estimation formula. This study presented the speckle errors of SeaWiFS chlorophyll-${\alpha}$ concentration in the East Sea and suggested that more reliable chlorophyll-${\alpha}$ data based on appropriate ocean color remote sensing techniques should be used for the oceanic application researches.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
• /
• v.30 no.2
• /
• pp.177-180
• /
• 2019

To improve the accuracy rate of guided weapons, many studies have been conducted on the accurate detection and identification of targets from sea clutter. Because of the variety and complicated characteristics of both sea-clutter and target signals, an active target recognition technique is required. In this study, we propose an algorithm to distinguish clutter and recognize targets by applying a fractal signature(FS) classifier, which is a fractal dimension, and a high-resolution target image(HRTI) classifier, which applies scene matching to an image formed from a scanned image. Simulation results using the algorithm revealed that the HRTI classifier recognized targets 1 and 2 at a 100 % rate, whereas the FS classifier recognized targets 1 and 2 at rates of 90 % and 93 %, respectively.

• Geomechanics and Engineering
• /
• v.25 no.1
• /
• pp.1-16
• /
• 2021

Machine learning models have been widely used for landslide susceptibility assessment (LSA) in recent years. The large number of inputs or conditioning factors for these models, however, can reduce the computation efficiency and increase the difficulty in collecting data. Feature selection is a good tool to address this problem by selecting the most important features among all factors to reduce the size of the input variables. However, two important questions need to be solved: (1) how do feature selection methods affect the performance of machine learning models? and (2) which feature selection method is the most suitable for a given machine learning model? This paper aims to address these two questions by comparing the predictive performance of 13 feature selection-based machine learning (FS-ML) models and 5 ordinary machine learning models on LSA. First, five commonly used machine learning models (i.e., logistic regression, support vector machine, artificial neural network, Gaussian process and random forest) and six typical feature selection methods in the literature are adopted to constitute the proposed models. Then, fifteen conditioning factors are chosen as input variables and 1,017 landslides are used as recorded data. Next, feature selection methods are used to obtain the importance of the conditioning factors to create feature subsets, based on which 13 FS-ML models are constructed. For each of the machine learning models, a best optimized FS-ML model is selected according to the area under curve value. Finally, five optimal FS-ML models are obtained and applied to the LSA of the studied area. The predictive abilities of the FS-ML models on LSA are verified and compared through the receive operating characteristic curve and statistical indicators such as sensitivity, specificity and accuracy. The results showed that different feature selection methods have different effects on the performance of LSA machine learning models. FS-ML models generally outperform the ordinary machine learning models. The best FS-ML model is the recursive feature elimination (RFE) optimized RF, and RFE is an optimal method for feature selection.

• The Journal of the Acoustical Society of Korea
• /
• v.21 no.8
• /
• pp.735-743
• /
• 2002

In this paper, we propose three new text-independent speaker identification methods. At first, to exclude the frames not having enough features of speaker's vocal from calculation of the maximum likelihood, we propose the FS(Frame Selection) method. This approach selects the important frames by evaluating the difference between the biggest likelihood and the second in each frame, and uses only the frames in calculating the score of likelihood. Our secondly proposed, called the Hybrid, is a combined version of the FS and WMR(Weighting Model Rank). This method determines the claimed speaker using exponential function weights, instead of likelihood itself, only on the selected frames obtained from the FS method. The last proposed, called MWMR (Modified WMR), considers both original likelihood itself and its relative position, when the claimed speaker is determined. It is different from the WMR that take into account only the relative position of likelihood. Through the experiments of the speaker identification, we show that the all the proposed have higher identification rates than the ML. In addition, the Hybrid and MWMR have higher identification rate about 2% and about 3% than WMR, respectively.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
• /
• v.29 no.11
• /
• pp.702-706
• /
• 2016

We demonstrated that self-separation FS-GaN (freestanding-GaN) was grown on MELO (maskless epitaxially lateral overgrowth) GaN template by horizontal HVPE (hydride vapor phase epitaxy). Before thick GaN grwoth, MELO GaN template was grown on patterned GaN template by MOCVD (metal organic chemical vapor deposition). The laterally overgrown GaN would consist of a continuous well coalesced layer. The mixed TDD (threading dislocation density) of seed and wing region were $8{\times}10^8cm^{-2}$ and $7{\times}10^7cm^{-2}$, respectively. After thick GaN grown by HVPE, the self-separation between thick GaN and sapphire substrate was generated at seed region. The regions of self-separation for FS-GaN and sapphire were observed by FE-SEM. Moreover, Raman results indicated that the compressive strain of seed and wing regions at FS-GaN substrate were slightly released compared to that of thick GaN grown on conventional GaN template. The optical properties of the FS-GaN substrate were examined by using PL (photoluminescence). The PL exhibited that donor bound exciton and donor acceptor pair were observed at low temperature. The effects on optical and structural properties of FS-GaN substrate have been discussed in detail.

• Journal of the Korea Concrete Institute
• /
• v.18 no.4 s.94
• /
• pp.553-558
• /
• 2006

In this study, fluorine-silicate hybrid type crack reducing agent(FS) consisted of fluorine and silicate compounds applied to concrete mix(specification : 25-30-18) between 0.5% and 2.0% at intervals of 0.5% based on cement weight. Experiments for material properties of concrete such as slump, air content and bleeding with elapsed time were performed. Experiment and elucidation for shrinkage crack resistance as well as adiabatic hydration temperature were also carried out. It was appeared that FS addition contributed to lower bleeding and hydration temperature without disturbance of fresh properties of concrete such as slump and air content compared to non-added concrete. Especially, shrinkage crack resistance of concrete resulted from plastic and drying shrinkage could be effectively reduced by the addition of FS ranging from 1.0% to 1.5%.

• Korean Journal of Remote Sensing
• /
• v.26 no.2
• /
• pp.209-220
• /
• 2010

One of the most difficult tasks in measuring oceanic conditions is to produce oceanic current information. In efforts to overcome the difficulties, various attempts have been carried out to estimate the speed and direction of ocean currents by utilizing sequential satellite images. In this study, we have estimated sea surface current vectors to the south of the Korean Peninsula, based on the maximum cross-correlation method by using sequential ocean color images of SeaWiFS chlorophyll-a. Comparison of surface current vectors estimated by this method with the geostrophic current vectors estimated from satellite altimeter data and in-situ ADCP measurements are good in that current speeds are underestimated by about 15% and current directions are show differences of about $36^{\circ}$ compared with previous results. The technique of estimating current vectors based on maximum cross-correlation applied on sequential images of SeaWiFS is promising for the future application of GOCI data for the ocean studies.

• Journal of the Korea Convergence Society
• /
• v.10 no.2
• /
• pp.49-56
• /
• 2019

This study was to examine whether an elderly can health-related quality of life(EQ-5D) by the mediating effect of dental health determinants on the association between health practice behavior and EQ-5D. The analysis was conducted on 1,311 of above the age of 65 in elderly by using raw data from the 2015 National Health and Nutrition Survey. The data were analyzed using SPSS for windows version 24.0 and SPSS PROCESS-macro. The health practice behavior and EQ-5D by living arrangement were the highest in the one-generation family(4.62, 0.90) and the lowest the elderly living alone(4.40, 0.86). Also, analysis using the PROCESS macro indicated that the FS-T index has a mediating effect between health practice behavior and EQ-5D(${\beta}=.0011$, BCCI [.003~.0024]). These findings suggest that FS-T index is closely related to EQ-5D and this will be used as basic data for development of health promotion programs for elderly.

• Asian Journal of Atmospheric Environment
• /
• v.7 no.4
• /
• pp.199-208
• /
• 2013

Mercury exchange fluxes between atmosphere and soil surface were measured in two different types of soils; lawn soil (LS) and forest soil (FS). Average Hg emission from LS was higher than from FS although the soil Hg content was more than 2 times higher in forest soil. In LS, Hg emissions were much greater in warm season than in cold season; however, deposition was dominant in FS during warm season because of leafy trees blocking the solar radiation reaching on the soil surface. In both LS and FS, Hg fluxes showed significantly positive correlations with UV radiation and soil surface temperature during cold season. In addition, it was observed that emission showed positive correlation with UV radiation and soil temperature while there was negative relationship between deposition and UV radiation.

• Journal of the Korean Society for Precision Engineering
• /
• v.27 no.2
• /
• pp.29-33
• /
• 2010

We have investigated fs-laser ablation as well as optoperforation threshold of PDMS (Polydimethylsiloxane) thin lid cover on ${\mu}$-channel with changing the flow medium from water to hemoglobin. The ablation threshold is found to be independent of both PDMS thin film thickness and flow medium, but the optoperforation threshold is dependent on the films thickness. The observation that the ablation process is well described with simple two-temperature model supposed that the cover lid PDMS of $\mu$-channel be processed with minimized thermal effects by fs-laser with low laser fluence.