• Journal of Biomedical Engineering Research
• /
• v.21 no.4
• /
• pp.333-338
• /
• 2000

In this paper, an automated segmentation algorithm is proposed for MR brain images using T1-weighted, T2-weighted, and PD images complementarily. The proposed segmentation algorithm is composed of 3 step. In the first step, cerebrum images are extracted by putting a cerebrum mask upon the three input images. In the second step, outstanding clusters that represent inner tissues of the cerebrum are chosen among 3-dimensional(3D) clusters. 3D clusters are determined by intersecting densely distributed parts of 2D histogram in the 3D space formed with three optimal scale images. Optimal scale image is made up of applying scale space filtering to each 2D histogram and searching graph structure. Optimal scale image best describes the shape of densely distributed parts of pixels in 2D histogram and searching graph structure. Optimal scale image best describes the shape of densely distributed parts of pixels in 2D histogram. In the final step, cerebrum images are segmented using FCM algorithm with its initial centroid value as the outstanding clusters centroid value. The proposed cluster's centroid accurately. And also can get better segmentation results from the proposed segmentation algorithm with multi spectral analysis than the method of single spectral analysis.

• Journal of Korean Society for Geospatial Information Science
• /
• v.14 no.2 s.36
• /
• pp.89-94
• /
• 2006

Forest damage is a worldwide issue and specially, a forest fire involves damage to itself and causes secondary damage such as a flood etc. However, actually, clear analysis on forest fire damage can be hardly conducted due to difficulty in approaching a forest fire and quite a long period of time for analysis. To overcome such difficulty, recently, forest fire damage has been actively investigated with satellite image data, but it is also difficult to obtain satellite image data fitted to the time a forest fire occurred. In addition, it is burdensome to verify accuracy of the obtained image. Therefore, this study was attempted to look into the damaged districts from forest fires by reference to spectroradiometric characteristics of the obtained vegetation with a spectroradiometer as preliminary work to use satellite image data. To begin with, the researcher analyzed the field survey data each measured 3 months and 6 months after occurrence of a forest fire by judging the extent of the damage through visual observation and using a spectroradiometer in order to investigate any potential errors arising out of one-time visual observation. Besides, in this study, groups showing possibilities that trees might be restored to life and wither to death could be classified on the sampling points where forest fire damage is minor.

• Korean Journal of Remote Sensing
• /
• v.36 no.5_3
• /
• pp.1067-1076
• /
• 2020

In this paper, an unsupervised saliency guided change detection method using UAV and aerial imagery is proposed. Regions that are more different from other areas are salient, which make them more distinct. The existence of the substantial difference between two images makes saliency proper for guiding the change detection process. Change Vector Analysis (CVA), which has the capability of extracting of overall magnitude and direction of change from multi-spectral and temporal remote sensing data, is used for generating an initial difference image. Combined with an unsupervised CVA and the saliency, Principal Component Analysis(PCA), which is possible to implemented as the guide for change detection method, is proposed for UAV and aerial images. By implementing the saliency generation on the difference map extracted via the CVA, potentially changed areas obtained, and by thresholding the saliency map, most of the interest areas correctly extracted. Finally, the PCA method is implemented to extract features, and K-means clustering is applied to detect changed and unchanged map on the extracted areas. This proposed method is applied to the image sets over the flooded and typhoon-damaged area and is resulted in 95 percent better than the PCA approach compared with manually extracted ground truth for all the data sets. Finally, we compared our approach with the PCA K-means method to show the effectiveness of the method.

• Journal of Biosystems Engineering
• /
• v.38 no.3
• /
• pp.185-191
• /
• 2013

Purpose: The present study focused on the estimation of soluble solids content (SSC) of chestnut using reflectance and transmittance spectra in range of VIS/NIR. Methods: Four species intact/peeled chestnuts were used for acquisition of spectral data. Transmittance and reflectance spectra were used to develop the best PLS model to estimate SSC of chestnut. Results: The model developed with the transmitted energy spectra of peeled chestnuts rather than intact chestnuts and with range of NIR rather than VIS performed better. The best $R^2$ and RMSEP of cross validation were represented as 0.54 and $1.85^{\circ}Brix$. The results presented that the reflectance spectra of peeled chestnuts by species showed the best performance to predict SSC of chestnut. $R^2$ and RMSEP were 0.55 and $1.67^{\circ}Brix$. Conclusions: All developed models showed RMSEP around $1.44{\sim}2.54^{\circ}Brix$, which is considered not enough to estimate SSC accurately. It was noted that $R^2$ of cross validation that we found were not high. For all that, grading of the fruits in two or three classes of SSC during postharvest handling seems possible with an inexpensive spectrophotometer. Furthermore, the development of estimation of SSC by each chestnut species could be considered in that SSC distribution is clustering in different range by species.

• Journal of Information Processing Systems
• /
• v.13 no.5
• /
• pp.1243-1258
• /
• 2017

A new medical materials scheduling system and its modeling method for the complex rescue are presented. Different from other similar system, first both the BeiDou Satellite Communication System (BSCS) and the Special Fiber-optic Communication Network (SFCN) are used to collect the rescue requirements and the location information of disaster areas. Then all these messages will be displayed in a special medical software terminal. After that the bipartite graph models are utilized to compute the optimal scheduling of medical materials. Finally, all these results will be transmitted back by the BSCS and the SFCN again to implement a fast guidance of medical rescue. The sole drug scheduling issue, the multiple drugs scheduling issue, and the backup-scheme selection issue are all utilized: the Kuhn-Munkres algorithm is used to realize the optimal matching of sole drug scheduling issue, the spectral clustering-based method is employed to calculate the optimal distribution of multiple drugs scheduling issue, and the similarity metric of neighboring matrix is utilized to realize the estimation of backup-scheme selection issue of medical materials. Many simulation analysis experiments and applications have proved the correctness of proposed technique and system.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.26 no.9
• /
• pp.1367-1373
• /
• 2022

In this paper, we consider a power re-allocation technique in order to enhance the frequency efficiency of the low performance user in a cell-free multiple input multiple output (MIMO) network. The AP first allocates transmit power to the user to be proportional to the large-scale fading coefficients of the connected users. Then, the AP reduces the power of the users who were allocated power greater than the threshold ratio of total allocated power to be equal to the threshold ratio of the allocated power. Finally, the AP re-allocates the reduced power from the strong channel user to the user who has the worst channel condition, and thus, the frequency efficiency of the low performance user can be enhanced. In the simulation results, we verify the performance of the power re-allocation technique in terms of the spectral efficiency of the low performance user.

• Journal of Plant Biotechnology
• /
• v.43 no.2
• /
• pp.213-222
• /
• 2016

This study aims to establish a system for the rapid discrimination of Zoysia species using metabolite fingerprinting of FT-IR spectroscopy combined with multivariate analysis. Whole cell extracts from leaves of 19 identified Zoysia japonica, 6 identified Zoysia sinica, and 38 different unidentified Zoysia species were subjected to Fourier transform infrared spectroscopy (FT-IR). PCA (principle component analysis) and PLS-DA (partial least square discriminant analysis) from FT-IR spectral data successfully divided the 25 identified turf grasses into two groups, representing good agreement with species identification using molecular markers. PC (principal component) loading values show that the $1,100{\sim}950cm^{-1}$ region of the FT-IR spectra are important for the discrimination of Zoysia species. A dendrogram based on hierarchical clustering analysis (HCA) from the PCA and PLS-DA data of turf grasses showed that turf grass samples were divided into Zoysia japonica and Zoysia sinica in a species-dependent manner. PCA and PLS-DA from FT-IR spectral data of Zoysia species identified and unidentified by molecular markers successfully divided the 49 turf grasses into Z. japonica and Z. sinica. In particular, PLS-DA and the HCA dendrogram could mostly discriminate the 47 Z. japonica grasses into two groups depending on their origins (mountainous areas and island area). Considering these results, we suggest that FT-IR fingerprinting combined with multivariate analysis could be applied to discriminate between Zoysia species as well as their geographical origins of various Zoysia species.

• The Journal of Internal Korean Medicine
• /
• v.30 no.3
• /
• pp.510-524
• /
• 2009

Objective : This study was designed to find the correlation between Sasang Constitution and heart rate variability(HRV). Method : There were 665 subjects (280 men and 385 women), between 39 and 72 years old. in a rural community. Sasang Constitution was diagnosed by a Sasang constitutional specialist using PSSC (Phonetic System for Sasang Constitution), face and tongue photo and checkup-list. A structured-questionnaire was used to assess the general characteristics. HRV was recorded using SA-2000 (medi-core). HRV was assessed by time domain and by frequency domain analysis. Metabolic syndrome was defined on the basis of clustering of risk factors, when three or more of the following cardiovascular risk factors were included : blood pressure, fasting blood sugar, triglyceride HDL-cholesterol, and abdominal obesity (waist). Because of the skewness of the data, logarithmic transformation was performed on the absolute units of the spectral components of HRV, and the resulting logarithmic values and normalized units were compared between the groups by a logistic regression. The 95% confidence interval (CI) of the odds ratio was used and calculated from the data laid out for a cross sectional study. Results : 1. Odds ratios of Taeeumin and Soeumin in female adults below 60 years old were significantly lower than that of Soyangin in LF norm and LF/HF ratio. Odds ratios of Taeeumin and Soeumin in female adults below 60 years old were significantly higher than that of Soyangin in HF norm. 2. There was no significant correlation between HRV and Sasang Constitution in female adults from 60 years old and over. 3. There was no significant correlation between HRV and Sasang Constitution in male adults. Conclusion : There is a statistically significant correlation between the HRV and Sasang Constitution. There is a tendency of increase in the sympathetic activity in Soyangin. There is a tendency of decrease in the parasympathetic activity in Taeeumin and Soeumin.

• Publications of The Korean Astronomical Society
• /
• v.30 no.1
• /
• pp.11-16
• /
• 2015

First light galaxies have predictable linear clustering, and are expected to produce fluctuations with a characteristic spatial power spectrum, which peaks at an angular scale of ~ 10 arcminutes and in the $1-2{\mu}m$ spectral regions. The Cosmic Infrared Background ExpeRiment 2 (CIBER2) is a dedicated sounding rocket mission for measuring the fluctuations in the extragalactic infrared background light, following up the previous successful measurements of CIBER1. With a 28.5 cm telescope accompanied with three arms of camera barrels and a dual broadband filter on each H2RG (${\lambda}_c=2.5{\mu}m$) array, CIBER2 can measure 6 bands of wide field ($1.1{\times}2.2$ degrees) up to 3 AB magnitudes deeper than CIBER1. This project is leaded by California Institute of Technology/Jet Propulsion Laboratory, collaborating internationally with Institute of Space and Astronautical Science in Japan, Korea Astronomy and Space Science Institute, Korea Basic Science Institute, and Seoul National University. The Korean team is in charge of 1) one H2RG scientific array, 2) ground station hardware and software, 3) telescope lenses, and 4) flight and test bed electronics fabrication. In this paper, we describe the detailed activities of the Korean participation as well as the current status of the CIBER2 project.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.53 no.5
• /
• pp.19-24
• /
• 2016

In Long Term Evolution-Advanced (LTE-A), small cell enhancement(SCE) has been developed as a cost-effective way of supporting exponentially increasing demand of wireless data services and satisfying the user quality of service(QoS). However, due to the dense and irregular distribution of a large number of small cells, the offloading scheme should be applied in the small cell network. In this paper, we propose an user offloading scheme for SCE in LTE-Advanced system. We divide the small cells into different clusters according to the reference signal received power(RSRP) from user equipment(UE). Within a cluster, We apply the user offloading scheme with the consideration of the number of users and interference conditions. Simulation results show that proposed scheme can improve the throughput, and spectral efficiency of small cell users. Eventually, proposed scheme can improve overall cell performance.