• Journal of applied mathematics & informatics
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• v.33 no.1_2
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• pp.193-201
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• 2015

In this paper, we present preconditioned generalized accelerated overrelaxation (GAOR) methods for solving weighted linear least square problems. We compare the spectral radii of the iteration matrices of the preconditioned and the original methods. The comparison results show that the preconditioned GAOR methods converge faster than the GAOR method whenever the GAOR method is convergent. Finally, we give a numerical example to confirm our theoretical results.

• Korean Journal of Remote Sensing
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• v.31 no.2
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• pp.161-170
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• 2015

This paper presents an efficient image fusion method to be appropriate for the KOMPSAT-2 and 3 satellites. The proposed method is based on the well-established component substitution (CS) approach. The proposed method is divided into two parts: 1) The first step is to create a intensity image by the weighted-averaging operation of a multi-spectral (MS) image and 2) the second step is to produce an optimal high-frequency image using the statistical properties of the original MS and panchromatic (PAN) images. The performance of the proposed method is evaluated in both quantitative and visual analysis. Quantitative assessments are performed by using the relative global dimensional synthesis error (Spatial and Spectral ERGAS), the image quality index (Q4), and the spectral angle mapper index (SAM). The qualitative and quantitative assessment results show that the fusion performance of the proposed method is improved in both the spectral and spatial qualities when it is compared with previous CS-based fusion methods.

• Journal of Korea Multimedia Society
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• v.3 no.4
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• pp.339-346
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• 2000

Medical image is analyzed to get an anatomical information for diagnostics. Segmentation must be preceded to recognize and determine the lesion more accurately. In this paper, we propose automatic segmentation algorithm for MR brain images using T1-weighted, T2-weighted and PD images complementarily. The proposed segmentation algorithm is first, extracts cerebrum images from 3 input images using cerebrum mask which is made from PD image. And next, find 3D clusters corresponded to cerebrum tissues using scale filtering and 3D clustering in 3D space which is consisted of T1, T2, and PD axis. Cerebrum images are segmented using FCM algorithm with its initial centroid as the 3D cluster's centroid. The proposed algorithm improved segmentation results using accurate cluster centroid as initial value of FCM algorithm and also can get better segmentation results using multi spectral analysis than single spectral analysis.

• The Journal of the Acoustical Society of Korea
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• v.35 no.1
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• pp.49-54
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• 2016

In this paper, we propose a vocal separation method using weighted ${\beta}$-order minimum mean wquare error estimation (WbE) based on kernel back-fitting algorithm. In spoken speech enhancement, it is well-known that the WbE outperforms the existing Bayesian estimators such as the minimum mean square error (MMSE) of the short-time spectral amplitude (STSA) and the MMSE of the logarithm of the STSA (LSA), in terms of both objective and subjective measures. In the proposed method, WbE is applied to a basic iterative kernel back-fitting algorithm for improving the vocal separation performance from monaural music signal. The experimental results show that the proposed method achieves better separation performance than other existing methods.

• The Journal of the Acoustical Society of Korea
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• v.24 no.7
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• pp.402-409
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• 2005

In this paper. we propose a coding method using a matching pursuit algorithm in a strongly periodic highband signal. Also. we propose an efficient quantizer for the estimated parameters : spectral magnitude and phase. Based on the error concealment principle and sinusoidal model. the MP algorithm requires the high-precision pitch period estimation. To estimate more accurate pitch period. the refined pitch obtained from lowband speech is used. which increases the efficiency of bit allocation. The spectral magnitude parameters are quantized by the method which is combined with MDCT (Modified Discrete Cosine Transform) and multi-stage structure. The spectral phase quantizer uses the $2{\pi}$ modular characteristic of phases and the weighted function by spectral magnitudes. To evaluate the efficiency of the proposed method. we applied it to analysis-by-synthesis system. Furthermore we suggest the possibillity of scalable wideband speech codecs based on band-split structure.

• The Korean Journal of Applied Statistics
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• v.33 no.4
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• pp.511-526
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• 2020

Single-cell RNA-sequencing (scRNA-seq) data consists of each cell's RNA expression extracted from large populations of cells. One main purpose of using scRNA-seq data is to identify inter-cellular heterogeneity. However, scRNA-seq data pose statistical challenges when applying traditional clustering methods because they have many missing values and high level of noise due to technical and sampling issues. In this paper, motivated by analyzing scRNA-seq data, we propose a novel spectral-based clustering method by imposing different weights on genes when computing a similarity between cells. Assigning weights on genes and clustering cells are performed simultaneously in the proposed clustering framework. We solve the proposed non-convex optimization using an iterative algorithm. Both real data application and simulation study suggest that the proposed clustering method better identifies underlying clusters compared with existing clustering methods.

• Journal of the Ergonomics Society of Korea
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• v.18 no.2
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• pp.103-120
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• 1999

The purpose of this study was to evaluate the manual workload in repetitive wrist and finger motion. To evaluate manual workload, angular displacement of the joint, EMG of the muscle and subjective rating were studied. Both wrist motion and finger motion were studied. A screw-driving task was used for the wrist motion experiment. A keyboard typing task was used for the finger motion experiment. All finger joint angles and wrist angles were measured by an angle-measuring glove($CyberGlove^{TM}$, Virtual Technologies, Inc.). Surface EMG was recorded from FCU muscle and FDS muscle simultaneously with the angle measurement. Subjective ratings of exertion were also recorded using the modified Borg's CR-10 scale. Repetition rates of 0.5, 1, 2 motions per second were used with each task. As a result, manual workload increased with increasing repetitiveness. Peak spectral magnitude and frequency components corresponded closely with joint angular displacement amplitudes and repetition rates. Results of the correlation analysis showed that there were significant correlation among EMG, frequency-weighted motion and subjective measurement. Both EMG and frequency-weighted filtering showed consistent workload estimation with increasing task frequency. Subjective ratings showed slight over-estimation of the workload as the task frequency is increased.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.2
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• pp.647-669
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• 2016

Multiple attribute for decision making including user preference will increase the complexity of route selection process. Various approaches have been proposed to solve the optimal route selection problem. In this paper, multi attribute decision making (MADM) algorithms such as Simple Additive Weighting (SAW), Weighted Product Method (WPM), Analytic Hierarchy Process (AHP) method and Total Order Preference by Similarity to the Ideal Solution (TOPSIS) methods have been proposed for acoustic signature based optimal route selection to facilitate user with better quality of service. The traffic density state conditions (very low, low, below medium, medium, above medium, high and very high) on the road segment is the occurrence and mixture weightings of traffic noise signals (Tyre, Engine, Air Turbulence, Exhaust, and Honks etc) is considered as one of the attribute in decision making process. The short-term spectral envelope features of the cumulative acoustic signals are extracted using Mel-Frequency Cepstral Coefficients (MFCC) and Adaptive Neuro-Fuzzy Classifier (ANFC) is used to model seven traffic density states. Simple point method and AHP has been used for calculation of weights of decision parameters. Numerical results show that WPM, AHP and TOPSIS provide similar performance.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.4
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• pp.1837-1860
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• 2020

We propose a general framework for studying resource allocation problem and the tradeoff between spectral efficiency (SE) and energy efficiency (EE) for downlink traffic in power domain-non-orthogonal multiple access (PD-NOMA) and device to device (D2D) based heterogeneous cloud radio access networks (H-CRANs) under imperfect channel state information (CSI). The aim is jointly optimize radio remote head (RRH) selection, spectrum allocation and power control, which is formulated as a multi-objective optimization (MOO) problem that can be solved with weighted Tchebycheff method. We propose a low-complexity algorithm to solve user association, spectrum allocation and power coordination separately. We first compute the CSI for RRHs. Then we study allocating the cell users (CUs) and D2D groups to different subchannels by constructing a bipartite graph and Hungrarian algorithm. To solve the power control and EE-SE tradeoff problems, we decompose the target function into two subproblems. Then, we utilize successive convex program approach to lower the computational complexity. Moreover, we use Lagrangian method and KKT conditions to find the global optimum with low complexity, and get a fast convergence by subgradient method. Numerical simulation results demonstrate that by using PD-NOMA technique and H-CRAN with D2D communications, the system gets good EE-SE tradeoff performance.

• The Journal of the Acoustical Society of Korea
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• v.32 no.6
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• pp.556-562
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• 2013

This paper is aimed to improve performance of Band-Selection speech/audio Coder reconstucted band spectrum that is not sent by the comfort noise. To improve the performance, we use the Spectral Band Replication(SBR) technique instead of substitution of Comfort noise. To synthesize SBR signal, the SBR algorithm is referenced in selected signals and the spectrum synthesized by SBR is injected to non-selected band. Each sub-band spectrum has been energy-weighted by real audio signal. We propose the enhanced the Band-Selection Coder that utilizes synthesized SBR signal from selected signal instead of comfort noise.