• ETRI Journal
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• 제41권2호
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• pp.235-241
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• 2019

In this paper, we propose a rank-weighted reconstruction feature to improve the robustness of a feed-forward deep neural network (FFDNN)-based acoustic model. In the FFDNN-based acoustic model, an input feature is constructed by vectorizing a submatrix that is created by slicing the feature vectors of frames within a context window. In this type of feature construction, the appropriate context window size is important because it determines the amount of trivial or discriminative information, such as redundancy, or temporal context of the input features. However, we ascertained whether a single parameter is sufficiently able to control the quantity of information. Therefore, we investigated the input feature construction from the perspectives of rank and nullity, and proposed a rank-weighted reconstruction feature herein, that allows for the retention of speech information components and the reduction in trivial components. The proposed method was evaluated in the TIMIT phone recognition and Wall Street Journal (WSJ) domains. The proposed method reduced the phone error rate of the TIMIT domain from 18.4% to 18.0%, and the word error rate of the WSJ domain from 4.70% to 4.43%.

• 한국음향학회:학술대회논문집
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• 한국음향학회 1994년도 FIFTH WESTERN PACIFIC REGIONAL ACOUSTICS CONFERENCE SEOUL KOREA
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• pp.1009-1014
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• 1994

This paper improves the previously proposed spectral mapping method for supervised speaker adaptation in which a mapped spectrum is interpolated from speaker difference vectors at typical spectra based on a minimized distortion criterion. In estimating these difference vectors, it is important to find an appropriate number of typical points. The previous method empirically adjusts the number of typical points, while the present method optimizes the effective number by rank reduction of normal equation. This algorithm was applied to a supervised speaker adaptation for Korean word recognition using the templates form a prototype male speaker. The result showed that the rank reduction technique not only can automatically determine an optimal number of code vectors, but also slightly improves the recognition scores compared with those obtained by the previous method.

• The Korean Journal of Pain
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• 제30권2호
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• pp.86-92
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• 2017

Osteoblasts, originating from mesenchymal cells, make the receptor activator of the nuclear factor kappa B ligand (RANKL) and osteoprotegerin (OPG) in order to control differentiation of activated osteoclasts, originating from hematopoietic stem cells. When the RANKL binds to the RANK of the pre-osteoclasts or mature osteoclasts, bone resorption increases. On the contrary, when OPG binds to the RANK, bone resorption decreases. Denosumab (AMG 162), like OPG (a decoy receptor), binds to the RANKL, and reduces binding between the RANK and the RANKL resulting in inhibition of osteoclastogenesis and reduction of bone resorption. Bisphosphonates (BPs), which bind to the bone mineral and occupy the site of resorption performed by activated osteoclasts, are still the drugs of choice to prevent and treat osteoporosis. The merits of denosumab are reversibility targeting the RANKL, lack of adverse gastrointestinal events, improved adherence due to convenient biannual subcutaneous administration, and potential use with impaired renal function. The known adverse reactions are musculoskeletal pain, increased infections with adverse dermatologic reactions, osteonecrosis of the jaw, hypersensitivity reaction, and hypocalcemia. Treatment with 60 mg of denosumab reduces the bone resorption marker, serum type 1 C-telopeptide, by 3 days, with maximum reduction occurring by 1 month. The mean time to maximum denosumab concentration is 10 days with a mean half-life of 25.4 days. In conclusion, the convenient biannual subcutaneous administration of 60 mg of denosumab can be considered as a first-line treatment for osteoporosis in cases of low compliance with BPs due to gastrointestinal trouble and impaired renal function.

• Investigative Magnetic Resonance Imaging
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• 제20권4호
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• pp.215-223
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• 2016

Purpose: The management of metal-induced field inhomogeneities is one of the major concerns of distortion-free magnetic resonance images near metallic implants. The recently proposed method called "Slice Encoding for Metal Artifact Correction (SEMAC)" is an effective spin echo pulse sequence of magnetic resonance imaging (MRI) near metallic implants. However, as SEMAC uses the noisy resolved data elements, SEMAC images can have a major problem for improving the signal-to-noise ratio (SNR) without compromising the correction of metal artifacts. To address that issue, this paper presents a novel reconstruction technique for providing an improvement of the SNR in SEMAC images without sacrificing the correction of metal artifacts. Materials and Methods: Low-rank approximation in each coil image is first performed to suppress the noise in the slice direction, because the signal is highly correlated between SEMAC-encoded slices. Secondly, SEMAC images are reconstructed by the best linear unbiased estimator (BLUE), also known as Gauss-Markov or weighted least squares. Noise levels and correlation in the receiver channels are considered for the sake of SNR optimization. To this end, since distorted excitation profiles are sparse, $l_1$ minimization performs well in recovering the sparse distorted excitation profiles and the sparse modeling of our approach offers excellent correction of metal-induced distortions. Results: Three images reconstructed using SEMAC, SEMAC with the conventional two-step noise reduction, and the proposed image denoising for metal MRI exploiting sparsity and low rank approximation algorithm were compared. The proposed algorithm outperformed two methods and produced 119% SNR better than SEMAC and 89% SNR better than SEMAC with the conventional two-step noise reduction. Conclusion: We successfully demonstrated that the proposed, novel algorithm for SEMAC, if compared with conventional de-noising methods, substantially improves SNR and reduces artifacts.

• 대한원격탐사학회지
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• 제25권1호
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• pp.21-30
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• 2009

본 논문의 목적은 원격 탐사 영상에서 잡음을 제거하기 위해 중심 화소와 통계적으로 유사한 이웃화소들을 선택하늘 방법을 제시하고 이 결과를 평균 곡률 확산과 결합하는 방법을 제시하는데 있다. 균일한 밝기값 영역에 속하는 화소들을 검출하기 위해 이웃 화소들을 순차적으로 선택할 때 그 선택하는 순서에 따라 선택된 영역의 통계적 특성이 달라지므로 이웃 화소의 선택 순서는 매우 중요하다. 본 논문에서는 통계적으로 유사한 특성을 가지는 이웃 화소를 선택하기 위해서 중심 화소와 이웃 화소의 밝기값 차를 계산하고 이를 크기 순으로 정렬하여 얻어지는 순위 차 벡터(rank-ordered differences vector)를 이용하는 효과적인 방법을 제안한다. 순위 차 벡터의 항들을 영역 확장 방법을 이용하여 균일 순위 차 벡터(homogeneous rank-ordered differences vector)와 이상점 순위 차 벡터 (outlier rank-ordered differences vector)로 분할한다. 균일 순위 차 벡터의 항에 속하는 이웃 화소에 대해서만 중심 화소의 밝기값 갱신에 기여하도록 확산 계수를 선택적으로 할당하는 라인 프로세스를 평균 곡률 확산에 결합한다. 제안한 방법은 모든 이웃 화소를 이용하여 중심 화소의 밝기값을 갱신하는 기존의 잡음 제거 필터에 비해 잡음 제거 효과가 뛰어남을 항공 영상 및 TerraSAR-X 위성 영상을 이용한 실험을 통해 확인하였다.

• 대한전기학회논문지:시스템및제어부문D
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• 제50권2호
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• pp.93-99
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• 2001

A new type geometric and mathematical network reduction model is introduced. Large-scale network is analyzed with analytic approach. The graph has many nodes, branches and loops. Circuit equation are obtained from these elements and connection rule. In this paper, the analytic relation between voltage source has a mutual different graphic property. Node-reduction procedure is achieved with this circuit property. Consequently voltage source value is included into the adjacent node-analyzing equation. A resultant model equations are reduced as much as voltage source number. Matrix rank is (n-1-k), where n, k is node and voltage source number. The reduction procedure is described and verified with geometric principle and circuit theory. Matrix type circuit equation can be composed with this technique. The last results shall be calculated by using computer.

• 한국통신학회논문지
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• 제36권2B호
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• pp.159-167
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• 2011

LTE-Advanced 시스템은 최대 15bps/Hz의 주파수 효율을 달성하기 위해 상향링크 다중 안테나 전송을 지원해야 한다 본 논문은 LTE-Advanced 상향링크 MIMO 시스템 구조를 제안하고 프리코딩에 의한 링크 적응방식을 고려하여 단말당 오류율을 줄이고 시스템 용량을 향상시키는데 기여할 수 있다 특히, $2{\times}4$ MIMO 시스템에서 최적의 프리코딩 행렬을 선택하여 랭크를 결정하는 방식을 제안하고 MMSE(minimum mean squared error) 수신기에 대한 SINR(signal-to-interference and noise ratio)을 유도한다. 제안 방식의 성능 검증을 위해 실질적인 MIMO 채널 모델에서 BLER(BLock Error Rate) 시뮬레이션을 수행한다. 제안 방식이 full-rank로 고정해서 보내는 경우 보다 더 좋은 성능을 발휘하며 MCS가 낮거나 고속 이동시에 더 큰 이득을 얻을 수 있다.

• 한국컴퓨터정보학회논문지
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• 제18권11호
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• pp.31-38
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• 2013

특징 정규화는 인식기를 적용하기 이전의 전처리 단계로 특징의 스케일에 따른 오류를 줄이기 위해 널리 사용되고 있다. 하지만 기존 정규화 방법은 특징의 분포를 가정하는 경우가 많으며, 클래스 라벨을 고려하지 않으므로 정규화 결과가 인식률에서 최적임을 보장하지 못하는 문제점이 있다. 이 논문에서는 특징의 분포를 가정하지 않는 랭크 정규화 방법과 클래스 라벨을 사용하는 교사 학습법을 결합한 교사 랭크 정규화 방법을 제안하였다. 제안하는 방법은 데이터의 분포를 바탕으로 특징의 분포를 자동으로 추정하므로 특징의 분포를 가정하지 않으며, 데이터 포인트의 최근접 이웃이 가지는 클래스 라벨을 바탕으로 정규화를 시행하므로 오류의 발생을 최소화할 수 있다. 특히 SVM의 경우 서로 다른 클래스에 속하는 데이터 포인트들이 혼재되어 나타나는 영역에 경계선을 설정하므로 이 영역의 밀도를 줄임으로써 경계선 설정을 보다 용이하게 하고 결과적으로 일반화 오류를 감소시킬 수 있다. 이러한 사실들은 실험 결과를 통해 확인할 수 있다.

• 대한물리치료과학회지
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• 제9권1호
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• pp.1-8
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• 2002

This study set out to investigate what kind of effects the consistent visual stimuli and verbal and non verbal auditory stimuli have on pain alleviation, as well as to see the influence of joint application of visual and auditory stimuli at the same time on pain alleviation, according to lightness of 50lux and 200lux, ultimately providing basic data in setting up an environment in case of treating pain. The subject were comprised of 30 male and female adults with pain in the neck and back area. The subject were treated in their pain area with Transcutaneous Electrical Nerve Stimulator(TENS) 100HZ for 20 minutes in the research set where each visual, auditory, and joint visual and auditory stimuli was given. For analysis methods, Visual Analogue Scale(VAS) and McGill Pain Questionnaire were adopted to see the changes before and after treatment, and the electrocardiogram, systolic and diastolic pressure, number of heart rate and breathing frequence and endorphin were compared and analyzed using the Wilcoxon singed-rank test. And The Kreskal-walllis test was used to compare the two subgroups from each group. Wilcoxon singed-rank test and the Kreskal-walllis test was used to compare the two subgroups from each group. The results were as follows: 1. The group of 50lux and 200lux were compared given varying degrees of visual stimuli. The group of 200lux showed more reduction in pain points, average systolic and diastolic pressure and average endorphin. 2. The group of verbal and non verbal were compared given varying degrees of auditory stimuli. The group of non-verbal showed more reduction in average systolic and diastolic pressure. 3. The group of 200lux+verbal and 200lux+non verbal were compared given varying degrees of joint visual and auditory stimuli. There was found a statistical significance(p<0.05) in endorphin between the two groups, with more endorphin reduction for 200lux+non verbal group. And there was a statistically significant reduction in VAS and McGill before and after the treatment between the two groups.

• 전자공학회논문지
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• 제52권4호
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• pp.145-155
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• 2015

디지털 영상 처리 분야에서 잡음 제거는 활발히 연구되어오고 있으며, 최근에는 블록 기반의 잡음 제거 알고리즘이 널리 사용되고 있다. 저계수행렬 근사 기반의 잡음 제거 알고리즘은 WNNM(Weighted Nuclear Norm Minimization)과 블록 기반의 잡음 제거 방법을 적용하여 잡음 제거 방법에 대한 잠재력을 입증했다. 그러나 저계수행렬 근사 기반의 잡음 제거 알고리즘은 영상복원 과정에서 의도치 않은 아티팩트를 발생시킨다. 본 논문에서는 STFT(Short Time Fourier Transform)을 이용해 영상을 분석하여 기존 알고리즘에서 발생하는 아티팩트를 적응적으로 최소화시키는 방법을 제안한다. 성능을 확인하기 위해 다양한 잡음정도를 포함하는 영상에서 실험하였으며, 비교를 통해 제안된 방법이 기존의 잡음 제거 알고리즘보다 효과적으로 잡음을 제거하는 것을 확인했다.