• 한국안전학회지
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• 제12권3호
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• pp.60-66
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• 1997

In this paper, a moving object surveillance system, which can extract moving object in real-time, using image subtraction method is described. This technique based on the novelty filter having the structure of neural network associative memory. Digital arithmetic and timing control parts were composed of hardwired controller to treat two-dimensional massive image information. SRAMS having 20 ns access time were used for the image buffer that has high speed write/read property. Image extraction algorithm is discussed and supported by simulation and experiments.

• 대한수학회논문집
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• 제25권2호
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• pp.173-184
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• 2010

Using $\cal{N}$-structures, the notion of an $\cal{N}$-ideal in a subtraction algebra is introduced. Characterizations of an $\cal{N}$-ideal are discussed. Conditions for an $\cal{N}$-structure to be an $\cal{N}$-ideal are provided. The description of a created $\cal{N}$-ideal is established.

• 한국정보전자통신기술학회논문지
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• 제7권1호
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• pp.61-67
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• 2014

Motion segmentation is a fundamental technique for analysing image sequences of real scenes. A process of identifying moving objects from data is a typical task in many computer vision applications. In this paper, we propose motion segmentation that generally consists from background subtraction and foreground pixel segmentation. The Approximated Median Filter(AMF) was chosen to perform background modeling. Motion segmentation in this paper covers RGB video data.

• 충청수학회지
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• 제32권4호
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• pp.441-451
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• 2019

In this paper, we introduce the notion of symmetric bi-f-derivation on subtraction algebra and investigated some related properties. Also, we prove that if D : X → X is a symmetric bi-f-derivation on X, then D satisfies D(x - y, z) = D(x, z) - f(y) for all x, y, z ∈ X.

• 대한음성학회:학술대회논문집
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• 대한음성학회 2003년도 5월 학술대회지
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• pp.207-210
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• 2003

In this paper, the combinations of speech enhancement techniques are experimented. Specifically, the spectral subtraction, KLT based comb-filtering, and their combinations are applied to the Aurora2 database. The results show that recognition accuracy is improved when KLT based comb-filtering is applied after spectral subtraction.

• Korean Journal of Mathematics
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• 제29권2호
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• pp.387-393
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• 2021

In this paper, we introduce the notion of symmetric bi-derivations on subtraction algebra and investigated some related properties. We prove that a map D : X × X → X is a symmetric bi-derivation on X if and only if D is a symmetric map and it satisfies D(x - y, z) = D(x, z) - y for all x, y, z ∈ X.

• The Journal of the Acoustical Society of Korea
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• 제22권2E호
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• pp.62-68
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• 2003

This paper addresses a novel noise-compensation scheme to solve the mismatch problem between training and testing condition for the automatic speech recognition (ASR) system, specifically in car environment. The conventional spectral subtraction schemes rely on the signal-to-noise ratio (SNR) such that attenuation is imposed on that part of the spectrum that appears to have low SNR, and accentuation is made on that part of high SNR. However, these schemes are based on the postulation that the power spectrum of noise is in general at the lower level in magnitude than that of speech. Therefore, while such postulation is adequate for high SNR environment, it is grossly inadequate for low SNR scenarios such as that of car environment. This paper proposes an efficient spectral subtraction scheme focused specifically to low SNR noisy environment by extracting harmonics distinctively in speech spectrum. Representative experiments confirm the superior performance of the proposed method over conventional methods. The experiments are conducted using car noise-corrupted utterances of Aurora2 corpus.

• The Journal of the Acoustical Society of Korea
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• 제22권2E호
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• pp.87-92
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• 2003

In this paper, a new speech enhancement method using level adapted wavelet packet is presented. First, we propose a level adapted wavelet packet to alleviate a drawback of the conventional node adapted one in noisy environment. Next, we suggest an adaptive noise estimation method at each node on level adapted wavelet packet tree. Then, for more accurate noise component subtraction, we propose a new estimation method of spectral subtraction weight. Finally, we present a modified spectral subtraction method. The proposed method is evaluated on various noise conditions: speech babble noise, F-l6 cockpit noise, factory noise, pink noise, and Volvo car interior noise. For an objective evaluation, the SNR test was performed. Also, spectrogram test and a very simple listening test as a subjective evaluation were performed.

• 융합신호처리학회논문지
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• 제14권4호
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• pp.231-234
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• 2013

This paper introduces a mixture of background subtraction technique and K-Means clustering algorithm for removing shadows from video sequences. Lighting conditions cause an issue with segmentation. The proposed method can successfully eradicate artifacts associated with lighting changes such as highlight and reflection, and cast shadows of moving object from segmentation. In this paper, K-Means clustering algorithm is applied to the foreground, which is initially fragmented by background subtraction technique. The estimated shadow region is then superimposed on the background to eliminate the effects that cause redundancy in object detection. Simulation results depict that the proposed approach is capable of removing shadows and reflections from moving objects with an accuracy of more than 95% in every cases considered.

• 사상체질의학회지
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• 제23권2호
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• pp.139-152
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• 2011

1. Objectives: This research was proposed to find out the selection and form of addition and subtraction of the Sasang prescription. 2.Methods: The related contents of the pathology and the medical action of a Sasang disease were selected in "Donguisusebowon- Sasangchobongyun, -Gabobon, -Shinchukbon(東醫壽世保元-四象草本卷, -甲午本, -辛丑本)", "Donguisasangsinfyun(東醫四象新編)". 3.Results and Conclusions: 1) The change and development of the Sasang prescription. 2) The selection of drugs are caused by immunity of the ordinary times and a class of present disease. 3) Addition and subtraction of the Sasang prescription can divide 4-type.