• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.3
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• pp.294-299
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• 2005

This paper presents the separation performance of the linearly mixed image signals with additive noises by using an independent component analyses(ICAs) of the fixed-point(FP) algorithm based on Newton and secant method, respectively. The Newton's FP-ICA uses the slope of objective function, and the secant's FP-ICA also uses the tangent line of objective function. The 2 kinds of ICA have been applied to the 2 dimensional 2-image with $512\times512$ pixels. Then Gaussian noise and Laplacian noise are added to the mixed images, respectively. The experimental results show that the Newton's FP-ICA has better the separation speed than secant FP-ICA and the secant's FP-ICA has also the better separation rate than Newton's FP-ICA. Especially, the Newton and secant method gives relatively larger improvement degree in separation speed and rate as the noise increases.

• Bulletin of the Korean Chemical Society
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• v.35 no.10
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• pp.3115-3118
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• 2014

• Sleep Medicine and Psychophysiology
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• v.8 no.1
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• pp.67-71
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• 2001

Independent Component Analysis (ICA) is a blind source separation method using unsupervised learning and mutual information theory created in the late eighties and developed in the nineties. It has already succeeded in separating eye movement artifacts from human scalp EEG recording. Several characteristic sleep waves such as sleep spindle, K-complex, and positive occipital sharp transient of sleep (POSTS) can be recorded during sleep EEG recording. They are used as stage determining factors of sleep staging and might be reflections of unknown neural sources during sleep. We applied the ICA method to sleep EEG for sleep waves separation. Eighteen channel scalp longitudinal bipolar montage was used for the EEG recording. With the sampling rate of 256Hz, digital EEG data were converted into 18 by n matrix which was used as a original data matrix X. Independent source matrix U (18 by n) was obtained by independent component analysis method ($U=W{\timex}X$, where W is an 18 by 18 matrix obtained by ICA procedures). ICA was applied to the original EEG containing sleep spindle, K-complex, and POSTS. Among the 18 independent components, those containing characteristic shape of sleep waves could be identified. Each independent component was reconstructed into original montage by the product of inverse matrix of W (inv(W)) and U. The reconstructed EEG might be a separation of sleep waves without other components of original EEG matrix X. This result (might) demonstrates that characteristic sleep waves may be separated from original EEG of unknown mixed neural origins by the Independent Component Analysis (ICA) method.

• KSBB Journal
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• v.18 no.1
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• pp.70-73
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• 2003

TLC condition was developed for its simple separation and quantitative analysis of lactic acid. Rapid and clear separation of lactic acid by silica gel TLC plate was obtained by using nitromethane : 1-propanol : $H_2O$ (2 : 5 : 1.5, v/v/v) and a suitable dipping solution of 40 mg bromocresol purple in 100 mL 5% ethanol (pH 10.0). The lactic acid was shown as a bright yellow spot on a light cinnabar background. The quantitatively detectable concentration range of lactic acid was between 0.5 and 4% with 99.4%, confidence. Quantitative TLC analysis result was confirmed with HPLC and with enzymatic Quantitative analysis methods (by using lactate dehydrogenase).

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.10
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• pp.4072-4091
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• 2015

A separation of text and non-text elements plays an important role in document layout analysis. A number of approaches have been proposed but the quality of separation result is still limited due to the complex of the document layout. In this paper, we present an efficient method for the classification of text and non-text components in document image. It is the combination of whitespace analysis with multi-layer homogeneous regions which called recursive filter. Firstly, the input binary document is analyzed by connected components analysis and whitespace extraction. Secondly, a heuristic filter is applied to identify non-text components. After that, using statistical method, we implement the recursive filter on multi-layer homogeneous regions to identify all text and non-text elements of the binary image. Finally, all regions will be reshaped and remove noise to get the text document and non-text document. Experimental results on the ICDAR2009 page segmentation competition dataset and other datasets prove the effectiveness and superiority of proposed method.

• MALSORI
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• no.48
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• pp.81-91
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• 2003

In this paper, we propose a speech recognition method based on independent component analysis (ICA) and spectral enhancement techniques. While ICA tris to separate speech signal from noisy speech using multiple channels, some noise remains by its algorithmic limitations. Spectral enhancement techniques can compensate for lack of ICA's signal separation ability. From the speech recognition experiments with instantaneous and convolved mixing environments, we show that the proposed approach gives much improved recognition accuracies than conventional methods.

• Proceedings of the Korean Information Science Society Conference
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• 2001.10b
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• pp.304-306
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• 2001

Various methods for blind source separation (BSS) are based on independent component analysis (ICA) which can be viewed as a nonlinear extension of principal component analysis (PCA). Most existing ICA methods require certain nonlinear functions, the shapes of which depend on the probability distributions of sources (which is not known in advance), whereas FCA is a linear learning method based on only second-order statistics. In this paper we show how BSS can be achieved by FCA, provided that sources are spatially uncorrelated but temporally correlated.

• Journal of The Korean Society of Agricultural Engineers
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• v.59 no.2
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• pp.1-11
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• 2017

The analysis of baseflow contribution is very significant in Korea because most rivers have high variability of streamflow due to the monsoon climate. Recently, the importance of such analysis is being more evident especially in terms of river management because of the changing pattern of rainfall and runoff resulted from climate change. Various baseflow separation methods have been developed to separate baseflow from streamflow. However, it is very difficult to identify which method is the most accurate way due to the lack of measured baseflow data. Moreover, it is inappropriate to analyze the annual baseflow contribution for Korean rivers because rainfall patterns varies significantly with the seasons. Thus, this study compared the baseflow contributions at various time-scales (annual, seasonal and monthly) for the 4 major river basins through BFI (baseflow index) and suggested baseflow contribution of each basin by the BFI ranges searched from different baseflow separation methods (e.g., BFLOW, HYSEP, PART, WHAT). Based on the comparison of baseflow contributions at the three time scales, this study showed that the baseflow contributions from the monthly and seasonal analysis are more reasonable than that from the annual analysis. Furthermore, this study proposes that defining BFI with its range is more proper than a specific value for a watershed, considering the difference of BFIs between various baseflow separation methods.

• Proceedings of the IEEK Conference
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• 2001.10a
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• pp.111-116
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• 2001

Waste office paper, photocopied or laser printed, has recently increased along with office automatization. In waste office paper, toner ink is used as the printing medium in place of conventional oil ink. Since toner ink cannot be saponificated by alkali and be decolored by bleaching, different from the case of oil ink, toner remains on regenerated paper as black specks. Although cascade recycling of waste office paper is compelled at present, the demand for low-grade paper is limited. From such circumstances, a new separation process for waste office paper is demanded to achieve parallel recycling. At the first stage of separation studies, the sharpness of separation is evaluated using small separators to obtain fundamental data. In a lab-scale separator, the sample amount of one feed is generally a few grams. However, the sample amount used for brightness, ERIC, and image analysis that are generally used to evaluate the efficiency of deinking are not small for lab-scale tests of these analyses. This paper describes an investigation of a sheet preparation method by a small amount of sample under 0.5g and compares the precision of toner content determination of spectroscopic analysis and image analysis from the viewpoint of separation evaluation. The easiness and convenience of the operation using only general-purpose equipments has also been set as a principle purpose. From the viewpoint of an analysis that yields high precision with a small amount of sample in short time, the method calculating the absorption coefficient from diffuse reflectance in the visible region is the most rational method in this study.

• Journal of the Korean Society of Propulsion Engineers
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• v.19 no.2
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• pp.1-8
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• 2015

Dual pulse rocket motor is a variant of solid rocket motor with two propellant grain separated by a pulse separation device. The major performance of such a rocket motor is influenced by the change in the hole area of pulse separation device to nozzle throat area ratio. In this study, we performed flow analysis to investigate the internal flow characteristics according to the pulse separation device hole area to nozzle throat area ratio change. Gases used flow analysis were used combustion gas of HTPB/AP composite propellant and nitrogen gas. Flow analysis results of the dual pulse rocket motor were validated by comparison with experimental results of pneumatics. Commercial CFD code ANSYS FLUENT 14.5 is used in this study to simulate flow analysis.