• Journal of Korea Multimedia Society
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• v.12 no.12
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• pp.1755-1760
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• 2009

In this research, for the first time, we tried to analyse Raman hyperspectral dentin data using Independent Component Analysis (ICA) to see its possibility of adoption for the dental analysis software. We captured hyperspectral dentin data on 569 spots on a molar with dental lesion by HR800 Micro Raman Spectrometer at UMKC-CRISP (University of Missouri at Kansas City-Center for Research on Interfacial Structure and Properties). Each spot has 1,005 hyperspectral data. We applied ICA to the captured hyperspectral data of dentin for evaluating ICA approach, and compared it with the well known multivariate analysis method, PCA. As a result of the experiment, ICA approach shows better local characteristic of dentin than the result of PCA. We confirmed that ICA also could be a good method along with PCA in the dental analysis software.

• Annals of Clinical Neurophysiology
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• v.3 no.1
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• pp.26-30
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• 2001

Purpose : Eyeball movement is one of the main artifacts in EEG. A new approach to the removal of these artifacts is presented using independent component analysis(ICA). This technique is a signal-processing algorithm to separate independent sources from unknown mixed signals. This study was performed to show that ICA is a useful method for the separation of EEG components with little data deformity. Methods : 12 sets of 10 sec digital EEG data including eye opening and closure were obtained using international 10~20 system scalp electrodes. ICA with 18 tracings of double banana bipolar montage was performed. Among obtained 18 independent components, two components, which were thought to be eyeball movements were removed. Other 16 components were reconstructed into original bipolar montage. Power spectral analysis of EEGs before and after ICA was done and compared statistically. Total 12 pairs of data were compared by visual inspection and relative power comparison. Results : Waveforms of each pair looked alike by visual inspection. Means of relative power before and after ICA were 29.16% vs. 28.27%, 12.12% vs. 12.41%, 10.55% vs. 10.52%, and 19.33% vs. 18. 33% for alpha, beta, theta, and delta, respectively. These values were statistically same before and after ICA. Conclusions : We found little data deformity after ICA and it was possible to isolate eyeball movements in EEG recordings. Many other components of EEG could be selectively separated using ICA.

• The KIPS Transactions:PartB
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• v.11B no.7 s.96
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• pp.813-820
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• 2004

This paper proposes a digital image watermarking which is robust to geometric distortions using an independent component analysis(ICA) of fixed-point(FP) algorithm based on secant method. The FP algorithm of secant method is applied for better performance in a separation time and rate, and ICA is applied to reject the prior knowledges for original image, key, and watermark such as locations and size, etc. The proposed method embeds the watermark into the spatial domain of original image The proposed watermarking technique has been applied to lena, key, and two watermarks(text and Gaussian noise) respectively. The simulation results show that the proposed method has higher speed and better rate for extracting the original images than the FP algorithm of Newton method. And the proposed method has a watermarking which is robust to geometric distortions such as resizing, rotation, and cropping. Especially, the watermark of images with Gaussian noise has better extraction performance than the watermark with text since Gaussian noise has lower correlation coefficient than the text to the original and key images. The watermarking of ICA doesn't require the prior knowledge for the original images.

• 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.

• Journal of Korean Society of Archives and Records Management
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• v.16 no.1
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• pp.223-245
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• 2016

Previously, the International Council of Archives (ICA) provided the General International Standard Archival Description (ISAD(G)) and the International Standard Archival Authority Record for Corporate Bodies, Persons and Families (ISAAR(CPF)) for the systematic archival description by the Committee on Best Practice and Standards. Recently, the new conceptual model and ontology, which is called "Record in Context" (RIC), is being developed by the ICA Experts Group on Archival Description (EGAD). For developing the new archival standard, ICA EGAD has referenced the archival standards of Australia, Spain, and Finland, as well as the FRBRoo integrated model of the museum and library fields and the legacy ICA's descriptive standards. This study, therefore, examined these international trends on the archival descriptive standards and derived a number of suggestions for improvement. As a result, descriptive standards are changing from the guidelines for the standardized archival description to the upper conceptual model and ontology for the flexible archival description and sharing of archival metadata. There is a need to adapt the change of the information environment and promote cooperation among cultural heritage institutions.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.5
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• pp.623-629
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• 2004

In this paper, a Efficient method for the mixed image separation is presented using independent component analysis and the new fast expectation-maximization(EM) algorithm. In general, the independent component analysis (ICA) is one of the widely used statistical signal processing scheme in various applications. However, it has been known that ICA does not establish good performance in source separation by itself. So, Innovation process which is one of the methods that were employed in image separation using ICA, which produces improved the mixed image separation. Unfortunately, the innovation process needs long processing time compared with ICA or EM. Thus, in order to overcome this limitation, we proposed new method which combined ICA with the New fast EM algorithm instead of using the innovation process. Proposed method improves the performance and reduces the total processing time for the Image separation. We compared our proposed method with ICA combined with innovation process. The experimental results show the effectiveness of the proposed method by applying it to image separation problems.

• The Journal of the Society of Korean Medicine Diagnostics
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• v.14 no.2
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• pp.85-100
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• 2010

Objectives: The purpose of this study was to evaluate diagnostic value of Transcranial Doppler Ultrasound about risk factor of stroke by comparing blood flow between patients with metabolic syndrome(MS group) and Normal group. Methods: 62 metabolic syndrome patients and 106 healthy adults were selected who had no cerebrovascular diseases, cardiovascular diseases and other systemic diseases. We measured the mean velocity(Vm), peak systolic velocity(Vs) and pulsatility index(PI) of MCA, ACA, PCA, VA, ICA in two groups using TCD. All subjects were divided by gender and age. Results: In comparing Ms group with normal group, Vm in the MCA, ACA, PCA, ICA and Vs in the MCA, ICA were lower in MS group. In all vessels, PI of MS group were higher than that of Normal group. In all vessels, Vm and Vs revealed negative correlation with age and PI revealed positive correlation with age. In 20-39 year olds, there was decrease in the Vs and Vm and increase of PI of MS group in comparison with normal group. There was significant difference in the Vm of PCA, ICA, Vs of MCA, PCA, ICA and PI of MCA, ACA. In 40-59 year olds, Vm in the MCA, ACA, ICA and Vs in the MCA, ACA were lower in MS group. PI in the MCA, ACA, PCA, ICA were higher in MS group. In 60-79 year olds, Vm of MCA, PCA, ICA was decreased in MS group than Normal group with no statistical signification. Vs in the MCA was lower and PI in the PCA was higher in MS group. In male, Vm of PCA and Vs of MCA were lower and PI of MCA, ACA, PCA, ICA were higher in MS group. In female, Vm of MCA, PCA, ICA and Vs of MCA, ICA were lower and PI of ACA, PCA, VA, ICA were higher in MS group. Conclusions: The significant difference in Vm, Vs, PI between MS group and normal group suggests hemodynamic disorder. Screening and prognosing high risk group can be done through TCD and this can be used to prevent stroke. More detailed study will be needed.

• 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.

• Journal of Korean Neurosurgical Society
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• v.37 no.2
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• pp.160-162
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• 2005

Aneurysms arising at locations other than arterial division are rare and the incidence of intraoperative bleeding is far higher in such aneurysms than in usual aneurysms. The authors report a case of intraoperative rupture and laceration on internal carotid artery(ICA) wall during dissecting a dorsal wall aneurysm on supraclinoid ICA and successful repair of the laceration on the parent ICA with microsuture and a Sundt clip-graft.

• Proceedings of the Korean Information Science Society Conference
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• 2001.04a
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• pp.505-507
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• 2001

본 논문에서는 그람-슈미트 방법 및 독립 성분 해석(Independent Component Analysis, ICA)기법을 이용한 영상분리방법을 제안한다. 이 제안된 방법은 전처리 없이 ICA나 주성분 해석(Principal Component Analysis, PCA)을 이용한 것에 비해 개선된 영상을 보여준다. 이는 원래의 ICA 모델에 대하여 동일한 조건으로 일반화하여 그람-슈미트의 독립된 성분들이 ICA 모델에 충분히 동일하다는 것을 보여준다.