• Proceedings of the Korean Information Science Society Conference
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• 2004.10b
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• pp.250-252
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• 2004

In this paper we apply several variations of independent component analysis( ICA) methods, such as spatial ICA (sICA), temporal ICA (tICA), and spatiotemporal ICA (stICA), to yeast cell cycle datasets, and compare their performance in finding components that result in gene clusters coherent with annotations and in extract ins meaningful temporal modes. It turns out that the results of tICA are superior to those of PCA, sICA, and stICA in terms of gene clustering and the temporal modes extracted by stICA highlights particular cellular processes.

• Proceedings of the Korean Information Science Society Conference
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• 1999.10b
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• pp.470-472
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• 1999

Sparse coding은 최소한의 active한 (non-orthogonal) basis vector를 이용하여 데이터를 표시하는 하나의 방법이다. Sparse coding에서 basis coefficient들이 statistically independent 하다는 constraint를 주기에 sparse coding은 independent component analysis(ICA)와 밀접한 관계를 가지고 있다. 본 논문에서는 sparse representation을 위하여 super-Gaussian prior를 이용한 ICA, 즉 sparse ICA 방법을 제시한다. Sparse ICA 방법을 이용하여 natural scenes의 basis vector를 찾고 이와 sparse coding과의 관계를 고찰한다. 여러 가지 super-Gaussian prior들을 고려하지 않고 이들이 ICA에 미치는 영향에 대해 살펴본다.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.367-369
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• 2004

In this paper we propose an effective and reliable hand detection method using neural network with ICA(Independent Component Analysis) Features. Many algorithms of hand detection have been proposed yet. Among them, ICA is the one of the interesting topics in image processing. ICA can not only separate mixed signals but also efficiently extract low-dimensional features in signals. ICA features are able to represent the characteristic of the images well. The object of this paper is to use effectively ICA that has above advantage. That is, by the proper number of Independent component the arithmetic speed is faster and by normalization of ICA feature the performance of detection is more reliable. For this, we adopt the algorithm, the Proportion of variance, which select the ICA feature by comparing the ratio of variance of ICA feature. By this method, we can extract the feature that is good at classifying hand and non-hand. Our experimental results show that by using ICA features, we obtained a better performance in hand detection than by only training NN on the image. And we can use hand detection system effectively and reliably by our proposal.

• THE INTERNATIONAL COMMERCE & LAW REVIEW
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• v.35
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• pp.125-144
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• 2007

The objective of this study is to find out whether Korean companies which are doing a lot of commercial transactions with Indian companies can consider appointing ICA as a trustworthy institution and using ICA arbitration rules as a governing arbitration rule, when a dispute between Korean companies and Indian companies occurs. Up to now, in the case of dispute with Indian companies, Korean companies are hesitant to utilize ICA as well as ICA arbitration rules as a alternative dispute resolution, owing to lack of understanding on its rules. But, it is obvious that Korean companies which come to have better knowledge on ICA and its rules may consider more positively using ICA as well as ICA arbitration rules as a dispute resolution rather than using other arbitration institutions like ICC and KCAB etc. in the case of disputes with Indian companies because ICA arbitration rules are very objective and similar to other arbitration rules like ICC rules as well as KCAB(Korean Commercial Arbitration Board) international arbitration rules which are frequently being used by Korean companies and also have other several advantages like cheaper cost of arbitration and fast track arbitration procedures. In conclusion, ICA and its rules can also be recommended as a public-trustworthy arbitration option if Korean companies want to resolve some dispute cases with Indian companies.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.7
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• pp.3419-3424
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• 2013

Diverse immunoassays including a chemiluminescent immunoassay (CIA) are used to detect hepatitis B surface antigen (HBsAg) and antibody (anti-HBs). Recently, an increasing number of institutions have been utilizing an immunochromatography assay (ICA), which is easy to use. In this study, We evaluated ICA kits for the rapid detection of HBsAg and anti-HBs by comparing them with a CIA. A total of 120 serum hospital samples, were collected for the whole month, were assayed using ICA kit. The Concordance rate, sensitivity, specificity, positive predictive value and negative predictive value of the ICA for HBsAg based on CIA results were 97%, 97%, 100%, 100%, and 96.8%, respectively. The diagnostic performances of the ICA for Anti-HBs were 90%, 90%, 93.3%, 93.1%, and 90.3%, respectively. The ICA kit failed to detect HBsAg and anti-HBs in low reactive samples. The ICA kits for the rapid detection of HBsAg might be recommended for interpreted with caution and dual analysis in the clinical laboratory.

• Journal of KIISE:Software and Applications
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• v.33 no.5
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• pp.481-488
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• 2006

The performance of face recognition methods using subspace projection is directly related to the characteristics of their basis images, especially in the cases of local distortion or partial occlusion. In order for a subspace projection method to be robust to local distortion and partial occlusion, the basis images generated by the method should exhibit a part-based local representation. We propose an effective part-based local representation method named locally salient ICA (LS-ICA) method for face recognition that is robust to local distortion and partial occlusion. The LS-ICA method only employs locally salient information from important facial parts in order to maximize the benefit of applying the idea of 'recognition by parts.' It creates part-based local basis images by imposing additional localization constraint in the process of computing ICA architecture I basis images. We have contrasted the LS-ICA method with other part-based representations such as LNMF (Localized Non-negative Matrix Factorization) and LFA (Local Feature Analysis). Experimental results show that the LS-ICA method performs better than PCA, ICA architecture I, ICA architectureII, LFA, and LNMF methods, especially in the cases of partial occlusions and local distortions.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.4
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• pp.687-692
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• 2006

In a conventional ICA(Independent Component Analysis) based face recognition method, PCA(Principal Component Analysis) first is used for feature extraction, ICA learning method then is applied for feature enhancement in the reduced dimension. It is not considered that a necessary component can be located in the discarded feature space. In the new ICA(NICA), learning extracts features using the magnitude of kurtosis (4-th order central moment or cumulant). But, the pure ICA method can not discard noise effectively. The synergy effect of PCA and ICA can be achieved if PCA is used for noise reduction filter. Namely, PCA does whitening and noise filtering. ICA performs feature extraction. Experiment results show the effectiveness of the new ICA method compared to the conventional ICA approach.

• Proceedings of the Korean Information Science Society Conference
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• 1999.10b
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• pp.467-469
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• 1999

Independent component analysis (ICA)는 주어진 데이터를 통계적으로 독립인 요소들의 선형 결합으로 표시하는 통계학적 방법이다. ICA의 주요한 적용분야중의 하나는 source들의 선형 mixture로부터 어떠한 서전 정보도 없는 상태에서 원래의 통계학적 독립변수인 source를 복원하는 blind separation이다. ICA와 source separation을 위한 다양한 신경 학습 알고리듬이 제시되어왔다. ICA의 학습 알고리듬에서는 비선형 함수가 중요한 역할을 한다. 이 논문에서는 generalized 가우시안 prior를 도입하여 다양한 확률분포를 갖는 source들의 mixture를 분리하는 효율적인 source separation 알고리즘을 제시한다. 모의실험을 통하여 제안된 방법의 우수성을 살펴본다.

• Journal of the Korean Society of Clothing and Textiles
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• v.22 no.8
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• pp.971-977
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• 1998

For the purpose of standardization and practicability of nautral dyeing, the mordanting and dyeing properties of Rhusjara ica was studied. Appropriate extraction, dyeing and mordanting condition of Rhusjara ica were determined, and the effect of mordanting method on dye uptake and color fastness of dyed fabric was investigated. The most absorbance of Rhusjara ica solution was 299 nm. The color of Rhusjara ica solution was affected by pH 8~9. The optimum temperature to extract Rhusjara ica was 6$0^{\circ}C$ and dyeing solution for 1 hour. Effective dyeing time to silk was 60min. Effective mordanting temperature was 80~10$0^{\circ}C$, and its time was 30 min. K/S value of dyeing fabrics was recoginazed by mordanting treatment, specially Fe, Al, Cu. K/S value of pre-mordanting was higher than post-mordanting. In the case of Rhusjara ica fastness was increased by mordanting treatment.

• Journal of Biomedical Engineering Research
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• v.30 no.5
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• pp.373-380
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• 2009

In general, Independent component analysis (ICA) is a statistical blind source separation technique, used either in spatial or temporal domain. The spatial or temporal ICAs are designed to extract maximally independent sources in respective domains. The underlying sources for spatiotemporal data (sequence of images) can not always be guaranteed to be independent, therefore spatial ICA extracts the maximally independent spatial sources, deteriorating the temporal sources and vice versa. For such data types, spatiotemporal ICA tries to create a balance by simultaneous optimization in both the domains. However, the spatiotemporal ICA suffers the problem of source ambiguity. Recently, constrained ICA (c-ICA) has been proposed which incorporates a priori information to extract the desired source. In this study, we have extended the c-ICA for better analysis of spatiotemporal data. The proposed algorithm, i.e., constrained spatiotemporal ICA (constrained st-ICA), tries to find the desired independent sources in spatial and temporal domains with no source ambiguity. The performance of the proposed algorithm is tested against the conventional spatial and temporal ICAs using simulated data. Furthermore, its performance for the real spatiotemporal data, functional magnetic resonance images (fMRI), is compared with the SPM (conventional fMRI data analysis tool). The functional maps obtained with the proposed algorithm reveal more activity as compared to SPM.