• Genomics & Informatics
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• v.1 no.2
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• pp.94-100
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• 2003

Motivation: Many have observed a nonlinear relationship between the signal intensity and the transcript abundance in microarray data. The first step in analyzing the data is to normalize it properly, and this should include a correction for the nonlinearity. The commonly used linear normalization schemes do not address this problem. Results: Nonlinearity is present in both cDNA and oligonucleotide arrays, but we concentrate on the latter in this paper. Across a set of chips, we identify those genes whose within-chip ranks are relatively constant compared to other genes of similar intensity. For each gene, we compute the sum of the squares of the differences in its within-chip ranks between every pair of chips as our statistic and we select a small fraction of the genes with the minimal changes in ranks at each intensity level. These genes are most likely to be non-differentially expressed and are subsequently used in the normalization procedure. This method is a generalization of the rank-invariant normalization (Li and Wong, 2001), using all available chips rather than two at a time to gather more information, while using the chip that is least likely to be affected by nonlinear effects as the reference chip. The assumption in our method is that there are at least a small number of non­differentially expressed genes across the intensity range. The normalized expression values can be substantially different from the unnormalized values and may result in altered down-stream analysis.

• 대한핵의학회:학술대회논문집
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• 2002.11a
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• pp.17.1-17.1
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• 2002

• IE interfaces
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• v.24 no.4
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• pp.314-322
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• 2011

This study analyzes a relationship between Data Envelopment Analysis(DEA) efficiency scores and a normalization index in order to examine the validity of DEA models. A normalization index concerned in this study is 'sales per R&D project fund' which is regarded as a crucial R&D project performance evaluation index in practice. For this correlation analysis, three distinct DEA models are selected such as DEA basic model, DEA/AR-I revised model(i.e. DEA basic model with Acceptance Region Type I constraints) and Super-Efficiency(SE) model. Especially, SE model is adopted where efficient R&D projects(i.e. Decision Making Units, DMU's) with DEA efficiency score of unity from DEA basic model can be further differentiated in ranks. Considering the non-normality and outliers, two rank correlation coefficients such as Spearman's ${\rho}_s$ and Kendall's ${\tau}_B$ are investigated in addition to Pearson's ${\gamma}$. With an up-to-date empirical massive dataset of n = 482 R&D projects associated with R&D Loan Program of Korea Information Communication Promotion Fund in the year of 2011, statistically significant (+) correlations are verified between the normalization index and every model's DEA efficiency scores with all three correlation coefficients. Especially, the congruence verified in this empirical analysis can be a useful reference for enhancing the practitioner's acceptability onto DEA efficiency scores as a real-world R&D project performance evaluation index.

• Korean Journal of Computational Design and Engineering
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• v.13 no.6
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• pp.403-411
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• 2008

The alignment of facial images is crucial for 2D face recognition. This is the same to facial meshes for 3D face recognition. Most of the 3D face recognition methods refer to 3D alignment but do not describe their approaches in details. In this paper, we focus on describing an automatic 3D alignment in viewpoint of quantitative analysis. This paper presents a framework of 3D face alignment and normalization based on feature points obtained by Active Shape Models (ASMs). The positions of eyes and mouth can give possibility of aligning the 3D face exactly in three-dimension space. The rotational transform on each axis is defined with respect to the reference position. In aligning process, the rotational transform converts an input 3D faces with large pose variations to the reference frontal view. The part of face is flopped from the aligned face using the sphere region centered at the nose tip of 3D face. The cropped face is shifted and brought into the frame with specified size for normalizing. Subsequently, the interpolation is carried to the face for sampling at equal interval and filling holes. The color interpolation is also carried at the same interval. The outputs are normalized 2D and 3D face which can be used for face recognition. Finally, we carry two sets of experiments to measure aligning errors and evaluate the performance of suggested process.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.51 no.1
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• pp.95-106
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• 2018

To evaluate appropriate reference genes for the normalization of quantitative reverse transcription PCR (RT-qPCR) data with embryonic and larval samples from Russian sturgeon Acipenser gueldenstaedtii, the expression stability of eight candidate housekeeping genes, including beta-actin (ACTB), elongation factor-1A (EF1A), glyceraldehyde-3-phosphate dehydrogenase (GAPDH), histone 2A (H2A), ribosomal protein L5 (RPL5), ribosomal protein L7 (RPL7), succinate dehydrogenase (SDHA), and ubiquitin-conjugating enzyme E2 (UBE2A), were tested using embryonic samples from 12 developmental stages and larval samples from 11 ontogenic stages. Based on the stability rankings from three statistic software packages, geNorm, NormFinder, and BestKeeper, the expression stability of the embryonic subset was ranked as UBE2A>H2A>SDHA>GAPDH>RPL5>EF1A>ACTB>RPL7. On the other hand, the ranking in the larval subset was determined as UBE2A>GAPDH>SDHA>RPL5>RPL7>H2A>EF1A>AC TB. When the two subsets were combined, the overall ranking was UBE2A>SDHA>H2A>RPL5>GAPDH>EF1A>ACTB>RPL7. Taken together, our data suggest that UBE2A and SDHA are recommended as suitable references for developmental and ontogenic samples of this sturgeon species, whereas traditional housekeepers such as ACTB and GAPDH may not be suitable candidates.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.4
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• pp.1-8
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• 1994

In this paper, we propose an efficient two-step pattern matching method which promises shape distortion-tolerant recognition of handwritten of handwritten Hangul syllables. In the first step, nonlinear shape normalization is carried out to compensate for global shape distortions in handwritten characters, then a preliminary classification based on simple pattern matching is performed. In the next step, nonlinear pattern matching which achieves best matching between input and reference pattern is carried out to compensate for local shape distortions, then detailed classification which determines the final result of classification is performed. As the performance of recognition systems based on pattern matching methods is greatly effected by the quality of reference patterns. we construct reference patterns by combining the proposed nonlinear pattern matching method with a well-known averaging techniques. Experimental results reveal that recognition performance is greatly improved by the proposed two-step pattern matching method and the reference pattern construction scheme.

• Proceedings of the Korea Water Resources Association Conference
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• 2011.05a
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• pp.460-460
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• 2011

국내에서는 수자원 정보화 사업에 일환으로 국가수자원종합정보시스템(WAMIS)을 개발하여 수자원에 관련된 많은 기초 자료 정보를 일반에 공개 제공하고 있으나, 주 이용 계층은 수자원관련 종사자 또는 연구자들이 대부분이다. 국가수자원종합정보시스템에서 제공하는 양질의 수자원 정보를 일반 국민들이 보다 쉽게 이해하고, 이용할 수 있도록 국내에서는 이들 기초자료를 바탕으로 다양한 수자원 지표 및 지수를 개발하였다. 이러한 수자원 관련 지표 및 지수를 개발하기 위해서는 서로 다른 단위와 특성을 가진 자료들을 모아 하나의 지표로 정의하는 과정이 필요하며, 하나의 지표로 정의되기 위해서는 반드시 표준화(normalization)과정이 필요하다. 국내에서 가장 보편적으로 사용하고 있는 방법은 Z-score법이며, 이외에도 가장 단순하고 간단한 방법인 Ranking 법, 자료의 극값(최대값, 최소값)을 이용하는 Re-scaling법, 일정 지표를 기준으로 하는 Distance to a reference country법 등이 있다. 표준화 방법은 각기 다른 장 단점을 가지고 있으며, 그 특성에 따라 정의되는 지표값은 다르게 나타날 수 있기에 지수값의 변화를 야기시킬 수 있다. 본 연구에서는 기 개발된 물이용안전성지수를 이용하여 기존 분석과 다양한 표준화 방법을 이용하여 지표를 산정하였을 때 표준화 방법에 따른 변화를 분석해 보고자 한다. 기존 연구에서 사용된 표준화 방법은 Z-score법이며, 다른 표준화 방법을 적용해 봄으로서 기존 산정 결과와의 차이를 비교 분석하였다. 지수를 구성하는 세부지표에 따라 수집되는 기초자료의 단위 및 특성은 다양하기 때문에 적합한 표준화 방법을 찾는 과정은 매우 중요하며, 이는 지표를 보다 정확하게 산정할 수 있도록 한다. 합리적인 표준화 방법을 통해 올바른 지수를 도출할 수 있고 객관적으로 수자원 환경을 평가할 수 있으며, 또한 수자원 계획 및 정책 개발에 있어 중요한 기준으로서 적용 할 수 있을 것으로 기대된다.

• Phonetics and Speech Sciences
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• v.4 no.2
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• pp.79-86
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• 2012

In this paper, we propose a novel approach to improve histogram equalization for speaker identification. Our method collects all speech features of UBM training data to make a reference distribution. The ranks of the feature vectors are calculated in the sorted list of the collection of the UBM training data and the test data. We use the ranks to perform order-based histogram equalization. The proposed method improves the accuracy of the speaker recognition system with short utterances. We use four kinds of speech databases to evaluate the proposed speaker recognition system and compare the system with cepstral mean normalization (CMN), mean and variance normalization (MVN), and histogram equalization (HEQ). Our system reduced the relative error rate by 33.3% from the baseline system.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.10
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• pp.1774-1779
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• 2016

This paper proposes a portable cable fault detection system with automatic fault distinction and distance measurement using time-frequency correlation and reference signal elimination method and automatic fault classification algorithm in order to have more accurate fault determination and location detection than conventional time domain refelectometry (TDR) system despite increased signal attenuation due to the long distance to cable fault location. The performance of the developed system method was validated via an experiment in the test field constructed for the standardized performance test of power cable fault location equipments. The performance evaluation showed that accuracy of the developed system is less than 1.34%. Also, an error of automatic fault type and location by detection of phase and peak value through elimination of the reference signal and normalization of correlation coefficient and automatic fault classification algorithm not occurred.

• Korean Journal of Remote Sensing
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• v.36 no.5_2
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• pp.917-927
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• 2020

The Ministry of Land, Infrastructure and Transport of Korea is developing a CAS 500-1/2 satellite capable of photographing a GSD 0.5 m level image, and is developing a technology to utilize this. Therefore, this study attempted to develop a geospatial feature extraction technique aimed at automation as a technique for utilizing CAS 500-1/2 satellite images. KOMPSAT-3A satellite images that are expected to be most similar to CAS 500-1/2 were used for research and the possibility of automation of geospatial feature extraction was analyzed through relative radiometric normalization. For this purpose, the parameters and thresholds were applied equally to the reference images and relative radiometric normalized images, and the geospatial feature were extracted. The qualitative analysis was conducted on whether the extracted geospatial feature is extracted in a similar form from the reference image and relative radiometric normalized image. It was also intended to analyze the possibility of automation of geospatial feature extraction by quantitative analysis of whether the classification accuracy satisfies the target accuracy of 90% or more set in this study. As a result, it was confirmed that shape of geospatial feature extracted from reference image and relative radiometric normalized image were similar, and the classification accuracy analysis results showed that both satisfies the target accuracy of 90% or more. Therefore, it is believed that automation will be possible when extracting spatial objects through relative radiometric normalization.