• Genomics & Informatics
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• v.17 no.4
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• pp.47.1-47.12
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• 2019

The achievements of genome-wide association studies have suggested ways to predict diseases, such as type 2 diabetes (T2D), using single-nucleotide polymorphisms (SNPs). Most T2D risk prediction models have used SNPs in combination with demographic variables. However, it is difficult to evaluate the pure additive contribution of genetic variants to classically used demographic models. Since prediction models include some heritable traits, such as body mass index, the contribution of SNPs using unmatched case-control samples may be underestimated. In this article, we propose a method that uses propensity score matching to avoid underestimation by matching case and control samples, thereby determining the pure additive contribution of SNPs. To illustrate the proposed propensity score matching method, we used SNP data from the Korea Association Resources project and reported SNPs from the genome-wide association study catalog. We selected various SNP sets via stepwise logistic regression (SLR), least absolute shrinkage and selection operator (LASSO), and the elastic-net (EN) algorithm. Using these SNP sets, we made predictions using SLR, LASSO, and EN as logistic regression modeling techniques. The accuracy of the predictions was compared in terms of area under the receiver operating characteristic curve (AUC). The contribution of SNPs to T2D was evaluated by the difference in the AUC between models using only demographic variables and models that included the SNPs. The largest difference among our models showed that the AUC of the model using genetic variants with demographic variables could be 0.107 higher than that of the corresponding model using only demographic variables.

• Journal of the Korean Society for Precision Engineering
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• v.20 no.7
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• pp.138-146
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• 2003

A critical issue in area-based stereo matching lies in selecting a fixed rectangular window size. Previous stereo methods doesn't deal effectively with occluding boundary due to inevitable window-based problems, and so give inaccurate and noisy matching results in areas with steep disparity variations. In this paper, a variable window approach is presented to estimate accurate, detailed and smooth disparities for three-dimensional structure reconstruction. It makes the smoothing of depth discontinuity reduced by evaluating corresponding correlation values and intensity gradient-based similarity in the three-dimensional disparity space. In addition, it investigates maximum connected match candidate points and then devise the novel arbitrarily shaped variable window representative of a same disparity to treat with disparity variations of various structure shapes. We demonstrate the performance of the proposed variable window method with synthetic images, and show how our results improve on those of closely related techniques for accuracy, robustness, matching density and computing speed.

• Journal of Biomedical Engineering Research
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• v.28 no.5
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• pp.601-608
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• 2007

2 Dimensional Gel Electrophoresis(2DGE) is an essentialmethodology for analysis on the expression of various proteins. For example, information for the location, mass, expression, size and shape of the proteins obtained by 2DGE can be used for diagnosis, prognosis and biological progress by comparison of patients with the normal persons. Protein spot matching for this purpose is comparative analysis of protein expression pattern for the 2DGE images generated under different conditions. However, visual analysis of protein spots which are more than several hundreds included in a 2DGE image requires long time and heavy effort. Furthermore, geometrical distortion makes the spot matching for the same protein harder. In this paper, an iterative algorithm is introduced for more efficient spot matching. Proposed method is first performing global matching step, which reduces the geometrical difference between the landmarks and the spot to be matched. Thus, movement for a spot is defined by a weighted sum of the movement of the landmark spots. Weight for the summation is defined by the inverse of the distance from the spots to the landmarks. This movement is iteratively performed until the total sum of the difference between the corresponding landmarks is larger than a pre-selected value. Due to local distortion generally occurred in 2DGE images, there are many regions in whichmany spot pairs are miss-matched. In the second stage, the same spot matching algorithm is applied to such local regions with the additional landmarks for those regions. In other words, the same method is applied with the expanded landmark set to which additional landmarks are added. Our proposed algorithm for spot matching empirically proved reliable analysis of protein separation image by producing higher accuracy.

• Transactions on Electrical and Electronic Materials
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• v.18 no.5
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• pp.273-278
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• 2017

Recently, one of the areas where research is being actively conducted is the Internet of Things (IoT). The field of using the Internet of Things system is increasing, coupled with a remarkable increase of the use of the camera. However, general cameras used in the Internet of Things have limited viewing angles as compared to those available to the human eye. Also, cameras restrict observation of objects and the performance of observation. Therefore, in this paper, we propose a panoramic image stitching method using feature extraction and matching based on an embedded system. After extracting the feature of the image, the speed of image stitching is improved by reducing the amount of computation using the necessary information so that it can be used in the embedded system. Experimental results show that it is possible to improve the speed of feature matching and panoramic image stitching while generating a smooth image.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.3
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• pp.167-173
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• 2023

The cash flow matching problem(CFMP) aims to minimize the initial investment by paying the total amount due for the T-year in principal and interest of bonds or bank deposits without paying the full amount in cash. Linear programming(LP) is the only known way to solve CFMP. The linear programming method is a problem that optimizes T linear functions, and it cannot be solved by handwriting, so LINGO, which is a solution to the linear programming method, is used. This paper proposes an algorithm that obtains the solution of CFMP solely by handwriting without the help of LINGO. The proposed algorithm determines the amount of bond purchases by covering payments until the previous year of the next maturity bond in the order that the maturity date falls from the longest to the short term. In addition, until the year before the maturity of the shortest maturity bond, the amount of deposit covered by the principal and interest of the bank deposit was determined. As a result of applying the proposed algorithm to two experimental data, it was shown that more accurate results can be obtained compared to the linear programming method.

• Journal of the Korea Convergence Society
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• v.11 no.10
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• pp.97-106
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• 2020

The factory information provided by the Industrial Location Information System (ILIS) is provided as raw data by the Korea Industrial Complex Corporation and registered after a filtering process, so the new factory information update is slow. In this study, to solve the problem of updating factory information of industrial location information system, using building data of road name address with relatively fast renewal cycle and building data of real estate, we compared the factory information of existing ILIS and extracted new factory information. In the process of comparison, a method was proposed to compare spatial objects of different types with point data and polygon data. Attribute information matching and object matching were performed, and attribute values of new factory information were extracted. The accuracy evaluation of the proposed spatial analysis method showed 79% accuracy, and the above matching technique was used to confirm the possibility of convergence of road name address data, real estate data and factory information of ILIS.

• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.6-8
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• 2005

Study that uses geometrical information in computer vision is lively. Problem that should be preceded is matching problem before studying. Feature point should be extracted for well matching. There are a lot of methods that extract feature point from former days are studied. Because problem does not exist algorithm that is applied for all images, it is a hot water. Specially, it is not easy to find feature point in endoscope image. The big problem can not decide easily a point that is predicted feature point as can know even if see endoscope image as eyes. Also, accuracy of matching problem can be decided after number of feature points is enough and also distributed on whole image. In this paper studied algorithm that can apply to endoscope image. SIFT method displayed excellent performance when compared with alternative way (Affine invariant point detector etc.) in general image but SIFT parameter that used in general image can't apply to endoscope image. The gual of this paper is abstraction of feature point on endoscope image that controlled by contrast threshold and curvature threshold among the parameters for applying SIFT method on endoscope image. Studied about method that feature points can have good distribution and control number of feature point than traditional alternative way by controlling the parameters on experiment result.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.10
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• pp.1310-1316
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• 2021

Recently, with the development of artificial intelligence and IoT technology, the importance of video processing such as object tracking, medical imaging, and object recognition is increasing. In particular, the noise reduction technology used in the preprocessing process demands the ability to effectively remove noise and maintain detailed features as the importance of system images increases. In this paper, we provide a modified weight filter based on pixel matching in an AWGN environment. The proposed algorithm uses a pixel matching method to maintain high-frequency components in which the pixel value of the image changes significantly, detects areas with highly relevant patterns in the peripheral area, and matches pixels required for output calculation. Classify the values. The final output is obtained by calculating the weight according to the similarity and spatial distance between the matching pixels with the center pixel in order to consider the edge component in the filtering process.

• Journal of Information Display
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• v.13 no.1
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• pp.7-16
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• 2012

In this paper, the problem concerning the color accuracy of imaging systems using color filters is examined. It is shown that the only solution to the problem is to build systems with the spectral response matching the CIE curves as closely as possible. If the spectral response does not closely match the CIE curves, it was demonstrated that calibration cannot solve the problem and will result in very unstable colorimeters. A practical solution that uses telecentric lenses on the sensor side in addition to dedicated color filters for each CCD detector is presented. For systems that closely match the CIE curves, an innovative method of improving the color accuracy based on the precise measurement of the spectral response is presented. The small discrepancies in the spectral response with regard to the CIE curves are corrected in different ways during the measurements. Finally, it is shown that the tristimulus calibration that is used for display measurement is very unstable for systems without CIE matching and is much more stable with systems that closely match the CIE curves.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.41 no.5
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• pp.541-550
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• 1992

The fourth harmonic conversion(FHC) efficiency of high-power Nd laser pulse with wavelength of 1.054x10S0-6Tm using two KDP crystals(doubler adn quadrupler) was simulated numerically. Simulation results show that for the perfect phase-matching condition the FHC efficiency were 60-70% for several hundreds MW/cmS02T class and over 70% for GW/cmS02T class laser pulses. And the overall characteristics of FHC were discussed in terms of effects of input intensity, crystal length, and mismatch angle Δ$\theta$. Optimum method to FHC was type-II doubler & type-I quadrupler KDP crystal because type-II KDP doubler crystal has wide tolerance of acceptance matching-angle.