• Asian-Australasian Journal of Animal Sciences
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• 제27권12호
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• pp.1691-1694
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• 2014

Copy number variation (CNV) or single nucleotide phlyorphism (SNP) is useful genetic resource to aid in understanding complex phenotypes or deseases susceptibility. Although thousands of CNVs and SNPs are currently avaliable in the public databases, they are somewhat difficult to use for analyses without visualization tools. We developed a web-based tool called the VCS (visualization of CNV or SNP) to visualize the CNV or SNP detected. The VCS tool can assist to easily interpret a biological meaning from the numerical value of CNV and SNP. The VCS provides six visualization tools: i) the enrichment of genome contents in CNV; ii) the physical distribution of CNV or SNP on chromosomes; iii) the distribution of log2 ratio of CNVs with criteria of interested; iv) the number of CNV or SNP per binning unit; v) the distribution of homozygosity of SNP genotype; and vi) cytomap of genes within CNV or SNP region.

• 천문학회보
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• 제36권1호
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• pp.59.1-59.1
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• 2011

We report the HST pixel analysis results of the interacting S0 galaxy, NGC 5195 (M51B), using the HST/ACS images in the F435W, F555W and F814W (BVI) bands. After 4x4 binning of the HST/ACS images to secure sufficient signal-to-noise ratio for each pixel, we derive several quantities describing the pixel color-magnitude diagram (pCMD) of NGC 5195, such as blue/red color cut, red pixel sequence parameters, blue pixel sequence parameters and blue-to-red pixel ratio. Those parameters reflect the internal properties of NGC 5195 like age, metallicity, dust content and galaxy morphology. To investigate the spatial distributions of stellar populations, we divide pixel stellar populations using the pixel color-color diagram and population synthesis models. As a result, we find that the tidal interaction with NGC 5194 significantly affects the stellar populations in their dust content and mean stellar age.

• 한국응용약물학회:학술대회논문집
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• 한국응용약물학회 2007년도 Proceedings of The Convention
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• pp.19-27
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• 2007

An important potential of metabolomics-based approach is the possibility to develop fingerprints of diseases or cellular responses to classes of compounds with known common biological effect. Such fingerprints have the potential to allow classification of disease states or compounds, to provide mechanistic information on cellular perturbations and pathways and to identify biomarkers specific for disease severity and drug efficacy. Metabolic profiles of biological fluids contain a vast array of endogenous metabolites. Changes in those profiles resulting from perturbations of the system can be observed using analytical techniques, such as NMR and MS. $^1H$ NMR was used to generate a molecular fingerprint of serum or urinary sample, and then pattern recognition technique was applied to identity molecular signatures associated with the specific diseases or drug efficiency. Several metabolites that differentiate disease samples from the control were thoroughly characterized by NMR spectroscopy. We investigated the metabolic changes in human normal and clinical samples using $^1H$ NMR. Spectral data were applied to targeted profiling and spectral binning method, and then multivariate statistical data analysis (MVDA) was used to examine in detail the modulation of small molecule candidate biomarkers. We show that targeted profiling produces robust models, generates accurate metabolite concentration data, and provides data that can be used to help understand metabolic differences between healthy and disease population. Such metabolic signatures could provide diagnostic markers for a disease state or biomarkers for drug response phenotypes.

• 대한원격탐사학회지
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• 제24권5호
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• pp.397-408
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• 2008

A wide variety of applications of imaging spectrometer have been proved using data from airborne systems. The Compact Airborne Imaging Spectrometer System (CAISS) was jointly designed and developed as the airborne hyperspectral imaging system by Korea Aerospace Research Institute (KARI) and ELOP inc., Israel. The primary mission of the CAISS is to acquire and provide full contiguous spectral information with high spatial resolution for advanced applications in the field of remote sensing. The CAISS consists of six physical units; the camera system, the gyro-stabilized mount, the jig, the GPS/INS, the power inverter and distributor, and the operating system. These subsystems are to be tested and verified in the laboratory before the flight. Especially the camera system of the CAISS has to be calibrated and validated with the calibration equipments such as the integrating sphere and spectral lamps. To improve data quality and its availability, it is the most important to understand the mechanism of imaging spectrometer system and the radiometric and spectral characteristics. The several performance tests of the CAISS were conducted in the camera system level. This paper presents the major characteristics of the CAISS, and summarizes the results of performance tests in the camera system level.

• 천문학회보
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• 제44권1호
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• pp.52.1-52.1
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• 2019

The Helioseismic and Magnetic Imager (HMI) is the instrument of Solar Dynamics Observatory (SDO) to study the magnetic field and oscillation at the solar surface. The HMI image is not enough to analyze very small magnetic features on solar surface since it has a spatial resolution of one arcsec. Super resolution is a technique that enhances the resolution of a low resolution image. In this study, we use a method for enhancing the solar image resolution using a Deep-learning model which generates a high resolution HMI image from a low resolution HMI image (4 by 4 binning). Deep learning networks try to find the hidden equation between low resolution image and high resolution image from given input and the corresponding output image. In this study, we trained a model based on a very deep residual channel attention networks (RCAN) with HMI images in 2014 and test it with HMI images in 2015. We find that the model achieves high quality results in view of both visual and measures: 31.40 peak signal-to-noise ratio(PSNR), Correlation Coefficient (0.96), Root mean square error (RMSE) is 0.004. This result is much better than the conventional bi-cubic interpolation. We will apply this model to full-resolution SDO/HMI and GST magnetograms.

• Investigative Magnetic Resonance Imaging
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• 제25권4호
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• pp.252-265
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• 2021

Cardiac magnetic resonance imaging (MRI) serves as a clinical gold-standard non-invasive imaging technique for the assessment of global and regional cardiac function. Conventional cardiac MRI is limited by the long acquisition time, the need for ECG gating and/or long breathhold, and insufficient spatiotemporal resolution. Real-time cardiac cine MRI refers to high spatiotemporal cardiac imaging using data acquired continuously without synchronization or binning, and therefore of potential interest in overcoming the limitations of conventional cardiac MRI. Novel acquisition and reconstruction techniques must be employed to facilitate real-time cardiac MRI. The goal of this study is to discuss methods that have been developed for real-time cardiac MRI. In particular, we classified existing techniques into two categories based on the use of non-iterative and iterative reconstruction. In addition, we present several research trends in this direction, including deep learning-based image reconstruction and other advanced real-time cardiac MRI strategies that reconstruct images acquired from real-time free-breathing techniques.

• 천문학회보
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• 제44권2호
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• pp.70.4-70.4
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• 2019

Image super-resolution (SR) is a technique that enhances the resolution of a low resolution image. In this study, we use three SR models (RCAN, ProSRGAN and Bicubic) for enhancing solar SDO/HMI magnetograms using deep learning. Each model generates a high resolution HMI image from a low resolution HMI image (4 by 4 binning). The pixel resolution of HMI is about 0.504 arcsec. Deep learning networks try to find the hidden equation between low resolution image and high resolution image from given input and the corresponding output image. In this study, we trained three models with HMI images in 2014 and test them with HMI images in 2015. We find that the RCAN model achieves higher quality results than the other two methods in view of both visual aspects and metrics: 31.40 peak signal-to-noise ratio(PSNR), Correlation Coefficient (0.96), Root mean square error (RMSE) is 0.004. This result is also much better than the conventional bi-cubic interpolation. We apply this model to a full-resolution SDO/HMI image and compare the generated image with the corresponding Hinode NFI magnetogram. As a result, we get a very high correlation (0.92) between the generated SR magnetogram and the Hinode one.

• Current Optics and Photonics
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• 제7권5호
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• pp.485-495
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• 2023

The pixel size in high-resolution complementary metal-oxide-semiconductor (CMOS) image sensors continues to shrink due to chip size limitations. However, the pixel pitch's miniaturization causes deterioration of optical performance. As one solution, a quad color filter (CF) array with pixel binning has been developed to enhance sensitivity. For high sensitivity, the microlens structure also needs to be optimized as the CF arrays change. In this paper, the covered microlens, which consist of four microlenses covered by one large microlens, are proposed for the quad CF array in the backside illumination pixel structure. To evaluate the optical performance, the suggested microlens structure was simulated from 0.5 ㎛ to 1.0 ㎛ pixels at the center and edge of the sensors. Moreover, all pixel structures were compared with and without in-pixel deep trench isolation (DTI), which works to distribute incident light uniformly into each photodiode. The suggested structure was evaluated with an optical simulation using the finite-difference time-domain method for numerical analysis of the optical characteristics. Compared to the conventional microlens, the suggested microlens show 29.1% and 33.9% maximum enhancement of sensitivity at the center and edge of the sensor, respectively. Therefore, the covered microlens demonstrated the highly sensitive image sensor with a quad CF array.

• 전자공학회논문지
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• 제51권9호
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• pp.129-138
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• 2014

현재까지 단일 영상센서를 사용하는 디지털 이미징 장치들을 위해 다양한 보간 기법들이 제안되어 왔다. 그러나 기존 보간 기법들은 주기적 샘플링을 사용하는 영상센서의 출력 해상도 모드를 고려하지 않았다. 따라서 출력 영상에서 해상도 화질 열화 및 color artifacts(color moire, zipper)현상들이 문제점으로 나타난다. 본 논문은 영상센서의 출력 해상도 모드를 고려한 색상 보간 알고리즘을 제안한다. 제안하는 보간 알고리즘은 효과적으로 에지 예측을 보상하는 초기단계와 해상도 모드를 고려하여 최소한의 방향성을 이용한 화질 개선단계로 구성되었다. 기존 기법들과 제안하는 알고리즘 결과를 분석 하기위해 주관적 화질비교와 PSNR(Peak Signal to Noise Ratio)을 통한 객관적 화질평가를 비교하였다. 객관적인 수치와 시각적인 부분에서 기존 기법 대비 color artifacts를 효과적으로 개선하였다.

• 한국약용작물학회지
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• 제24권2호
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• pp.93-100
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• 2016

Background: A set of logical criteria that can accurately identify and verify the cultivation region of raw materials is a critical tool for the scientific management of traditional herbal medicine. Methods and Results: Volatile compounds were obtained from 19 and 32 samples of Angelica gigas Nakai cultivated in Korea and China, respectively, by using steam distillation extraction. The metabolites were identified using GC/MS by querying against the NIST reference library. Data binning was performed to normalize the number of variables used in statistical analysis. Multivariate statistical analyses, such as Principal Component Analysis (PCA), Partial Least Squares-Discriminant Analysis (PLS-DA), and Orthogonal Partial Least Squares-Discriminant Analysis (OPLS-DA) were performed using the SIMCA-P software. Significant variables with a Variable Importance in the Projection (VIP) score higher than 1.0 as obtained through OPLS-DA and those that resulted in p-values less than 0.05 through one-way ANOVA were selected to verify the marker compounds. Among the 19 variables extracted, styrene, ${\alpha}$-pinene, and ${\beta}$-terpinene were selected as markers to indicate the origin of A. gigas. Conclusions: The statistical model developed was suitable for determination of the geographical origin of A. gigas. The cultivation regions of six Korean and eight Chinese A. gigas. samples were predicted using the established OPLS-DA model and it was confirmed that 13 of the 14 samples were accurately classified.