• Korean Journal of Optics and Photonics
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• v.30 no.4
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• pp.154-158
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• 2019

We have used a mid-IR (mid-infrared) continuous-wave (cw) optical parametric oscillator (OPO), developed previously and described in Ref. 12, to build a performance-evaluation setup for a mid-IR spectrometer. The used CW OPO had a wavelength tuning range of $ 2.5-3.6{\mu}m$ using a pump laser with a wavelength of 1064 nm and a fan-out MgO-doped periodically poled lithium niobate (MgO:PPLN) nonlinear crystal in a concentric cavity design. The OPO was combined with a near-IR integrating sphere and a Fourier-transform IR optical spectrum analyzer to build a performance-evaluation setup for mid-IR spectrometers. We applied this performance-evaluation setup to evaluating a mid-IR spectrometer developed domestically, and demonstrated the capability of evaluating the performance, such as spectral resolution, signal-to-noise ratio, spectral stray light, and so on, based on this setup.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1407-1422
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• 2022

This study was conducted to classify tree species and assess the classification accuracy, using SE-Inception, a classification-based deep learning model. The input images of the dataset used Worldview-3 and GeoEye-1 images, and the size of the input images was divided into 10 × 10 m, 30 × 30 m, and 50 × 50 m to compare and evaluate the accuracy of classification of tree species. The label data was divided into five tree species (Pinus densiflora, Pinus koraiensis, Larix kaempferi, Abies holophylla Maxim. and Quercus) by visually interpreting the divided image, and then labeling was performed manually. The dataset constructed a total of 2,429 images, of which about 85% was used as learning data and about 15% as verification data. As a result of classification using the deep learning model, the overall accuracy of up to 78% was achieved when using the Worldview-3 image, the accuracy of up to 84% when using the GeoEye-1 image, and the classification accuracy was high performance. In particular, Quercus showed high accuracy of more than 85% in F₁ regardless of the input image size, but trees with similar spectral characteristics such as Pinus densiflora and Pinus koraiensis had many errors. Therefore, there may be limitations in extracting feature amount only with spectral information of satellite images, and classification accuracy may be improved by using images containing various pattern information such as vegetation index and Gray-Level Co-occurrence Matrix (GLCM).

• Korean Journal of Remote Sensing
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• v.38 no.5_1
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• pp.535-543
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• 2022

A drone is used to diagnose crop growth and to provide information through images in the agriculture field. In the case of using high spatial resolution drone images, growth information for each object can be produced. However, accurate object detection is required and adjacent objects should be efficiently classified. The purpose of this study is to develop a Chinese cabbage object detection algorithm using multispectral reflectance images observed from drone and computer vision techniques. Drone images were captured between 7 and 15 days after planting a Chinese cabbage from 2018 to 2020 years. The thresholds of object detection algorithm were set based on 2019 year, and the algorithm was evaluated based on images in 2018 and 2019 years. The vegetation area was classified using the characteristics of spectral reflectance. Then, morphology techniques such as dilatation, erosion, and image segmentation by considering the size of the object were applied to improve the object detection accuracy in the vegetation area. The precision of the developed object detection algorithm was over 95.19%, and the recall and accuracy were over 95.4% and 93.68%, respectively. The F1-Score of the algorithm was over 0.967 for 2 years. The location information about the center of the Chinese cabbage object extracted using the developed algorithm will be used as data to provide decision-making information during the growing season of crops.

• Journal of Biomedical Engineering Research
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• v.43 no.1
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• pp.52-60
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• 2022

Purpose: For now, cognitive load is assessed based on survey-based methods, which can be difficult to track the amount of cognitive load in real-time. In this study, we investigated the difference in electrophysiological activation due to different levels of cognitive load not only at sensor-level but also at source-level using electroencephalogram that might be potentially used for quantitative cognitive load evaluation. Materials and Methods: In this study, ten healthy subjects (mean age 24.3 ± 2.1, three female) participated the experiment. All participants performed 4 sessions of n-back task in different difficulties: 0-, 1-, 2-, and 3-back during electroencephalogram recording. For sensor-level analysis, we calculated the event-related potential and event-related spectral perturbation while low resolution brain electromagnetic tomography (LORETA) to estimate the source activation. Each result was compared between different workload conditions using statistical analysis. Results: Statistical results revealed that the accuracy of the task performance was significantly different between different cognitive loads (p = 0.018). The post-hoc analysis confirmed that the accuracy of the 3-back task was significantly decreased compared to 1-back condition (p = 0.018), but not with 2-back condition (p = 0.180). ERP results showed that P300 target amplitude between 1-back and 3-back had a marginal difference in Cz (p = 0.059) and Pz(p = 0.093). A significant inhibition in Cz high-beta activation (p = 0.017) and decrease in source activation of right parahippocampal gyrus was found in 3-back condition compared to 1-back condition (p < 0.05). Conclusion: In this study, we compared the sensor- and source-level differences in electroencephalogram between different levels of cognitive load, that were found to be in line with the previous reports related to cognitive load evaluation. We expect that the outcome of the current study can be used as a feature to establish a quantitative cognitive load assessment system.

• The Journal of the Acoustical Society of Korea
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• v.42 no.5
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• pp.429-440
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• 2023

This study explores recent research trends and potential applications of ultrasound optical imaging-based multimodal technology. Ultrasound imaging has been widely utilized in medical diagnostics due to its real-time capability and relative safety. However, the drawback of low resolution in ultrasound imaging has prompted active research on multimodal imaging techniques that combine ultrasound with other imaging modalities to enhance diagnostic accuracy. In particular, ultrasound optical imaging-based multimodal technology enables the utilization of each modality's advantages while compensating for their limitations, offering a means to improve the accuracy of the diagnosis. Various forms of multimodal imaging techniques have been proposed, including the fusion of optical coherence tomography, photoacoustic, fluorescence, fluorescence lifetime, and spectral technology with ultrasound. This study investigates recent research trends in ultrasound optical imaging-based multimodal technology, and its potential applications are demonstrated in the biomedical field. The ultrasound optical imaging-based multimodal technology provides insights into the progress of integrating ultrasound and optical technologies, laying the foundation for novel approaches to enhance diagnostic accuracy in the biomedical domain.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.37 no.6
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• pp.491-498
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• 2019

This study analyzed how the accuracy of co-registration varies depending on the convergence angles between two KOMPSAT-3·3A images. Most very-high-resolution satellite images provide initial coordinate information through metadata. Since the search area for performing image co-registration can be reduced by using the initial coordinate information, in this study, the mutual information method showing high matching reliability in the small search area is used. Initial coarse co-registration was performed by using multi-spectral images with relatively low resolution, and precise fine co-registration was conducted centering on the region of interest of the panchromatic image for more accurate co-registration performance. The experiment was conducted by 120 combination of 16 KOMPSAT-3·3A 1G images taken in Daejeon area. Experimental results show that a correlation coefficient between the convergence angles and fine co-registration errors was 0.59. In particular, we have shown the larger the convergence angle, the lower the accuracy of co-registration performance.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2009.06a
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• pp.23-23
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• 2009

GaN-based nitride semiconductors have attracted considerable attention in high-brightness light-emitting-diodes (LEDs) and laser diodes (LDs) covering from green to ultraviolet spectral range. LED and LD heterostructures are usually grown on (0001)-$Al_2O_3$. The large lattice mismatch between $Al_2O_3$ substrates and the GaN layers leads to a high density of defects(dislocations and stacking faults). Moreover, Ga and N atoms are arranged along the polar [0001] crystallographic direction, which leads to spontaneous polarization. In addition, in the InGaN/GaN MQWs heterostructures, stress applied along the same axis can also give rise to piezoelectric polarization. The total polarization, which is the sum of spontaneous and piezoelectric polarizations, is aligned along the [0001] direction of the wurtzite heterostructures. The change in the total polarization across the heterolayers results in high interface charge densities and spatial separation of the electron and hole wave functions, redshifting the photoluminescence peak and decreasing the peak intensity. The effect of polarization charges in the GaN-based heterostructures can be eliminated by growing along the non-polar [$11\bar{2}0$] (a-axis) or [$1\bar{1}00$] (m-axis) orientation instead of thecommonly used polar [0001] (c-axis). For non-polar GaN growth on non-polar substrates, the GaN films have high density of planar defects (basal stacking fault BSFs, prismatic stacking fault PSFs), because the SFs are formed on the basal plane (c-plane) due to their low formation energy. A significant reduction in defect density was recently achieved by applying blocking layer such as SiN, AlN, and AlGaN in non-polar GaN. In this work, we were performed systematic studies of the defects in the nonpolar GaN by conventional and high-resolution transmission electron microscopy.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1526-1526
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• 2001

To improve the accuracy of sweetness sensor in automated sorting operations, it is necessary to clarify unevenness of the sugar content distribution within fruits. And it is expected that the technique to evaluate the content distribution in fruits contribute to the development of the near-infrared (NIR) imaging spectroscopy. Sugiyama (1999) had succeeded to visualize the distribution of the sugar content on the surface of a half-cut green fresh melon. However, this method cannot be applied to red flesh melons because it depends on information of the absorption band of chlorophyll (676 nm), which is affected by the color of the fresh. The objective of this study was to develop the universal visualization method depends on the absorption band of sugar, which can be applied to various kinds of melons and other fruits. The relationship between the sugar contents and absorption spectra of both green and red fresh melons were investigated by using a NIR spectrometer to determine the absorption band of sugar. The combination of 2$\^$nd/ derivative absorbances at 902 nm and 874 nm was highly correlated with the sugar contents. The wavelength of 902 nm is attributed to the absorption band of sugar. A cooled charge-coupled device (CCD) imaging camera which has 16 bit (65536 steps) A/D resolution was equipped with rotating band-pass filter wheel and used to capture the spectral absorption images of the flesh of a vertically half-cut red fresh melon. The advantage of the high A/D resolution in this research is that each pixel of the CCD is expected to function as a detector of the NIR spectrometer for quantitative analysis. Images at 846 nm, 874 nm, 902 nm and 930 nm were acquired using this CCD camera. Then the 2$\^$nd/ derivative absorbances at 902 nm and 874 nm at each pixel were calculated using these four images. On the other hand, parts of the same melon were extracted for capturing the images and squeezed for the measurement of sugar content. Then the calibration curve between the combination of 2$\^$nd/ derivative absorbances at 902 nm and 874 nm and sugar content was developed. The calibration method based on NIR spectroscopy techniques was applied to each pixel of the images to convert the 2$\^$nd/ derivative absorbances into the Brix sugar content. Mapping the sugar content value of each pixel with linear color scale, the distribution of the sugar content was visualized. As a result of the visualization, it was quantitatively confirmed that the Brix sugar contents are low at the near of the skin and become higher towards the seeds. This result suggests that the visualization technique by the NIR imaging spectroscopy could become a new useful method fer quality evaluation of melons.

• The Bulletin of The Korean Astronomical Society
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• v.37 no.1
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• pp.42-42
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• 2012

The First stars (Pop.III stars) in the universe are expected to be formed between the recombination era at z - 1100 and the most distant quasar (z - 8). They have never been directly detected due to its faintness so far, but can be observed as a background radiation at around 1${\mu}m$ which is called the Cosmic Near-Infrared Background (CNB). Main part of the CNB is thought to be redshifted Lyman-alpha from gas clouds surrounding the Pop.III stars. Until now, the COBE (COsmic Background Explorer) and the IRTS (Infrared Telescope in Space) observed excess emission over the background due to galaxies. To confirm the COBE and the IRTS results and pursue more observational evidences, we carried out the sounding rocket experiment named the Cosmic Infrared Background ExpeRiment (CIBER). The CIBER is successfully launched on July 10, 2010 at White Sands Missile Range, New Mexico, USA. It consists of three kinds of instruments. We report the results obtained by LRS (Low Resolution Spectrometer) which is developed to fill the uncovered spectrum around 1${\mu}m$. LRS is a refractive telescope of 5.5 cm aperture with spectral resolution of 20 - 30 and wavelength coverage of 0.7 to 2.0${\mu}m$. After subtracting foreground components (zodiacal light, integrated star light and diffuse galactic light) from the sky brightness of observed five fields, there remained significant residual emission (even for the lower limit case) consistent with the IRTS and the COBE results. In addition, there exists a clear gap at 0.7 - 0.8${\mu}m$ in the CNB spectrum over the background due to galaxies according to recent results (Matsuoka et al. 2011; Mattila et al. 2011). The origin of the excess emission could be ascribed to the Pop.III stars with its active era of z = 7 - 10.

• Journal of Korea Spatial Information System Society
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• v.12 no.1
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• pp.66-75
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• 2010

The authors argues that the current road updating system based on traditional aerial photograph or multi-spectral satellite image appears to be non-user friendly due to lack of the frequent cartographic representation for the new construction sites. Google Earth are currently being emerged as one of important places to extract road features since the RGB satellite image with high multi-temporal resolution can be accessed freely over large areas. This paper is primarily intended to evaluate optimal threshold of RGB pixel values to extract road features from Google Earth. An empirical study for five experimental sites was conducted to confirm how a RGB picture provided Google Earth can be used to extact the road feature. The results indicate that optimal threshold of RGB pixel values to extract road features was identified as 126, 125, 127 for manual operation which corresponds to 25%, 30%, 19%. Also, it was found that display scale difference of Google Earth was not very influential in tracking required RGB pixel value. As a result the 61cm resolution of Quickbird RGB data has shown the potential to realistically identified the major type of road feature by large scale spatial precision while the typical algorithm revealed successfully the area-wide optimal threshold of RGB pixel for road appeared in the study area.