• Korean Journal of Remote Sensing
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• v.37 no.5_1
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• pp.917-926
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• 2021

Lodging rice is one of critical agro-meteorological disasters. In this study, the UAV-based multispectral imageries before and after rice lodging in rice paddy field of Jeollanamdo agricultural research and extension servicesin 2020 was analyzed. The UAV imagery on 14th Aug. includesthe paddy rice without any damage. However, 4th and 19th Sep. showed the area of rice lodging. Multispectral camera of 10 bands from 444 nm to 842 nm was used. At the area of restoration work against lodging rice, the reflectance from 531 nm to 842 nm were decreased in comparison to un-lodging rice. At the area of lodging rice, the reflectance of around 668 nm had small increases. Further, the blue and NIR (Near-Infrared) wavelength had larger. However, according to the types of lodging, the change of reflectance was different. The NDVI (Normalized Difference Vegetation Index) and NDRE (Normalized Difference Red Edge) shows dome sensitivities to lodging rice, but they were different to types of lodging. These results will be useful to make algorithm to detect the area of lodging rice using a UAV.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.3
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• pp.500-506
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• 2019

In this study, we present a decision function of optimal smoothing parameter for baseline correction using Asymmetrically reweighted penalized least squares (arPLS). Baseline correction is very important due to influence on performance of spectral analysis in application of spectroscopy. Baseline is often estimated by parameter selection using visual inspection on analyte spectrum. It is a highly subjective procedure and can be tedious work especially with a large number of data. For these reasons, an objective procedure is necessary to determine optimal parameter value for baseline correction. The proposed function is defined by modeling the median value of possible parameter range as the length and order of the background signal. The median value increases as the length of the signal increases and decreases as the degree of the signal increases. The simulated data produced a total of 112 signals combined for the 7 lengths of the signal, adding analytic signals and linear and quadratic, cubic and 4th order curve baseline respectively. According to the experimental results using simulated data with linear, quadratic, cubic and 4th order curved baseline, and real Raman spectra, we confirmed that the proposed function can be effectively applied to optimal parameter selection for baseline correction using arPLS.

• Atmosphere
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• v.29 no.1
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• pp.105-112
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• 2019

Measurements of vertical air motion and microphysics are essential for improving our understanding of convective clouds. In this paper, the author reviews the current research on the retrieval of vertical air motions using the cloud radar. At radar wavelengths of 3 mm (W-band radar; 94-GHz radar; cloud radar), the raindrop backscattering cross-section (${\sigma}b$) varies between successive maxima and minima as a function of the raindrop diameter (D) that are well described by Mie theory. The first Mie minimum in the backscattering cross-section occurs at D~1.68 mm, which translates to a raindrop terminal fall velocity of ${\sim}5.85m\;s^{-1}$ based on the Gunn and Kinzer relationship. Since raindrop diameters often exceed this size, the signal is captured in the radar Doppler spectrum, and thus, the location of the first Mie minimum can be used as a reference for retrieving the vertical air motion. The Mie technique is applied to radar Doppler spectra from the surface-based and airborne, upward pointing W-band radars. The contributions of aircraft motion to the vertical air motion are also described and further the first-order aircraft motion corrected equation is presented. The review also shows that the separate spectral peaks due to the cloud droplets can provide independent validation of the Mie technique retrieved vertical air motion using the cloud droplets as a tracer of vertical air motion.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.30 no.5
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• pp.418-426
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• 2019

Recently, many studies on vital sign detection using a radar sensor related to Internet of Things(IoT) smart home systems have been conducted. Because vital signs such as respiration and cardiac rates generally cause micro-motions in the chest or back, the phase of the received echo signal from a target fluctuates according to the micro-motion. Therefore, vital signs are usually detected via spectral analysis of the phase. However, the probability of false alarms in cardiac rate detection increases as a result of various problems in the measurement environment, such as very weak phase fluctuations caused by the cardiac rate. Therefore, this study analyzes the difficulties of vital sign detection and proposes an efficient vital sign detection algorithm consisting of four main stages: 1) phase decomposition, 2) phase differentiation and filtering, 3) vital sign detection, and 4) reduction of the probability of false alarm. Experimental results using impulse-radio ultra-wideband radar show that the proposed algorithm is very efficient in terms of computation and accuracy.

• Journal of the Korean Applied Science and Technology
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• v.36 no.1
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• pp.84-89
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• 2019

To characterize the molecular structure of BzO-gal synthesized using Escherichia coli ${\beta}$-gal, NMR ($^1H$- and $^{13}C$-) spectroscopy and mass spectrometry of BzO-gal were conducted. $^1H$ NMR spectrum of BzO-gal showed multiple peaks corresponding to the galactosyl group, which is an evidence of galactosylation on BzOH. Five proton peaks around the aromatic region at ${\delta}_H$ 7.43 ~ 7.24 ppm and 2 peaks from ${\delta}_H$ 4.93 and 4.67 ppm were evidence of the presence of the benzyl group. Seven proton peaks at ${\delta}_H$ 4.32 ~ 3.46 ppm showed the presence of a monosaccharide and were indicative of galactosylation on BzOH. $^{13}C$ NMR spectrum also revealed the presence of 11 carbons suggestive of BzO-gal. The mass value (sodium adduct ion of BzO-gal, m/z = 293.0994) from mass spectrometry analysis of BzO-gal, and $^1H$ and $^{13}C$ NMR spectral data were in good agreement with the expecting structure of BzO-gal. We are expecting that through future study it will eventually be able to develop a new additive of low cytotoxicity.

• The Bulletin of The Korean Astronomical Society
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• v.44 no.1
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• pp.57.2-57.2
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• 2019

The NISS (Near-infrared Imaging Spectrometer for Star formation history) onboard NEXTSat-1 was successfully launched on last December and is now under the operation phase. The capability of both imaging and spectroscopy is a unique function of the NISS. It has realized the imaging spectroscopy (R~20) with a wide field of view of $2{\times}2deg$. in a wide near-infrared range from 0.95 to $2.5{\mu}m$. The major scientific mission is to study the cosmic star formation history in the local and distant universe. It also demonstrated the space technologies related to the infrared spectro-photometry in space. The NISS is performing the imaging spectroscopic survey for local star-forming galaxies, clusters of galaxies, star-forming regions, ecliptic deep fields and so on. As an extension of the NISS, the SPEHREx (Spectro-Photometer for the History of the Universe Epoch of Reionization, and Ices Explorer) was selected as the NASA MIDEX (Medium-class Explorer) mission (PI Institute: Caltech). As an international partner, KASI will participate in the development and the science for SPHEREx. It will perform the first all-sky infrared spectro-photometric survey to probe the origin of our Universe, to explore the origin and evolution of galaxies, and to explore whether planets around other stars could harbor life. Compared to the NISS, the SPHEREx is designed to have a much wider FoV of $3.5{\times}11.3deg$. as well as wider spectral range from 0.75 to $5.0{\mu}m$. Here, we introduce the status of the two space missions.

• Korean journal of applied entomology
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• v.60 no.1
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• pp.135-143
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• 2021

Aerospace and geospatial technologies have become more accessible by researchers and agricultural practitioners, and these technologies can play a pivotal role in transforming current pest management practices in agriculture and forestry. During the past 20 years, technologies including satellites, manned and unmanned aircraft, spectral sensors, information systems, and autonomous field equipment, have been used to detect pests and apply control measures site-specifically. Despite the availability of aerospace and geospatial technologies, along with big-data-driven artificial intelligence, applications of such technologies to apple IPM have not been realized yet. Using a case study conducted at the Korea Apple Research Institute, this article discusses the advances and limitations of current aerospace and geospatial technologies that can be used for improving apple IPM.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.3
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• pp.777-783
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• 2021

Aircraft are affected by various vibrations during maneuvering. These vibrations may have a fatal effect on the survival of aircraft in some cases, so the safety of components applied to the aircraft should be proven against various vibrations through random vibration analysis. In this study, the structural robustness of an external fuel tank and pylon for military aircraft was evaluated under random vibration conditions using commercial software, MSC Random. In the random vibration analysis, a frequency response analysis was performed by imposing a unit load on the boundary condition point, and then excitation was performed with a PSD profile. In this process, the required mode data was extracted through a modal analysis method. In addition, the random vibration profile specified in the US Defense Environment Standard was applied as random vibration conditions, and the PSD profile given in units of G's was converted into units of gravitational acceleration. As a result of the numerical analysis, we evaluated the structural robustness of the external fuel tank and pylon by identifying the safety margins of beam elements, shell elements, and solid elements in a numerical model for random vibration in the x, y, and z directions.

• Korean Journal of Remote Sensing
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• v.37 no.3
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• pp.409-418
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• 2021

The land cover map is a very important data that is used as a basis for decision-making for land policy and environmental policy. The land cover map is mapped using remote sensing data, and the classification results may vary depending on the acquisition time of the data used even for the same area. In this study, to overcome the classification accuracy limit of single-period data, multi-series satellite images were used to learn the difference in the spectral reflectance characteristics of the land surface according to seasons on a U-Net model, one of the deep learning algorithms, to improve classification accuracy. In addition, the degree of improvement in classification accuracy is compared by comparing the accuracy of single-period data. Seoul, which consists of various land covers including 30% of green space and the Han River within the area, was set as the research target and quarterly Sentinel-2 satellite images for 2020 were aquired. The U-Net model was trained using the sub-class land cover map mapped by the Korean Ministry of Environment. As a result of learning and classifying the model into single-period, double-series, triple-series, and quadruple-series through the learned U-Net model, it showed an accuracy of 81%, 82% and 79%, which exceeds the standard for securing land cover classification accuracy of 75%, except for a single-period. Through this, it was confirmed that classification accuracy can be improved through multi-series classification.

• Korean Journal of Agricultural Science
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• v.48 no.2
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• pp.299-310
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• 2021

Glycerol is a non-volatile compound with no aromatic properties that contributes significantly to the quality of wine by providing sweetness and richness of taste. In addition, it is also the third most significant byproduct of alcoholic fermentation in terms of quantity after ethanol and carbon dioxide. In this study, Fourier transform infrared (FT-IR) spectroscopy was employed as a fast non-destructive method in conjugation with multivariate regression analysis to build a model for the quantitative analysis of glycerol concentration in wine samples. The samples were prepared by using three varieties of red wine samples (i.e., Shiraz, Merlot, and Barbaresco) that were adulterated with glycerol in concentration ranges from 0.1 to 15% (v·v^-1), and subjected to analysis together with pure wine samples. A net analyte signal (NAS)-based methodology, called hybrid linear analysis in the literature (HLA/GO), was applied for predicting glycerol concentrations in the collected FT-IR spectral data. Calibration and validation sets were designed to evaluate the performance of the multivariate method. The obtained results exhibited a high coefficient of determination (R²) of 0.987 and a low root mean square error (RMSE) of 0.563% for the calibration set, and a R² of 0.984 and a RMSE of 0.626% for the validation set. Further, the model was validated in terms of sensitivity, selectivity, and limits of detection and quantification, and the results confirmed that this model can be used in most applications, as well as for quality assurance.