• ETRI Journal
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• v.33 no.4
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• pp.569-579
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• 2011

This paper presents a novel approach for human activity recognition (HAR) using the joint angles from a 3D model of a human body. Unlike conventional approaches in which the joint angles are computed from inverse kinematic analysis of the optical marker positions captured with multiple cameras, our approach utilizes the body joint angles estimated directly from time-series activity images acquired with a single stereo camera by co-registering a 3D body model to the stereo information. The estimated joint-angle features are then mapped into codewords to generate discrete symbols for a hidden Markov model (HMM) of each activity. With these symbols, each activity is trained through the HMM, and later, all the trained HMMs are used for activity recognition. The performance of our joint-angle-based HAR has been compared to that of a conventional binary and depth silhouette-based HAR, producing significantly better results in the recognition rate, especially for the activities that are not discernible with the conventional approaches.

• The Bulletin of The Korean Astronomical Society
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• v.44 no.2
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• pp.73.3-73.3
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• 2019

The AGN unification model suggested the presence of obscuring material, a dusty torus, to explain the various types of AGN. IR SED model fitting is a crucial tool to probe the structure and properties of the dusty torus. We use a sample of 16 local quasi-stellar objects in Martinez-Paredes et al. (2017) with obtained NIR and MIR high-angular resolution (~0.3") imaging data from EMIR, CIRCE and CanariCam on the 10.4-m Gran Telescopio CANARIAS (GTC) while 4 objects have NIR high-angular resolution photometry from NICMOS/HST from the literature. The unresolved NIR emission from the NIR image analysis and low-resolution Spitzer/IRS spectra are used to construct NIR-MIR SEDs covering a larger spectral range. We investigate the sensitivity of the geometrical (e.g. viewing angle) and physical parameters (e.g. optical depth) of the clumpy dusty torus model of Nenkova et al. and the clumpy disk+outflow model of Hoenig et al. We aim to investigate the minimal dataset needed to well constrain the parameters of the models and derive the properties of the dusty torus. These results will allow us to plan future observations for a larger sample of high luminosity AGNs with the James Webb Space Telescope and the Giant Magellan Telescope.

• The Bulletin of The Korean Astronomical Society
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• v.44 no.2
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• pp.37.1-37.1
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• 2019

We perform Lyα radiative transfer calculations for reproducing Lyα properties of star-forming galaxies at high redshifts. We model a galaxy as a halo in which the density distributions of Lyα sources and HI plus dust medium are described with exponential functions. We also consider an outflow of the medium that represents a momentum-driven wind in a gravitational potential well. We demonstrate that this outflowing halo model with Lyα scattering can successfully reproduce both the spectrum and the surface brightness profile of eight star-forming galaxies at z=3-6 observed with MUSE. The best-fit model parameters (i.e., the outflowing velocity and optical depth) for these galaxies are in good agreement with other studies. We also demonstrate benefits of using spectrum and surface brightness profile simultaneously to the constraints on model parameters and thus spatial/kinematic distributions of medium. We examine the impacts of individual model parameters and intrinsic spectrum on emerging spectrum and surface brightness profile. Further investigations on the escape fraction, spatially resolved spectra, and the spatial extent of Lyα halos are presented as well.

• Korean Journal of Remote Sensing
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• v.33 no.6_1
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• pp.961-970
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• 2017

Despite of large demand for high spatial resolution products of aerosol properties from satellite remote sensing, it has been very difficult due to the weak signal by a single pixel and higher noise from clouds. In this study, aerosol retrieval algorithm with the high spatial resolution ($500m{\times}500m$) was developed using Geostationary Ocean Color Imager (GOCI) data during the Korea-US Air Quality (KORUS-AQ) period in May-June, 2016.Currently, conventional GOCI Yonsei aerosol retrieval(YAER) algorithm provides $6km{\times}6km$ spatial resolution product. The algorithm was tested for its best possible resolution of 500 m product based on GOCI YAER version 2 algorithm. With the new additional cloud masking, aerosol optical depth (AOD) is retrieved using the inversion method, aerosol model, and lookup table as in the GOCI YAER algorithm. In some cases, 500 m AOD shows consistent horizontal distribution and magnitude of AOD compared to the 6 km AOD. However, the 500 m AOD has more retrieved pixels than 6 km AOD because of its higher spatial resolution. As a result, the 500 m AOD exists around small clouds and shows finer features of AOD. To validate the accuracy of 500 m AOD, we used dataset from ground-based Aerosol Robotic Network (AERONET) sunphotometer over Korea. Even with the spatial resolution of 500 m, 500 m AOD shows the correlation coefficient of 0.76 against AERONET, and the ratio within Expected Error (EE) of 51.1%, which are comparable to the results of 6 km AOD.

• Korean Journal of Remote Sensing
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• v.37 no.6_2
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• pp.1891-1900
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• 2021

Fine particulate matter (FPM; diameter ≤ 2.5 ㎛) is frequently found in metropolitan areas due to activities associated with rapid urbanization and population growth. Many adolescents spend a substantial amount of time at school where, for various reasons, FPM generated outdoors may flow into indoor areas. The aims of this study were to estimate FPM concentrations and categorize types of FPM in schools. Meteorological and chemical variables as well as satellite-based aerosol optical depth were analyzed as input data in a random forest model, which applied 10-fold cross validation and a grid-search method, to estimate school FPM concentrations, with four statistical indicators used to evaluate accuracy. Loose and strict standards were established to categorize types of FPM in schools. Under the former classification scheme, FPM in most schools was classified as type 2 or 3, whereas under strict standards, school FPM was mostly classified as type 3 or 4.

• Journal of The Korean Astronomical Society
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• v.54 no.5
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• pp.139-155
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• 2021

We present an updated version of the multilayer spectral inversion (MLSI) recently proposed as a technique to infer the physical parameters of plasmas in the solar chromosphere from a strong absorption line. In the original MLSI, the absorption profile was constant over each layer of the chromosphere, whereas the source function was allowed to vary with optical depth. In our updated MLSI, the absorption profile is allowed to vary with optical depth in each layer and kept continuous at the interface of two adjacent layers. We also propose a new set of physical requirements for the parameters useful in the constrained model fitting. We apply this updated MLSI to two sets of Hα and Ca II line spectral data taken by the Fast Imaging Solar Spectrograph (FISS) from a quiet region and an active region, respectively. We find that the new version of the MLSI satisfactorily fits most of the observed line profiles of various features, including a network feature, an internetwork feature, a mottle feature in a quiet region, and a plage feature, a superpenumbral fibril, an umbral feature, and a fast downflow feature in an active region. The MLSI can also yield physically reasonable estimates of hydrogen temperature and nonthermal speed as well as Doppler velocities at different atmospheric levels. We conclude that the MLSI is a very useful tool to analyze the Hα line and the Ca II 8542 line spectral daya, and will promote the investigation of physical processes occurring in the solar photosphere and chromosphere.

• Imaging Science in Dentistry
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• v.51 no.2
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• pp.107-115
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• 2021

Purpose: This study aimed to demonstrate the presence of dental caries through a photoacoustic imaging system with visible and near-infrared wavelengths, highlighting the differences between the 2 spectral regions. The depth at which carious tissue could be detected was also verified. Materials and Methods: Fifteen permanent molars were selected and classified as being sound or having incipient or advanced caries by visual inspection, radiography, and optical coherence tomography analysis prior to photoacoustic scanning. A photoacoustic imaging system operating with a nanosecond pulsed laser as the light excitation source at either 532 nm or 1064 nm and an acoustic transducer at 5 MHz was developed, characterized, and used. En-face and lateral(depth) photoacoustic signals were detected. Results: The results confirmed the potential of the photoacoustic method to detect caries. At both wavelengths, photoacoustic imaging effectively detected incipient and advanced caries. The reconstructed photoacoustic images confirmed that a higher intensity of the photoacoustic signal could be observed in regions with lesions, while sound surfaces showed much less photoacoustic signal. Photoacoustic signals at depths up to 4 mm at both 532 nm and 1064 nm were measured. Conclusion: The results presented here are promising and corroborate that photoacoustic imaging can be applied as a diagnostic tool in caries research. New studies should focus on developing a clinical model of photoacoustic imaging applications in dentistry, including soft tissues. The use of inexpensive light-emitting diodes together with a miniaturized detector will make photoacoustic imaging systems more flexible, user-friendly, and technologically viable.

• The Bulletin of The Korean Astronomical Society
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• v.41 no.1
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• pp.54.1-54.1
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• 2016

Multi-wavelength variability is a staple of active galactic nuclei (AGN). Optical variability probes the nature of the central engine of AGN at smaller linear scales than conventional imaging and spectroscopic techniques. Previous studies have shown that optical variability is more prevalent at longer timescales and at shorter wavelengths. Intra-night variability can be explained through the damped random walk model but small samples and inhomogeneous data have made constraining this model hard. To understand the properties and physical mechanism of intra-night optical variability, we are performing the KMTNet Active Nuclei Variability Survey (KANVaS). Using KMTNet, we aim to study the intra-night variability of ~1000 AGN at a magnitude depth of ~19mag in R band over a total area of ${\sim}24deg^2$ on the sky. Test data in the COSMOS, XMM-LSS, and S82-2 fields was obtained over 4, 6, and 8 nights respectively during 2015, in B, V, R, and I bands. Each night was composed of 5-13 epoch with ~30 min cadence and 80-120 sec exposure times. As a pilot study, we analyzed data in the COSMOS field where we reach a magnitude depth of ~19.5 in R band (at S/N~100) with seeing varying between 1.5-2.0 arcsec. We used the Chandra-COSMOS catalog to identify 166 AGNs among 549 AGNs at B<23. We performed differential photometry between the selected AGN and nearby stars, achieving photometric uncertainty ~0.01mag. We employ various standard time-series analysis tools to identify variable AGN, including the chi-square test. Preliminarily results indicate that intra-night variability is found for ~17%, 17%, 8% and 7% of all X-ray selected AGN in the B, V, R, and I band, respectively. The majority of the identified variable AGN are classified as Type 1 AGN, with only a handful of Type 2 AGN showing evidence for variability. The work done so far confirms there are more variable AGN at shorter wavelengths and that intra-night variability most likely originates in the accretion disk of these objects. We will briefly discuss the quality of the data, challenges we encountered, solutions we employed for this work, and our updated future plans.

• The Bulletin of The Korean Astronomical Society
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• v.45 no.1
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• pp.44.4-45
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• 2020

The solar chromosphere can be observed well through strong absorption lines. We infer the physical parameters of chromospheric plasmas from these lines using a multilayer spectral inversion. This is a new technique of spectral inversion. We assume that the atmosphere consists of a finite number of layers. In each layer the absorption profile is constant and the source function is allowed to vary with optical depth. Specifically, we consider a three-layer model of radiative transfer where the lowest layer is identified with the photosphere and the two upper layers are identified with the chromosphere. This three-layer model is fully specified by 13 parameters. Four parameters can be fixed to prescribed values, and one parameter can be determined from the analysis of a satellite photospheric line. The remaining eight parameters are determined from a constrained least-squares fitting. We applied the multilayer spectral inversion to the spectral data of the Hα and the Ca II 854.21 nm lines taken in a quiet region by the Fast Imaging Solar Spectrograph (FISS) of the Goode Solar Telescope (GST). We find that our model successfully fits most of the observed profiles and produces regular maps of the model parameters. We conclude that our multilayer inversion is useful to infer chromospheric plasma parameters on the Sun.

• Korean Journal of Remote Sensing
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• v.39 no.5_3
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• pp.933-948
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• 2023

Atmospheric aerosols not only have adverse effects on human health but also exert direct and indirect impacts on the climate system. Consequently, it is imperative to comprehend the characteristics and spatiotemporal distribution of aerosols. Numerous research endeavors have been undertaken to monitor aerosols, predominantly through the retrieval of aerosol optical depth (AOD) via satellite-based observations. Nonetheless, this approach primarily relies on a look-up table-based inversion algorithm, characterized by computationally intensive operations and associated uncertainties. In this study, a novel high-resolution AOD direct retrieval algorithm, leveraging machine learning, was developed using top-of-atmosphere reflectance data derived from the Geostationary Ocean Color Imager-II (GOCI-II), in conjunction with their differences from the past 30-day minimum reflectance, and meteorological variables from numerical models. The Light Gradient Boosting Machine (LGBM) technique was harnessed, and the resultant estimates underwent rigorous validation encompassing random, temporal, and spatial N-fold cross-validation (CV) using ground-based observation data from Aerosol Robotic Network (AERONET) AOD. The three CV results consistently demonstrated robust performance, yielding R²=0.70-0.80, RMSE=0.08-0.09, and within the expected error (EE) of 75.2-85.1%. The Shapley Additive exPlanations(SHAP) analysis confirmed the substantial influence of reflectance-related variables on AOD estimation. A comprehensive examination of the spatiotemporal distribution of AOD in Seoul and Ulsan revealed that the developed LGBM model yielded results that are in close concordance with AERONET AOD over time, thereby confirming its suitability for AOD retrieval at high spatiotemporal resolution (i.e., hourly, 250 m). Furthermore, upon comparing data coverage, it was ascertained that the LGBM model enhanced data retrieval frequency by approximately 8.8% in comparison to the GOCI-II L2 AOD products, ameliorating issues associated with excessive masking over very illuminated surfaces that are often encountered in physics-based AOD retrieval processes.