• Investigative Magnetic Resonance Imaging
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• 제23권1호
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• pp.38-45
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• 2019

Purpose: To demonstrate the high-resolution numerical simulation of the respiration-induced dynamic $B_0$ shift in the head using generalized susceptibility voxel convolution (gSVC). Materials and Methods: Previous dynamic $B_0$ simulation research has been limited to low-resolution numerical models due to the large computational demands of conventional Fourier-based $B_0$ calculation methods. Here, we show that a recently-proposed gSVC method can simulate dynamic $B_0$ maps from a realistic breathing human body model with high spatiotemporal resolution in a time-efficient manner. For a human body model, we used the Extended Cardiac And Torso (XCAT) phantom originally developed for computed tomography. The spatial resolution (voxel size) was kept isotropic and varied from 1 to 10 mm. We calculated $B_0$ maps in the brain of the model at 10 equally spaced points in a respiration cycle and analyzed the spatial gradients of each of them. The results were compared with experimental measurements in the literature. Results: The simulation predicted a maximum temporal variation of the $B_0$ shift in the brain of about 7 Hz at 7T. The magnitudes of the respiration-induced $B_0$ gradient in the x (right/left), y (anterior/posterior), and z (head/feet) directions determined by volumetric linear fitting, were < 0.01 Hz/cm, 0.18 Hz/cm, and 0.26 Hz/cm, respectively. These compared favorably with previous reports. We found that simulation voxel sizes greater than 5 mm can produce unreliable results. Conclusion: We have presented an efficient simulation framework for respiration-induced $B_0$ variation in the head. The method can be used to predict $B_0$ shifts with high spatiotemporal resolution under different breathing conditions and aid in the design of dynamic $B_0$ compensation strategies.

• 대한원격탐사학회지
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• 제33권2호
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• pp.149-158
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• 2017

시간해상도와 공간해상도가 높은 영상 자료는 효과적인 식생의 모니터링을 위해서 필수적이다. 하지만 단일 센서를 통한 영상은 공간해상도와 시간해상도가 높은 자료를 동시에 제공할 수 없는 한계점이 있다. 최근에는 위성영상의 공간적 해상도를 높이고 시간해상도를 보완하기 위해서 시공간 융합연구가 진행되고 있다. 그 중에서도 FSDAF(Flexible spatiotemporal data fusion) 방법론은 위성영상의 각 밴드를 융합하는 방법으로 적절한 것으로 나타났다. 본 연구에서는 FSDAF 융합기법을 활용하여 MODIS NDVI와 Landsat 영상으로 계산한 NDVI를 융합 후 검증을 실시하였으며 식생 계절 모니터링에서의 활용가능성을 제시하였다. 그 결과, 1월부터 12월까지 융합을 통해 NDVI 예측한 영상은 활엽수, 침엽수, 농지의 계절적인 특징을 잘 반영하고 있었다. 융합된 결과의 검증을 위하여 8월과 10월의 예측한 NDVI와 실제 값(Landsat NDVI) 간의 RMSE 값을 계산한 결과 각각 0.049와 0.085, 상관계수는 0.765, 0.642로 비교적 일치한 것으로 나타났다. 본 연구에서 활용된 FSDAF 시공간 융합 기법은 픽셀기반의 융합기법으로 다양한 공간스케일의 영상과도 융합 가능할 것이며 다양한 식생 관련 연구에 활용될 것으로 기대된다.

• 대기
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• 제32권4호
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• pp.307-322
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• 2022

A drone has recently got attention as an instrument for weather observation in lower atmosphere because it can produce the high spatiotemporal resolution weather data even though the weather phenomenon is inaccessible. Sea fog is a weather phenomenon occurred in lower atmosphere, and has observational limitations because it occurs on the sea. Therefore, goal of this study is to analyze the vertical structures about inflow, development and dispersion of sea fog using the high-resolution weather data with the meteorological sensor-equipped drone. This study observed sea fogs in the west coast of the Korean peninsula from March to October 2021 and investigated one sea fog inflowed into the coast on June 8th 2021. θ_e - q_v diagrams (θ_e: equivalent potential temperature, q_v: water vapor ratio) and vertical wind structures were analyzed. At inflow of sea fog, moist adiabatically stable layer was formed in 0-300 m and prevailing wind was switched from south-southwesterly to west-southwesterly under 120 m. Both changes are favorable for sea fog on the location. θ_e and q_v plummeted in a layer 0-183 m. The inflowed sea fog developed from 183 m to 327 m by mixing with ambient atmosphere on top of sea fog. Also, strong mechanical turbulence near ground drove a vertical mixing under stable layer. At dispersion of sea fog, as θ_e on ground gradually increased, air condition was changed to neutral. Evaporation occurred on both bottom and top in sea fog. These results induced dissipation of sea fog.

• Ocean and Polar Research
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• 제35권2호
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• pp.135-146
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• 2013

This study investigates the characteristic of the Tsushima Warm Current from an assimilated high resolution global ocean prediction model, $1/12^{\circ}$ Global HYbrid Coordiate Ocean Model (HYCOM). The model results were verified through a comparison with current measurements obtained by acoustic Doppler current profiler (ADCP) mounted on the passenger ferryboat between Busan, Korea, and Hakata, Japan. The annual mean transport of the Tsushima Warm Current was 2.56 Sverdrup (Sv) (1 Sv = $10^6m^3s^{-1}$), which is similar to those from previous studies (Takikawa et al. 1999; Teague et al. 2002). The volume transport time series of the Tsushima Warm Current from HYCOM correlates to a high degree with that from the ADCP observation (the correlation coefficient between the two is 0.82). The spatiotemporal structures of the currents as well as temperature and salinity from HYCOM are comparable to the observed ones.

• 대한원격탐사학회지
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• 제36권5_1호
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• pp.807-821
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• 2020

이 연구에서는 작물 모니터링을 위한 시계열 고해상도 영상 구축을 위해 기존 중저해상도 위성영상의 융합을 위해 개발된 대표적인 시공간 융합 모델의 적용성을 평가하였다. 특히 시공간 융합 모델의 원리를 고려하여 입력 영상 pair의 특성 차이에 따른 모델의 예측 성능을 비교하였다. 농경지에서 획득된 시계열 Sentinel-2 영상과 RapidEye 영상의 시공간 융합 실험을 통해 시공간 융합 모델의 예측 성능을 평가하였다. 시공간 융합 모델로는 Spatial and Temporal Adaptive Reflectance Fusion Model(STARFM), SParse-representation-based SpatioTemporal reflectance Fusion Model(SPSTFM)과 Flexible Spatiotemporal DAta Fusion(FSDAF) 모델을 적용하였다. 실험 결과, 세 시공간 융합 모델은 예측 오차와 공간 유사도 측면에서 서로 다른 예측 결과를 생성하였다. 그러나 모델 종류와 관계없이, 예측 시기와 영상 pair가 획득된 시기 사이의 시간 차이보다는 예측 시기의 저해상도 영상과 영상 pair의 상관성이 예측 능력 향상에 더 중요한 것으로 나타났다. 또한 작물 모니터링을 위해서는 오차 전파 문제를 완화할 수 있는 식생지수를 시공간 융합의 입력 자료로 사용해야 함을 확인하였다. 이러한 실험 결과는 작물 모니터링을 위한 시공간 융합에서 최적의 영상 pair 및 입력 자료 유형의 선택과 개선된 모델 개발의 기초정보로 활용될 수 있을 것으로 기대된다.

• 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.

• 대한원격탐사학회지
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• 제36권4호
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• pp.609-626
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• 2020

Satellite-based land surface temperature (LST) has been used as one of the major parameters in various climate and environmental models. Especially, Moderate Resolution Imaging Spectroradiometer (MODIS) LST is the most widely used satellite-based LST product due to its spatiotemporal coverage (1 km spatial and sub-daily temporal resolutions) and longevity (> 20 years). However, there is an increasing demand for LST products with finer spatial resolution (e.g., 10-250 m) over regions such as urban areas. Therefore, various methods have been proposed to produce high-resolution MODIS-like LST less than 250 m (e.g., 100 m). The purpose of this review is to provide a comprehensive overview of recent research trends and challenges for the downscaling of MODIS LST. Based on the recent literature survey for the past decade, the downscaling techniques classified into three groups-kernel-driven, fusion-based, and the combination of kernel-driven and fusion-based methods-were reviewed with their pros and cons. Then, five open issues and challenges were discussed: uncertainty in LST retrievals, low thermal contrast, the nonlinearity of LST temporal change, cloud contamination, and model generalization. Future research directions of LST downscaling were finally provided.

• 한국환경과학회지
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• 제23권3호
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• pp.503-510
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• 2014

To estimate the benefit of high-resolution meteorological data for building energy estimation, a building energy analysis has been conducted over Busan metropolitan areas. The heating and cooling load has been calculated at seven observational sites by using temperature, wind and relative humidity data provided by WRF model combined with the inner building data produced by American Society of Heating Refrigeration and Air-conditioning Engineers (ASHRAE). The building energy shows differences 2-3% in winter and 10-30% in summer depending on locations. This result implicates that high spatiotemporal resolution of meteorological model data is significantly important for building energy analysis.

• BMB Reports
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• 제52권10호
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• pp.589-594
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• 2019

Single-molecule techniques have been used successfully to visualize real-time enzymatic activities, revealing transient complex properties and heterogeneity of various biological events. Especially, conventional force spectroscopy including optical tweezers and magnetic tweezers has been widely used to monitor change in DNA length by enzymes with high spatiotemporal resolutions of ~nanometers and ~milliseconds. However, DNA metabolism results from coordination of a number of components during the processes, requiring efficient monitoring of a complex of proteins catalyzing DNA substrates. In this min-review, we will introduce a simple and multiplexed single-molecule assay to detect DNA substrates catalyzed by enzymes with high-throughput data collection. We conclude with a perspective of possible directions that enhance capability of the assay to reveal complex biological events with higher resolution.

• 한국농공학회논문집
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• 제63권4호
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• pp.23-32
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• 2021

For agricultural water management, it is essential to establish the digital infrastructure data such as agricultural watershed, irrigated area and canal network in rural areas. Approximately 70,000 irrigation facilities in agricultural watershed, including reservoirs, pumping and draining stations, weirs, and tube wells have been installed in South Korea to enable the efficient management of agricultural water. The total length of irrigation and drainage canal network, important components of agricultural water supply, is 184,000 km. Major problem faced by irrigation facilities management is that these facilities are spread over an irrigated area at a low density and are difficult to access. In addition, the management of irrigation facilities suffers from missing or errors of spatial information and acquisition of limited range of data through direct survey. Therefore, it is necessary to establish and redefine accurate identification of irrigated areas and canal network using up-to-date high resolution images. In this study, previous existing data such as RIMS (Rural Infrastructure Management System), smart farm map, and land cover map were used to redefine irrigated area and canal network based on appropriate image data using satellite imagery, aerial imagery, and drone imagery. The results of the building the digital infrastructure in rural areas are expected to be utilized for efficient water allocation and planning, such as identifying areas of water shortage and monitoring spatiotemporal distribution of water supply by irrigated areas and irrigation canal network.