• Bulletin of the Korean Space Science Society
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• 2010.04a
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• pp.30.3-31
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• 2010

We performed a comprehensive comparison between GPS Global Ionosphere Map (GIM) and TOPEX/Jason (T-J) TEC data for the periods of 1998~2009 in order to assess the performance of GIM over the global ocean where the GPS ground stations are very sparse. Using the GIM model constructed by CODE at University of Bern, the GIM TEC values were obtained along the T-J satellite orbit at the locations and times of the measurements and then binned into various geophysical conditions for direct comparison with the T-J TECs. On the whole, the GIM model was able to reproduce the spatial and temporal variations of the global ionosphere as well as the seasonal variations. However, the GIM model was not accurate enough to represent the well-known ionospheric structures such as the equatorial anomaly, the Weddell Sea Anomaly, and the longitudinal wave structure. Furthermore, there seems to be a fundamental limitation of the model showing the unexpected negative differences (i.e., GPS < T-J) in the northern high latitude and the southern middle and high latitude regions. The positive relative differences (i.e., GIM > T-J) at night represent the plasmaspheric contribution to GPS TEC, which is maximized, reaching up to 100% of the corresponding T-J TEC values in the early morning sector. In particular, the relative differences decreased with increasing solar activity and this may indicate that the plasmaspheric contribution to the maintenance of the nighttime ionosphere does not increase with solar activity, which is different from what we normally anticipate. Among these results, the plasmaspheric contribution to the ionospheric GPS TEC will be presented in this talk and the rest of it will presented in the companion paper (poster presentation).

• Korean Journal of Remote Sensing
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• v.35 no.5_2
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• pp.781-796
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• 2019

This study attempted to simulate the flood discharge in the Duman River basin containing Hoeryong City and Musan County of North Korea where were damaged from Typhoon Lionrock on August, 2016. For hydrological modelling remotely sensed datasets were used to estimate watershed properties and hydrologic factors because the basin is ungauged where hydrological observation is not exist or sparse. For validation we applied our methodology and datasets to the Soyanggang Dam basin. It has not only similar shape factor and compactness ratio to those of the target basin but also accurate, adequate, and abundant measurements. The results showed that the flood discharge from Typhoon Lionrock corresponded to three to five years design floods in the Duman River basin. This indicate that the Duman River basin has a high risk of flood in the near future. Finally this study demonstrated that remotely sensed data and geographic information could be utilized to simulate flood discharge in an ungauged watershed.

• Nuclear Engineering and Technology
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• v.55 no.8
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• pp.3030-3038
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• 2023

Nowadays, mobile robots have been used to search for uncontrolled radioactive source in indoor environments to avoid radiation exposure for technicians. However, in the indoor environments, especially in the presence of obstacles, how to make the robots with limited sensing capabilities automatically search for the radioactive source remains a major challenge. Also, the source search efficiency of robots needs to be further improved to meet practical scenarios such as limited exploration time. This paper proposes an automatic source search strategy, abbreviated as ACA: the location of source is estimated by a convolutional neural network (CNN), and the path is planned by the A-star algorithm. First, the search area is represented as an occupancy grid map. Then, the radiation dose distribution of the radioactive source in the occupancy grid map is obtained by Monte Carlo (MC) method simulation, and multiple sets of radiation data are collected through the eight neighborhood self-avoiding random walk (ENSAW) algorithm as the radiation data set. Further, the radiation data set is fed into the designed CNN architecture to train the network model in advance. When the searcher enters the search area where the radioactive source exists, the location of source is estimated by the network model and the search path is planned by the A-star algorithm, and this process is iterated continuously until the searcher reaches the location of radioactive source. The experimental results show that the average number of radiometric measurements and the average number of moving steps of the ACA algorithm are only 2.1% and 33.2% of those of the gradient search (GS) algorithm in the indoor environment without obstacles. In the indoor environment shielded by concrete walls, the GS algorithm fails to search for the source, while the ACA algorithm successfully searches for the source with fewer moving steps and sparse radiometric data.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39A no.12
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• pp.746-755
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• 2014

Compressive sensing (CS) has drawn much interest as a new sampling technique that enables signals to be sampled at a much lower than the Nyquist rate. By noting that the block-based compressive sensing can still keep spatial correlation in measurement domain, in this paper, we propose a novel encoding technique for measurement data obtained in the block-based CS of natural image. We apply discrete wavelet transform (DWT) to decorrelate CS measurements and then assign a proper quantization scheme to those DWT coefficients. Thus, redundancy of CS measurements and bitrate of system are reduced remarkably. Experimental results show improvements in rate-distortion performance by the proposed method against two existing methods of scalar quantization (SQ) and differential pulse-code modulation (DPCM). In the best case, the proposed method gains up to 4 dB, 0.9 dB, and 2.5 dB compared with the Block-based CS-Smoothed Projected Landweber plus SQ, Block-based CS-Smoothed Projected Landweber plus DPCM, and Multihypothesis Block-based CS-Smoothed Projected Landweber plus DPCM, respectively.

• Economic and Environmental Geology
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• v.35 no.3
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• pp.273-284
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• 2002

The Gravity-Geologic Method (GGM) was implemented for bathymetric determinations in the Drake Passage, Antarctica, using global marine Free-air Gravity Anomalies (FAGA) data sets by Sandwell and Smith (1997) and local echo sounding measurements. Of the 6548 bathymetric sounding measurements, two thirds of these points were used as control depths, while the remaining values were used as checkpoints. A density contrast of 9.0 gm/㎤ was selected based on the checkpoints predictions with changes in the density contrast assumed between the seawater and ocean bottom topographic mass. Control depths from the echo soundings were used to determine regional gravity components that were removed from FAGA to estimate the gravity effects of the bathymetry. These gravity effects were converted to bathymetry by inversion. In particular, a selective merging technique was developed to effectively combine the echo sounding depths with the GGM bathymetiy to enhance high frequency components along the shipborne sounding tracklines. For the rugged bathymetry of the research area, the GGM bathymetry shows correlation coefficients (CC) of 0.91, 0.92, and 0.85 with local shipborne sounding by KORDI, GEODAS, and a global ETOPO5 model, respectively. The enhanced GGM by selective merging shows imploved CCs of 0.948 and 0.954 with GEODAS and Smith & Sandwell (1997)'s predictions with RMS differences of 449.8 and 441.3 meters. The global marine FAGA data sets and other bathymetric models ensure that the GGM can be used in conjunction with shipborne bathymetry from echo sounding to extend the coverage into the unmapped regions, which should generate better results than simply gridding the sparse data or relying upon lower resolution global data sets such as ETOPO5.

• Journal of the East Asian Society of Dietary Life
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• v.18 no.4
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• pp.554-562
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• 2008

In this study, we attempted to assess the efficacy of a method to improve the quality of prepared bread via the addition Poria cocos powder to wheat flour at a range of concentrations from $0{\sim}5%$. The approximate composition for Poria cocos powder was as follow: moisture 7.67%, crude protein 0.61%, crude fat 0.58%, crude ash 0.32%, and crude fiber 0.30%, when using the flour to which the Poria cocos powder had been added, specific volume, falling number, and dough yield values all increased with increasing concentrations of added Poria cocos powder. The result of our microscopic observations revealed a relative scarcity of larger starch granules, and the bread prepared with the Poria cocos powder evidenced a sparse structure. With regard to the Hunters color value measurements, the L value decreased with increasing concentrations of Poria cocos powder. but the a and b values evidenced an inverse relationship with the concentration of added powder. The texture, hardness, and adhesiveness characteristics of the bread decreased with increasing concentration of added Poria cocos powder. but the gumminess and chewiness of the bread increased. However, we noted no significant differences in the springiness and cohesiveness characteristics among the experimental groups assessed herein. In the sensory evaluation, the quality of the 2% or 3% Poria cocos powder breads was optimal in terms of its taste and flavor.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.1
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• pp.82-88
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• 2021

Sun-induced fluorescence (SIF) retrieval using remote sensing technique has been used in an effort to understand the photosynthetic efficiency and stress condition of vegetation. Although optical devices and SIF retrieval methodologies were established in order to retrieve SIF, the SIF measurements are domestically sparse. SIF data of paddy rice w as measured in Naju, South Korea from June 10, 2020 to October 5, 2020. The SIFs based red (O2A) and far-red (O2B) w ere retrieved using a spectral fitting method and an improved Fraunhofer line depth, and photosynthetically active radiation was also produced. In addition, the SIF data was filtered considering solar zenith angle, saturation conditions, the rapid and sudden change of solar irradiance, and sun glint. The provided SIF data can help to understand a SIF product and the filtering method of SIF data can contribute to producing high-quality SIF data.