• The Korean Journal of Nuclear Medicine Technology
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• v.14 no.1
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• pp.24-27
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• 2010

Purpose: Early diagnosis of breast is of the utmost importance to improve prognosis. We have a limitation for mammography and sonography detecting small cancer. Clinical importance of Breast Specific Gamma Imaging (BSGI) has improved for that reason. So We studied performance evaluation test of count rate and resolution with high sensitivity to the low dose of BSGI. Materials and Methods: BSGI of Dilon 6800, point source of $^{99m}Tc$ from 1.85~148 MBq (0.05~4 mCi) at the intervals of 1.85~37 MBq (0.05~1 mCi) was used for the test. Performance evaluation method was performed for measuring deadtime for choosing at the 5 different point in the useful field of view (UFOV), acquired image for 60 seconds. Compared with reference of clinical uptake distribution of breast, activity increased according to the distance change 10, 20, 30, 40, 50 mm in the useful field of view. Results: Counting curve increased according to the activity from 1.85 MBq (0.05 mCi) to the 74 MBq (2 mCi), and it change flat shape over 74 MBq (2 mCi). The variation of the full width of half maximum (FWHM) to the distance is 4.05, 4.73, 5.77, 6.90, 8.00, 9.32 mm in 1.85 MBq (0.05 mCi), 4.30, 4.80, 5.90, 7.00, 8.10, 9.07 mm in 3.7 MBq (0.1 mCi), 4.90, 5.60, 6.20, 7.20, 8.20, 9.10 mm in 5.55 MBq (0.15 mCi), 5.30, 6.10, 6.60, 7.00, 7.90, 8.70 mm in 7.40 MBq (0.2 mCi). Conclusion: Distortions of image would be acquired because of the deadtime in BSGI. We found out the fact that specification of $^{99m}Tc$ reaction under 74 MBq (2 mCi) for BSGI. Second, FWHM distribution change from varied distance from the detector, clearly distinguished the location of the lesion.

• Korean Journal of Cognitive Science
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• v.27 no.4
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• pp.573-597
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• 2016

Recent fMRI and EEG research for neural representations of action concepts insist that processing of action concepts evoke the simulation of sensory-motor information. Moreover, there are several behavioral studies showing that understanding of action verbs or sentences describing actions interfere or facilitate current action performance. However, it is unclear that online interaction between processing of action concepts and current action is based on the simulation of sensory-motor information, or other neural mechanisms. The present research aims to explore the underlying neural mechanism that how the perception of action language influence the performance of current action using high-spacial temporal resolution EEG and multiple source analysis techniques. For this, participants were asked to perform a cued-motor reaction task in which button-pressing hand action and pedal-stepping foot action were required according to the color of the cue, and we presented auditorily action verbs describing the responding actions (i.e., /press/, /step/, /stop/) just before the color cue and examined the interaction effect from the semantic congruency between the action verbs and the current action. Behavioral results revealed consistently a facilitatory effect when action verbs and responding actions were semantically congruent in both button-pressing and pedal-stepping actions, and an inhibitory effect when semantically incongruent in the button-pressing action condition. In the results of EEG source waveform analysis, the semantic congruency effects between action verbs and the responding actions were observed in the Wernicke's area during the perception of action verbs, in the anterior cingulate gyrus and the supplementary motor area (SMA) at the time when the motor-cue was presented, and in the SMA and primary motor cortex (M1) during action execution stage. Based on the current findings, we argue that perceived action verbs evoke the facilitation/inhibition effect by influencing the expectation and preparation stage of following actions rather than the directly activating the particular motor cortex. Finally we discussed the implication on the neural representation of action concepts and methodological limitations of the current research.

• The Journal of the Acoustical Society of Korea
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• v.35 no.4
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• pp.261-271
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• 2016

In the prediction of response of a pile in soil, numerical approaches such as a finite element method are generally applied due to complicate nonlinear behaviors of soils. However, the numerical methods based on the finite elements require heavy efforts in pile and soil modelling and also take long computing time. So their usage is limited especially in the early design stage in which principal dimensions and properties are not specified and tend to vary. On the contrary, theoretical approaches adopting linear approximations for soils are relatively simple and easy to model and take short computing time. Therefore, if they are validated to be reliable, they would be applicable in predicting responses of a pile in soil, particularly in early design stage. In case of wind turbines regarded in this study, it is required to assess their natural frequencies in early stages, and in this simulation the supporting pile inserted in soil could be replaced with a simplified elastic boundary condition at the bottom end of the wind turbine tower. To do this, analysis for a pile in soil is performed in this study to extract the spring constants at the top end of the pile. The pile in soil can be modelled as a beam on elastic spring by assuming that the soils deform within an elastic range. In this study, it is attempted to predict pile deformations and influence factors for lateral loads by means of the beam-on-spring model. As two example supporting structures for wind turbines, mono pile and suction pile models with different diameters are examined by evaluating their influence factors and validated by comparing them with those reported in literature. In addition, the deflection profiles along the depth and spring constants at the top end of the piles are compared to assess their supporting features.

• Journal of the Mineralogical Society of Korea
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• v.20 no.4
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• pp.277-287
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• 2007

To understand the effects of the powdered manganese nodule and sea bottom sediment pumped up with nodules on the mining process, the shattering ratio of manganese nodule and their physical properties are analyzed. The self shattering ratio and crushing shattering ratio are about 27% and about 3%, respectively. Then total shattering ratio is about 30%. The initial turbidity of the powdered manganese nodule and the bottom sediment show high, i.e., about 3,100 and 1,850 respectively. But their turbidities decrease rapidly with time. After 1 hour, turbidity of the powdered manganese nodule drops to about 1,570 and that of the bottom sediment to 1,310. The turbidity of Na-bentonite changes from 820 to 730 after 1 h and to 700 after 2 h. The viscosity of powdered manganese nodule is $1.4{\sim}1.5cP$, and the viscosity of bottom sediment is less than 1 cP. The viscosity fo Na-bentonite is initially 37.2 and increase with time to 86.4 cP after 30 min. The high initial turbidity of powdered manganese nodule is due to dark color of the powder. The high specific gravity makes rapid precipitation and then decreases the turbidity rapidly. The bottom sediment shows high initial turbidity because of easy suspension with very fine particle size. But it cannot be hydrated and formed gel in suspension, then it is easily precipitated. However Na-bentonite is hydrated to the expended state and makes gel state, then it shows high turbidity and high viscosity. These physical properties of the powdered manganese nodule suggest that the powder of manganese nodule should not make scaling inside of lifting pipe or pump. And the bottom sediment lifted up with manganese nodule should not play the role of drilling mud shch as Na-bentonite.

• Korean Journal of Remote Sensing
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• v.37 no.5_2
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• pp.1259-1268
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• 2021

The 2nd Geostationary Ocean Color Imager (GOCI-II) is the successor to the Geostationary Ocean Color Imager (GOCI), which employs one near-ultraviolet wavelength (380 nm) and eight visible wavelengths(412, 443, 490, 510, 555, 620, 660, 680 nm) and three near-infrared wavelengths(709, 745, 865 nm) to observe the marine environment in Northeast Asia, including the Korean Peninsula. However, the multispectral radiance image observed at satellite altitude includes both the water-leaving radiance and the atmospheric path radiance. Therefore, the atmospheric correction process to estimate the water-leaving radiance without the path radiance is essential for analyzing the ocean environment. This manuscript describes the GOCI-II standard atmospheric correction algorithm and its initial phase validation. The GOCI-II atmospheric correction method is theoretically based on the previous GOCI atmospheric correction, then partially improved for turbid water with the GOCI-II's two additional bands, i.e., 620 and 709 nm. The match-up showed an acceptable result, with the mean absolute percentage errors are fall within 5% in blue bands. It is supposed that part of the deviation over case-II waters arose from a lack of near-infrared vicarious calibration. We expect the GOCI-II atmospheric correction algorithm to be improved and updated regularly to the GOCI-II data processing system through continuous calibration and validation activities.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.24 no.3
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• pp.375-388
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• 2019

Accurate evaluation of sea-to-air $CO_2$ flux and its variability is crucial information to the understanding of global carbon cycle and the prediction of atmospheric $CO_2$ concentration. $fCO_2$ observations are sparse in space and time in the East Sea. In this study, we derived high resolution time series of surface $fCO_2$ values in the southwest East Sea, by feeding sea surface temperature (SST), salinity (SSS), chlorophyll-a (CHL), and mixed layer depth (MLD) values, from either satellite-observations or numerical model outputs, to three machine learning models. The root mean square error of the best performing model, a Random Forest (RF) model, was $7.1{\mu}atm$. Important parameters in predicting $fCO_2$ in the RF model were SST and SSS along with time information; CHL and MLD were much less important than the other parameters. The net $CO_2$ flux in the southwest East Sea, calculated from the $fCO_2$ predicted by the RF model, was $-0.76{\pm}1.15mol\;m^{-2}yr^{-1}$, close to the lower bound of the previous estimates in the range of $-0.66{\sim}-2.47mol\;m^{-2}yr^{-1}$. The time series of $fCO_2$ predicted by the RF model showed a significant variation even in a short time interval of a week. For accurate evaluation of the $CO_2$ flux in the Ulleung Basin, it is necessary to conduct high resolution in situ observations in spring when $fCO_2$ changes rapidly.

• Journal of Korea Water Resources Association
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• v.52 no.5
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• pp.361-372
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• 2019

The purpose of this study is to develop a two-dimensional land surface flood analysis model based on uniform square grid using the governing equations except for the convective acceleration term in the momentum equation. Finite volume method and implicit method were applied to spatial and temporal discretization. In order to reduce the execution time of the model, parallel computation techniques using CPU were applied. To verify the developed model, the model was compared with the analytical solution and the behavior of the model was evaluated through numerical experiments in the virtual domain. In addition, inundation analyzes were performed at different spatial resolutions for the domestic Janghowon area and the Sebou river area in Morocco, and the results were compared with the analysis results using the CAESER-LISFLOOD (CLF) model. In model verification, simulation results were well matched with the analytical solution, and the flow analyses in the virtual domain were also evaluated to be reasonable. The results of inundation simulations in the Janghowon and the Sebou river area by this study and CLF model were similar with each other and for Janghowon area, the simulation result was also similar to the flooding area of flood hazard map. The different parts in the simulation results of this study and the CLF model were compared and evaluated for each case. The results of this study suggest that the model proposed in this study can simulate the flooding well in the floodplain. However, in case of flood analysis using the model presented in this study, the characteristics and limitations of the model by domain composition method, governing equation and numerical method should be fully considered.

• The Korean Journal of Nuclear Medicine Technology
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• v.26 no.1
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• pp.27-32
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• 2022

Purpose When performing a whole-body bone scan, many patients are experiencing psychological difficulties due to the close distance to the detector. Recently, in the medical field, there is a report that using virtual reality (VR) equipment can give pain relief to pediatric patients with weak concentration or patients receiving severe treatment through a distraction method. Therefore, in this paper, VR equipment was used to provide psychological stability to patients during nuclear medicine tests, and it is intended to evaluate whether it can be used in clinical practice. Materials and Methods As VR equipment, ALLIP Z6 VR (ALLIP, Korea) was used and the experiment was conducted after connecting to a mobile phone. The subjects were 30 patients who underwent whole-body bone examination from September 1, 2021 to September 30, 2021. After intravenous injection of 99mTc-HDP, 3 to 6 hours later, VR equipment was put on and whole body images were obtained. After the test, a survey was conducted, and a Likert scale of 5 points was used for psychological anxiety and satisfaction with VR equipment. Hypothesis verification and reliability of the survey were analyzed using SPSS Statistics 25 (IBM, Corp., Armonk, NY, USA). Results Anxiety about the existing whole-body bone test was 3.03±1.53, whereas that of anxiety after wearing VR equipment was 2.0±1.21, indicating that anxiety decreased to 34%. When regression analysis of the effect of the patient's concentration on VR equipment on anxiety about the test, the B value was 0.750 (P<0.01) and the t value was 6.181 (P<0.01). decreased and showed an influence of 75%. In addition, overall satisfaction with VR equipment was 3.76±1.28, and the intention to reuse was 66%. The Cronbach α value of the reliability coefficient of the questionnaire was 0.901. Conclusion When using VR equipment, patients' attention was dispersed, anxiety was reduced, and psychological stability was found. In the future, as VR equipment technology develops, it is thought that if the equipment can be miniaturized and the resolution of VR content images is increased, it can be used in various clinical settings if it provides more realistic stability to the patient.

• Journal of Korea Water Resources Association
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• v.55 no.8
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• pp.623-634
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• 2022

Due to river maintenance projects such as the creation of hydrophilic areas around rivers and the Four Rivers Project, the flow characteristics of rivers are continuously changing, and the risk of water quality accidents due to the inflow of various pollutants is increasing. In the event of a water quality accident, it is necessary to minimize the effect on the downstream side by predicting the concentration and arrival time of pollutants in consideration of the flow characteristics of the river. In order to track the behavior of these pollutants, it is necessary to calculate the diffusion coefficient and dispersion coefficient for each section of the river. Among them, the dispersion coefficient is used to analyze the diffusion range of soluble pollutants. Existing experimental research cases for tracking the behavior of pollutants require a lot of manpower and cost, and it is difficult to obtain spatially high-resolution data due to limited equipment operation. Recently, research on tracking contaminants using RGB drones has been conducted, but RGB images also have a limitation in that spectral information is limitedly collected. In this study, to supplement the limitations of existing studies, a hyperspectral sensor was mounted on a remote sensing platform using a drone to collect temporally and spatially higher-resolution data than conventional contact measurement. Using the collected spatio-temporal hyperspectral images, the tracer concentration was calculated and the transverse dispersion coefficient was derived. It is expected that by overcoming the limitations of the drone platform through future research and upgrading the dispersion coefficient calculation technology, it will be possible to detect various pollutants leaking into the water system, and to detect changes in various water quality items and river factors.

• Korean Journal of Remote Sensing
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• v.39 no.6_2
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• pp.1651-1669
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• 2023

Sea ice currently covers approximately 7% of the world's ocean area, primarily concentrated in polar and high-altitude regions, subject to seasonal and annual variations. It is very important to analyze the area and type classification of sea ice through time series monitoring because sea ice is formed in various types on a large spatial scale, and oil and gas exploration and other marine activities are rapidly increasing. Currently, research on the type and area of sea ice is being conducted based on high-resolution satellite images and field measurement data, but there is a limit to sea ice monitoring by acquiring field measurement data. High-resolution optical satellite images can visually detect and identify types of sea ice in a wide range and can compensate for gaps in sea ice monitoring using Geostationary Ocean Color Imager-II (GOCI-II), an ocean satellite with short time resolution. This study tried to find out the possibility of utilizing sea ice monitoring by training a rule-based machine learning model based on learning data produced using high-resolution optical satellite images and performing detection on GOCI-II images. Learning materials were extracted from Liaodong Bay in the Bohai Sea from 2021 to 2022, and a Random Forest (RF) model using GOCI-II was constructed to compare qualitative and quantitative with sea ice areas obtained from existing normalized difference snow index (NDSI) based and high-resolution satellite images. Unlike NDSI index-based results, which underestimated the sea ice area, this study detected relatively detailed sea ice areas and confirmed that sea ice can be classified by type, enabling sea ice monitoring. If the accuracy of the detection model is improved through the construction of continuous learning materials and influencing factors on sea ice formation in the future, it is expected that it can be used in the field of sea ice monitoring in high-altitude ocean areas.