• Journal of the Korean Association of Geographic Information Studies
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• v.17 no.2
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• pp.156-172
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• 2014

This research measures and compares on-site net radiation energy, air temperature, wind speed, and surface temperature considering various spatial characteristics with a focus on land use types in urban areas in Changwon, Southern Gyeongsangnam-do, to analyze the accuracy of an ENVI-met model, which is an analysis program of microclimate. The on-site measurement was performed for three days in a mobile measurement: two days during the daytime and one day during the nighttime. The analysis using the ENVI-met model was also performed in the same time zone as the on-site measurement. The results indicated that the ENVI-met model showed higher net radiation than the on-site measurement by approximately $300Wm^{-2}$ during the daytime whereas the latter showed higher net radiation energy by approximately $200Wm^{-2}$ during the nighttime. The temperature was found to be much higher by approximately $2-6^{\circ}C$ in the on-site measurement during both the daytime and nighttime. The on-site measurement also showed higher surface temperature than the ENVI-met by approximately $7-13^{\circ}C$. In terms of the wind speed, there was a significant difference between the results of the ENVI-met model and on-site measurement. As for the correlation between the results of the ENVI-met model and on-site measurement, the temperature showed significantly high correlation whereas the correlations for the net radiation energy, surface temperature, and wind speed were very low. These results appear to be affected by excessive or under estimation of solar and terrestrial radiation and climatic conditions of the surrounding areas and characteristics of land cover. Hence, these factors should be considered when applying these findings in urban and environment planning for improving the microclimate in urban areas.

• Journal of the Korea Concrete Institute
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• v.19 no.1
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• pp.121-130
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• 2007

To investigate the enhancement in strength and deformation capacities of concrete confined by FRP composites, tests under axial loads were carried out on three groups of thirty six short columns in circular section with diverse GFRP confining reinforcement. The major test variables considered include fiber content or orientation, wrap or tube type by varying the end loading condition, and continuous or discontinuous confinement depending on the presence of vortical spices between its two halves. The circumferential FRP strains at failure for different types of confinements were also investigated with emphasis. Various analytical models capable of predicting the ultimate strength and strain of the confined concrete were examined by comparing to observed results. Tests results showed that FRP wraps or tubes provide the substantial increase in strength and deformation, while partial wraps comprising the vertical discontinuities fail in an explosive manner with less increase in strength, particularly in deformation. A bilinear stress-strain response was observed throughout all tests with some variations of strain hardening. The failure hoop strains measured on the FRP surface were less than those obtained from the tensile coupons in all tests with a high degree of variation. In overall, existing predictive equations overestimated ultimate strengths and strains observed in present tests, with a much larger scatter related to the latter. For more accuracy, two simple design- oriented equations correlated with present tests are proposed. The strength equation was derived using the Mohr-Coulomb failure criterion, whereas the strain equation was based on entirely fitting of test data including the unconfined concrete strength as one of governing factors.

• Journal of the Korean Society of Food Science and Nutrition
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• v.31 no.1
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• pp.160-169
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• 2002

This study was carried to investigate the nutrition knowledge, dietary habits and nutrition attitude of 227 teachers of elementary and middle school in Masan city. The survey was conducted by a self-administered questionnaire. The results showed that the subjects had a high level of perceived nutrition knowledge (85.2%), but the accuracy of the knowledge was 76.2%, and percentage of correct answers was 65.5%. The average nutrition knowledge score was 13.1 out of possible 20 points, the average score of dietary habits was 76.2 and nutrition attitudes score was 70.8 out of 100 points. Most of the subjects are belonged to the 'good'group in terms of nutrition knowledge, dietary habits and nutrition attitudes level. Female teachers scored significantly higher on nutrition knowledge and nutrition attitudes than male teachers did (p<0.001). And elementary school teachers scored significantly higher on dietary habits than noddle school teachers (p<0.01). There was a highly significant correlations between nutrition knowledge and nutrition attitude (r =0.3, p<0.001); dietary habit and nutrition attitude (r : 0.4, p<0.001). But the correlation between nutrition knowledge and dietary habits was not significant.

• Journal of Radiation Protection and Research
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• v.39 no.1
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• pp.54-60
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• 2014

IAEA has employed various types of radiation detectors - HPGe, NaI, CZT - for accountancy of nuclear material. Among them, HPGe has been mainly used in verification activities required for high accuracy. Due to its essential cooling component(a liquid-nitrogen cooling or a mechanical cooling system), it is large and heavy and needs long cooling time before use. New hand-held portable HPGe has been developed to address such problems. This paper deals with results of performance evaluation test of the new hand-held portable HPGe prototype which was used during IAEA's inspection activities. Radioactive spectra obtained with the new portable HPGe showed different characteristics depending on types and enrichments of nuclear materials inspected. Also, Gamma-rays from daughter radioisotopes in the decay series of $^{235}U$ and $^{238}U$ and characteristic x-rays from uranium were able to be remarkably separated from other peaks in the spectra. A relative error of enrichment measured by the new portable HPGe was in the range of 9 to 27%. The enrichment measurement results didn't meet partially requirement of IAEA because of a small size of a radiation sensing material. This problem might be solved through a further study. This paper discusses how to determine enrichment of nuclear material as well as how to apply the new hand-held portable HPGe to safeguard inspection. There have been few papers to deal with IAEA inspection activity in Korea to verify accountancy of nuclear material in national nuclear facilities. This paper would contribute to analyzing results of safeguards inspection. Also, it is expected that things discussed about further improvement of a radiation detector would make contribution to development of a radiation detector in the related field.

• Progress in Medical Physics
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• v.5 no.2
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• pp.57-68
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• 1994

Purpose : The purposes are to discuss the reason to measure dose distributions of circular small fields for stereotactic radiosurgery based on medical linear accelerator, finding of beam axis, and considering points on dosimetry using home-made small water phantom, and to report dosimetric results of 10MV X-ray of Clinac-18, like as TMR, OAR and field size factor required for treatment planning. Method and material : Dose-response linearity and dose-rate dependence of a p-type silicon (Si) diode, of which size and sensitivity are proper for small field dosimetry, are determined by means of measurement. Two water tanks being same in shape and size, with internal dimension, 30${\times}$30${\times}$30cm$^3$ were home-made with acrylic plates and connected by a hose. One of them a used as a water phantom and the other as a device to control depth of the Si detector in the phantom. Two orthogonal dose profiles at a specified depth were used to determine beam axis. TMR's of 4 circular cones, 10, 20, 30 and 40mm at 100cm SAD were measured, and OAR's of them were measured at 4 depths, d$\sub$max/, 6, 10, 15cm at 100cm SCD. Field size factor (FSF) defined by the ratio of D$\sub$max/ of a given cone at SAD to MU were also measured. Result : The dose-response linearity of the Si detector was almost perfect. Its sensitivity decreased with increasing dose rate but stable for high dose rate like as 100MU/min and higher even though dose out of field could be a little bit overestimated because of low dose rate. Method determining beam axis by two orthogonal profiles was simple and gave 0.05mm accuracy. Adjustment of depth of the detector in a water phantom by insertion and remove of some acryl pates under an auxiliary water tank was also simple and accurate. TMR, OAR and FSF measured by Si detector were sufficiently accurate for application to treatment planning of linac-based stereotactic radiosurgery. OAR in field was nearly independent of depth. Conclusion : The Si detector was appropriate for dosimetry of small circular fields for linac-based stereotactic radiosurgery. The beam axis could be determined by two orthogonal dose profiles. The adjustment of depth of the detector in water was possible by addition or removal of some acryl plates under the auxiliary water tank and simple. TMR, OAR and FSF were accurate enough to apply to stereotactic radiosurgery planning. OAR data at one depth are sufficient for radiosurgery planning.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.35 no.6
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• pp.553-562
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• 2017

GPS (Global Positioning System) receiver among various sensors mounted on UAV (Unmanned Aerial Vehicle) helps to perform various functions such as hovering flight and waypoint flight based on GPS signals. GPS receiver can be used in an environment where GPS signals are smoothly received. However, recently, the use of UAV has been diversifying into various fields such as facility monitoring, delivery service and leisure as UAV's application field has been expended. For this reason, GPS signals may be interrupted by UAV's flight in a shadow area where the GPS signal is limited. Multipath can also include various noises in the signal, while flying in dense areas such as high-rise buildings. In this study, we used analytical photogrammetry and auto tracking total station technique for 3D positioning of UAV. The analytical photogrammetry is based on the bundle adjustment using the collinearity equations, which is the geometric principle of the center projection. The auto tracking total station technique is based on the principle of tracking the 360 degree prism target in units of seconds or less. In both techniques, the target used for positioning the UAV is mounted on top of the UAV and there is a geometric separation in the x, y and z directions between the targets. Data were acquired at different speeds of 0.86m/s, 1.5m/s and 2.4m/s to verify the flight speed of the UAV. Accuracy was evaluated by geometric separation of the target. As a result, there was an error from 1mm to 12.9cm in the x and y directions of the UAV flight. In the z direction with relatively small movement, approximately 7cm error occurred regardless of the flight speed.

• Journal of The Korean Society of Grassland and Forage Science
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• v.26 no.1
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• pp.53-62
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• 2006

Near infrared reflectance spectroscopy (NIRS) has been increasingly used as a rapid, accurate method of evaluating some chemical compositions in forages. Analysis of forage quality by NIRS usually involves dry ground samples. Costs might be reduced if samples could be analyzed without drying or grinding. The objective of this study was to investigate effect of sample preparations and spectral math treatments on prediction ability of chemical composition for corn silage by NIRS. A population of 112 corn silage representing a wide range in chemical parameters were used in this investigation. Samples of com silage were scanned at 2nm intervals over the wavelength range 400-2500nm and the optical data recorded as log l/Reflectance(log l/R) and scanned in overt-dried grinding(ODG), liquid nitrogen grinding(LNG) or intact fresh(IF) condition. Samples were analysed for neutral detergent fiber(NDF), acid detergent fiber(ADF), acid detergent lignin(ADL), crude protein(CP) and crude ash content were expressed on a dry-matter(DM) basis. The spectral data were regressed against a range of chemical parameters using modified partial least squares(MPLS) multivariate analysis in conjunction with four spectral math treatments to reduce the effect of extraneous noise. The optimum calibrations were selected on the basis of minimizing the standard error of cross validation(SECV). The results of this study show that NIRS predicted the chemical parameters with very high degree of accuracy(the correlation coefficient of cross validation$(R^2cv)$ range from $0.70{\sim}0.95$) in ODG. The optimum equations were selected on the basis of minimizing the standard error of prediction(SEP). The Optimum sample preparation methods and spectral math treatment were for ADF, the ODG method using 2,10,5 math treatment(SEP = 0.99, $R^2v=0.93$), and for CP, the ODG method using 1,4,4 math treatment(SEP = 0.29. $R^2v=0.91$).

• Journal of radiological science and technology
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• v.31 no.1
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• pp.71-81
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• 2008

Our objective was to evaluate the image of spatial domain filtering as an alternative to additional image reconstruction using different kernels in MDCT. Derived from thin collimated source images were generated using water phantom and abdomen B10(very smooth), B20(smooth), B30(medium smooth), B40 (medium), B50(medium sharp), B60(sharp), B70(very sharp) and B80(ultra sharp) kernels. MTF and spatial resolution measured with various convolution kernels. Quantitative CT attenuation coefficient and noise measurements provided comparable HU(Hounsfield) units in this respect. CT attenuation coefficient(mean HU) values in the water were values in the water were $1.1{\sim}1.8\;HU$, air($-998{\sim}-1000\;HU$) and noise in the water($5.4{\sim}44.8\;HU$), air($3.6{\sim}31.4\;HU$). In the abdominal fat a CT attenuation coefficient($-2.2{\sim}0.8\;HU$) and noise($10.1{\sim}82.4\;HU$) was measured. In the abdominal was CT attenuation coefficient($53.3{\sim}54.3\;HU$) and noise($10.4{\sim}70.7\;HU$) in the muscle and in the liver parenchyma of CT attenuation coefficient($60.4{\sim}62.2\;HU$) and noise ($7.6{\sim}63.8\;HU$) in the liver parenchyma. Image reconstructed with a convolution kernel led to an increase in noise, whereas the results for CT attenuation coefficient were comparable. Image scanned with a high convolution kernel(B80) led to an increase in noise, whereas the results for CT attenuation coefficient were comparable. Image medications of image sharpness and noise eliminate the need for reconstruction using different kernels in the future. Adjusting CT various kernels, which should be adjusted to take into account the kernels of the CT undergoing the examination, may control CT images increase the diagnostic accuracy.

• Korean Journal of Remote Sensing
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• v.33 no.5_1
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• pp.469-480
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• 2017

This study aims to understand the relationship between lineaments and epicenters in Geochang region, Gyungsangnam-do, South Korea. An instrumental observation of earthquakes has been started by Korea Meteorological Administration (KMA) since 1978 and there were 6 earthquakes with magnitude ranging 2 to 2.5 in Geochang region from 1978 to 2016. Lineaments were extracted from LANDSAT 8 satellite image and shaded relief map displayed in 3-dimension using Digital Elevation Model (DEM). Then, lineament density was statistically examined by hotspot analysis. Hexagonal grids were generated to perform the analysis because hexagonal pattern expresses lineaments with less discontinuity than square girds, and the size of the grid was selected to minimize a variance of lineament density. Since hotspot analysis measures the extent of clustering with Z score, Z scores computed with lineaments' frequency ($L_f$), length ($L_d$), and intersection ($L_t$) were used to find lineament clusters in the density map. Furthermore, the Z scores were extracted from the epicenters and examined to see the relevance of each density elements to epicenters. As a result, 15 among 18 densities,recorded as 3 elements in 6 epicenters, were higher than 1.65 which is 95% of the standard normal distribution. This indicates that epicenters coincide with high density area. Especially, $L_f$ and $L_t$ had a significant relationship with epicenter, being located in upper 95% of the standard normal distribution, except for one epicenter in $L_t$. This study can be used to identify potential seismic zones by improving the accuracy of expressing lineaments' spatial distribution and analyzing relationship between lineament density and epicenter. However, additional studies in wider study area with more epicenters are recommended to promote the results.

• Korean Journal of Remote Sensing
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• v.34 no.5
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• pp.811-827
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• 2018

The purpose of this study is to compare machine learning algorithm and deep learning algorithm in crop classification using multi-temporal remote sensing data. For this, impacts of machine learning and deep learning algorithms on (a) hyper-parameter and (2) training sample size were compared and analyzed for Haenam-gun, Korea and Illinois State, USA. In the comparison experiment, support vector machine (SVM) was applied as machine learning algorithm and convolutional neural network (CNN) was applied as deep learning algorithm. In particular, 2D-CNN considering 2-dimensional spatial information and 3D-CNN with extended time dimension from 2D-CNN were applied as CNN. As a result of the experiment, it was found that the hyper-parameter values of CNN, considering various hyper-parameter, defined in the two study areas were similar compared with SVM. Based on this result, although it takes much time to optimize the model in CNN, it is considered that it is possible to apply transfer learning that can extend optimized CNN model to other regions. Then, in the experiment results with various training sample size, the impact of that on CNN was larger than SVM. In particular, this impact was exaggerated in Illinois State with heterogeneous spatial patterns. In addition, the lowest classification performance of 3D-CNN was presented in Illinois State, which is considered to be due to over-fitting as complexity of the model. That is, the classification performance was relatively degraded due to heterogeneous patterns and noise effect of input data, although the training accuracy of 3D-CNN model was high. This result simply that a proper classification algorithms should be selected considering spatial characteristics of study areas. Also, a large amount of training samples is necessary to guarantee higher classification performance in CNN, particularly in 3D-CNN.