• Journal of the Korean Society of Radiology
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• v.15 no.3
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• pp.345-353
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• 2021

Digital radiography imaging systems can also help diagnose lesions in patients, but if x-rays that enter the human body cause scatter x-ray due to interaction with substances, they affect the signal and noise characteristics of digital x-ray images. To regard the human body as polymethyl methacrylate (PMMA) and observe the properties of scattered x-ray generated from PMMA on x-ray images, we analyze signal and noise in the spatial domain as well as noise-power spectrum (NPS), and detective quantum efficiency (DQE) at zero frequency. As PMMA thickness increased, signals decreased, the noise increased, and NPS degradation was identified in overall spatial frequencies. Based on these characteristics, zero-frequency performance was also shown to be degraded. Comparative analysis with Monte-carlo simulations will need to be made to analyze the zero-frequency performance by scattered x-ray of indirect conversion-type x-ray detectors more quantitatively.

• Journal of the Korean Geotechnical Society
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• v.38 no.8
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• pp.17-27
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• 2022

To characterize the dynamic properties of Gimhae Plains sediments, we calculated natural frequencies using microtremor horizontal-to-vertical spectral ratios and derived shear wave velocity profiles by inversion of Rayleigh-wave dispersion curves obtained by the high frequency-wavenumber and modified spatial autocorrelation methods. Our results suggest that in this region, strong amplification of ground motion is expected in the vibration frequency (f ≥ 1 Hz). Additionally, obtained velocity profiles show that shear wave velocities are ~200 and 400 m/s for the shallow marine and old fluvial sediments, respectively. Bedrock is possibly encountered at depths of 60-100 m at most sites. We developed a simplified shear wave velocity model of shallow sediments based on the obtained profiles. Our results suggest that a large area in the Gimhae Plains could be categorized as an S6 site based on the Korean seismic design code (KDS 17 10 00).

• Journal of Korean Association for Spatial Structures
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• v.23 no.2
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• pp.19-28
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• 2023

Timber structures are susceptible to moisture, contamination, and pest infestation, which can compromise their integrity and pose a significant fire hazard. Despite these drawbacks, timber's lightweight properties, eco-friendliness, and alignment with current architectural trends emphasizing sustainability make it an attractive option for construction. Moreover, timber structures offer economic benefits and provide a natural aesthetic that regulates building temperature and humidity. In recent years, timber domes have gained popularity due to their high recyclability, lightness, and improved fire resistance. Researchers are exploring hybrid timber and steel domes to enhance stability and rigidity. However, shallow dome structures still face challenges related to structural instability. This study investigates stability problems associated with timber domes, the behavior of timber and steel hybrid domes, and the impact of timber member positioning on dome stability and critical load levels. The paper analyzes unstable buckling in single-layer lattice domes using an incremental analysis method. The critical buckling load of the domes is examined based on the arrangement of timber members in the inclined and horizontal directions. The analysis shows that nodal snapping is observed in the case of a concentrated load, whereas snap-back is also observed in the case of a uniform load. Furthermore, the use of inclined timber and horizontal steel members in the lattice dome design provides adequate stability.

• Journal of The Korean Society of Agricultural Engineers
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• v.66 no.4
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• pp.41-50
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• 2024

Precipitation is an important component of the hydrological cycle and a key input parameter for many applications in hydrology, climatology, meteorology, and weather forecasting research. Grid-based satellite rainfall products with wide spatial coverage and easy accessibility are well recognized as a supplement to ground-based observations for various hydrological applications. The error properties of satellite rainfall products vary as a function of rainfall intensity, climate region, altitude, and land surface conditions. Therefore, this study aims to evaluate the commonly used new global grid-based satellite rainfall product, Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS), using data collected at different spatial and temporal scales. Additionally, in this study, grid-based CHIRPS satellite precipitation data were used to evaluate the 2022 extreme drought. CHIRPS provides high-resolution precipitation data at 5 km and offers reliable global data through the correction of ground-based observations. A frequency analysis was performed to determine the precipitation deficit in 2022. As a result of comparing droughts in 2015, 2017, and 2022, it was found that May 2022 had a drought frequency of more than 500 years. The 1-month SPI in May 2022 indicated a severe drought with an average value of -1.8, while the 3-month SPI showed a moderate drought with an average value of 0.6. The extreme drought experienced in South Korea in 2022 was evident in the 1-month SPI. Both CHIRPS precipitation data and observations from weather stations depicted similar trends. Based on these results, it is concluded that CHIRPS can be used as fundamental data for drought evaluation and monitoring in unmeasured areas of precipitation.

• Journal of Korean Association for Spatial Structures
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• v.24 no.3
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• pp.43-51
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• 2024

Dynamic responses of nuclear power plant structure subjected to earthquake loads should be carefully investigated for safety. Because nuclear power plant structure are usually constructed by material of reinforced concrete, the aging deterioration of R.C. have no small effect on structural behavior of nuclear power plant structure. Therefore, aging deterioration of R.C. nuclear power plant structure should be considered for exact prediction of seismic responses of the structure. In this study, a machine learning model for seismic response prediction of nuclear power plant structure was developed by considering aging deterioration. The OPR-1000 was selected as an example structure for numerical simulation. The OPR-1000 was originally designated as the Korean Standard Nuclear Power Plant (KSNP), and was re-designated as the OPR-1000 in 2005 for foreign sales. 500 artificial ground motions were generated based on site characteristics of Korea. Elastic modulus, damping ratio, poisson's ratio and density were selected to consider material property variation due to aging deterioration. Six machine learning algorithms such as, Decision Tree (DT), Random Forest (RF), Support Vector Machine (SVM), K-Nearest Neighbor (KNN), Artificial Neural Networks (ANN), eXtreme Gradient Boosting (XGBoost), were used t o construct seispic response prediction model. 13 intensity measures and 4 material properties were used input parameters of the training database. Performance evaluation was performed using metrics like root mean square error, mean square error, mean absolute error, and coefficient of determination. The optimization of hyperparameters was achieved through k-fold cross-validation and grid search techniques. The analysis results show that neural networks present good prediction performance considering aging deterioration.

• Journal of the Korea Society of Computer and Information
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• v.29 no.10
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• pp.157-164
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• 2024

In this paper, we propose a technique that utilizes the physical properties of foam particles to synthesize foam sounds and efficiently control their size. A typical way to represent sound in physics-based simulation environments is to generate and synthesize virtual sounds. In particular, foam particles have a large number of particles, so synthesizing sounds using only particles is computationally expensive, and a way to reduce the amount of computation is to use spatial information, lattices. In this paper, we present a method for reliably mapping and clustering foam particles into a lattice space. Furthermore, we utilize this structure to control the loudness of the sound according to the location of the sound source and the audience. As a result, the method proposed in this paper proposes an efficient way to synthesize the sound of bubble particles, which utilizes the velocity and position of the bubble particles projected in the lattice space, and synthesizes the sound of bubble particles based on the position relationship of the audience and the directionality of the sound.

• Journal of Bio-Environment Control
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• v.29 no.2
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• pp.161-170
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• 2020

There is systematic spatial variations in environmental properties due to sensitive reaction to external conditions at plastic greenhouse occupied 99.2% of domestic agricultural facilities. In order to construct 3 dimensional distribution of temperature, relative humidity, CO₂ and illuminance, measurement matrix as 3 by 3 by 5 in direction of width, height and length, respectively, dividing indoor space of greenhouse was designed and tested at experimental site. Linear regression analysis was conducted to evaluate optimal estimation method in terms with horizontal and vertical variations. Even though sole measurement point for temperature and relative humidity could be feasible to assess indoor condition, multiple measurement matrix is inevitably required to improve spatial precision at certain time domain such as period of sunrise and sunset. In case with CO₂, multiple measurement matrix could not successfully improve the spatial predictability during a whole experimental period. In case with illuminance, prediction performance was getting smaller after a time period of sunrise due to systematic interference such as indoor structure. Thus, multiple sensing methodology was proposed in direction of length at higher height than growing bed, which could compensate estimation error in spatial domain. Appropriate measurement matrix could be constructed considering the transition of stability in indoor environmental properties due to external variations. As a result, optimal measurement matrix should be carefully designed considering flexibility of construction relevant with the type of property, indoor structure, the purpose of crop and the period of growth. For an instance, partial cooling and heating system to save a consumption of energy supplement could be successfully accomplished by the deployment of multiple measurement matrix.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.50 no.4
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• pp.247-255
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• 2005

ice yield and plant growth response to nitrogen (N) fertilizer may vary within a field, probably due to spatially variable soil conditions. An experiment designed for studying the response of rice yield to different rates of N in combination with variable soil conditions was carried out at a field where spatial variation in soil properties, plant growth, and yield across the field was documented from our previous studies for two years. The field with area of 6,600 m2 was divided into six strips running east-west so that variable soil conditions could be included in each strip. Each strip was subjected to different N application level (six levels from 0 to 165kg/ha), and schematically divided into 12 grids $(10m \times10m\;for\;each\;grid)$ for sampling and measurement of plant growth and rice grain yield. Most of plant growth parameters and rice yield showed high variations even at the same N fertilizer level due to the spatially variable soil condition. However, the maximum plant growth and yield response to N fertilizer rate that was analyzed using boundary line analysis followed the Mitcherlich equation (negative exponential function), approaching a maximum value with increasing N fertilizer rate. Assuming the obtainable maximum rice yield is constrained by a limiting soil property, the following model to predict rice grain yield was obtained: $Y=10765{1-0.4704^*EXP(-0.0117^*FN)}^*MIN(I-{clay},\;I_{om},\;I_{cec},\;I_{TN},\; I_{Si})$ where FN is N fertilizer rate (kg/ha), I is index for subscripted soil properties, and MIN is an operator for selecting the minimum value. The observed and predicted yield was well fitted to 1:1 line (Y=X) with determination coefficient of 0.564. As this result was obtained in a very limited condition and did not explain the yield variability so high, this result may not be applied to practical N management. However, this approach has potential for quantifying the grain yield response to N fertilizer rate under variable soil conditions and formulating the site-specific N prescription for the management of spatial yield variability in a field if sufficient data set is acquired for boundary line analysis.

• The Transactions of the Korea Information Processing Society
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• v.4 no.6
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• pp.1418-1432
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• 1997

Most general content_based image retrieval techniques use color and texture as retrieval indices. In color techniques, color histogram and color pair based color retrieval techniques suffer from a lack of spatial information and text. And This paper describes the design and implementation of content_based image retrieval system using color space and keywords. The preprocessor for image retrieval has used the coordinate system of the existing HSI(Hue, Saturation, Intensity) and preformed to split One image into chromatic region and achromatic region respectively, It is necessary to normalize the size of image for 200*N or N*200 and to convert true colors into 256 color. Two color histograms for background and object are used in order to decide on color selection in the color space. Spatial information is obtained using a maximum entropy discretization. It is possible to choose the class, color, shape, location and size of image by using keyword. An input color is limited by 15 kinds keyword of chromatic and achromatic colors of the Korea Industrial Standards. Image retrieval method is used as the key of retrieval properties in the similarity. The weight values of color space ${\alpha}(%)and\;keyword\;{\beta}(%)$ can be chosen by the user in inputting the query words, controlling the values according to the properties of image_contents. The result of retrieval in the test using extracted feature such as color space and keyword to the query image are lower that those of weight value. In the case of weight value, the average of te measuring parameters shows approximate Precision(0.858), Recall(0.936), RT(1), MT(0). The above results have proved higher retrieval effects than the content_based image retrieval by using color space of keywords.

• 한국지구물리탐사학회:학술대회논문집
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• 2009.10a
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• pp.147-154
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• 2009

Physical properties of rocks, such as velocity, are strongly dependant on detailed pore structures, and recently, pore micro-structures by X-ray tomography techniques have been used to simulate and understand the physical properties. However, the smoothing effect during the tomographic reconstruction procedure often causes an artifact - overestimating the contact areas between grains. The pore nodes near a grain contact are affected by neighboring grain nodes, and are classified into grain nodes. By this artifact, the pore structure has higher contact areas between grains and thus higher velocity estimation than the true one. To reduce this artifact, we tried two image processing techniques - sharpening filter and neural network classification. Both methods gave noticeable improvement on contact areas between grains visually; however, the estimated velocities showed only incremental improvement. We then tried to change the resolutions of tomogram and quantify its impact on velocity estimation. The estimated velocity from the tomogram with higher spatial resolution was improved significantly, and with around 2 micron spatial resolution, the calculated velocity was very close to the lab measurement. In conclusion, the resolution of pore micro-structure is the most important parameter for accurate estimation of velocity using pore-scale simulation techniques. Also the estimation can be incrementally improved if combined with image processing techniques during the pore-grain classification.