• Journal of the Korean earth science society
• /
• v.41 no.1
• /
• pp.31-39
• /
• 2020

Cheonji, the largest caldera lake in Asia, is located at the summit of Baekdu Mountain. Cheonji is covered with snow and ice for about six months of the year due to its high altitude and its surrounding environment. Since most of the sources of water are from groundwater, the water temperature is closely related to the volcanic activity. However, in the 2000s, many volcanic activities have been monitored on the mountain. In this study, we analyzed the dimension of ice produced during winter in Baekdu Mountain using Sentinel-1 satellite image data provided by the European Space Agency (ESA). In order to calculate the dimension of ice from the backscatter image of the Sentinel-1 satellite, 20 Gray-Level Co-occurrence Matrix (GLCM) layers were generated from two polarization images using texture analysis. The method used in calculating the area was utilized with the Support Vector Machine (SVM) algorithm to classify the GLCM layer which is to calculate the dimension of ice in the image. Also, the calculated area was correlated with temperature data obtained from Samjiyeon weather station. This study could be used as a basis for suggesting an alternative to the new method of calculating the area of ice before using a long-term time series analysis on a full scale.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.49 no.4
• /
• pp.49-57
• /
• 2012

This paper presents a fast multiple-image-based deblurring method that decreases the computation loads in the image deblurring, enhancing the sharpness of the textures or edges of the restored images. First, two blurred images with some blurring artifacts and one noisy image including severe noises are consecutively captured under a relatively long and short exposures, respectively. To improve the processing speeds, the captured multiple images are downsampled at the ratio of two, and then a way of estimating the point spread function(PSF) based on the image or edge patches extracted from the whole images, is introduced. The method enables to effectively reduce the computation time taken in the PSF prediction. Next, the texture-enhanced image deblurring method of supplementing the ability of the texture representation degraded by the downsampling of the input images, is developed and then applied. Finally, to get the same image size as the original input images, an upsampling method of utilizing the sharp edges of the captured noisy image is applied. By using the proposed method, the processing times taken in the image deblurring, which is the main obstacle of its application to the digital cameras, can be shortened, while recovering the fine details of the textures or edge components.

• Advanced Composite Materials
• /
• v.17 no.1
• /
• pp.25-40
• /
• 2008

The research and development in soundproof materials for preventing noise have attracted great attention due to their social impact. Noise insulation materials are especially important in the field of soundproofing. Since the insulation ability of most materials follows a mass rule, the heavy weight materials like concrete, lead and steel board are mainly used in the current noise insulation materials. To overcome some weak points in these materials, fiber reinforced composite materials with lightweight and other high performance characteristics are now being used. In this paper, innovative insulation sheet materials with carbon and/or glass fabrics and nano-silica hybrid PU resin are developed. The parameters related to sound performance, such as materials and fabric texture in base fabric, hybrid method of resin, size of silica particle and so on, are investigated. At the same time, the wave analysis code (PZFlex) is used to simulate some of experimental results. As a result, it is found that both bundle density and fabric texture in the base fabrics play an important role on the soundproof performance. Compared with the effect of base fabrics, the transmission loss in sheet materials increased more than 10 dB even though the thickness of the sample was only about 0.7 mm. The results show different values of transmission loss factor when the diameters of silica particles in coating materials changed. It is understood that the effect of the soundproof performance is different due to the change of hybrid method and the size of silica particles. Fillers occupying appropriate positions and with optimum size may achieve a better effect in soundproof performance. The effect of the particle content on the soundproof performance is confirmed, but there is a limit for the addition of the fillers. The optimization of silica content for the improvement of the sound insulation effect is important. It is observed that nano-particles will have better effect on the high soundproof performance. The sound insulation effect has been understood through a comparison between the experimental and analytical results. It is confirmed that the time-domain finite wave analysis (PZFlex) is effective for the prediction and design of soundproof performance materials. Both experimental and analytical results indicate that the developed materials have advantages in lightweight, flexibility, other mechanical properties and excellent soundproof performance.

• Journal of Korean Society for Geospatial Information Science
• /
• v.25 no.1
• /
• pp.19-27
• /
• 2017

This research was aimed to analyze landslide susceptibility and compare the prediction accuracy using ensemble frequency ratio (FR) and logistic regression at the Inje area, Korea. The landslide locations were identified with the before and after aerial photographs of landslide occurrence that were randomly selected for training (70%) and validation (30%). The total twelve landslide-related factors were elevation, slope, aspect, distance to drainage, topographic wetness index, stream power index, soil texture, soil sickness, timber age, timber diameter, timber density, and timber type. The spatial relationship between landslide occurrence and landslide-related factors was analyzed using FR and ensemble model. The produced LSI maps were validated and compared using relative operating characteristics (ROC) curve. The prediction accuracy of produced ensemble LSI map was about 2% higher than FR LSI map. The LSI map produced in this research could be used to establish land use planning and mitigate the damages caused by disaster.

• Asian Pacific Journal of Cancer Prevention
• /
• v.14 no.10
• /
• pp.6019-6023
• /
• 2013

Lung cancer, one of the leading causes of cancer-related deaths, usually appears as solitary pulmonary nodules (SPNs) which are hard to diagnose using the naked eye. In this paper, curvelet-based textural features and clinical parameters are used with three prediction models [a multilevel model, a least absolute shrinkage and selection operator (LASSO) regression method, and a support vector machine (SVM)] to improve the diagnosis of benign and malignant SPNs. Dimensionality reduction of the original curvelet-based textural features was achieved using principal component analysis. In addition, non-conditional logistical regression was used to find clinical predictors among demographic parameters and morphological features. The results showed that, combined with 11 clinical predictors, the accuracy rates using 12 principal components were higher than those using the original curvelet-based textural features. To evaluate the models, 10-fold cross validation and back substitution were applied. The results obtained, respectively, were 0.8549 and 0.9221 for the LASSO method, 0.9443 and 0.9831 for SVM, and 0.8722 and 0.9722 for the multilevel model. All in all, it was found that using curvelet-based textural features after dimensionality reduction and using clinical predictors, the highest accuracy rate was achieved with SVM. The method may be used as an auxiliary tool to differentiate between benign and malignant SPNs in CT images.

• Journal of the Korean Society of Food Science and Nutrition
• /
• v.22 no.2
• /
• pp.222-225
• /
• 1993

To obtain a thermal diffusivity predicting equation for meat products, minced pork meat was mixed with some additives such as lard, isolated soybean protein, 1.5% of table salt and 2% of polyphosphate to control the composition and texture of the products and then stuffed in a model can. Heat penetration curves were measured in the temperature range of 80.76~121.03$^{\circ}C$ by using a thermocouple fixed at the cold point of the model can and the thermal diffusivities were calculated from the plotted heat penetration curves. At constant heating temperature, the thermal diffusivities of pork meat with water content of 49.01~77.55% increased linearly with increasing water content. The thermal diffusivities of the products with constant water content also increased linearly with increasing heating temperature and the values could be predicted by following equation: $\alpha$p=(2.1394+0.5X$_{w}$).$\alpha$$_{w}$+0.0035.10$^{-6}$ .X$_{w}$-0.2785.10$^{-6}$ ,(m$^2$.s$^{-1}$ ). The maximal difference of the values predicted with this equation on the basis of the practical measured values were less than 1.7%. 1.7%.

• Korean Journal of Soil Science and Fertilizer
• /
• v.44 no.5
• /
• pp.944-958
• /
• 2011

Soil hydraulic properties such as hydraulic conductivity or water retention which are costly to measure can be indirectly generated by soil pedotransfer function (PTF) using easily obtainable soil data. The field soil structure description which is routinely recorded could also be used in PTF as an input to reduce the uncertainty. The purposes of this study were to use qualitative morphological soil structure descriptions and soil structural index into PTF and to evaluate their contribution in the prediction of soil hydraulic properties. We transformed categorical morphological descriptions of soil structure into quantitative values using categorical principal component analysis (CATPCA). This approach was tested with a large data set from the US National Pedon Characterization database with the aid of a categorical regression tree analysis. Six different PTFs were used to predict the saturated hydraulic conductivity and those results were averaged to quantify the uncertainty. Quantified morphological description was successively used in multiple linear regression approach to predict the averaged ensemble saturated conductivity. The selected stepwise regression model with only the transformed morphological variables and structural index as predictors predicted the $K_{sat}$ with $r^2$ = 0.48 (p = 0.018), indicating the feasibility of CATPCA approach. In a regression tree analysis, soil structure index and soil texture turned out to be important factors in the prediction of the hydraulic properties. Among structural descriptions size class turned out to be an important grouping parameter in the regression tree. Bulk density, clay content, W33 and structural index explained clusters selected by a two step clustering technique, implying the morphologically described soil structural features are closely related to soil physical as well as hydraulic properties. Although this study provided relatively new method which related soil structure description to soil structure index, the same approach should be tested using a datasets containing the actual measurement of hydraulic properties. More insight on the predictive power of soil structure index to estimate hydraulic properties would be achieved by considering measured the saturated hydraulic conductivity and the soil water retention.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.52 no.5
• /
• pp.85-91
• /
• 2015

This paper presents a novel frame rate up-conversion (FRUC) algorithm. Existing algorithms, in general, employ rectangular blocks for motion estimation and arbitrary shape of an actual object region cannot be precisely represented. On the other hand, the proposed wedge-shaped block partitioning algorithm partitions a rectangular block into two wedge-shaped blocks using the texture information, which makes better approximation for an actual object region. The wedge-shaped block partitioning algorithm as well as the adaptive motion vector prediction algorithm is used to reliably estimate the actual motion. Experimental results show that the proposed FRUC algorithm is superior to existing algorithms up to 1.988dB in PSNR and 0.0167 in SSIM comparisons.

• Journal of Advanced Navigation Technology
• /
• v.18 no.2
• /
• pp.151-157
• /
• 2014

Recently UAV(unmanned aerial vehicle) is frequently used not only for military purpose but also for civil purpose. UAV automatically navigates following the coordinates input in advance using GPS information. However it is impossible when GPS cannot be received because of jamming or external interference. In order to solve this problem, we propose a real-time segmentation and classification algorithm for the specific regions from UAV image in this paper. We use the super-pixels algorithm using graph-based image segmentation as a pre-processing stage for the feature extraction. We choose the most ideal model by analyzing various color models and mixture color models. Also, we use support vector machine for classification, which is one of the machine learning algorithms and can use small quantity of training data. 18 color and texture feature vectors are extracted from the UAV image, then 3 classes of regions; river, vinyl house, rice filed are classified in real-time through training and prediction processes.

• Journal of Broadcast Engineering
• /
• v.17 no.6
• /
• pp.1029-1039
• /
• 2012

In this papar, we propose a new motion estimation and coding technique using adaptive motion vector resolution. Currently, HEVC encodes a video using 1/4 motion vector resolution. If there are high texture regions in a picture, HEVC can't get a performance enough. So, we insert additional 1-bit flag meaning whether motion vector resolution is 1/4 or 1/8 in PU syntax. Therefore, decoder can recognize the transmitted motion vector resolution. Experimental results show that maximum coding efficiency gain of the proposed method is up to 5.3% in luminance and 7.9% in chrominance. Average computional time complexity is increased about 33% in encoder and up to 5% in decoder.