• The Journal of Korean Academy of Prosthodontics
• /
• v.52 no.2
• /
• pp.97-104
• /
• 2014

This study was aimed to compare the radiopacity of four kinds of currently available resin based implant cements using digital radiography. Materials and Methods: Four resin-based implant cements((Estemp $Implant^{TM}$ (Spident, Incheon, Korea), $Premier^{(R)}$Implant (Premier, Pennsylvania, USA), $Cem-Implant^{TM}$ (B.J.M lab, Or-yehuda, Israel), $InterCem^{TM}$ (SCI-PHARM, California, USA)) and control group (Elite Cement $100^{TM}$ (GC, Tokyo, Japan) ) were mixed and cured according to the manufacturer's instructions on the custom made split-type metal mold. A total of 150 specimens of each cement were prepared and each specimen (purity over 99%) was placed side-by-side with an aluminum step wedge for image taking with Intraoral X-ray unit (Esx, Vatech, Korea) and digital X-ray sensor (EzSensor, Vatech, Korea). For the evaluation of aluminum wedge equivalent thickness (mm Al), ImageJ 1.47 m (Wayne Rasband, National Institutes of Health, USA) and Color inspector 3D ver 2.0 (Interaktive Visualisierung von Farbraumen, Berlin, Germany) programs were used. Result: Among the 5 cements, Elite cement $100^{TM}$ (control group) showed the highest radio-opacity in all thickness. In the experimental group, $InterCem^{TM}$ had the highest radio-opacity followed by $Premier^{(R)}$ Implant $Cement^{TM}$, $Cem-Implant^{TM}$ and Estemp $Implant^{TM}$. In addition, $InterCem^{TM}$ showed radio-opacity that met the ISO No. 4049 standard in all the tested specimen thickness. Cem-Implant on 0.5 mm thickness showed radiopacity that met the ISO No. 4049 standard. Conclusion: Among the implant resin-based cements tested in the study, $Premier^{(R)}$ Implant Cement and Estemp $Implant^{TM}$ did not show appropriate radio-opacity. Only $InterCem^{TM}$ and $Cem-Implant^{TM}$ 0.5 mm specimen had the proper radiopacity and met the experiment standard.

• Journal of the korean academy of Pediatric Dentistry
• /
• v.32 no.2
• /
• pp.270-277
• /
• 2005

The purpose of this study was to clarify the palatal volume and anterior palatal slope of the children with class II div.1 malocclusion and normal occlusion in mixed dentition(Hellman dental age III A) using three-dimensional laser scanner. Samples were consisted of 31 children with skeletal class II div.1 malocclusion in mixed dentition and 29 children with normal occlusion and profile among the contestants in 2000-2004 Healthy Dentition Contest in Seoul. Totally 60 maxillary study model were taken. Each cast was scanned by three-dimensional laser scanner (Breuckmann opto-TOP HE, INUS, Korea) and shaped into the three-dimension image by Rapidform 2004 program(INUS, Korea). And the palatal volume and anterior palatal slope of each cast were calculated by Rapidform 2004 program(INUS, Korea). The values were statistically compared and evaluated by independent samples t-test with 95% of significance level. The results were as follows: 1. Palatal volume was significantly lesser in children with class II div.1 malocclusion than that of normal occlusion in mixed dentition(p<0.05). 2. No significant difference in the anterior palatal slope and palatal height was found between the children with class II div.1 malocclusion and normal occlusion in mixed dentition(p>0.05). 3. Palatal length was significantly greater in children with class II div.1 malocclusion than that of normal occlusion in mixed dentition(p<0.01). 4. Intercanine and intermolar width were significantly lesser in children with class II div.1 malocclusion than those of normal occlusion in mixed dentition(respectively p<0.05 and p<0.01).

• Food Science and Preservation
• /
• v.20 no.4
• /
• pp.554-563
• /
• 2013

The changes in quality properties and nutritional components for two mugworts, namely, Artemisia capillaris Thumberg Artemisiae asiaticae Nakai fermented by Bacillus strains were characterized followed by rapid pattern analysis of volatile flavor compounds through the SAW-based electronic nose sensor in the GC system. After fermentation, the pH has remarkably decreased from 6.0~6.4 to 4.6~5.1 and there has been a slight change in the total soluble solids. The L (lightness) and b (yellowness) values in the Hunter's color system significantly decreased, whilst the a (redness) value increased via fermentation. The HPLC analysis demonstrated that the total amino acids increased in quantity and the essential amino acids were higher in the A. asiaticae Nakai than in the A. capillaris Thumberg, specially with high contents of glutamic and aspartic acid. After fermentation, the monounsaturated fatty acid increased in the A. asiaticae Nakai and the polyunsaturated fatty acids increased in the A. capillaris Thumberg. While the total polyphenol contents have not been affected by fermentation, the total sugar contents have dramatically decreased. Scopoletin, which is one of the most important index components in mugworts, was highly abundant in the A. capillaris Thumberg; however, it was not detected in the A. asiaticae Nakai. Small pieces of plant tissue in the surface microstructure were found in the fermented mugworts through the use of the scanning electron microscope (SEM). Volatile flavor compounds via electronic nose showed that the intensity of several peaks has increased and additional seven flavor peaks have been produced after fermentation. The VaporPrintTM images demonstrated a notable difference in flavors between the A. asiaticae Nakai and A. capillaris Thumberg, and the fermentation enabled the mugworts to produce subtle differences in flavor.

• Journal of the Korean Institute of Traditional Landscape Architecture
• /
• v.31 no.4
• /
• pp.1-21
• /
• 2013

This study has researched the characteristics and elements of the chuibyong, a sort of trellis in the Joseon Dynasty through the old pictorial data. The results were as follows; First, as a result of the analysis for the 25 pictorial data in the Joseon Dynasty, the chuibyongs have usually functioned as screening the facility to protect the private life and dividing the spaces of the site, but it was internally regarded as the props which symbolized the dignity and elegance of high class. Especially, not only the faunas such as crane and deer, and the floras such as Pinus densiflora, Musa basjoo, bamboo species and Paulownia coreana, but also various garden elements including oddly shaped stone, pond and pavilion were shown in the surrounding area of the chuibyong, and they were considered as a series of combination that was needed in the ideal garden for the literati. Secondly, the chuibyong was recognized as the ideological object which was typical of the literati culture in the story derived from an ancient event of China. Such image has been reflected intactly in the garden culture, and the chuibyong has been used(considered) as the important scenery of the season to imitate and reenact the Chinese Classical Garden in the narrative painting. Thirdly, in terms of the shape and function, the chuibyong in the paintings in the Joseon Dynasty basically had the function of the shielding and spatial division. Fourthly, the height of the chuibyung was similar to the one of fence which exceeds the person's height or Youngbyek(影壁) which is installed in the front and the rear of the main gate in China, and the various shape's chuibyung was properly set up in many spaces. Lastly, the making of the chuibyong in Joseon Dynasty was related to the trend of the writer's culture which was popular nationally in Ming dynasty rather than the particular functions or the location conditions. Especially, the symbol expression of the chuibyong showed on 'Elegant Gathering in the Western Garden' which was brought from China was recreated in the mansion of the upper class in Hanyang city as the center, and the primary mode for the expression of the wealth and writer's spirit through the chuibyong was transformed into the high-quality's garden element which could be created in the royal palace or the mansion of the upper class. Also, the use of the chuibyung was changed by spreading into the residential style for common people after the mid-nineteenth century, and it means that the chuibyung was developed into Korean styles.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.24 no.3
• /
• pp.83-98
• /
• 2021

Urban green space is an important component for enhancing urban ecosystem health. Thus, identifying the spatial structure of urban green space is required to manage a healthy urban ecosystem. The Ministry of Environment has provided the level 3 land cover map(the highest (1m) spatial resolution map) with a total of 41 classes since 2010. However, specific urban green information such as street trees was identified just as grassland or even not classified them as a vegetated area in the map. Therefore, this study classified detailed urban green information(i.e., tree, shrub, and grass), not included in the existing level 3 land cover map, using two types of high-resolution(<1m) remote sensing data(i.e., airborne LiDAR and RGB ortho imagery) in Suwon, South Korea. U-Net, one of image segmentation deep learning approaches, was adopted to classify detailed urban green space. A total of three classification models(i.e., LRGB10, LRGB5, and RGB5) were proposed depending on the target number of classes and the types of input data. The average overall accuracies for test sites were 83.40% (LRGB10), 89.44%(LRGB5), and 74.76%(RGB5). Among three models, LRGB5, which uses both airborne LiDAR and RGB ortho imagery with 5 target classes(i.e., tree, shrub, grass, building, and the others), resulted in the best performance. The area ratio of total urban green space(based on trees, shrub, and grass information) for the entire Suwon was 45.61%(LRGB10), 43.47%(LRGB5), and 44.22%(RGB5). All models were able to provide additional 13.40% of urban tree information on average when compared to the existing level 3 land cover map. Moreover, these urban green classification results are expected to be utilized in various urban green studies or decision making processes, as it provides detailed information on urban green space.

• Korean Journal of Remote Sensing
• /
• v.37 no.5_3
• /
• pp.1475-1490
• /
• 2021

Detecting oil spill area using statistical characteristics of SAR images has limitations in that classification algorithm is complicated and is greatly affected by outliers. To overcome these limitations, studies using neural networks to classify oil spills are recently investigated. However, the studies to evaluate whether the performance of model shows a consistent detection performance for various oil spill cases were insufficient. Therefore, in this study, two CNNs (Convolutional Neural Networks) with basic structures(Simple CNN and U-net) were used to discover whether there is a difference in detection performance according to the structure of CNN and distribution characteristics of oil spill. As a result, through the method proposed in this study, the Simple CNN with contracting path only detected oil spill with an F1 score of 86.24% and U-net, which has both contracting and expansive path showed an F1 score of 91.44%. Both models successfully detected oil spills, but detection performance of the U-net was higher than Simple CNN. Additionally, in order to compare the accuracy of models according to various oil spill cases, the cases were classified into four different categories according to the spatial distribution characteristics of the oil spill (presence of land near the oil spill area) and the clarity of border between oil and seawater. The Simple CNN had F1 score values of 85.71%, 87.43%, 86.50%, and 85.86% for each category, showing the maximum difference of 1.71%. In the case of U-net, the values for each category were 89.77%, 92.27%, 92.59%, and 92.66%, with the maximum difference of 2.90%. Such results indicate that neither model showed significant differences in detection performance by the characteristics of oil spill distribution. However, the difference in detection tendency was caused by the difference in the model structure and the oil spill distribution characteristics. In all four oil spill categories, the Simple CNN showed a tendency to overestimate the oil spill area and the U-net showed a tendency to underestimate it. These tendencies were emphasized when the border between oil and seawater was unclear.

• Korean Journal of Remote Sensing
• /
• v.39 no.6_1
• /
• pp.1413-1425
• /
• 2023

The increasing frequency of wildfires due to climate change is causing extreme loss of life and property. They cause loss of vegetation and affect ecosystem changes depending on their intensity and occurrence. Ecosystem changes, in turn, affect wildfire occurrence, causing secondary damage. Thus, accurate estimation of the areas affected by wildfires is fundamental. Satellite remote sensing is used for forest fire detection because it can rapidly acquire topographic and meteorological information about the affected area after forest fires. In addition, deep learning algorithms such as convolutional neural networks (CNN) and transformer models show high performance for more accurate monitoring of fire-burnt regions. To date, the application of deep learning models has been limited, and there is a scarcity of reports providing quantitative performance evaluations for practical field utilization. Hence, this study emphasizes a comparative analysis, exploring performance enhancements achieved through both model selection and data design. This study examined deep learning models for detecting wildfire-damaged areas using Landsat 8 satellite images in California. Also, we conducted a comprehensive comparison and analysis of the detection performance of multiple models, such as U-Net and High-Resolution Network-Object Contextual Representation (HRNet-OCR). Wildfire-related spectral indices such as normalized difference vegetation index (NDVI) and normalized burn ratio (NBR) were used as input channels for the deep learning models to reflect the degree of vegetation cover and surface moisture content. As a result, the mean intersection over union (mIoU) was 0.831 for U-Net and 0.848 for HRNet-OCR, showing high segmentation performance. The inclusion of spectral indices alongside the base wavelength bands resulted in increased metric values for all combinations, affirming that the augmentation of input data with spectral indices contributes to the refinement of pixels. This study can be applied to other satellite images to build a recovery strategy for fire-burnt areas.