• Maxillofacial Plastic and Reconstructive Surgery
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• v.37
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• pp.2.1-2.9
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• 2015

Background: The aim of this study was to evaluate the effect of autogenous tooth bone as a graft material for regeneration of bone in vertical bony defects of the minipigs. Material and Methods: Six minipigs were used in this study. Four molars were extracted in the right mandibular dentition and sent to the Korea Tooth Bank for fabrication of autogenous tooth bone. Ten days later, each extraction site was implanted with MS Implant Narrow Ridge $3.0{\times}10mm$ fixture (Osstem, Seoul, Korea) after standardized 2mm-sized artificial vertical bony defect formation. Pineappleshaped Root-On type autogenous tooth bones were applied to the vertical defects around the neck area of the posterior three fixtures and the fore-most one was not applied with autogenous bone as a control group. Each minipig was sacrificed at 4, 8, 12 weeks after fixture installation and examined radiologically and histologically. Histological evaluation was done under light microscope with Villanueva osteochrome bone staining with semi-quantitative histomorphometric study. Percentage of new bone over total area (NBF) and bone to implant contact (BIC) ratio were evaluated using digital software for area calculation. Result: NBF were $48.15{\pm}18.02%$, $45.50{\pm}28.37%$, and $77.13{\pm}15.30%$ in 4, 8, and 12 weeks, respectively for experimental groups. The control group showed $37.00{\pm}11.53%$, $32.25{\pm}26.99%$, and $1.33{\pm}2.31%$ in 4,8,12 weeks, respectively. BIC ratio were $53.08{\pm}19.82%$, $45.00{\pm}28.37%$, and $75.13{\pm}16.55%$ in 4,8,12 weeks, respectively. Those for the control groups were $38.33{\pm}6.43%$, $33.50{\pm}29.51%$, and $1.33{\pm}2.31%$ in 4, 8, 12 weeks, respectively. Conclusion: Autogenous tooth bone showed higher score than control group in NBF and BIC in all the data encompassing 4,8,12 weeks specimens, but statistically significant only 12 weeks data in both NBF and BIC.

• Journal of Digital Contents Society
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• v.16 no.3
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• pp.389-395
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• 2015

Digital image provides many conveniences at the internet environment recently. A great number of applications, like Digital Library, Stock Image, Personal Image and Important Information, require the use of digital image. However it has fatal defect which is easy to be modified because digital image is only electronic file. Numerous digital image forgeries have become a serious problem due to the sophistication and accessibility of image editing software. Copy-Move forgery is the simplest type of forgery that involves copying portion of an image and paste it on different location within the image. There are many approaches to detect Copy-Move forgery, but all of them have their own limitations. In this paper, visual and invisible feature based forgery detection techniques are tested and analyzed. The analysis shows that pros and cons of these two techniques compensate each other. Therefore, a hybrid of visual based and invisible feature based forgery detection that combine the merits of both techniques is proposed. The experimental results show that the proposed algorithm has enhanced performance compared to individual techniques. Moreover, it provides more information about the forgery, like identifying copy and duplicate regions.

• The KIPS Transactions:PartA
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• v.16A no.2
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• pp.125-134
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• 2009

This paper proposes a change management system of sensor network applications based on version synchronization that supports to effectively manage defect correction of applications, change of functions for applications or improvement of applications without suspending the sensor network. The proposed change management system consists of the NADE which is an application development environment, the Node Management Server, and the Node Agent. NADE is an Eclipse-based development environment for developing applications which are installed into nodes. NADE is also connected with CVSNT which is a version management tool and performs application version management using the CVSNT. Node Management Server manages nodes to maintain latest versions of applications by synchronizing versions of applications which are performed on the nodes with the versions of applications which are developed in the NADE. Node Agent which is loaded into the node periodically sends the version information of the application to the server, and stores and updates the version information of the application. Through the proposed change management system, applications of nodes are automatically updated when versions of applications are changed by correcting defects, changing functions or improving applications. Therefore, the user can effectively manage the execution of sensor network system without suspending or delaying the sensor network. Also, visibility of change management for sensor network applications will be improved.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.3
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• pp.16-22
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• 2019

Off-line programming and robot calibration through simulation are essential when setting up a robot in a robot automation production line. In this study, we developed a new robot calibration method to match the CAD data of the production line with the measurement data on the site using 3D scanner. The proposed method calibrates the robot using 3D point cloud data through Iterative Closest Point algorithm. Registration is performed in three steps. First, vertices connected by three planes are extracted from CAD data as feature points for registration. Three planes are reconstructed from the scan point data located around the extracted feature points to generate corresponding feature points. Finally, the transformation matrix is calculated by minimizing the distance between the feature points extracted through the ICP algorithm. As a result of applying the software to the automobile welding robot installation, the proposed method can calibrate the required accuracy to within 1.5mm and effectively shorten the set-up time, which took 5 hours per robot unit, to within 40 minutes. By using the developed system, it is possible to shorten the OLP working time of the car body assembly line, shorten the precision teaching time of the robot, improve the quality of the produced product and minimize the defect rate.

• Journal of the Society of Cosmetic Scientists of Korea
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• v.45 no.1
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• pp.95-103
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• 2019

Lips have a defect in maintenance of moisture due to their thin layer. As aging progresses, lips lose volume and redness, and become wrinkled. Fat grafting and filler surgery have been used to achieve attractive lips, but little research has been reported to develop better materials to replace the present methods. Recently, a study suggests that the increase of adipocyte number can be enhancing the expansion endogenous fat. In previous study, we identified that the efficacy of Magnolia officinalis bark extract (MOBE) was effective on the induction of adipogenic differentiation. In this study, we confirmed that MOBE enhanced the differentiation of human adipose-derived stem cells on the fat mimic 3D structure built by 3D bioprinting method From further experiments in human, we established a method to quantify the severity of lip wrinkle by measurement of standard deviation of gray value using Image J software. Finally, we found that topical treatment with 1% MOBE formulated lip balm significantly improved the lip wrinkle after using for 12 weeks. In conclusion, these findings suggest that MOBE has great potential, as a cosmetic ingredient, to reduce the lip wrinkle through the effect of promoting adipogenic differentiation.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.7
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• pp.299-306
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• 2022

In recent, sensors embedded in robots, equipment, and circuits have become common, and research for diagnosing device failures by learning measured sensor data is being actively conducted. This failure diagnosis study is divided into a classification model for predicting failure situations or types and a regression model for numerically predicting failure conditions. In the case of a classification model, it simply checks the presence or absence of a failure or defect (Class), whereas a regression model has a higher learning difficulty because it has to predict one value among countless numbers. So, the reason that regression modeling is more difficult is that there are many irregular situations in which it is difficult to determine one output from a similar input when predicting by matching input and output. Therefore, in this paper, we focus on input and output data with periodicity, analyze the input/output relationship, and secure regularity between input and output data by performing sliding window-based input data patterning. In order to apply the proposed method, in this study, current and temperature data with periodicity were collected from MMC(Modular Multilevel Converter) circuit system and learning was carried out using ANN. As a result of the experiment, it was confirmed that when a window of 2% or more of one cycle was applied, performance of 97% or more of fit could be secured.

• Progress in Medical Physics
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• v.22 no.1
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• pp.42-51
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• 2011

Nuclear medicine images (SPECT, PET) were widely used tool for assessment of myocardial viability and perfusion. However it had difficult to define accurate myocardial infarct region. The purpose of this study was to investigate methodological approach for automatic measurement of rat myocardial infarct size using polar map with adaptive threshold. Rat myocardial infarction model was induced by ligation of the left circumflex artery. PET images were obtained after intravenous injection of 37 MBq $^{18}F$-FDG. After 60 min uptake, each animal was scanned for 20 min with ECG gating. PET data were reconstructed using ordered subset expectation maximization (OSEM) 2D. To automatically make the myocardial contour and generate polar map, we used QGS software (Cedars-Sinai Medical Center). The reference infarct size was defined by infarction area percentage of the total left myocardium using TTC staining. We used three threshold methods (predefined threshold, Otsu and Multi Gaussian mixture model; MGMM). Predefined threshold method was commonly used in other studies. We applied threshold value form 10% to 90% in step of 10%. Otsu algorithm calculated threshold with the maximum between class variance. MGMM method estimated the distribution of image intensity using multiple Gaussian mixture models (MGMM2, ${\cdots}$ MGMM5) and calculated adaptive threshold. The infarct size in polar map was calculated as the percentage of lower threshold area in polar map from the total polar map area. The measured infarct size using different threshold methods was evaluated by comparison with reference infarct size. The mean difference between with polar map defect size by predefined thresholds (20%, 30%, and 40%) and reference infarct size were $7.04{\pm}3.44%$, $3.87{\pm}2.09%$ and $2.15{\pm}2.07%$, respectively. Otsu verse reference infarct size was $3.56{\pm}4.16%$. MGMM methods verse reference infarct size was $2.29{\pm}1.94%$. The predefined threshold (30%) showed the smallest mean difference with reference infarct size. However, MGMM was more accurate than predefined threshold in under 10% reference infarct size case (MGMM: 0.006%, predefined threshold: 0.59%). In this study, we was to evaluate myocardial infarct size in polar map using multiple Gaussian mixture model. MGMM method was provide adaptive threshold in each subject and will be a useful for automatic measurement of infarct size.