• Restorative Dentistry and Endodontics
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• v.30 no.4
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• pp.303-311
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• 2005

The purpose of this study was to evaluate which type of Ni-Ti files are able to maintain canal configuration better in the simulated canal with abrupt curvature near it's apex. Ninety six simulated root canals were made in epoxy resin and $\sharp$15 finger spreader was used as root canal templates. The simulated root canals were made with radius of curvature of 1.5mm, 3.0mm, 4.0mm, 6.0mm respectively and the angle of curvature of all simulated canals were adjusted to 90 degree. The simulated canals were instrumented by ProFile, ProTaper, Hero 642, and $K^3$ at a 300 rpm using crown-down pressureless technique. Pre-instrumented and post-instrumented images were taken by digital camera and were superimposed with Adobe Photos hop 6.0 program. Images were compared by image analysis program. The changes of canal width at the inner and outer side of the canal curvature. canal transportation were measured at 9 measuring point with 1 mm interval. Statistical analysis among the types of Ni-Ti files was performed using Kruskal-Wallis test and Mann-Whitney U-test. The result was that ProFile maintain original canal configuration better than other engine driven Ni-Ti files in the canals above 3.0mm radius of curvature, and in the 1.5mm radius of curvature, most of Ni-Ti flies were deformed or separated during instrumentation.

• Archives of design research
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• v.18 no.3 s.61
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• pp.85-94
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• 2005

Most of product designers use 3D CAD system as a inevitable design tool nowadays and many new products are developed through a concurrent engineering process. However, it is very difficult for novice designers to get the sense of reality from modeling objects shown in the computer screens. Such a intangibility problem comes from the lack of haptic interactions and contextual information about the real space because designers tend to do 3D modeling works only in a virtual space of 3D CAD system. To address this problem, this research investigate the possibility of a interactive quantified structure simulation for product design using AR(augmented reality) which can register a 3D CAD modeling object on the real space. We built a quantified structure simulation system based on AR and conducted a series of experiments to measure how accurately human perceive and adjust the size of virtual objects under varied experimental conditions in the AR environment. The experiment participants adjusted a virtual cube to a reference real cube within 1.3% relative error(5.3% relative StDev). The results gave the strong evidence that the participants can perceive the size of a virtual object very accurately. Furthermore, we found that it is easier to perceive the size of a virtual object in the condition of presenting plenty of real reference objects than few reference objects, and using LCD panel than HMD. We tried to apply the simulation system to identify preference characteristics for the appearance design of a home-service robot as a case study which explores the potential application of the system. There were significant variances in participants' preferred characteristics about robot appearance and that was supposed to come from the lack of typicality of robot image. Then, several characteristic groups were segmented by duster analysis. On the other hand, it was interesting finding that participants have significantly different preference characteristics between robot with arm and armless robot and there was a very strong correlation between the height of robot and arm length as a human body.

• Journal of Korean Society of Forest Science
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• v.101 no.1
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• pp.163-174
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• 2012

CBI(Composite Burn Index) developed by USDA Forest Service is a index to measure burn severity based on remote sensing. In Korea, the CBI has been used to investigate the burn severity of fire sites for the last few years. However, it has been an argument on that CBI is not adequate to capture unique characteristics of Korean forests, and there has been a demand to develop KCBI(Korean Composite Burn Index). In this regard, this study aimed to develop KCBI by adjusting the CBI and to validate its applicability by using remote sensing technique. Uljin and Youngduk, two large fire sites burned in 2011, were selected as study areas, and forty-four sampling plots were assigned in each study area for field survey. Burn severity(BS) of the study areas were estimated by analyzing NDVI from SPOT images taken one month later of the fires. Applicability of KCBI was validated with correlation analysis between KCBI index values and NDVI values and their confusion matrix. The result showed that KCBI index values and NDVI values were closely correlated in both Uljin (r = -0.54 and p<0.01) and Youngduk (r = -0.61 and p<0.01). Thus this result supported that proposed KCBI is adequate index to measure burn severity of fire sites in Korea. There was a number of limitations, such as the low correlation coefficients between BS and KCBI and skewed distribution of KCBI sampling plots toward High and Extreme classes. Despite of these limitations, the proposed KCBI showed high potentials for estimating burn severity of fire sites in Korea, and could be improved by considering the limitations in further studies.

• Radiation Oncology Journal
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• v.19 no.3
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• pp.287-292
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• 2001

Prupose : We analyzed setup errors induced by using air-vacuum cushion as immobilization device in patients with rectal cancer. Materials and methods : We had treated the twenty patients with rectal cancer by 6 MV, 10 MV X-ray from Aug. 1998 to Aug. 1999 at Chungnam National University Hospital. All patients were treated at prone position. They were separated to two groups, control group, 10 patients using styrofoam, and test group, 10 patients using styrofoam and air-vacuum cushion. We measured errors of posterior field for x, y axis and lateral field for z, y axis with simulation film and EPID image using a matching technique. Results : In control group, the mean displacement values of pelvic bone landmark for x axis and y axis were 0.02 mm. 0.78 mm, respectively and the standard deviations of systematic error were 2.13 mm, 2.40 mm, respectively and the standard deviation of random error were 1.46 mm. 1.51 mm, respectively. In test group, the mean displacement values of x axis and y axis were -0.33 mm. 0.81 mm, respectively and the standard deviations of systematic error were 1.71 mm, 3.08 mm, respectively and the standard deviations of random errors were 1.40 mm. 1.88 mm, respectively. The mean displacement values of z axis and y axis were 2.98 mm. 0.74 mm, respectively and the standard deviations of systematic error were 4.75 mm, 2.65 mm, respectively and standard deviations of random error were 2.69 mm. 1.86 mm, respectively. The statistical difference of field size by using air vacuum cushion between two groups in posterior direction and lateral direction was not shown. Conclusion : We think that use of air-vacuum cushion may not be an advantage for improving setup accuracy in rectal cancer patients.

• The Korean Journal of Nuclear Medicine
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• v.36 no.6
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• pp.344-356
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• 2002

Purpose: RBC blood pool SPECT has been used to diagnose focal liver lesion such as hemangioma owing to its high specificity. However, low spatial resolution is a major limitation of this modality. Recently, ordered subset expectation maximization (OSEM) has been introduced to obtain tomographic images for clinical application. We compared this new modified iterative reconstruction method, OSEM with conventional filtered back projection (FBP) in imaging of liver hemangioma. Materials and Methods: Sixty four projection data were acquired using dual head gamma camera in 28 lesions of 24 patients with cavernous hemangioma of liver and these raw data were transferred to LINUX based personal computer. After the replacement of header file as interfile, OSEM was performed under various conditions of subsets (1,2,4,8,16, and 32) and iteration numbers (1,2,4,8, and 16) to obtain the best setting for liver imaging. The best condition for imaging in our investigation was considered to be 4 iterations and 16 subsets. After then, all the images were processed by both FBP and OSEM. Three experts reviewed these images without any information. Results: According to blind review of 28 lesions, OSEM images revealed at least same or better image quality than those of FBP in nearly all cases. Although there showed no significant difference in detection of large lesions more than 3 cm, 5 lesions with 1.5 to 3 cm in diameter were detected by OSEM only. However, both techniques failed to depict 4 cases of small lesions less than 1.5 cm. Conclusion: OSEM revealed better contrast and define in depiction of liver hemangioma as well as higher sensitivity in detection of small lesions. Furthermore this reconstruction method dose not require high performance computer system or long reconstruction time, therefore OSEM is supposed to be good method that can be applied to RBC blood pool SPECT for the diagnosis of liver hemangioma.

• Journal of Bio-Environment Control
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• v.28 no.4
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• pp.461-470
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• 2019

This study was carried out to quantify the drought stress in grafted watermelon seedlings non-destructively by using chlorophyll fluorescence (CF) imaging technique rather than the visual judgment. Six-day old watermelon seedlings were grown under uniform irrigation for 3 days, and then given drought stress. Afterward, the sensor for the measurement of water content in plug tray cell unit was used to classify the drought-stress level into nine groups from D1 (53.0%, sufficient moisture state) to D9 (15.7%, extremely dry stress), and the 16 CF parameters were measured. In addition, re-irrigation was performed on the drought stressed seedlings(D5 - D9) to determine the growth and photosynthesis recovery level, which was not confirmed by visual judgment. The kinetic curve patterns of CF in three different drought stressed seedling groups were found to be different for the early detection of drought stress. All the 16 CF parameters decreased continuously with exposure to drought stress and drastically decreased from D5 (32.1%) where the visual judgment was possible. The fluorescence decline ratio (Rfd_Lss) started to decrease from the initial drought stress level (D5 - D6), and the Maximum PSII quantum yield (Fv/Fm) was significantly decreased in the later extreme drought stress range (D7 - D9) by re-irrigation recovery test. Thus, Rfd_Lss and Fv/Fm parameters were finally selected as potent indicators of growth and photosynthesis recovery in the initial and later stages of drought stress. Also, to the differences in the numerical values of the individual chlorophyll fluorescence parameters, the drought stress level was intuitively confirmed through the image. These results indicate that Rfd and Fv/Fm can be considered as potential CF parameters for the detection of low and extremely high drought stress, respectively. Furthermore, Fv/Fm can be considered as the best CF parameters for recovery at re-irrigation.

• Korean Journal of Remote Sensing
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• v.37 no.5_1
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• pp.959-974
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• 2021

Forel-Ule Index (FUI) is an index which classifies the colors of inland and seawater exist in nature into 21 gradesranging from indigo blue to cola brown. FUI has been analyzed in connection with the eutrophication, water quality, and light characteristics of water systems in many studies, and the possibility as a new water quality index which simultaneously contains optical information of water quality parameters has been suggested. In thisstudy, Ocean Colour-Climate Change Initiative (OC-CCI) based 4 km FUI was spatially downscaled to the resolution of 500 m using the Geostationary Ocean Color Imager (GOCI) data and Random Forest (RF) machine learning. Then, the RF-derived FUI was examined in terms of its correlation with various water quality parameters measured in coastal areas and its spatial distribution and seasonal characteristics. The results showed that the RF-derived FUI resulted in higher accuracy (Coefficient of Determination (R²)=0.81, Root Mean Square Error (RMSE)=0.7784) than GOCI-derived FUI estimated by Pitarch's OC-CCI FUI algorithm (R²=0.72, RMSE=0.9708). RF-derived FUI showed a high correlation with five water quality parameters including Total Nitrogen, Total Phosphorus, Chlorophyll-a, Total Suspended Solids, Transparency with the correlation coefficients of 0.87, 0.88, 0.97, 0.65, and -0.98, respectively. The temporal pattern of the RF-derived FUI well reflected the physical relationship with various water quality parameters with a strong seasonality. The research findingssuggested the potential of the high resolution FUI in coastal water quality management in the Korean Peninsula.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.7
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• pp.271-278
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• 2021

As the current cyber attacks become more intelligent, the existing Intrusion Detection System is difficult for detecting intelligent attacks that deviate from the existing stored patterns. In an attempt to solve this, a model of a deep learning-based intrusion detection system that analyzes the pattern of intelligent attacks through data learning has emerged. Intrusion detection systems are divided into host-based and network-based depending on the installation location. Unlike network-based intrusion detection systems, host-based intrusion detection systems have the disadvantage of having to observe the inside and outside of the system as a whole. However, it has the advantage of being able to detect intrusions that cannot be detected by a network-based intrusion detection system. Therefore, in this study, we conducted a study on a host-based intrusion detection system. In order to evaluate and improve the performance of the host-based intrusion detection system model, we used the host-based Leipzig Intrusion Detection-Data Set (LID-DS) published in 2018. In the performance evaluation of the model using that data set, in order to confirm the similarity of each data and reconstructed to identify whether it is normal data or abnormal data, 1D vector data is converted to 3D image data. Also, the deep learning model has the drawback of having to re-learn every time a new cyber attack method is seen. In other words, it is not efficient because it takes a long time to learn a large amount of data. To solve this problem, this paper proposes the Siamese Convolutional Neural Network (Siamese-CNN) to use the Few-Shot Learning method that shows excellent performance by learning the little amount of data. Siamese-CNN determines whether the attacks are of the same type by the similarity score of each sample of cyber attacks converted into images. The accuracy was calculated using Few-Shot Learning technique, and the performance of Vanilla Convolutional Neural Network (Vanilla-CNN) and Siamese-CNN was compared to confirm the performance of Siamese-CNN. As a result of measuring Accuracy, Precision, Recall and F1-Score index, it was confirmed that the recall of the Siamese-CNN model proposed in this study was increased by about 6% from the Vanilla-CNN model.

• Anatomy & Biological Anthropology
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• v.31 no.4
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• pp.133-142
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• 2018

3D histology is a imaging system for the 3D structural information of cells or tissues. The synchrotron radiation propagation phase contrast micro-CT has been used in 3D imaging methods. However, the simple phase contrast micro-CT did not give sufficient micro-structural information when the specimen contains soft elements, as is the case with many biomedical tissue samples. The purpose of this study is to develop a new technique to enhance the phase contrast effect for soft tissue imaging. Experiments were performed at the imaging beam lines of Pohang Accelerator Laboratory (PAL). The biomedical tissue samples under frozen state was mounted on a computer-controlled precision stage and rotated in $0.18^{\circ}$ increments through $180^{\circ}$. An X-ray shadow of a specimen was converted into a visual image on the surface of a CdWO4 scintillator that was magnified using a microscopic objective lens(X5 or X20) before being captured with a digital CCD camera. 3-dimensional volume images of the specimen were obtained by applying a filtered back-projection algorithm to the projection images using a software package OCTOPUS. Surface reconstruction and volume segmentation and rendering were performed were performed using Amira software. In this study, We found that synchrotron phase contrast imaging of frozen tissue samples has higher contrast power for soft tissue than that of non-frozen samples. In conclusion, synchrotron radiation propagation phase contrast cryo-microCT imaging offers a promising tool for non-destructive high resolution 3D histology.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.8
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• pp.29-37
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• 2019

Textile quality management targets the physical properties of fabrics and the subjective discriminations of color and fitting. Color is the most representative quality factor that consumers can use to evaluate quality levels without any instruments. For this reason, quantification using a color discrimination device has been used for statistical quality management in the textile industry. However, small and medium-sized domestic textile manufacturers use only visual inspection for color discrimination. As a result, color discrimination is different based on the inspectors' individual tendencies and work procedures. In this research, we want to develop a textile industry-friendly quality management method, evaluating the possibility of rapid color discrimination using a digital imaging device, which is one of the office-automation instruments. The results show that an imaging process-based color discrimination method is highly correlated with conventional color discrimination instruments ($R^2=0.969$), and is also applicable to field discrimination of the manufacturing process, or for different lots. Moreover, it is possible to recognize quality management factors by analyzing color components, ${\Delta}L$, ${\Delta}a$, ${\Delta}b$. We hope that our rapid discrimination method will be a substitute technique for conventional color discrimination instruments via elaboration and optimization.