• Publications of The Korean Astronomical Society
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• v.30 no.2
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• pp.671-673
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• 2015

Before analyzing the images taken with a Mosaic CCD imager, the images have to reach a state which can be used for further scientific analysis. The transformation of raw images into calibrated images is called data reduction. Transforming HEavely Light into Images (THELI) is a nearly fully automated reduction pipeline software (Erben et al., 2005). This pipeline works on raw images to remove instrumental signatures, mask unwanted signals, and perform photometric and astrometric calibration. Finally THELI constructs a deep co-added mosaic image and a weight map. In this poster, THELI data reduction procedures will be reviewed and the reduction process for raw images of seven X-ray bright groups, extracted from GEMS groups (Osmond & Ponman, 2004) obtained by the Wide Field Imager (WFI) mounted on MPG/ESO telescope at La Silla in March 2006 will be discussed.

• YAKHAK HOEJI
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• v.46 no.6
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• pp.416-425
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• 2002

A comparative study to validate the reliability of a fully automated docking program, FlexiDock, was carried out to predict the binding modes of DHFR-inhibitor complex. The inhibitors were extracted from the crystallographically determined DHFR-NADP$^{+}$(H)-inhibitor ternary complexes of human, Escherichia coli and Candida albicans and then docked back into the remaining DHFR-NADP$^{+}$(H) binary complexes using FlexiDock. The resulting conformations and orientations were compared to the original crystal complex structures for reproducibility. Then, folate, the substrate, and known inhibitors such as methotrexate, piritrexim and trimethoprim were docked into the wild-type human DHFR and their binding modes were compared with X-ray crystallographic or other modeling data. The root mean square deviations (RMSDs) for ligands ranged from 1.14 to 1.57$\AA$, and the protein backbone RMSDs from 0.94 to 1.26$\AA$. FlexiDock reproduced the orientations and binding modes of all seven ligands in good agreement with the crystal structures. It proved to be a reliable and efficient program in studying binding modes of DHFR-inhibitor complexes of different species, and the information obtained from this work may provide additional insight into the design of new agents with improved activity.ity.

• Proceedings of the KOSOMBE Conference
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• v.1996 no.11
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• pp.286-288
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• 1996

To make correct prognoses in the area of orthodontics, dentists use cephalometric analysis methods. Currently, most of them involve two main steps: initial diagnosis and treatment establishment. Currently, dentists work manually on X-ray film to measure the cephalogmetric parameters. The work is tedious and time-consuming, and sometimes produces incorrect results. We developed an automated cephalometric analysis system, in which dentists can easily locate reference points needed for the analysis and get the results almost at the same time.

• Restorative Dentistry and Endodontics
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• v.36 no.2
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• pp.98-107
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• 2011

Caries remains prevalent throughout modern society and is the main disease in the field of dentistry. Although studies of this disease have used diverse methodology, recently, X-ray microtomography has gained popularity as a non-destructive, 3-dimensional (3D) analytical technique, and has several advantages over the conventional methods. According to X-ray source, it is classified as monochromatic or polychromatic with the latter being more widely used due to the high cost of the monochromatic source despite some advantages. The determination of mineral density profiles based on changes in X-ray attenuation is the principle of this method and calibration and image processing procedures are needed for the better image and reproducible measurements. Using this tool, 3D reconstruction is also possible and it enables to visualize the internal structures of dental caries. With the advances in the computer technology, more diverse applications are being studied, such automated caries assessment algorithms.

• Journal of the Korean Society for Nondestructive Testing
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• v.22 no.4
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• pp.386-392
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• 2002

Ultrasonic has been proposed as an attractive means of detecting bone loss. There have been several commercial ultrasound devices developed for measuring the heel to predict fracture at other bones. However, these devices select only single point of heel bone as measurement site. It causes poor assessment of bone quality due to the error of transducer positioning. In an effort to improve current ultrasound systems, we evaluated the linear scanning method which provides better prediction of bone quality and an accurate image of bone shape. The system used in this study biaxially scans a heel bone using automated linear scanning technique. The results demonstrated that the values of ultrasound parameters varied with different positions within bone specimen. It has been also found that the linear scanning method could better pre야ct bone quality, eliminating the error of transducer positioning.

• International Journal of Computer Science & Network Security
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• v.24 no.3
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• pp.59-70
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• 2024

Background: The COVID-19 pandemic (the form of coronaviruses) developed at the end of 2019 and spread rapidly to almost every corner of the world. It has infected around 25,334,339 of the world population by the end of September 1, 2020 [1] . It has been spreading ever since, and the peak specific to every country has been rising and falling and does not seem to be over yet. Currently, the conventional RT-PCR testing is required to detect COVID-19, but the alternative method for data archiving purposes is certainly another choice for public departments to make. Researchers are trying to use medical images such as X-ray and Computed Tomography (CT) to easily diagnose the virus with the aid of Artificial Intelligence (AI)-based software. Method: This review paper provides an investigation of a newly emerging machine-learning method used to detect COVID-19 from X-ray images instead of using other methods of tests performed by medical experts. The facilities of computer vision enable us to develop an automated model that has clinical abilities of early detection of the disease. We have explored the researchers' focus on the modalities, images of datasets for use by the machine learning methods, and output metrics used to test the research in this field. Finally, the paper concludes by referring to the key problems posed by identifying COVID-19 using machine learning and future work studies. Result: This review's findings can be useful for public and private sectors to utilize the X-ray images and deployment of resources before the pandemic can reach its peaks, enabling the healthcare system with cushion time to bear the impact of the unfavorable circumstances of the pandemic is sure to cause

• Journal of the Korean Society of Radiology
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• v.18 no.3
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• pp.267-273
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• 2024

Using a cloud-based vertex AI platform that can develop an artificial intelligence learning model without coding, this study easily developed an artificial intelligence learning model by the non-professional general public and confirmed its clinical applicability. Nine dental diseases and 2,999 root disease X-ray images released on the Kaggle site were used for the learning data, and learning, verification, and test data images were randomly classified. Image classification and multi-label learning were performed through hyper-parameter tuning work using a learning pipeline in vertex AI's basic learning model workflow. As a result of performing AutoML(Automated Machine Learning), AUC(Area Under Curve) was found to be 0.967, precision was 95.6%, and reproduction rate was 95.2%. It was confirmed that the learned artificial intelligence model was sufficient for clinical diagnosis.

• Ceramist
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• v.22 no.4
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• pp.368-380
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• 2019

A ceramic is used as a key material in various fields. Accordingly, the use of scanning electron microscopy is increased for the purpose of evaluating the reliability and defects of advanced ceramic materials. The scanning electron microscope is developed to overcome the limitations of optical microscopy and uses accelerated electrons for imaging. Various signals such as SE, BSE and characteristic X-rays provide useful information about the surface microstructure of specimens and, the content and distribution of chemical components. The development of electron guns, such as FEG, and the improved lens system combined with the advanced in-lens detectors and STEM-in-SEM system have expanded the applications of SEM. Automated SEM-EDS analysis also greatly increases the amount of data, enabling more statistically reliable results. In addition, X-ray CT, XRF, and WDS, which are installed in scanning electron microscope, have transformed SEM a more versatile analytical equipment. The performance and specifications of the scanning electron microscope to evaluate ceramics were reviewed and the selection criteria for SEM analysis were described.

• Progress in Medical Physics
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• v.26 no.1
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• pp.52-58
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• 2015

The automated dental cavity detection program for a new concept intra-oral dental x-ray imaging device, an auxiliary diagnosis system, which is able to assist a dentist to identify dental caries in an early stage and to make an accurate diagnosis, was to be developed. The primary theory of the automatic dental cavity detection program is divided into two algorithms; one is an image segmentation skill to discriminate between a dental cavity and a normal tooth and the other is a computational method to analyze feature of an tooth image and take an advantage of it for detection of dental cavities. In the present study, it is, first, evaluated how accurately the DRLSE (Direct Regularized Level Set Evolution) method extracts demarcation surrounding the dental cavity. In order to evaluate the ability of the developed algorithm to automatically detect dental cavities, 7 tooth phantoms from incisor to molar were fabricated which contained a various form of cavities. Then, dental cavities in the tooth phantom images were analyzed with the developed algorithm. Except for two cavities whose contours were identified partially, the contours of 12 cavities were correctly discriminated by the automated dental caries detection program, which, consequently, proved the practical feasibility of the automatic dental lesion detection algorithm. However, an efficient and enhanced algorithm is required for its application to the actual dental diagnosis since shapes or conditions of the dental caries are different between individuals and complicated. In the future, the automatic dental cavity detection system will be improved adding pattern recognition or machine learning based algorithm which can deal with information of tooth status.

• Journal of the Korean Ceramic Society
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• v.12 no.3
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• pp.8-12
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• 1975

The crystal structure of synthetic magnesite has been studied by X-ray method. Magnesite is trigonal R3c, with a=4.637$\AA$, c=15.023$\AA$ and Z=6. Intensity data were collected with a Rigaku automated four-circle diffractometer and Mo-K$\alpha$ radiation. The structure was refined by the full-matrix least squares method using anisotropic thermal parameters. The final R index for 234 reflections is 0.037. The C-O and Mg-O bond lengths were 1.283 and 2.105$\AA$, respectively. The interatomic angles of three kinds of O-Mg-O were 88.25, 91.75 and 180.00$^{\circ}$, respectively. It is clarified that the distortion of the Mg-O6 octahedron in magnesite is smaller than that of Ca-O6 in calcite.