• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2003.11a
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• pp.418-421
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• 2003

Today, much terminologies such as noise spectrum, Sharpness, contrast, MTF had been defined for Image quality revaluation of radiation Image. Since development of Xeroradiography In the 1970s, Digital radiation detector that use amorphous selenium was developed. The aim of this research is to analyze physical phenomenon of digital radiation detector that use amorphous selenium. Result of Monte Carlo simulations on amorphous selenium based on physical properties(creation of electron-hole pairs) by induced x-ray are described. From the simulation, intrinsic point spread function(PSF) was found and used to observe modulation transfer function(MTF). We investigated how PSF and MTF changed with various x-ray energy. This result can be used to design digital x-ray detector based on a-Se.

• Journal of the Korean Society for Heat Treatment
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• v.16 no.4
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• pp.205-210
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• 2003

Various types of high strength steel sheets were usually used for improving the automobile safety and fuel efficiency by reducing the vehicle weight. The present study aimed to develop the TRIP (transformation induced plasticity) aided high-strength low carbon steel sheets by using a reverse transformation process. The 0.1C-4~8Mn steels were reverse-transformed by slow heating to intercritical temperature region and then furnace cooled to the room temperature. Granular type retained austenite was observed in 4Mn steel and lath type retained austenite was also observed in 6~8Mn steel. The results show that the 6Mn steel under reverse transformed at $625^{\circ}C$ for 6 hrs has maximum elongation up to 39%. The optimum strength-elongation combination was 3,888 ($kg/mm^2{\times}%$) when the 8Mn steel was reverse transformed at $625^{\circ}C$ for 12 h.

• Journal of the Optical Society of Korea
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• v.17 no.6
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• pp.525-532
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• 2013

Contrary to the academic interests of other existing studies elsewhere, this study deals with how the alignment algorithms such as sensitivity or Differential Wavefront Sampling (DWS) can be better used under effects from field, compensator positioning and environmental errors unavoidable from the shop-floor alignment work. First, the influences of aforementioned errors to the alignment state estimation was investigated with the algorithms. The environmental error was then found to be the dominant factor influencing the alignment state prediction accuracy. Having understood such relationship between the distorted system wavefront caused by the error sources and the alignment state prediction, we used it for simulated and experimental alignment runs for Infrared Optical System (IROS). The difference between trial alignment runs and experiment was quite close, independent of alignment methods; 6 nm rms for sensitivity method and 13 nm rms for DWS. This demonstrates the practical usefulness and importance of the prior error analysis using the alignment algorithms before the actual alignment runs begin. The error analysis methodology, its application to the actual alignment of IROS and their results are described together with their implications.

• International conference on construction engineering and project management
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• 2009.05a
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• pp.457-463
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• 2009

The earthwork is essential procedure for all civil engineering projects. Because of its importance in terms of cost and time, it should be managed effectively. In light of this, The Intelligent Excavating System (IES) research consortium has established to improve the productivity, quality and safety of current excavating/earthwork system by the Ministry of Land, Transportation and Maritime Affairs (MLTM) of Korea. This paper summarizes ongoing research aimed at development knowledge and presents a framework of task planning and visualization system for IES. The task planning and visualization system consists of three functions. 1) Using digital terrain model which created by 3D laser scanner, the system can divide it and generates global/local work area so that the excavator can work through the area. 2) In order to operate and/or control the excavator, the system exports the location, paths of boom, arm and bucket data of the excavator to control center. 3) The task planning system is visualized on the computer programming aided-graphic interface which simulates the planned work processes and eventually assists the operator for the control of the excavator. The case study which we have performed, demonstrates the effectiveness of the proposed system.

• Transactions of the Korean Society of Automotive Engineers
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• v.17 no.4
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• pp.10-15
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• 2009

Emission regulations on greenhouse gas(GHG) in automobiles have been stringent because of global warming effect. Over 90% of total GHG emission are carbon dioxides and about 20% of this $CO_2$ emission are emitted from automobiles. In this study, 110 vehicles were tested on a chassis dynamometer and $CO_2$ emissions and fuel economy were measured in order to investigate the characteristics of $CO_2$ emission factor from passenger vehicles which are the most dominant vehicle type in Korea. The characteristics of emissions in accordance with displacements, gross vehicle weight, NIER and CVS-75 speed mode were discussed. It was found that vehicles having larger displacement, heavier gross vehicle weight, automatic transmission and specially at cold start emitted more $CO_2$ emissions. From these results, correlation between $CO_2$ emission and fuel economy was also obtained. This study may contribute to evaluate domestic greenhouse gas emissions and establish national policies on climate changes in future.

• Imaging Science in Dentistry
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• v.43 no.3
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• pp.153-161
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• 2013

Purpose: To prevent low bone mineral density (BMD), that is, osteoporosis, in postmenopausal women, it is essential to diagnose osteoporosis more precisely. This study presented an automatic approach utilizing a histogram-based automatic clustering (HAC) algorithm with a support vector machine (SVM) to analyse dental panoramic radiographs (DPRs) and thus improve diagnostic accuracy by identifying postmenopausal women with low BMD or osteoporosis. Materials and Methods: We integrated our newly-proposed histogram-based automatic clustering (HAC) algorithm with our previously-designed computer-aided diagnosis system. The extracted moment-based features (mean, variance, skewness, and kurtosis) of the mandibular cortical width for the radial basis function (RBF) SVM classifier were employed. We also compared the diagnostic efficacy of the SVM model with the back propagation (BP) neural network model. In this study, DPRs and BMD measurements of 100 postmenopausal women patients (aged >50 years), with no previous record of osteoporosis, were randomly selected for inclusion. Results: The accuracy, sensitivity, and specificity of the BMD measurements using our HAC-SVM model to identify women with low BMD were 93.0% (88.0%-98.0%), 95.8% (91.9%-99.7%) and 86.6% (79.9%-93.3%), respectively, at the lumbar spine; and 89.0% (82.9%-95.1%), 96.0% (92.2%-99.8%) and 84.0% (76.8%-91.2%), respectively, at the femoral neck. Conclusion: Our experimental results predict that the proposed HAC-SVM model combination applied on DPRs could be useful to assist dentists in early diagnosis and help to reduce the morbidity and mortality associated with low BMD and osteoporosis.

• Maxillofacial Plastic and Reconstructive Surgery
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• v.41
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• pp.41.1-41.6
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• 2019

Backgrounds: The purpose of this study is to discuss the total joint reconstruction surgery for a patient with recurrent ankylosis in bilateral temporomandibular joints (TMJs) using three-dimensional (3D) virtual surgical planning, computer-aided manufacturing (CAD/CAM)-fabricated surgical guides, and stock TMJ prostheses. Case presentation: A 66-year-old female patient, who had a history of multiple TMJ surgeries, complained of severe difficulty in eating and trismus. The 3D virtual surgery was performed with a virtual surgery software (FACEGIDE, MegaGen implant, Daegu, South Korea). After confirmation of the location of the upper margin for resection of the root of the zygoma and the lower margin for resection of the ankylosed condyle, and the position of the fossa and condyle components of stock TMJ prosthesis (Biomet, Jacksonville, FL, USA), the surgical guides were fabricated with CAD/CAM technology. Under general anesthesia, osteotomy and placement of the stock TMJ prosthesis (Biomet) were carried out according to the surgical planning. At 2 months after the operation, the patient was able to open her mouth up to 30 mm without complication. Conclusion: For a patient who has recurrent ankylosis in bilateral TMJs, total joint reconstruction surgery using 3D virtual surgical planning, CAD/CAM-fabricated surgical guides, and stock TMJ prostheses may be an effective surgical treatment option.

• Journal of radiological science and technology
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• v.35 no.3
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• pp.227-235
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• 2012

Digital Mammography makes it possible to reproduce the entire breast image. And it is used to detect microcalcification and mass which are the most important point of view of nonpalpable early breast cancer, so it has been used as the primary screening test of breast disease. It is reported that microcalcification of breast lesion is important in diagnosis of early breast cancer. In this study, six types of texture features algorithms are used to detect microcalcification on breast US images and the study has analyzed recognition rate of lesion between normal US images and other US images which microcalification is seen. As a result of the experiment, Computer aided diagnosis recognition rate that distinguishes mammography and breast US disease was considerably high 70~98%. The average contrast and entropy parameters were low in ROC analysis, but sensitivity and specificity of four types parameters were over 90%. Therefore it is possible to detect microcalcification on US images. If not only six types of texture features algorithms but also the research of additional parameter algorithm is being continually proceeded and basis of practical use on CAD is being prepared, it can be a important meaning as pre-reading. Also, it is considered very useful things for early diagnosis of breast cancer.

• Journal of Biomedical Engineering Research
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• v.42 no.3
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• pp.71-79
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• 2021

Currently, the naked eyes-based diagnosis of bone metastases on CT images relies on qualitative assessment. For this reason, there is a great need for a state-of-the-art approach that can assess and follow-up the bone metastases with quantitative biomarker. Radiomics can be used as a biomarker for objective lesion assessment by extracting quantitative numerical values from digital medical images. In this study, therefore, we evaluated the clinical applicability of non-invasive and objective bone metastases computer-aided diagnosis using radiomics-based biomarkers in CT. We employed a total of 21 approaches consist of three-classifiers and seven-feature selection methods to predict bone metastases and select biomarkers. We extracted three-dimensional features from the CT that three groups consisted of osteoblastic, osteolytic, and normal-healthy vertebral bodies. For evaluation, we compared the prediction results of the classifiers with the medical staff's diagnosis results. As a result of the three-class-classification performance evaluation, we demonstrated that the combination of the random forest classifier and the sequential backward selection feature selection approach reached AUC of 0.74 on average. Moreover, we confirmed that 90-percentile, kurtosis, and energy were the features that contributed high in the classification of bone metastases in this approach. We expect that selected quantitative features will be helpful as biomarkers in improving the patient's survival and quality of life.

• Journal of the Korean Institute of Gas
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• v.25 no.2
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• pp.64-71
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• 2021

Research on polymer matrix composites with excellent molding processability and mechanical properties in the automotive field including hydrogen fuel cell electric vehicles is expanding to Computer-Aided Engineering (CAE) to support the design of materials with specific mechanical properties. CAE automation requires the prediction of the mechanical properties and behavior of materials. Unlike single materials, the mechanical properties prediction of polymer matrix composites is difficult to explain with formulas because the mechanical behavior is complicated to be explained only by the relationship between the matrix and the filler. In this study, the stress-strain curve according to the composition of polymer matrix composites, which was difficult to predict due to its sensitivity to large plastic deformation and composition, was predicted based on machine learning of the test data. The developed model finds a complex correlation between matrix and filler types and compositions, and predicts the total stress-strain curve meaningfully even in the absence of learned test data. It is expected that the material design AI system can be completed in the future based on the developed model that predicts the mechanical properties of polymer matrix composites even for the combination and composition that have not been learned.