• Journal of the Institute of Electronics Engineers of Korea SP
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• v.39 no.2
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• pp.128-136
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• 2002

In this paper, we developed an acoustic echo canceller in real-time using TeakLite DSP Core, which will be placed in the vocoder chip of a mobile handset. Considering the limited computational capacity given to the acoustic echo canceller in a vocoder chip, we employed a FIR-type adaptive filter using a conventional NLMS algorithm. To begin with, we designed and implemented an acoustic echo canceller with floating-point format C-source code, and then converted it into fixed-point format through integer simulation. Then we programmed and optimized it in the assembler level to make it run ill real-time. After optimization procedure, the implemented echo canceller has approximately 624 words of program memory and 811 words of data memory. With 8 KHz sampling rate and 256 filter taps in the echo canceller that corresponds to 32 msec of echo delay, it requires 14.12 MIPS of computational capacity. For coverage of 16 msec echo delay, i.e., 128 filter taps, 9 MIPS is requited.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.11 no.5
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• pp.615-622
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• 2018

Recent advancements in camera communication (CamCom) technology using visible light exploited to use display as an luminance source to modulate the data for visible light data communication. The existing display-CamCom techniques uses the selected region of interest based camera capturing approach to detect and decode the 2D color coded data on display screen. This is not effective way to do communicate when the user on mobility. This paper propose the automatic display detection using Lambertian color segmentation combined with canny edge detection algorithms for CamCom in order to avoid manual region of interest selection to establish communication link between display and camera. The automatic display detection methods fails using conventional edge detection algorithms when content changes dynamically in displays. In order to solve this problem lambertian color segmentation combined with canny edge detection algorithms are proposed to detect display automatically. This research analysed different algorithms on display edge recognition and measured the performance on rendering dynamically changing content with color code on display. The display detection rate is achieved around 96% using this proposed solutions.

• The Plant Pathology Journal
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• v.33 no.4
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• pp.393-401
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• 2017

Efforts to control viral diseases in crop production include several types of physical or chemical treatments; antiviral extracts of a number of plants have also been examined to inhibit plant viral infection. However, treatments utilizing naturally selected microorganisms with activity against plant viruses are poorly documented. Here we report isolation of a soil inhabiting bacterium, Pseudomonas oleovorans strain KBPF-004 (developmental code KNF2016) which showed antiviral activity against mechanical transmission of tobamoviruses. Antiviral activity was also evaluated in seed transmission of two tobamoviruses, Pepper mild mottle virus (PMMoV) and Cucumber green mottle mosaic virus (CGMMV), by treatment of seed collected from infected pepper and watermelon, respectively. Pepper and watermelon seeds were treated with culture supernatant of P. oleovorans strain KBPF-004 or control strain ATCC 8062 before planting. Seeds germinated after treatment with water or ATCC 8062 yielded about 60% CGMMV or PMMoV positive plants, whereas < 20% of KBPF-004-treated seeds were virus-infected, a significantly reduced seed transmission rate. Furthermore, supernatant of P. oleovorans strain KBPF-004 remodeled aggregation of PMMoV 126 kDa protein and subcellular localization of movement protein in Nicotiana benthamiana, diminishing aggregation of the 126 kDa protein and essentially abolishing association of the movement protein with the microtubule network. In leaves agroinfiltrated with constructs expressing the coat protein (CP) of either PMMoV or CGMMV, less full-size CP was detected in the presence of supernatant of P. oleovorans strain KBPF-004. These changes may contribute to the antiviral effects of P. oleovorans strain KBPF-004.

• Journal of Trauma and Injury
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• v.21 no.1
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• pp.36-45
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• 2008

Purpose: We conducted this retrospective epidemiological study to assess the incidence and severity of lower extremity injuries in Korea Methods: For this study, we retrospectively reviewed nationwide lower-extremity injury data compiled from 2001 to 2003 based on the National Injury Database, what included National Health Insurance Corporation (NHIC), Car Insurance, and Industry Insurance data. Data were standardized in terms of demographic characteristics, region, and socioeconomic status by using NHIC data. To assess the degree of the injuries, we used the Modified Abbreviated Injury Scale (MoAIS), what has been changed from the International Classification of Disease-10 (ICD-10) code. By using the Excess Mortality Ratio-adjusted Injury Severity Score (EMR-ISS), we classified the degree of severity into four categories: mild, moderate, severe and critical. Results: From 2001 to 2003, lower extremity injuries increased slightly, with a yearly average of 2,437,335. Insurance data should that lower-extremity injuries were the most common, followed by upper-extremity injuries. Significant difference were seen in the numbers of lower extremity injuries based on gender and age. As for provinces, Seoul and Gyeongi provinces had the highest numbers of cases. Junlabukdo had the highest rate of 55,282 cases per 1 million people for standardized gender and population. The annual incidence of the insured patients with lower extrimity injuries was higher than the employer's medical insurance contributions to the medical insurance program. Daily cases occur most often in May and June, with the lowest occurrences being in January and February. Conclusion: The result of this study shows that lower extremity injuries comprised common cause of all injuries. In addition, differences associated with gender, location and socioeconomic status were observed. Further studies are needed to find reasons and then this knowledge will allow strategies to prevent the lower extremity injuries.

• Tunnel and Underground Space
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• v.20 no.2
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• pp.82-91
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• 2010

Grouting technology is one of the ground improvement methods used in water controlling and reinforcement of rock mass in underground structure construction. It is necessarily required to find out the characteristics of grout flow through discontinuities in a rock mass for an adequate grout design and performance assessment. Laminar flow is not always applicable in simulating a grout flow in a rock mass, since the rock joints usually have apertures at a micro-scale and the flow through these joints is affected by the joint roughness and the velocity profile of the flow changes partially near the roughness. Thus, the influence of joint roughness and aperture on the grout flow in rough rock joint was numerically investigated in this study. The commercial computational fluid dynamics code, FLUENT, was applied for this purpose. The computed results by embedded Herschel-Bulkley model and VOF (volume of fluid) model, which are applicable to simulate grout flow in a narrow rock joint that is filled with air and water, were well compared with that of analytical results and previously published laboratory test for the verification. The injection pressure required to keep constant injection rate of grout was calculated in a variety of Joint Roughness Coefficient (JRC) and aperture conditions, and the effect of joint roughness and aperture on grout flow were quantified.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.9
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• pp.126-132
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• 2016

This study numerically investigates the characteristics of chemical reactions and thermal deformation in a steam reformer. These phenomena are significantly affected by the high-temperature burner gas and the process gas conditions. Because the high temperature of the burner gas ranges from 800 to 1000 K, the reformer tubes undergo substantial thermal deformation, eventually resulting in structural failure. Thus, it is necessary to understand the characteristics of the reaction and thermal deformation under the operating conditions to evaluate the reformer tubes for sustainable, stable operation. Extensive numerical simulations were carried out using commercial CFD code (ANSYS FLUENT/MECHANICA Ver. 13.0) while considering three-dimensional turbulent flows and combined heat transfer including conduction, convection, and radiation. Structural analysis considering conjugated heat transfer between solid tubes and fluid flows was conducted using the Fluid-Solid Interaction (FSI) method. The results show that when the injection temperature of the process gas and burner gas decreased, the hydrogen production rate decreased significantly, and thermal deformation decreased by at least 15 to 20%.

• Nuclear Engineering and Technology
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• v.45 no.4
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• pp.513-522
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• 2013

The ODSCC detected in the TSP position of Ulchin 3&4 SGs are typical ODSCC of Alloy 600MA tubes. The causative chemical environment is formed by concentration of impurities inside the occluded region formed by the tube surface, egg crate strips, and sludge deposit there. Most cracks are detected at or near the line contacts between the tube surface and the egg crate strips. The region of dense crack population, as defined as between $4^{th}$ and $9^{th}$ TSPs, and near the center of hot leg hemisphere plane, coincided well with the region of preferential sludge deposition as defined by thermal hydraulics calculation using SGAP computer code. The cracks developed homogeneously in a wide range of SGs, so that the number of cracks detected each outage increased very rapidly since the first detection in the $8^{th}$ refueling outage. The root cause assessment focused on investigation of the difference in microstructure and manufacturing residual stress in order to reveal the cause of different susceptibilities to ODSCC among identical six units. The manufacturing residual stress as measured by XRD on OD surface and by split tube method indicated that the high residual stress of Alloy 600MA tube played a critical role in developing ODSCC. The level of residual stress showed substantial variations among the six units depending on details of straightening and OD grinding processes. Youngwang 3&4 tubes are less susceptible to ODSCC than U3 and U4 tubes because semi-continuous coarse chromium carbides are formed along the grain boundary of Y3&4 tubes, while there are finer less continuous chromium carbides in U3 and U4. The different carbide morphology is caused by the difference in cooling rate after mill anneal. There is a possibility that high chromium content in the Y3&4 tubes, still within the allowable range of Alloy 600, has made some contribution to the improved resistance to ODSCC. It is anticipated that ODSCC in Y5&6 SGs will be retarded more considerably than U3 SGs since the manufacturing residual stress in Y5&6 tubes is substantially lower than in U3 tubes, while the microstructure is similar with each other.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.11
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• pp.126-136
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• 2018

The purpose of this study was to develop a severity-adjustment model for predicting mortality in acute stroke patients using machine learning. Using the Korean National Hospital Discharge In-depth Injury Survey from 2006 to 2015, the study population with disease code I60-I63 (KCD 7) were extracted for further analysis. Three tools were used for the severity-adjustment of comorbidity: the Charlson Comorbidity Index (CCI), the Elixhauser comorbidity index (ECI), and the Clinical Classification Software (CCS). The severity-adjustment models for mortality prediction in patients with acute stroke were developed using logistic regression, decision tree, neural network, and support vector machine methods. The most common comorbid disease in stroke patients were hypertension, uncomplicated (43.8%) in the ECI, and essential hypertension (43.9%) in the CCS. Among the CCI, ECI, and CCS, CCS had the highest AUC value. CCS was confirmed as the best severity correction tool. In addition, the AUC values for variables of CCS including main diagnosis, gender, age, hospitalization route, and existence of surgery were 0.808 for the logistic regression analysis, 0.785 for the decision tree, 0.809 for the neural network and 0.830 for the support vector machine. Therefore, the best predictive power was achieved by the support vector machine technique. The results of this study can be used in the establishment of health policy in the future.

• Journal of Korean Neurosurgical Society
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• v.62 no.4
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• pp.442-449
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• 2019

Objective : Bone mineral density (BMD) is an important consideration during fusion surgery. Although dual X-ray absorptiometry is considered as the gold standard for assessing BMD, quantitative computed tomography (QCT) provides more accurate data in spine osteoporosis. However, QCT has the disadvantage of additional radiation hazard and cost. The present study was to demonstrate the utility of artificial intelligence and machine learning algorithm for assessing osteoporosis using Hounsfield units (HU) of preoperative lumbar CT coupling with data of QCT. Methods : We reviewed 70 patients undergoing both QCT and conventional lumbar CT for spine surgery. The T-scores of 198 lumbar vertebra was assessed in QCT and the HU of vertebral body at the same level were measured in conventional CT by the picture archiving and communication system (PACS) system. A multiple regression algorithm was applied to predict the T-score using three independent variables (age, sex, and HU of vertebral body on conventional CT) coupling with T-score of QCT. Next, a logistic regression algorithm was applied to predict osteoporotic or non-osteoporotic vertebra. The Tensor flow and Python were used as the machine learning tools. The Tensor flow user interface developed in our institute was used for easy code generation. Results : The predictive model with multiple regression algorithm estimated similar T-scores with data of QCT. HU demonstrates the similar results as QCT without the discordance in only one non-osteoporotic vertebra that indicated osteoporosis. From the training set, the predictive model classified the lumbar vertebra into two groups (osteoporotic vs. non-osteoporotic spine) with 88.0% accuracy. In a test set of 40 vertebrae, classification accuracy was 92.5% when the learning rate was 0.0001 (precision, 0.939; recall, 0.969; F1 score, 0.954; area under the curve, 0.900). Conclusion : This study is a simple machine learning model applicable in the spine research field. The machine learning model can predict the T-score and osteoporotic vertebrae solely by measuring the HU of conventional CT, and this would help spine surgeons not to under-estimate the osteoporotic spine preoperatively. If applied to a bigger data set, we believe the predictive accuracy of our model will further increase. We propose that machine learning is an important modality of the medical research field.

• Journal of radiological science and technology
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• v.44 no.4
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• pp.359-365
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• 2021

A heavy particle accelerator is a device that accelerates particles using high energy and is used in various fields such as medical and industrial fields as well as research. However, secondary neutrons and particle fragments are generated by the high-energy particle beam, and among them, the neutrons do not have an electric charge and directly interact with the nucleus to cause radiation of the material. Quantitative evaluation of the radioactive material produced in this way is necessary, but there are many difficulties in actual measurement during or after operation. Therefore, this study compared and evaluated the generated radioactive material in the concrete shield for protons and carbon ions of specific energy by using the simulation code FLUKA. For the evaluation of each energy of proton beam and carbon ion, the reliability of the source term was secured within 2% of the relative error with the data of the NASA Space Radiation Laboratory(NSRL), which is an internationally standardized data. In the evaluation, carbon ions exhibited higher neutron flux than protons. Afterwards, in the evaluation of radioactive materials under actual operating conditions for disposal, a large amount of short-lived beta-decay nuclides occurred immediately after the operation was terminated, and in the case of protons with a high beam speed, more radioactive products were generated than carbon ions. At this time, radionuclides of ⁴⁴Sc, ³H and ²²Na were observed at a high rate. In addition, as the cooling time elapsed, the ratio of long-lived nuclides increased. For nonparticulate radionuclides, ³H, ²²Na, and for particulate radionuclides, ⁴⁴Ti, ⁵⁵Fe, ⁶⁰Co, ¹⁵²Eu, and ¹⁵⁴Eu nuclides showed a high ratio. In this study, it is judged that it is possible to use the particle accelerator as basic data for facility maintenance, repair and dismantling through the prediction of radioactive materials in concrete according to the cooling time after operation and termination of operation.