• Design Convergence Study
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• v.16 no.5
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• pp.125-140
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• 2017

This study explores potential capability of a machine learning approach for monitoring urban morphology based on an evident case study. The case study conveys year 2006 investigations on interpreting urban morphology of Boston Main Streets by applying a machine learning approach. From the lesson of the precedent study, in 2016, another field research and interview was conducted to compare changes in urban situation, data commons culture, and technology innovation during the decade. This paper describes open possibilities to advance urban monitoring for morphological changes. Most of all, a multi-participatory data platform enables managing urban data system in real time. Second, collaboration with machines with artificial intelligence can intervene the framework of the urban management system as well as transform it through new demands of innovative industries. Recently, urban regeneration became a dominant urban planning strategy in Korean, therefore, urban monitoring is on demand. It is timely important to correspond to in-situ problems based on empirical research.

• Korean Journal of Remote Sensing
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• v.27 no.2
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• pp.75-87
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• 2011

This paper presents a method for region-based building extraction from high resolution satellite images(HRSI) using integrated information of spectral and color invariant features without user intervention such as selecting training data sets. The purpose of this study is also to evaluate the effectiveness of the proposed method by applying to IKONOS and QuickBird images. Firstly, the image is segmented by the MSRG method. The vegetation and shadow regions are automatically detected and masked to facilitate the building extraction. Secondly, the region merging is performed for the masked image, which the integrated information of the spectral and color invariant features is used. Finally, the building regions are extracted using the shape feature for the merged regions. The boundaries of the extracted buildings are simplified using the generalization techniques to improve the completeness of the building extraction. The experimental results showed more than 80% accuracy for two study areas and the visually satisfactory results obtained. In conclusion, the proposed method has shown great potential for the building extraction from HRSI.

• Geophysics and Geophysical Exploration
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• v.22 no.4
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• pp.225-238
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• 2019

Migration velocity analysis (MVA) for creating optimum depth-domain velocities in seismic imaging was applied to marine long-offset multi-channel data, and the effectiveness of the MVA approach was demonstrated by the combinations of conventional data processing procedures. The time-domain images generated by conventional time-processing scheme has been considered to be sufficient so far for the seismic stratigraphic interpretation. However, when the purpose of the seismic imaging moves to the hydrocarbon exploration, especially in the geologic modeling of the oil and gas play or lead area, drilling prognosis, in-place hydrocarbon volume estimation, the seismic images should be converted into depth domain or depth processing should be applied in the processing phase. CMP-based velocity analysis, which is mainly based on several approximations in the data domain, inherently contains errors and thus has high uncertainties. On the other hand, the MVA provides efficient and somewhat real-scale (in depth) images even if there are no logging data available. In this study, marine long-offset multi-channel seismic data were optimally processed in time domain to establish the most qualified dataset for the usage of the iterative MVA. Then, the depth-domain velocity profile was updated several times and the final velocity-in-depth was used for generating depth images (CRP gather and stack) and compared with the images obtained from the velocity-in-time. From the results, we were able to confirm the depth-domain results are more reasonable than the time-domain results. The spurious local minima, which can be occurred during the implementation of full waveform inversion, can be reduced when the result of MVA is used as an initial velocity model.

• Journal of Korea Water Resources Association
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• v.54 no.spc1
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• pp.1183-1193
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• 2021

Low flow affects various fields such as river water supply management and planning, and irrigation water. A sufficient period of flow data is required to calculate the Flow Duration Curve. However, in order to calculate the Flow Duration Curve, it is essential to secure flow data for more than 30 years. However, in the case of rivers below the national river unit, there is no long-term flow data or there are observed data missing for a certain period in the middle, so there is a limit to calculating the Flow Duration Curve for each river. In the past, statistical-based methods such as Multiple Regression Analysis and ARIMA models were used to predict sulfur in the unmeasured watershed, but recently, the demand for machine learning and deep learning models is increasing. Therefore, in this study, we present the DNN technique, which is a machine learning technique that fits the latest paradigm. The DNN technique is a method that compensates for the shortcomings of the ANN technique, such as difficult to find optimal parameter values in the learning process and slow learning time. Therefore, in this study, the Flow Duration Curve applicable to the unmeasured watershed is calculated using the DNN model. First, the factors affecting the Flow Duration Curve were collected and statistically significant variables were selected through multicollinearity analysis between the factors, and input data were built into the machine learning model. The effectiveness of machine learning techniques was reviewed through statistical verification.

• Progress in Medical Physics
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• v.26 no.3
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• pp.168-177
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• 2015

For evaluating the treatment planning accurately, the quality assurance for treatment planning is recommended when patients were treated with IMRT which is complex and delicate. To realize this purpose, treatment plan quality assurance software can be used to verify the delivered dose accurately before and after of treatment. The purpose of this study is to evaluate the accuracy of treatment plan quality assurance software for each IMRT plan according to MLC DLG (dosimetric leaf gap). Novalis Tx with a built-in HD120 MLC was used in this study to acquire the MLC dynalog file be imported in MobiusFx. To establish IMRT plan, Eclipse RTP system was used and target and organ structures (multi-target, mock prostate, mock head/neck, C-shape case) were contoured in I'mRT phantom. To verify the difference of dose distribution according to DLG, MLC dynalog files were imported to MobiusFx software and changed the DLG (0.5, 0.7, 1.0, 1.3, 1.6 mm) values in MobiusFx. For evaluation dose, dose distribution was evaluated by using 3D gamma index for the gamma criteria 3% and distance to agreement 3 mm, and the point dose was acquired by using the CC13 ionization chamber in isocenter of I'mRT phantom. In the result for point dose, the mock head/neck and multi-target had difference about 4% and 3% in DLG 0.5 and 0.7 mm respectively, and the other DLGs had difference less than 3%. The gamma index passing-rate of mock head/neck were below 81% for PTV and cord, and multi-target were below 30% for center and superior target in DLGs 0.5, 0.7 mm, however, inferior target of multi-target case and parotid of mock head/neck case had 100.0% passing rate in all DLGs. The point dose of mock prostate showed difference below 3.0% in all DLGs, however, the passing rate of PTV were below 95% in 0.5, 0.7 mm DLGs, and the other DLGs were above 98%. The rectum and bladder had 100.0% passing rate in all DLGs. As the difference of point dose in C-shape were 3~9% except for 1.3 mm DLG, the passing rate of PTV in 1.0 1.3 mm were 96.7, 93.0% respectively. However, passing rate of the other DLGs were below 86% and core was 100.0% passing rate in all DLGs. In this study, we verified that the accuracy of treatment planning QA system can be affected by DLG values. For precise quality assurance for treatment technique using the MLC motion like IMRT and VMAT, we should use appropriate DLG value in linear accelerator and RTP system.

• Journal of rehabilitation welfare engineering & assistive technology
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• v.11 no.1
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• pp.81-89
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• 2017

In this paper, we propose a gait pattern recognition method for intelligent prosthesis that enables walking in various environments of femoral amputees. The proposed gait mode changing method is a single sensor based algorithm which can discriminate gait surface and gait phase using only strain gauges sensor, and it is designed to simplify the algorithm based on multiple sensors of existing intelligent prosthesis and to reduce cost of prosthesis system. For the recognition algorithm, we analyzed characteristics of the ground reaction force generated during gait of normal person and defined gait step segmentation and gait detection condition, A gait analyzer was constructed for the gait experiment in the environment similar to the femoral amputee. The validity of the paper was verified through the defined detection conditions and fabricated instruments. The accuracy of the algorithm based on the single sensor was 95%. Based on the proposed single sensor-based algorithm, it is considered that the intelligent prosthesis system can be made inexpensive, and the user can directly grasp the state of the walking surface and shift the walking mode. It is confirmed that it is possible to change the automatic walking mode to switch the walking mode that is suitable for the walking mode.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.33 no.5
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• pp.363-371
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• 2015

Feature extraction is one of the main goals in many remote sensing analyses. After high-resolution imagery became more available, it became possible to extract more detailed and specific features. Thus, considerable image segmentation algorithms have been developed, because traditional pixel-based analysis proved insufficient for high-resolution imagery due to its inability to handle the internal variability of complex scenes. However, the individual segmentation method, which simply uses color layers, is limited in its ability to extract various target features with different spectral and shape characteristics. Spectral indices can be used to support effective feature extraction by helping to identify abundant surface materials. This study aims to evaluate a feature extraction method based on a segmentation technique with spectral indices. We tested the extraction of diverse target features-such as buildings, vegetation, water, and shadows from eight band WorldView-2 satellite image using decision tree classification and used the result to draw the appropriate spectral indices for each specific feature extraction. From the results, We identified that spectral band ratios can be applied to distinguish feature classes simply and effectively.

• Journal of the Korea Computer Graphics Society
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• v.26 no.1
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• pp.17-25
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• 2020

We present a novel multi-core CPU based parallel algorithm for the cell-connectivity information extraction algorithm, which is one of the preprocessing steps for volume rendering of unstructured grid data. We first check the synchronization issues when parallelizing the prior serial algorithm naively. Then, we propose a 3-step parallel algorithm that achieves high parallelization efficiency by removing synchronization in each step. Also, our 3-step algorithm improves the cache utilization efficiency by increasing the spatial locality for the duplicated triangle test process, which is the core operation of building cell-connectivity information. We further improve the efficiency of our parallel algorithm by employing a memory pool for each thread. To check the benefit of our approach, we implemented our method on a system consisting of two octa-core CPUs and measured the performance. As a result, our method shows continuous performance improvement as we add threads. Also, it achieves up to 82.9 times higher performance compared with the prior serial algorithm when we use thirty-two threads (sixteen physical cores). These results demonstrate the high parallelization efficiency and high cache utilization efficiency of our method. Also, it validates the suitability of our algorithm for large-scale unstructured data.

• Progress in Medical Physics
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• v.9 no.4
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• pp.201-206
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• 1998

IMRT optimization method on multiple slice has been developed by using gradient based algorithm. On about 10-30 CT slices including treatment region of a patient, dose optimization has been performed slice by slice to meet the condition that each organ should be exposed below maximum tolerable doses and that the tumor dose within the range of 100$\pm$5 %. Field size was limited to 8$\times$8 cm$^2$ and in this condition, beam divergence was not taken into account to calculate dose distribution. Total dose distribution was calculated by superposing each beamlet whose dose distribution had been precalculated. In order to investigate beam number dependency, dose optimization was performed for one, three, five, seven, and nine coplanar beams and then each optimization index was evaluated. It is found that optimization time was proportional to number of slices to be optimized, and the most efficient plan was obtained from the case of three-to-seven incident beams with respect to calculation time and optimization index. In conclusion, dose optimization of multiple slice was able to be obtained by repeating dose optimization of single slice under condition that the beam size is not too large to ignore beam divergence. And it turns out that result of dose optimization was so sensitive to the position of isocenter that some method to optimize isocenter position is needed to improve it.

• Korean Journal of Microbiology
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• v.43 no.2
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• pp.91-99
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• 2007

For the detection of Human Immunodeficiency Virus (HIV), multiple and ultra-rapid real-time PCR methods were developed. The target DNA sequences were deduced from HIV-1 specific 495bp partial env gene (gi_1184090) and from HIV-2 specific 294 bp partial env gene (gi_1332355), and were synthesized by using PCR-based gene synthesis on the reason of safety. Ultra-rapid real-time PCR was performed by $Genspector^{TM}$ using microchip-based, $1\;{\mu}l$ of reaction volume with extremely short time in each 3 step in PCR. The detection including DNA-amplification and melting temperature analysis was completed inner 15 minutes. The HIV-1 specific 117 bp-long and HIV-2 specific 119 bp-long PCR products were successfully amplified from minimum of template,2.3 molecules of each env gene. This kind of real-time PCR was designated as ultra-rapid real-time PCR in this study and it could be applied not only an alternative detection method against HIV, but also other pathogens using PCR-based detection.