• Journal of the Korean Society of Radiology
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• v.7 no.3
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• pp.181-189
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• 2013

The optimum exposure parameters are found when examined using the automatic mode in FFDM. improve the image quality by applying denoising algorithm and propose methods to reduce AGD(Average Grandular Dose) a patient can receive. For the experiment, Nuclear Associates Model 18-222 phantom was the used, and the entrance dose and AGD were measured. And then, Signal, Noise, SNR and FOM(Figure of Merit) were measured, compared and analyzed image denoising before and after. As the experiment result, first, SNR was the highest at Mo/Mo 23kVp and W/Rh 35kvp was the lowest for the average glandular dose. It showed to use 28kVp of W/Rh to be the best through the result of FOM. SNR was the highest at Mo/Mo 23kVp(image denoising), and it showed to W/Rh and 28kVp to be the best in the FOM result which AGD was considered at the same time. By the image denoising, it is possible to reduce noise while maintain important information in the image.

• Journal of the Korean Society of Hazard Mitigation
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• v.10 no.1
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• pp.73-80
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• 2010

The optimal design of water distribution system have started with the least cost design of single objective function using fixed hydraulic variables, eg. fixed water demand and pipe roughness. However, more adequate design is accomplished with considering uncertainties laid on water distribution system such as uncertain future water demands, resulting in successful estimation of real network's behaviors. So, many researchers have suggested a variety of approaches to consider uncertainties in water distribution system using uncertainties quantification methods and the optimal design of multi-objective function is also studied. This paper suggests the new approach of a multi-objective optimization seeking the minimum cost and maximum robustness of the network based on two uncertain variables, nodal demands and pipe roughness uncertainties. Total design procedure consists of two folds: least cost design and final optimal design under uncertainties. The uncertainties of demands and roughness are considered with Latin Hypercube sampling technique with beta probability density functions and multi-objective genetic algorithms (MOGA) is used for the optimization process. The suggested approach is tested in a case study of real network named the New York Tunnels and the applicability of new approach is checked. As the computation time passes, we can check that initial populations, one solution of solutions of multi-objective genetic algorithm, spread to lower right section on the solution space and yield Pareto Optimum solutions building Pareto Front.

• Steel and Composite Structures
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• v.34 no.5
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• pp.681-698
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• 2020

The paper addresses contribution to the modeling and optimization of major machinability parameters (cutting force, surface roughness, and tool wear) in finish dry hard turning (FDHT) for machinability evaluation of hardened AISI grade die steel D₃ with PVD-TiN coated (Al₂O₃-TiCN) mixed ceramic tool insert. The turning trials are performed based on Taguchi's L₁₈ orthogonal array design of experiments for the development of regression model as well as adequate model prediction by considering tool approach angle, nose radius, cutting speed, feed rate, and depth of cut as major machining parameters. The models or correlations are developed by employing multiple regression analysis (MRA). In addition, statistical technique (response surface methodology) followed by computational approaches (genetic algorithm and particle swarm optimization) have been employed for multiple response optimization. Thereafter, the effectiveness of proposed three (RSM, GA, PSO) optimization techniques are evaluated by confirmation test and subsequently the best optimization results have been used for estimation of energy consumption which includes savings of carbon footprint towards green machining and for tool life estimation followed by cost analysis to justify the economic feasibility of PVD-TiN coated Al₂O₃+TiCN mixed ceramic tool in FDHT operation. Finally, estimation of energy savings, economic analysis, and sustainability assessment are performed by employing carbon footprint analysis, Gilbert approach, and Pugh matrix, respectively. Novelty aspects, the present work: (i) contributes to practical industrial application of finish hard turning for the shaft and die makers to select the optimum cutting conditions in a range of hardness of 45-60 HRC, (ii) demonstrates the replacement of expensive, time-consuming conventional cylindrical grinding process and proposes the alternative of costlier CBN tool by utilizing ceramic tool in hard turning processes considering technological, economical and ecological aspects, which are helpful and efficient from industrial point of view, (iii) provides environment friendliness, cleaner production for machining of hardened steels, (iv) helps to improve the desirable machinability characteristics, and (v) serves as a knowledge for the development of a common language for sustainable manufacturing in both research field and industrial practice.

• Journal of Korean Society of Environmental Engineers
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• v.38 no.9
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• pp.482-496
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• 2016

Algal blooms of cyanobacteria (blue-green Algae) due to the eutrophication of rivers and lakes can cause not only the damage by its biological toxins but also the economic loss in drinking water treatment. The natural algae coagulant, a commercial product known as W.H. containing the algicidal and allelopathic material derived from oak, can control algal problems proactively through the coagulation flotation process. However, because there have been no applications of the process for pre-treatment in drinking water plants, we could find no report on the optimum injection dose of W.H.. In this study, we have conducted several sets of jar-tests while changing W.H. dose and concentration of chl-a for (1) Han-river samples and (2) subcultured cyanobacteria samples, and monitored the removal mechanisms of algae intensively. Based on these jar-test results, two linear equations with variables of chl-a and turbidity have been deduced to predict the optimal W.H. dose after the multiple regression analysis using IBM-SPSS. Also, prototypes of automatic control logic have been suggested to inject the optimal W.H. dose promptly in response to the variation of water quality.

• Journal of Korea Water Resources Association
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• v.51 no.8
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• pp.677-686
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• 2018

There remain numerous ungauged watersheds in Korea owing to limited spatial and temporal streamflow data with which to estimate hydrological model parameters. To deal with this problem, various regionalization approaches have been proposed over the last several decades. However, the results of the regionalization models differ according to climatic conditions and regional physical characteristics, and the results of the regionalization models in previous studies are generally inconclusive. Thus, to improve the performance of the regionalization methods, this study attaches hydrological model parameters obtained using a spatial proximity model to the explanatory variables of a regional regression model and defines it as a hybrid regionalization model (hybrid model). The performance results of the hybrid model are compared with those of existing methods for 37 test watersheds in South Korea. The GR4J model parameters in the gauged watersheds are estimated using a shuffled complex evolution algorithm. The variation inflation factor is used to consider the multicollinearity of watershed characteristics, and then stepwise regression is performed to select the optimum explanatory variables for the regression model. Analysis of the results reveals that the highest modeling accuracy is achieved using the hybrid model on RMSE overall the test watersheds. Consequently, it can be concluded that the hybrid model can be used as an alternative approach for modeling ungauged watersheds.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.5
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• pp.46-54
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• 2011

In this paper, we propose a low-complexity loop filtering method depending on transform-block regions. Block adaptive loop filter (BALF) was developed to improve about 10% in compression performance for the next generation video coding. The BALF employs the Wiener filter that makes reconstructed frames close to the original ones and transmits filter-related information. However, the BALF requires high computational complexity, while it can achieve high compression performance because the block adaptive loop filter is applied to all the pixels in blocks. The proposed method is a new loop filter that classifies pixels in a block into inner and boundary regions based on the characteristics of the integer transform and derives optimum filters for each region. Then, it applies the selected filters for the inner and/or boundary regions. The decoder complexity can be adjusted by selecting region-dependent filter to be used in the decoder side. We found that the proposed algorithm can reduce 35.5% of computational complexity with 2.56% of compression loss, in case that only boundary filter is used.

• Journal of the Korean earth science society
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• v.18 no.6
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• pp.515-521
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• 1997

To investigate the nature of the waste materials in the Nanjido Landfill, we have conducted multivariate statistical analysis of geophysical data set comprised of magnetic, gravity, LandSat TM thermal band and surface depression measurement data. Because these data sets show different responses to the depth, we have transformed the observed total field magnetic data and gravity data to the residual reduced-to-pole(RTP) magnetic anomalies and the three dimensional density anomalies, respectively, and utilized the informations about the upper shallow part of the landfills only in the following process. For the statistical analysis at the points of depression measurement, the magnetic, density and LandSat data values at these points are determined by interpolation process. Since the multivarite statistical analysis technique utilizes a clustering algorithm for classification of data set and we have measured the dissimilarity between objects by using Euclidean distance, standardization was applied prior to distance calculation in order to eliminate any scaling effects due to different measurement unit of each data set. The hierarchial grouping technique was used to construct the dendrogram. The optimum number of statistical groups(clusters), which are classified on the basis of geophysical and geotechnical characteristics, appeared to be six on the resulting dendrogram. The result of this study suggests that the dimension and nature of the multicomponent waste landfills can be identified by application of the multivarite statistical analysis technique to integrated geophysical data sets.

• Proceedings of the Korean Society of Medical Physics Conference
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• 2002.09a
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• pp.129-132
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• 2002

The practical virtual compensator, which uses a dynamic multi-leaf collimator (dMLC) and three-dimensional radiation therapy planning (3D RTP) system, was designed. And the feasibility study of the virtual compensator was done to verify that the virtual compensator acts a role as the replacement of the physical compensator. Design procedure consists of three steps. The first step is to generate the isodose distributions from the 3D RTP system (Render Plan, Elekta). Then isodose line pattern was used as the compensator pattern. Pre-determined compensating ratio was applied to generate the fluence map for the compensator design. The second step is to generate the leaf sequence file with Ma's algorithm in the respect of optimum MU-efficiency. All the procedure was done with home-made software. The last step is the QA procedure which performs the comparison of the dose distributions which are produced from the irradiation with the virtual compensator and from the calculation by 3D RTP. In this study, a phantom was fabricated for the verification of properness of the designed compensator. It is consisted of the styrofoam part which mimics irregular shaped contour or the missing tissues and the mini water phantom. Inhomogeneous dose distribution due to the styrofoam missing tissue could be calculated with the RTP system. The film dosimetry in the phantom with and without the compensator showed significant improvement of the dose distributions. The virtual compensator designed in this study was proved to be a replacement of the physical compensator in the practical point of view.

• Journal of the Korea Society of Computer and Information
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• v.16 no.2
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• pp.25-31
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• 2011

Principal component analysis (PCA) is a well-known method for dimensionality reduction and feature extraction. Although PCA has been applied in many areas successfully, it is sensitive to outliers due to the use of sum-square-error. Several variants of PCA have been proposed to resolve the noise sensitivity and, among the variants, improved robust fuzzy PCA (RF-PCA2) demonstrated promising results. RF-PCA2, however, still can fall into a local optimum due to equal initial membership values for all data points. Another reason comes from the fact that RF-PCA2 is based on sum-square-error although fuzzy memberships are incorporated. In this paper, a variant of RF-PCA2 called RF-PCA3 is proposed. The proposed algorithm is based on the objective function of RF-PCA2. RF-PCA3 augments RF-PCA2 with the objective function of PCA and initial membership calculation using data distribution, which make RF-PCA3 to have more chance to converge on a better solution than that of RF-PCA2. RF-PCA3 outperforms RF-PCA2, which is demonstrated by experimental results.

• Tunnel and Underground Space
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• v.25 no.1
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• pp.56-67
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• 2015

In this study, a source locating technique applicable to transversely isotropic media was developed. Wave velocity anisotropy was considered based on the partition approximation method, which simply enabled AE source locating. Sets of P wave arrival time were decided by the two-step AIC algorithm and they were later used to locate the AE sources when having the least error compared with the partitioned elements. In order to validate the technique, pencil lead break test on artificial transversely isotropic mortar specimen was carried out. Defining the absolute error as the distance between the pencil lead break point and the located point, 1.60 mm ~ 14.46 mm of range and 8.57 mm of average were estimated therefore it was regarded as thought to be 'acceptable' considering the size of the specimen and the AE sensors. Comparing each absolute error under different threshold levels, results showed small discrepancies therefore this technique was hardly affected by background noise. Absolute error could be decomposed into each coordinate axis error and through it, effect of AE sensor position could be understood so if optimum sensor position was able to be decided, one could get more precise outcome.