• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.27 no.12
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• pp.1036-1043
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• 2016

In this paper, an analysis about the elevation angle accuracy degradation of an APAR(Airport Precision Approach Radar) due to the multi-path effect using a phased array antenna was performed. An APAR installed around a runway of airport will be continuously affected in a runway surface of the fixed environment. In this paper, an analysis about the elevation angle accuracy degradation of APAR due to the multi-path effect of runway surface was conducted through a calculation of monopluse slope and sum/difference beam pattern analysis of array antenna. Also, a difference pattern for monopulse to minimize this degradation was optimized in an appropriate configuration to improve a elevation angle accuracy. Finally, a degree of improvement of elevation angle accuracy was confirmed by calculating a monopulse slope including the ground reflection after applying optimized difference patterns of array antenna.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.5
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• pp.744-752
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• 2012

In this study, the Polynomial-based Radial Basis Function Neural Networks is proposed as an one of the recognition part of overall face recognition system that consists of two parts such as the preprocessing part and recognition part. The design methodology and procedure of the proposed pRBFNNs are presented to obtain the solution to high-dimensional pattern recognition problems. In data preprocessing part, Principal Component Analysis(PCA) which is generally used in face recognition, which is useful to express some classes using reduction, since it is effective to maintain the rate of recognition and to reduce the amount of data at the same time. However, because of there of the whole face image, it can not guarantee the detection rate about the change of viewpoint and whole image. Thus, to compensate for the defects, Linear Discriminant Analysis(LDA) is used to enhance the separation of different classes. In this paper, we combine the PCA&LDA algorithm and design the optimized pRBFNNs for recognition module. The proposed pRBFNNs architecture consists of three functional modules such as the condition part, the conclusion part, and the inference part as fuzzy rules formed in 'If-then' format. In the condition part of fuzzy rules, input space is partitioned with Fuzzy C-Means clustering. In the conclusion part of rules, the connection weight of pRBFNNs is represented as two kinds of polynomials such as constant, and linear. The coefficients of connection weight identified with back-propagation using gradient descent method. The output of the pRBFNNs model is obtained by fuzzy inference method in the inference part of fuzzy rules. The essential design parameters (including learning rate, momentum coefficient and fuzzification coefficient) of the networks are optimized by means of Differential Evolution. The proposed pRBFNNs are applied to face image(ex Yale, AT&T) datasets and then demonstrated from the viewpoint of the output performance and recognition rate.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2008.03a
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• pp.283-292
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• 2008

The foremost criterion in the design of a Satellite Launch Vehicle(SLV) is its performance capability to boost the designated payload to the desired mission orbit; it starts from focusing on the SLV configuration to achieve the velocity requirements($}\Delta}V$) for the mission. In this paper we review an analytical approach which is suitable enough for preliminary conceptual design and is used previously to optimize stage configurations for Two Stage to Orbit SLV for Low Earth Orbit(LEO) Missions; we have extended this approach to Three Stage to Orbit SLV and compared different propellant options for the mission. The objective is to minimize the Gross Lift off Weight(GLOW). The primary performance figures of merit were the total inert weight of the SLV and the payload weight that the SLV could lift into LEO, given candidate propulsion systems. The optimization is achieved by configuring the $}\Delta}V$ between stages. A comparison of configurations of single-stage and multi-stage SLVs is made for different propellants. Based upon the optimized stage configurations a comparative performance analysis is made between Liquid and Solid fueled SLV. A 3 degree of freedom trajectory-analysis program is modeled in SIMULINK and used to conduct the performance analysis. Furthermore, a cost analysis is performed on our stage optimized SLVs. The cost estimation relationships(CER) used give us a comparison of development and fabrication costs for the Liquid vs. Solid fueled SLV in man years. The pros and cons of the production, operation ability, performance, responsiveness, logistics, price, shelf life, storage etc of both Solid and Liquid fueled SLVs are discussed. The statistics and data are used from existing or historical(real) SLV stages.

• Nuclear Engineering and Technology
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• v.16 no.3
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• pp.155-160
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• 1984

Analyzed is the thermal margin of the Korea Nuclear Unit 1 (KNU-1) reactor core consisting of either 14 x 14 standard fuel assemblies (SFA) or optimized fuel assemblies (OFA). Employed for the analysis are two different thermal design methods; traditional and statistical thermal design method. Compared to the traditional design thermal method, the statistical thermal design method improves the core thermal margin utilizing best-estimate values for the core operating parameters combining their uncertainties in a statistical manner. Calculations are performed using a steady state and transient thermal-hydraulic analysis computer program, COBRA-IV-i. Calculated results show that the statistical thermal design method significantly improves the thermal margin and satisfies the core thermal design base of the KNU-1 SFA and OFA core. However, the thermal design base can not be met, if the traditional thermal design method is employed for the OFA role analysis.

• Journal of Internet Computing and Services
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• v.20 no.2
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• pp.51-59
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• 2019

In this paper, we analyzed the relationship between charging operation system and electricity charges connected with charging infrastructure among data of many demonstration projects focused on electric vehicles recently. At this point in time, due to the rapid increase in demand for the electric charging infrastructure that will take place in the future, we can prepare for an upcoming era in the sense of forecasting the demand value. At the same time, demonstrating and modeling optimized system modeling centering on sites is a prerequisite. The modeling based on the existing small - scale simulation and the design of the operating system are based on the data linkage analysis. In this paper, we implemented a new optimized system modeling and introduced it as a standard format to analyze time - dependent time - divisional data for each vehicle and user in each point and node. In order to verify the efficiency of the optimization based on the data linkage analysis for the actual implemented electric car charging infrastructure and operation system.

• Journal of the Korean Society of Industry Convergence
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• v.25 no.2_2
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• pp.209-218
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• 2022

The purpose of this study is to analyze an economic assessment of PV-ESS systems based on the power generation performance data of solar power (PV) operating in domestic area, and to calculate the optimal capacity of the energy storage system. In this study, PVs in Gyeonggi-do, Jeollabuk-do, and Gyeongsangbuk-do were targeted, and PVs in this area were assumed to be installed on a general site, and the research was conducted by applying weights based on the facility's capacity. All the analysis was conducted using the actual amount of KPX transactions of PVs in 2019. In order to calculate the optimal capacity of PCS and BESS according to GHI, PV with a minimum/maximum/central value was selected by comparing the solar radiation before the horizontal plane between three years (2017-2019) of the location where PV was installed. As a result of the analysis, in Gyeonggi-do, if the REC weight decreases to 3.4 when there is no change in the cost of installing BESS and PCS, it is more economical to link BESS than PV alone operation of PV. In Jeollabuk-do, it was analyzed that if the REC weight was reduced to 3.6, it was more likely to link BESS than PV operated alone. In Gyeongsangbuk-do, it was analyzed that if the REC weight was reduced to 3.4, it was more likely to link BESS than PV operated alone.

• Journal of Sensor Science and Technology
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• v.31 no.2
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• pp.102-106
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• 2022

Currently, the demand for real-time monitoring of water quality has increased dramatically. Total organic carbon (TOC) analysis is a suitable method for real-time analysis compared with conventional biochemical oxygen demand (BOD) and chemical oxygen demand (COD) methods in terms of analysis time. However, this method is expensive because of the complicated internal processes involved. The photocatalytic titanium dioxide (TiO2)-based TOC method is simpler as it omits more than three preprocessing steps. This is because it reacts only with organic carbon (OC) without extra processes. We optimized the rate between the TiO2 photocatalyst and binder solution and the TiO2 concentration. The efficiency was investigated under 365 nm UV exposure onto a TiO2 coated substrate. The optimized conditions were sufficient to apply a real-time monitoring system for water quality with a short reaction time (within 10 min). We expect that it can be applied in a wide range of water quality monitoring industries.

• Journal of the Korean earth science society
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• v.32 no.6
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• pp.613-628
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• 2011

Restoration, prediction and noise analysis of geomagnetic data measured in the Korean Peninsula were performed. Restoration methods based on an optimized principal component analysis (PCA) and the geostatistical kriging approach were proposed, and its effectiveness was also interpreted. The PCA-based method seemed to be effective to restore the periodical signals and the geostatistical approach was stable to fill the gaps of measurements. To analyze the noise level for each observatory, the geomagnetic time-series was plotted by scattergram which reflects the spatial variation, using data observed during same period. The scattergram showed that the observation made at Cheongyang seemed to have better quality in spatial continuity and stability, and the restoration result was also better than that of Icheon site. For the restoration, both of the methods, geostatistical and optimizaed PCA, showed stable result when the missing of observation was within 20 points. However, in case of more missing observations than 20 points and prediction problem, the optimized PCA seemed to be closer to the real observation considering the frequency-domain characteristics. The prediction using the optimized PCA seems to be plausible for one day of period for interpretation.

• Journal of the Korean Society of Food Science and Nutrition
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• v.34 no.4
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• pp.567-571
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• 2005

In this study, the effects of varying the amount of water, soaking time at $25^{\circ}C$ and drying time after soaking at $45^{\circ}C$ on the induction of resveratrol were evaluated to optimize the soaking treatment by response surface methodology (RSM). After response surface regression (RSREG), the second-order polynomial equation was fitted to the experimental data. The analysis of variance showed that the model appeared to be adequate $(R^2=0.9547)$ with no significant lack of fit (p>0.1). From statistical analysis, amount of water and soaking time were found to be significant factors. On the other hand, drying time was not significant. Ridge analysis showed that the optimized parameters were $67.15\%$ for amount of water, 19.58 hr for soaking time, 65.56 hr for drying time. It was confirmed that resveratrol content was increased from $0.1\;{\mu}g/g$ to $4.55\;{\mu}g/g$ under the optimized conditions. In addition, the experimental values at the optimized condition agreed with values predicted by ridge analysis. The analytical method validation parameters such as accuracy, precision, and specificity were calculated to ensure the method's validity.

• Korean Journal of Radiology
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• v.21 no.4
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• pp.471-482
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• 2020

Objective: We aimed to determine the optimized image-based surrogate endpoints (IBSEs) in targeted therapies for glioblastoma through a systematic review and meta-analysis of phase III randomized controlled trials (RCTs). Materials and Methods: A systematic search of OVID-MEDLINE and EMBASE for phase III RCTs on glioblastoma was performed in December 2017. Data on overall survival (OS) and IBSEs, including progression-free survival (PFS), 6-month PFS (6moPFS), 12-month PFS (12moPFS), median PFS, and objective response rate (ORR) were extracted. Weighted linear regression analysis for the hazard ratio for OS and the hazard ratios or odds ratios for IBSEs was performed. The associations between IBSEs and OS were evaluated. Subgroup analyses according to disease stage (newly diagnosed glioblastoma versus recurrent glioblastoma), types of test treatment, and types of response assessment criteria were performed. Results: Twenty-three phase III RCTs published between 2000 and 2017, including 8387 patients, met the inclusion criteria. OS showed strong correlations with PFS (standardized β coefficient [R] = 0.719), 6moPFS (R = 0.647), and 12moPFS (R = 0.638). OS showed no correlations with median PFS and ORR. In subgroup analysis according to types of therapies, PFS showed the highest correlations with OS in targeted therapies for cell cycle pathways (R = 0.913) and growth factor receptors and their downstream pathways (R = 0.962). 12moPFS showed the highest correlation with OS in antiangiogenic therapy (R = 0.821). The response assessment in neuro-oncology criteria provided higher correlation coefficients between OS and IBSEs than the Macdonald criteria. Conclusion: Overall, PFS is an optimized IBSE in targeted therapies for glioblastoma; however, 12moPFS is optimal in antiangiogenic therapy.