• Land and Housing Review
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• v.12 no.2
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• pp.109-120
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• 2021

Global warming due to increased carbon dioxide is perceived as one of the factors threatening the future. Efforts are being made to reduce carbon dioxide emissions in each industry around the world. In particular, environmental loads and impacts during the life cycle of SOC structures and buildings have been quantitatively assessed through a quantitative method called Life Cycle Assessment (LCA). However, the construction sector has gone through difficulty in quantitative assessment for several reasons: 1) LCI DB is not fully established; 2) the life cycle is very long; 3) the building structures are unique. Therefore, it takes enormous effort and time to carry out LCA. Rather than estimating carbon emissions with accuracy, this study aims to present a simplified estimation model that allows owners or designers to easily estimate carbon dioxide emissions with little effort, given that rapid and rough decisions regarding environmental load reduction are to be made. This study performs the LCA using data from 25 road construction projects across the country, followed by multiple regression analyses to derive a simplified carbon estimation model (SLCA). The study also carries out a comparative analysis with values estimated by performing a typical LCA. The comparison analysis shows an error rate of less than 5% for 16 road projects.

• Journal of the Korean Geotechnical Society
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• v.35 no.4
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• pp.27-35
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• 2019

This study confirmed the applicability to the field of geotechnical engineering for relatively complicated space and many target design variables in back analysis. The Sharan's equation and the Blum's method were used for the tunnel field and the retaining wall as a model for the multi-variate problem of geotechnical engineering. Optimization methods are generally divided into a deterministic method and a stochastic method. In this study, Simulated Annealing Method (SA) was selected as a deterministic method and Differential Evolution Algorithm (DEA) and Particle Swarm Optimization Method (PSO) were selected as stochastic methods. The three selected optimization methods were compared by applying a multi-variate model. The problem of deterministic method has been confirmed in the multi-variate back analysis of geotechnical engineering, and the superiority of DEA can be confirmed. DEA showed an average error rate of 3.12% for Sharan's solution and 2.23% for Blum's problem. The iteration number of DEA was confirmed to be smaller than the other two optimization methods. SA was confirmed to be 117.39~167.13 times higher than DEA and PSO was confirmed to be 2.43~6.91 times higher than DEA. Applying a DEA to the multi-variate back analysis of geotechnical problems can be expected to improve computational speed and accuracy.

• Korean Journal of Clinical Laboratory Science
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• v.50 no.4
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• pp.470-476
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• 2018

Facial motor evoked potential (FMEP) by multi-pulse transcranial electrical stimulation (mpTES) can complement free-running electromyography (EMG) and direct facial nerve stimulation to predict the functional integrity of the facial nerve during cerebello-pontine angle (CPA) tumor surgery. The purpose of this paper is to examine the standardized test methods and the usefulness of FMEP as a predictor of facial nerve function and to minimize the incidence of facial paralysis as an aftereffect of surgery. TES was delivered through electrode Mz (cathode) - M3/M4 (anode), and extracranially direct distal facial muscle excitation was excluded by the absence of single pulse response (SPR) and by longer onset latency (more than 10 ms). FMEP from the orbicularis oris (o.oris) and the mentalis muscle simultaneously can improve the accuracy and success rate compared with FMEP from the o.oris alone. Using the methods described, we can effectively predict facial nerve outcomes immediately after surgery with a reduction of more than 50% of FMEP amplitude as a warning criterion. In conclusion, along with free-running EMG and direct facial nerve stimulation, FMEP is a useful method to reduce the incidence of facial paralysis as a sequela during CPA tumor surgery.

• Journal of the Korea Convergence Society
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• v.10 no.6
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• pp.7-14
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• 2019

In this paper, we propose a Cascade Classifier face detection method using the Haar-like feature, which is complemented by the Flood Fill algorithm for lossy areas due to illumination and shadow in YCbCr color space extraction. The Cascade Classifier using Haar-like features can generate noise and loss regions due to lighting, shadow, etc. because skin color extraction using existing YCbCr color space in image only uses threshold value. In order to solve this problem, noise is removed by erosion and expansion calculation, and the loss region is estimated by using the Flood Fill algorithm to estimate the loss region. A threshold value of the YCbCr color space was further allowed for the estimated area. For the remaining loss area, the color was filled in as the average value of the additional allowed areas among the areas estimated above. We extracted faces using Haar-like Cascade Classifier. The accuracy of the proposed method is improved by about 4% and the detection rate of the proposed method is improved by about 2% than that of the Haar-like Cascade Classifier by using only the YCbCr color space.

• Explosives and Blasting
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• v.37 no.2
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• pp.22-30
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• 2019

On sites where explosives are used, the effects of noise and vibration produced by the blast wave are subject to a number of operational restrictions. Recently, the number of civil complaints has increased and the standard of environmental regulations on secure goods has been greatly tighten. Therefore, work is generally carried out by machine excavation in case of close proximity of safety thing. Machine excavation methods have the advantage as reducing noise and vibration compared to blasting methods, but depending on the conditions of rock intended to be excavated, they are sometimes less constructive than planned. In general, the closer a rock type is to hard rock, the less constructible it becomes. In this paper, we are going to explain the construction of a construction section with a close proximity to a safety thing using electronic detonators. While the project site was designed with a machine excavation methods due to the close(9.9m) proximity of safety thing(the railroad), construction using electronic detonators was reviewed as an alternative method for improving rate of advance time and construction efficiency when expose to hard rock. Through blasting using electronic detonators, construction and economic efficiency were maximized while minimizing impact on surrounding safety things. Because $HiTRONIC^{TM}$, which is produced by Hanwha, has innovative stability and high explosion reliability, it is able to explode with high-precision accuracy. Electronic detonators are widely used in construction sites of railway or highway, other urban burrowing areas and large limestone mines.

• Journal of Food Hygiene and Safety
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• v.34 no.1
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• pp.52-57
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• 2019

Method development and validation of decursin for the standardization of Angelica gigas Nakai as a functional ingredient and health food were accomplished. The quantitative determination method of decursin as a marker compound of aerial parts of Angelica gigas Nakai extract (AAGE) was optimized by HPLC analysis using a C18 column ($3{\times}150mm$, $3{\mu}m$) with 0.1% TFA in water and acetonitrile as the mobile phase at a flow rate of 0.5 mL/min and detection wavelength of 330 nm. The HPLC/PDA method was applied successfully to quantification of the marker compound in AAGE after validation of the method with linearity, accuracy, and precision. The method showed high linearity in the calibration curve at a coefficient of correlation ($R^2$) of 0.9994 and the limit of detection and limit of quantitation were $0.011{\mu}g/mL$ and $0.033{\mu}g/mL$, respectively. Relative standard deviation (RSD) values of data from intra- and inter-day precision were less than 1.10% and 1.13%, respectively. Recovery of decursin at 0.5, 1, 5 and $10{\mu}g/mL$ were 92.38 ~ 104.11%. These results suggest that the developed HPLC method is very useful for the determination of marker compound in AAGE to develop a health functional material.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.2
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• pp.750-762
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• 2019

The importance of the call center as a contact point for the enterprise is growing. However, call centers have difficulty with their operating agents due to the agents' lack of knowledge and owing to frequent agent turnover due to downturns in the business, which causes deterioration in the quality of customer service. Therefore, through an N-bank call center case study, we developed a system to reduce the burden of keeping up business knowledge and to improve customer service quality. It is a "real-time agent advisor" system that provides agents with answers to customer questions in real time by combining AI technology for speech recognition, natural language processing, and questions & answers for existing call center information systems, such as a private branch exchange (PBX) and computer telephony integration (CTI). As a result of the case study, we confirmed that the speech recognition system for real-time call analysis and the corpus construction method improves the natural speech processing performance of the query response system. Especially with name entity recognition (NER), the accuracy of the corpus learning improved by 31%. Also, after applying the agent advisor system, the positive feedback rate of agents about the answers from the agent advisor was 93.1%, which proved the system is helpful to the agents.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.3
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• pp.16-22
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• 2019

Off-line programming and robot calibration through simulation are essential when setting up a robot in a robot automation production line. In this study, we developed a new robot calibration method to match the CAD data of the production line with the measurement data on the site using 3D scanner. The proposed method calibrates the robot using 3D point cloud data through Iterative Closest Point algorithm. Registration is performed in three steps. First, vertices connected by three planes are extracted from CAD data as feature points for registration. Three planes are reconstructed from the scan point data located around the extracted feature points to generate corresponding feature points. Finally, the transformation matrix is calculated by minimizing the distance between the feature points extracted through the ICP algorithm. As a result of applying the software to the automobile welding robot installation, the proposed method can calibrate the required accuracy to within 1.5mm and effectively shorten the set-up time, which took 5 hours per robot unit, to within 40 minutes. By using the developed system, it is possible to shorten the OLP working time of the car body assembly line, shorten the precision teaching time of the robot, improve the quality of the produced product and minimize the defect rate.

• Journal of the Korean Society of Radiology
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• v.13 no.2
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• pp.185-192
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• 2019

DXA is the most commonly used BMD examination equipment with the best performance on reflecting the biological alteration with tiny change of bone density. In spite of the importance of the quality control to maintain the accuracy and precision of the examination, considerable number of hospitals are not conducting QC due to the difficulty and high cost of the phantom product. This study develops the cross revision phantom with 3D printer and the change of the degree of infilling filaments which can be readily secured, and provides the usefulness assessment of the developed phantom by comparing with existing products. The Hounsfield Units of ABS, TPU, PLA, 30% Cu-PLA, and 30% Al-PLA are assessed. The Hounsfield Units result at infilling rate 100% was $-149.74{\pm}2.36$, $-55.62{\pm}7.14$, $-7.68{\pm}3.82$, $87.53{\pm}1.07$, and $1795.20{\pm}16.15$. The L1, L2, L3 BMD of 3D printing phantom with linear regression model were $0.620{\pm}0.010g/cm^2$, $1.092{\pm}0.025g/cm^2$, $1.554{\pm}0.026g/cm^2$ which are statistically relevant to the existing phantom products. This result provides the base line data for various medical phantom produce and capability of proper quality control of DXA equipment.

• Journal of Food Hygiene and Safety
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• v.34 no.4
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• pp.374-379
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• 2019

This study developed predictive growth models of Salmonella enterica Serovar Typhimurium on lettuce washed with chlorine (100~300 ppm) and ultrasound (US, 37 kHz, 380 W) treatment and stored at different temperatures ($10{\sim}25^{\circ}C$) using a polynomial equation. The primary model of specific growth rate (SGR) and lag time (LT) showed a good fit ($R^2{\geq}0.92$) with a Gompertz equation. A secondary model was obtained using a quadratic polynomial equation. The appropriateness of the secondary SGR and LT model was verified by coefficient of determination ($R^2=0.98{\sim}0.99$ for internal validation, 0.97~0.98 for external validation), mean square error (MSE=-0.0071~0.0057 for internal validation, -0.0118~0.0176 for external validation), bias factor ($B_f=0.9918{\sim}1.0066$ for internal validation, 0.9865~1.0205 for external validation), and accuracy factor ($A_f=0.9935{\sim}1.0082$ for internal validation, 0.9799~1.0137 for external validation). The newly developed models for S. Typhimurium could be incorporated into a tertiary modeling program to predict the growth of S. Typhimurium as a function of combined chlorine and US during the storage. These new models may also be useful to predict potential S. Typhimurium growth on lettuce, which is important for food safety purposes during the overall supply chain of lettuce from farm to table. Finally, the models may offer reliable and useful information of growth kinetics for the quantification microbial risk assessment of S. Typhimurium on washed lettuce.