• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.42 no.4
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• pp.326-335
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• 2014

Aerodynamic characteristics of the small two-stage turbo blower were investigated using commercial CFD tool(ANSYS CFX Ver. 14.5) in this paper. Turbo blower, which is a centrifugal type of turbomachinery, is used in various industries. It is used for application that required high static pressure rising at relatively small volumetric flow rate. In order to understand the mechanism of static pressure rising, the aerodynamic characteristics of the small two-stage turbo blower are analyzed at high rotating speed in this study. The k-${\omega}$ SST turbulence model, which is good at prediction of adverse pressure gradient flows, was applied. The CFD results of the turbo blower are validated by performance test. The static pressure rising of the turbo blower is nonlinearly increased over the first stage and the second stage. The secondary flow occurred at guide vanes, between the casing and the first impeller shroud, and the bottom of the impeller disk. As a result, It is required that whole fluid area is analyzed to predict aerodynamic characteristics of small two-stage turbo blower. and the result should be selected with considering for error from experiment and CFD.

• Applied Microscopy
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• v.40 no.2
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• pp.117-123
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• 2010

This study has examined experimentally the Beer's law which is a precondition for quantitative electron tomography. We used carbon support film and latex spheres, which have similar absorption coefficients with biological samples, as the test samples to take a tilt-series of images for electron tomography. First, the 3D information of carbon film and latex spheres was obtained by electron tomography. Then, the regression analysis on the relationship between the intensities of the incident and the transmitted beams in a tilt series was carried out to examine the Beer's law. The regression results with RMS error of 0.976 show the linear intensity variations of the transmitted beam as the tilt angles were increased. In addition, the relative absorption coefficients of carbon support film and latex spheres calculated experimentally through the Beer's law were 1.71 (5) and 2.67 (6)/${\mu}m$, respectively. The absorption coefficients remained constant within a full tilt range. Therefore, it is expected that quantitative electron tomography could be performed for biological samples by applying Beer's law provided the exact intensity of incident beam can be obtained under the thoroughly controlled experimental conditions.

• Journal of Broadcast Engineering
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• v.22 no.3
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• pp.350-365
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• 2017

Steganography is a technique for secret data communication, which is not perceived by third person between a receiver and a transmitter. It has been developed for thousands of years for the transmission of military, diplomatic or business information. The development of digital media and communication has led to the development of steganography techniques in modern times. Technic of image steganography include the LSB, which fixes the number of embedded bits into a pixel, and PVD, which exploits the difference value in the neighboring pixel pairs. In the case of PVD image steganography, a large amount of information is embedded fluidly by difference value in neighboring pixel pairs and the designed range table. However, since the secret information in order is embedded, if an error of the number of embedded bits occurs in a certain pixel pair, all subsequent information will be destroyed. In this paper, we proposes the method, which improve the vulnerability of PVD property about external attack or various noise and extract secret information. Experimental process is comparison analysis about stego-image, which embedded various noise. PVD shows that it is not possible to preserve secret information at all about noise, but it was possible to robustly extract secret information for partial noise of stego-image in case of the proposed PVD image steganography with locally-fixed number of embedding bits.

• Applied Chemistry for Engineering
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• v.25 no.4
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• pp.401-408
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• 2014

In membrane bio-reactor (MBR), the aeration control is one of the important independent variables to decrease fouling and to save energy with shear stress change on the membrane surface. The paper was carried out for numerical simulation of 3-dimensional fluid flow phenomena of the cylindrical bioreactor with submerged flat membranes equipped in the center and supplied the air from the bottom by using the COMSOL program. The viscosity and temperature of solution were assumed to be constant, and the specific air demand based on permeate volume ($SAD_p$) defined as scouring air per permeate rates was used as a variable. The calculated CFD velocities were compared with those of the velocity meter measurement and video image analysis, respectively. The results were good agreement each other within 11% error. For fluid flow in the reactor the liquid velocity increased rapidly between the air diffuser and membrane module, but the velocity decreased during flowing of the membrane module. Also, the velocity increased as it was near from the reactor wall to the central axis. The calculated shear stress on the membrane surface showed the highest value at the center part of the module bottom side and increased as aeration rate increased. Especially, the wall shear stress increased dramatically as the aeration rate increased from 0.15 to 0.25 L/min.

• Korean Journal of Food Science and Technology
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• v.30 no.1
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• pp.22-34
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• 1998

The purpose of this study is to develop biosensor for determination of glucose, lactate, and ethanol in foods and food-stuffs simultaneously. The multiple cathode system was prepared with an oxygen electrode having one anode and hexagonal cathode. Glucose oxidase, mutarotase, lactate oxidase, alcohol oxidase and catalase were used for immobilization to determine glucose, lactate, and ethanol. These components including ethanol were simultaneously determined by the immobilized enzymes in the multiple cathode system. The determination of the components by enzyme sensor was based on the maximum slope of oxygen consumption from enzyme reaction of each sensor part. The response time for analysis was 1 min. The optimum condition for glucose, lactate and ethanol sensor was found to be 0.1 M potassium phosphate buffer, pH 7.0 at $40^{\circ}C$. Interferences of various sugars and organic acids were investigated. Less than 10% of error was found in determination of the components except organic acids. This difference was compensated by the modified equation. This system was confirmed by conventional methods. It was concluded that the multiple cathode system of this study is for an effective method to determine sugar, organic acid, ethanol simultaneously in foods.

• Journal of Korean Society for Geospatial Information Science
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• v.23 no.2
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• pp.27-38
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• 2015

In this study, the 3D position coordinates were calculated for the targets using DLT and self-calibration bundle adjustment with additional parameters in close-range photogrammetry. And then, the accuracy of the results were analysed. For this purpose, the results of camera calibration and orientation parameters were calculated for each images by performing reference surveying using total station though the composition of experimental conditions attached numerous targets. To analyze the accuracy, 3D position coordinates were calculated for targets that has been identically selected and compared with the reference coordinates obtained from a total station. For the image coordinate measurement of the stereo images, we performed the ellipse fitting procedure for measuring the center point of the circular target. And then, the results were utilized for the image coordinate for targets. As a results from experiments, position coordinates calculated by the stereo images-based photogrammetry have resulted out the deviation of less than an average 4mm within the maximum error range of less than about 1cm. From this result, it is expected that the stereo images-based photogrammetry would be used to field of various close-range photogrammetry required for precise accuracy.

• Atmosphere
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• v.16 no.1
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• pp.19-31
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• 2006

The purpose of this study is to develop the statistical model to predict sea level pressure of typhoon period in south coast of the Korean Peninsula. Seven typhoons, which struck south coast of the Korean Peninsula, are selected for this study, and the data for analysis include the central pressure and location of typhoon, and sea level pressure and location of 19 observing site. Models employed in this study are the first order regression, the second order regression and the neural network. The dependent variable of each model is a 3-hr interval sea level pressure at each station. The cause variables are the central pressure of typhoon, distance between typhoon center and observing site, and sea level pressure of 3 hrs before, whereas the indicative variable reveals whether it is before or after typhoon passing. The data are classified into two groups - one is the full data obtained during typhoon period and the other is the data that sea level pressure is less than 1000 hPa. The stepwise selection method is used in the regression model while the node number is selected in the neural network by the Schwarz's Bayesian Criterion. The performance of each model is compared in terms of the root-mean square error. It turns out that the neural network shows better performance than other models, and the case using the full data produces similar or better results than the case using the other data.

• Journal of Construction Engineering and Project Management
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• v.5 no.1
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• pp.11-19
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• 2015

This paper presents optimized artificial neural networks (ANNs) claims prediction and decision awareness framework that guides owner organizations in their pre-bid construction project decisions to minimize claims. The framework is composed of two genetic optimization ANNs models: a Claims Impact Prediction Model (CIPM), and a Decision Awareness Model (DAM). The CIPM is composed of three separate ANNs that predict the cost and time impacts of the possible claims that may arise in a project. The models also predict the expected types of relationship between the owner and the contractor based on their behavioral and technical decisions during the bidding phase of the project. The framework is implemented using actual data from international projects in the Middle East and Egypt (projects owned by either public or private local organizations who hired international prime contractors to deliver the projects). Literature review, interviews with pertinent experts in the Middle East, and lessons learned from several international construction projects in Egypt determined the input decision variables of the CIPM. The ANNs training, which has been implemented in a spreadsheet environment, was optimized using genetic algorithm (GA). Different weights were assigned as variables to the different layers of each ANN and the total square error was used as the objective function to be minimized. Data was collected from thirty-two international construction projects in order to train and test the ANNs of the CIPM, which predicted cost overruns, schedule delays, and relationships between contracting parties. A genetic optimization backward analysis technique was then applied to develop the Decision Awareness Model (DAM). The DAM combined the three artificial neural networks of the CIPM to assist project owners in setting optimum values for their behavioral and technical decision variables. It implements an intelligent user-friendly input interface which helps project owners in visualizing the impact of their decisions on the project's total cost, original duration, and expected owner-contractor relationship. The framework presents a unique and transparent hybrid genetic algorithm-ANNs training and testing method. It has been implemented in a spreadsheet environment using MS Excel$^{(R)}$ and EVOLVERTM V.5.5. It provides projects' owners of a decision-support tool that raises their awareness regarding their pre-bid decisions for a construction project.

• Korean Journal of Construction Engineering and Management
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• v.11 no.4
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• pp.22-31
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• 2010

Because the estimated cost at early stage has great influence on decisions of project owner, the importance of early cost estimation is increasing. However, it depends on experience and knowledge of the estimator mainly due to shortage of information. Those tendency developed into case-based reasoning(CBR) method which solves new problems by adapting previous solution to similar past problems. The performance of CBR model is affected by attribute weight, so that its accurate determination is necessary. Previous research utilizes mathematical method or subjective judgement of estimator. In order to improve the problem of previous research, this suggests CBR schematic cost estimation method using genetic algorithm to determine attribute weight. The cost model employs nearest neighbor retrieval for selecting past case. And it estimates the cost of new cases based on cost information of extracted cases. As the result of validation for 17 testing cases, 3.57% of error rate is calculated. This rate is superior to accuracy rate proposed by AACE and the method to determine attribute weight using multiple regression analysis and feature counting. The CBR cost estimation method improve the accuracy by introducing genetic algorithm for attribute weight. Moreover, this makes user understand the problem-solving process easier than other artificial intelligence method, and find solution within short time through case retrieval algorithm.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.11A
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• pp.1027-1034
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• 2005

IEEE802.15.4a, which is started to realize the PHY layer including high precision ranging/positioning and low data rate communication functions, requires a simple and low power consumable transceiver architecture. To satisfy this requirements, the simple noncoherent on-off keying (OOK) UWB transceiver with the parallel energy window banks (PEWB) giving high precision signal processing interface is proposed. The flexibility of the proposed system in multipath fading channel environments is acquired with the pulse and bit repetition method. To analyze the bit error rate (BER) performance of this proposed system, a noise model in receiver is derived with commonly used random variable distribution, chi-square. BER of $10^{-5}$ under the line-of-sight (LOS) residential channel is achieved with the integration time of 32 ns and signal to noise ratio (SNR) of 15.3 dB. For the non-line-of-sight (NLOS) outdoor channel, the integration time of 72 ns and SNR of 16.2 dB are needed. The integrated energy to total received energy (IRR) for the best BER performance is about $86\%$.