• Korean Chemical Engineering Research
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• v.45 no.1
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• pp.17-24
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• 2007

The purpose of the present study is to identify the drying cylinder model in paper plants and to analyze characteristics of process responses for changes in input variables. The model developed in this work is based on actual plant operation data where the steam pressure applied to the cylinder behaves as the major variable. It is found that heat transfer coefficients from the condensate to the canvas could be represented as empirical relations based on heat conductivities and operation data. The effectiveness of the cylinder model is demonstrated by the measured moisture contents and web temperature. Stability of the drying process is analyzed based on the transfer functions derived from the cylinder model.

• The Journal of Fisheries Business Administration
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• v.39 no.3
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• pp.49-65
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• 2008

In Korea, deep-sea fishing industry is faced with pressure of being thrown out of business, because of the upcoming unfavorable business conditions such as the fishing regulation of coastal countries, Korea-US Free Trade Agreement(KORUS FTA), and the other socio-economic changes. Hence, we present an evaluation of future business competitive for the deep-sea fishing industry so that the government can develop a concession plan for the deep-sea fishing industry by utilizing the results of this study. In efficiency analysis of deep-sea fishing industry, the decision maker may have two problems: (1) how to deal with multiple inputs and outputs of deep-sea fishing industry and (2) how to assign the weights on different inputs and outputs, In this paper, we proposed to use Data Envelopment Analysis (DEA) to estimate efficiency of deep-sea fishing industry with multiple inputs and outputs. In the DEA, The direct impact of KORUS FTA, fishing regulation of coastal countries, fishing charges, and competitive fishing conditions were used as input parameters while the profitability and secured fishing quarters, as outputs. The results of DEA-BCC model indicate that 6 out of 12 DUMs have better efficiency under variable return to scale assumption.

• Computers and Concrete
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• v.19 no.2
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• pp.217-226
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• 2017

This paper summarizes the results of experimental research, and artificial intelligence methods focused on determination of compressive strength of lightweight cement mortar with silica fume and fly ash after sulfate attack. The artificial neural network and the support vector machine were selected as artificial intelligence methods. Lightweight cement mortar mixtures containing silica fume and fly ash were prepared in this study. After specimens were cured in $20{\pm}2^{\circ}C$ waters for 28 days, the specimens were cured in different sulfate concentrations (0%, 1% $MgSO_4^{-2}$, 2% $MgSO_4^{-2}$, and 4% $MgSO_4^{-2}$ for 28, 60, 90, 120, 150, 180, 210 and 365 days. At the end of these curing periods, the compressive strengths of lightweight cement mortars were tested. The input variables for the artificial neural network and the support vector machine were selected as the amount of cement, the amount of fly ash, the amount of silica fumes, the amount of aggregates, the sulfate percentage, and the curing time. The compressive strength of the lightweight cement mortar was the output variable. The model results were compared with the experimental results. The best prediction results were obtained from the artificial neural network model with the Powell-Beale conjugate gradient backpropagation training algorithm.

• Steel and Composite Structures
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• v.37 no.2
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• pp.193-209
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• 2020

In this paper, the efficiency of five Machine Learning (ML) methods consisting of Deep Learning (DL), Support Vector Machine (SVM), Random Forest (RF), Decision Tree (DT), and Gradient Tree Booting (GTB) for regression and classification of the Ultimate Load Factor (ULF) of nonlinear inelastic steel frames is compared. For this purpose, a two-story, a six-story, and a twenty-story space frame are considered. An advanced nonlinear inelastic analysis is carried out for the steel frames to generate datasets for the training of the considered ML methods. In each dataset, the input variables are the geometric features of W-sections and the output variable is the ULF of the frame. The comparison between the five ML methods is made in terms of the mean-squared-error (MSE) for the regression models and the accuracy for the classification models, respectively. Moreover, the ULF distribution curve is calculated for each frame and the strength failure probability is estimated. It is found that the GTB method has the best efficiency in both regression and classification of ULF regardless of the number of training samples and the space frames considered.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.22 no.2
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• pp.78-85
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• 2010

A dynamic model has been developed to investigate the operability of a single and double-effect solar energy assisted parallel type absorption chiller. In the study, main components and fluid transport mechanism were modeled. And solar radiation and the solar collector were also modeled along with its control design. The model was run for the single mode with solar energy supply only and the solar/gas driving double effect mode. From the simulation results, it was found that the present configuration of the chiller is not capable of regulating solution flow rates according to variable solar energy input. And the issues of the excessive circulation flow rate and the mismatch between available solar power and cooling load discourages the use of the single mode, but the dual use of gas and solar power is recommendable in view of controllability and enhanced COP.

• JSTS:Journal of Semiconductor Technology and Science
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• v.10 no.1
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• pp.37-44
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• 2010

New features of motion compensation, such as variable block size and multiple reference frames are introduced in H.264/AVC. However, these new features induce significant implementation complexity increases. In this paper, an efficient architecture for spiral-type motion estimation is proposed. First, we propose a hardware-friendly spiral search order. Then, an efficient processing element (PE) architecture for ME is proposed to achieve the proposed search order. The improved PE enables one-pixel-move of the reference pixel data to top, bottom, right, and left by four ports for input and output. Moreover, the parallel calculation architecture to calculate all block size with the SAD of 4x4 is introduced in the proposed architecture. As the result of hardware implementation, the hardware cost is about 145k gates. Maximum clock frequency is 134 MHz in the case of FPGA (Xilinx Vertex5) implementation.

• Journal of Digital Contents Society
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• v.16 no.5
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• pp.767-773
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• 2015

This study suggests a reliable auction right analysis system that improves the existing auction right analysis in a sense that the system is more applicable to a real economic world. The existing study has used an auction successful bidding price rate and an auction successful contract price for its estimation of the auction right analysis. But in this paper the degree of market vitality which is provided from the commercial zone analysis is used as an input variable so the expected auction price can be estimated and the auction right analysis is conducted in that manner.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.24 no.6
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• pp.461-466
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• 2012

Recently, building energy systems with solar collector and solar module have increased to improve energy problem, a heat island, a global warming and carbon dioxide emissions. In this study, value of solar radiation in areas was analyzed using TRNSYS simulation, and the optimum tilt and orientation angle for installing a photovoltaic module was examined. Average values of the weather data in the past twenty years in areas were used as input data. The results show that the tilt angle of a photovoltaic module for gaining the annual maximum solar radiation varies in different localities, and values of the annual solar radiation gained by using the variable photovoltaic module increased by 2.5 percent as compared with that gained by using the fixed photovoltaic module. When fixed photovoltaic module is installed, it should be examined the tilt and orientation angle for installing a photovoltaic module was examined.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.53 no.2
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• pp.114-122
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• 2004

This paper presents a novel single-stage active-clamp type high frequency resonant inverter. The proposed topology is integrated full-bridge boost rectifier as power factor corrector and active-clamp type high frequency resonant inverter into a single-stage. The input stage of the full-bridge boost rectifier works in discontinuous conduction mode(DCM) with constant duty cycle and variable switching frequency. So that a boost converter makes the line current follow naturally the sinusoidal line voltage waveform. By adding additional active-clamp circuit to conventional class-E high frequency resonant inverter, main switch of inverter part operates not only at Zero-Voltage-Switching mode but also reduces the switching voltage stress of main switch. Simulation results have demonstrated the feasibility of the proposed high frequency resonant inverter. Characteristics values based on characteristics estimation through circuit analysis is given as basis data in design procedure. Also, experimental results are presented to verify theoretical discussion. This proposed inverter will be able to be practically used as a power supply in the fields of induction heating applications, fluorescent lamp and DC-DC converter etc.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.54 no.12
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• pp.569-575
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• 2005

This paper proposes a gain scheduled control technique using time-delay for the nonlinear system with plant uncertainties and unexpected disturbances. The time delay-based gain scheduled control depends on a direct estimation of a function representing the effect of uncertainties. The information from the estimation is used to cancel the unknown dynamics and the unexpected disturbances simultaneously. The proposed estimation scheme with a finite convergence time is formulated in order to estimate the unknown scheduling variable variation. In other words, the time delay-based gain scheduled control uses the past observation of the system's response and the control input to directly modify the control actions rather than to adjust the controller gains or to identify system parameters. It has a simple structure so as to minimize the computational burden. The benefits of this proposed scheme are demonstrated in the simulation of an electromagnetic suspension system with plant uncertainties and external disturbances, and the proposed controller is compared with the conventional state feedback controller.