• Journal of the Korean Institute of Intelligent Systems
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• v.12 no.3
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• pp.210-218
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• 2002

This paper proposes an efficient separation method of the composite images by using independent component analysis(ICA) based on neural networks of the approximate learning algorithm. The Proposed learning algorithm is the fixed point(FP) algorithm based on Secant method which can be approximately computed by only the values of function for estimating the root of objective function for optimizing entropy. The secant method is an alternative of the Newton method which is essential to differentiate the function for estimating the root. It can achieve a superior property of the FP algorithm for ICA due to simplify the composite computation of differential process. The proposed algorithm has been applied to the composite signals and image generated by random mixing matrix in the 4 signal of 500-sample and the 10 images of $512{\times}512-pixel$, respectively The simulation results show that the proposed algorithm has better performance of the learning speed and the separation than those using the conventional algorithm based method. It also solved the training performances depending on initial points setting and the nonrealistic learning time for separating the large size image by using the conventional algorithm.

• Journal of Pharmacopuncture
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• v.18 no.2
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• pp.7-18
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• 2015

Objectives: Lawsone (1,4 naphthoquinone) is a non redox cycling compound that can be catalyzed by DT diaphorase (DTD) into 1,2,4-trihydroxynaphthalene (THN), which can generate reactive oxygen species by auto oxidation. The purpose of this study was to evaluate the toxicity of the phytomarker 1,4 naphthoquinone and its metabolite THN by using the molecular docking program AutoDock 4. Methods: The 3D structure of ligands such as hydrogen peroxide ($H_2O_2$), nitric oxide synthase (NOS), catalase (CAT), glutathione (GSH), glutathione reductase (GR), glucose 6-phosphate dehydrogenase (G6PDH) and nicotinamide adenine dinucleotide phosphate hydrogen (NADPH) were drawn using hyperchem drawing tools and minimizing the energy of all pdb files with the help of hyperchem by $MM^+$ followed by a semi-empirical (PM3) method. The docking process was studied with ligand molecules to identify suitable dockings at protein binding sites through annealing and genetic simulation algorithms. The program auto dock tools (ADT) was released as an extension suite to the python molecular viewer used to prepare proteins and ligands. Grids centered on active sites were obtained with spacings of $54{\times}55{\times}56$, and a grid spacing of 0.503 was calculated. Comparisons of Global and Local Search Methods in Drug Docking were adopted to determine parameters; a maximum number of 250,000 energy evaluations, a maximum number of generations of 27,000, and mutation and crossover rates of 0.02 and 0.8 were used. The number of docking runs was set to 10. Results: Lawsone and THN can be considered to efficiently bind with NOS, CAT, GSH, GR, G6PDH and NADPH, which has been confirmed through hydrogen bond affinity with the respective amino acids. Conclusion: Naphthoquinone derivatives of lawsone, which can be metabolized into THN by a catalyst DTD, were examined. Lawsone and THN were found to be identically potent molecules for their affinities for selected proteins.

• Journal of Korean Society of Environmental Engineers
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• v.32 no.10
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• pp.936-941
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• 2010

This study was conducted to investigate formaldehyde removals by silver nano-particles attached on the surface of granular activated carbon (Ag-AC) and to compare the results to those obtained with ordinary activated carbon (AC). The BET analysis showed that the overall surface area and the fraction of micropores (less than $20{\AA}$ diameter) of the Ag-AC were significantly decreased because the silver particles blocked the small pores on the surface of the Ag-AC. The formaldehyde removal capacity of the Ag-AC determined using the Freundlich isotherm was higher than that of AC. Despite the decreased BET surface area and micropore volume, the Ag-AC had the increased removal capacity for formaldehyde, presumably due to catalytic oxidation by silver nano-particles. In contrast, the adsorption intensity of the Ag-AC, estimated by 1/n in the Freundlich isotherm equation, was similar to that of the ordinary AC, indicating that the surface modification using silver nano-particles did not affect the adsorption characteristics of AC. In a column experiment, the Ag-AC also showed a longer breakthrough time than that of the AC. Simulation results using the homogeneous surface diffusion model (HSDM) were well fitted to the breakthrough curve of formaldehyde for the ordinary AC, but the predictions showed substantial deviations from the experimental data for the Ag-AC. The discrepancy was due to the catalytic oxidation of silver nano-particles that was not incorporated in the HSDM. Consequently, a new numerical model that takes the catalytic oxidation into accounts needs to be developed to predict the combined oxidation and adsorption process more accurately.

• Journal of Biosystems Engineering
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• v.41 no.4
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• pp.357-364
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• 2016

Purpose: This study was performed to define the drying characteristics of sorghum by developing thin layer drying equations and evaluating various grain drying equations. Thin layer drying equations lay the foundation characteristics to establish the thick layer drying equations, which can be adopted to determine the design conditions for an agricultural dryer. Methods: The drying rate of sorghum was measured under three levels of drying temperature ($40^{\circ}C$, $50^{\circ}C$, and $60^{\circ}C$) and relative humidity (30%, 40%, and 50%) to analyze the drying process and investigate the drying conditions. The drying experiment was performed until the weight of sorghum became constant. The experimental constants of four thin layer drying models were determined by developing a non-linear regression model along with the drying experiment results. Result: The half response time (moisture ratio = 0.5) of drying, which is an index of the drying rate, was increased as the drying temperature was high and relative humidity was low. When the drying temperature was $40^{\circ}C$ at a relative humidity (RH) of 50%, the maximum half response time of drying was 2.8 h. Contrastingly, the maximum half response time of drying was 1.2 h when the drying temperature was $60^{\circ}C$ at 30% RH. The coefficient of determination for the Lewis model, simplified diffusion model, Page model, and Thompson model was respectively 0.9976, 0.9977, 0.9340, and 0.9783. The Lewis model and the simplified diffusion model satisfied the drying conditions by showing the average coefficient of determination of the experimental constants and predicted values of the model as 0.9976 and Root Mean Square Error (RMSE) of 0.0236. Conclusion: The simplified diffusion model was the most suitable for every drying condition of drying temperature and relative humidity, and the model for the thin layer drying is expected to be useful to develop the thick layer drying model.

• Resources Recycling
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• v.26 no.1
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• pp.51-58
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• 2017

The present study to develop a process for extracting nitric acid and gold from aqua regia leach solution using TBP(tributyl phosphate) was conducted. The pure aqua regia was used to investigate the extractive behavior of nitric acid depending on the concentration of extractant, concentration ratio of nitric and hydrochloric acid. The extraction rate of nitric acid and gold from the gold bearing aqua regia was also examined. The theoretical extraction number was verified by counter current using the number of operations and the phase ratio obtained from McCabe-Thiele diagram. Stripping experiments were carried out for continuous recovery of nitric acid and gold in loaded organic. Considering the effect of extraction acid and gold, the simulation showed that greater than 99.9% extraction of $103.0mg{\cdot}L^{-1}$ gold and 98.0% of $151.2g{\cdot}L^{-1}$ nitric acid could be attained in a two and three-stage counter-current extraction at an O/A phase ratio of 1:0.85. Distilled water and sodium thiosulfate were used as the nitric acid and gold stripping solution. The stripping rates were 99.5% and 92.0%, respectively. The study revealed that the recovery of nitric acid and gold from gold bearing aqua regia was a plausible approach through simultaneous extraction and continuous stripping of nitric acid and gold.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.13 no.1
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• pp.48-57
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• 2020

MCU used in applications such as wireless chargers and USB type-C require MTP memory with a small cell size and a small additional process mask. Conventional double poly EEPROM cells are small in size, but additional processing masks of about 3 to 5 sheets are required, and FN tunneling type single poly EEPROM cells have a large cell size. In this paper, a 110nm MTP cell using a vertical PIP capacitor is proposed. The erase operation of the proposed MTP cell uses FN tunneling between FG and EG, and the program operation uses CHEI injection method, which reduces the MTP cell size to 1.09㎛2 by sharing the PW of the MTP cell array. Meanwhile, MTP memory IP required for applications such as USB type-C needs to operate over a wide voltage range of 2.5V to 5.5V. However, the pumping current of the VPP charge pump is the lowest when the VCC voltage is the minimum 2.5V, while the ripple voltage is large when the VCC voltage is 5.5V. Therefore, in this paper, the VPP ripple voltage is reduced to within 0.19V through SPICE simulation because the pumping current is suppressed to 474.6㎂ even when VCC is increased by controlling the number of charge pumps turned on by using the VCC detector circuit.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.28 no.1
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• pp.123-133
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• 2018

Cyber-Physical System (CPS) is a system in which a physical system and a cyber system are strongly integrated. In order to operate the target physical system stably, the CPS constantly monitors the physical system through the sensor and performs control using the actuator according to the current state. If a malicious attacker performs a forgery attack on the measured values of the sensors in order to conceal their attacks, the cyber system operated based on the collected data can not recognize the current operation status of the physical system. This causes the delay of the response of the automation system and the operator, and then more damage will occur. To protect the CPS from increasingly sophisticated and targeted attacks, countermeasures must be developed that can detect stealthy deception attacks. However, in the CPS environment composed of various heterogeneous devices, the process of analyzing and demonstrating the vulnerability to actual field devices requires a lot of time. Therefore, in this study, we propose a method of constructing the experiment environment of the PLCitM (PLC in the middle) which can verify the performance of the techniques to detect the CPS stealthy deception attack and present the experimental results.

• Journal of Navigation and Port Research
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• v.39 no.6
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• pp.457-463
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• 2015

A gas turbine engine plays an important role as a prime mover that is used in the marine transportation field as well as the space/aviation and power plant fields. However, it has a complicated structure and there is a time delay element in the combustion process. Therefore, an elaborate mathematical model needs to be developed to control a gas turbine engine. In this study, a modeling technique for a gas generator, a PLA actuator, and a metering valve, which are major components of a gas turbine engine, is explained. In addition, sub-models are obtained at several operating points in a steady state based on the trial running data of a gas turbine engine, and a method for controlling the engine speed is proposed by designing an NPID controller for each sub-model. The proposed NPID controller uses three kinds of gains that are implemented with a nonlinear function. The parameters of the NPID controller are tuned using real-coded genetic algorithms in terms of minimizing the objective function. The validity of the proposed method is examined by applying to a gas turbine engine and by conducting a simulation.

• Journal of the Institute of Convergence Signal Processing
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• v.10 no.4
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• pp.274-279
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• 2009

The flow of a universal system-level design methodology consists of system specification, system-level hardware/software partitioning, co-design, co-verification using virtual or physical prototype, and system integration. In this paper, verification environments based-on SystemVerilog and SystemC, one is native-code co-verification environment which makes prompt functional verification possible and another is SystemVerilog layered testbench which makes clock-level verification possible, are implemented. In native-code co-verification, HW and SW parts of SoC are respectively designed with SystemVerilog and SystemC after HW/SW partitioning using SystemC, then the functional interaction between HW and SW parts is carried out as one simulation process. SystemVerilog layered testbench is a verification environment including corner case test of DUT through the randomly generated test-vector. We adopt SystemC to design a component of verification environment which has multiple inheritance, and we combine SystemC design unit with the SystemVerilog layered testbench using SystemVerilog DPI and ModelSim macro. As multiple inheritance is useful for creating class types that combine the properties of two or more class types, the design of verification environment adopting SystemC in this paper can increase the code reusability.

• Journal of the Korean Institute of Gas
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• v.12 no.2
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• pp.38-41
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• 2008

In this research, we propose a new method for tracking the release rate using the concentration data obtained from the sensor. We used a sensor network that has already been set surrounding the area where hazardous gas releases can occur. From the real-time sensor data, we detected and analyzed releases of harmful materials and their concentrations. Based on the results, the release rate is estimated using the neural network. This model consists of 14 input variables (sensor data, material properties, process information, meteorological conditions) and one output (release rate). The dispersion model then performs the simulation of the expected dispersion consequence by combining the sensor data, GIS data and the diagnostic result of the source term. The result of this study will improve the safety-concerns of residents living next to storage facilities containing hazardous materials by providing the enhanced emergency response plan and monitoring system for toxic gas releases.