• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.8
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• pp.113-118
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• 2016

In this paper, a read-in integrated circuit (RIIC) for IR scene projectors (IRSPs) adopting a sub-frame control technique is proposed, which minimizes the reduction of the apparent temperature of the IR images projected from IRSPs operating at a frame rate of 30 Hz. The proposed sub-frame control technique significantly reduces the amount of scene data loss on capacitors, which is caused by leakage currents flowing through MOSFET switches during holding periods, by dividing a unit frame into 8 sub-frames and refreshing the same scene data for each sub-frame. A current-drive RIIC was designed for the higher apparent temperature of IR radiated from the emitter, and it receives the scene data as a form of analog voltages from an external DAC. A prototype chip with a $64{\times}32$ RIIC array was fabricated using Magnachip/SKhynix $0.35{\mu}m$ 2-poly 4-metal CMOS process, and the measured maximum output data current is $230.3{\mu}A$. This amount of current ensures the projection of IR images whose maximum apparent temperature is $366.2^{\circ}C$ in the mid-wavelength IR (MWIR) when applied to a prototype emitter having a resistance of $15k{\Omega}$.

• Structural Engineering and Mechanics
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• v.63 no.4
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• pp.429-438
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• 2017

Structural design has an imperative role in deciding the failure possibility of a Reinforced Concrete (RC) structure. Recent research works achieved the goal of predicting the structural failure of the RC structure with the assistance of machine learning techniques. Previously, the Artificial Neural Network (ANN) has been trained supported by Particle Swarm Optimization (PSO) to classify RC structures with reasonable accuracy. Though, keeping in mind the sensitivity in predicting the structural failure, more accurate models are still absent in the context of Machine Learning. Since the efficiency of multi-objective optimization over single objective optimization techniques is well established. Thus, the motivation of the current work is to employ a Multi-objective Genetic Algorithm (MOGA) to train the Neural Network (NN) based model. In the present work, the NN has been trained with MOGA to minimize the Root Mean Squared Error (RMSE) and Maximum Error (ME) toward optimizing the weight vector of the NN. The model has been tested by using a dataset consisting of 150 RC structure buildings. The proposed NN-MOGA based model has been compared with Multi-layer perceptron-feed-forward network (MLP-FFN) and NN-PSO based models in terms of several performance metrics. Experimental results suggested that the NN-MOGA has outperformed other existing well known classifiers with a reasonable improvement over them. Meanwhile, the proposed NN-MOGA achieved the superior accuracy of 93.33% and F-measure of 94.44%, which is superior to the other classifiers in the present study.

• JSTS:Journal of Semiconductor Technology and Science
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• v.14 no.1
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• pp.83-91
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• 2014

This paper presents a capacitive readout circuit for tri-axes microaccelerometer with sub-fF offset calibration capability. A charge sensitive amplifier (CSA) with correlated double sampling (CDS) and digital to equivalent capacitance converter (DECC) is proposed. The DECC is implemented using 10-bit DAC, charge transfer switches, and a charge-storing capacitor. The DECC circuit can realize the equivalent capacitance of sub-fF range with a smaller area and higher accuracy than previous offset cancelling circuit using series-connected capacitor arrays. The readout circuit and MEMS sensing element are integrated in a single package. The supply voltage and the current consumption of analog blocks are 3.3 V and $230{\mu}A$, respectively. The sensitivities of tri-axes are measured to be 3.87 mg/LSB, 3.87 mg/LSB and 3.90 mg/LSB, respectively. The offset calibration which is controlled by 10-bit DECC has a resolution of 12.4 LSB per step with high linearity. The noise levels of tri-axes are $349{\mu}g$/${\sqrt}$Hz, $341{\mu}g$/${\sqrt}$Hz and $411{\mu}g$/${\sqrt}$Hz, respectively.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.4
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• pp.691-698
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• 2008

This paper describes a 3.3V 10 bit CMOS digital-to-analog converter with a divided architecture of a 7 MSB and a 3 LSB, which uses an optimal Thermal-to-Binary Decoding method with monotonicity, glitch energy. The output stage utilizes here implements a return-to-zero circuit to obtain the dynamic performance. Most of D/A converters in decoding circuit is complicated, occupies a large chip area. For these problems, this paper describes a D/A converter using an optimal Thermal-to-Binary Decoding method. the designed D/A converter using the CMOS n-well $0.35{\mu}m$ process0. The experimental data shows that the rise/fall time, settling time, and INL/DNL are 1.90ns/2.0ns, 12.79ns, and a less than ${\pm}2.5/{\pm}0.7\;LSB$, respectively. The power dissipation of the D/A converter with a single power supply of 3.3V is about 250mW.

• The Transactions of the Korean Institute of Power Electronics
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• v.26 no.3
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• pp.192-198
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• 2021

The battery's State of Health (SOH) is a critical parameter in the process of battery use, as it represents the Remaining Useful Life (RUL) of the battery. Electrochemical Impedance Spectroscopy (EIS) is a widely used technique in observing the state of the battery. The measured impedance at certain frequencies can be used to evaluate the state of the battery, as it is intimately tied to the underlying chemical reactions. In this work, a low-cost portable EIS instrument is developed on the basis of the ARM Cortex-M4 Microcontroller Unit (MCU) for measuring the impedance spectrum of Li-ion battery packs. The MCU uses a built-in DAC module to generate the sinusoidal sweep perturbation signal. Moreover, it performs the dual-channel acquisition of voltage and current signals, calculates impedance using a Digital Lock-in Amplifier (DLA), and transmits the result to a PC. By using LabVIEW, an interface was developed with the real-time display of the EIS information. The developed instrument was suitable for measuring the impedance spectrum of the battery pack up to 1000 V. The measurement frequency range of the instrument was from 1 hz to 1 Khz. Then, to prove the performance of the developed system, the impedance of a Samsung SM3 battery pack and a Bexel pouch module were measured and compared with those obtained by the commercial instrument.

• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.19 no.4
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• pp.459-467
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• 2021

In the majority of countries, the upper limit of buffer temperature in a repository is set to below 100℃ due to the possible illitization. This smectite-to-illite transformation is expected to be detrimental to the swelling functions of the buffer. However, if the upper limit is increased while preventing illitization, the disposal density and cost-effectiveness for the repository will dramatically increase. Thus, understanding the characteristics and creating a database related to the buffer under the elevated temperature conditions is crucial. In this study, a strategy to investigate the bentonite found in Korea under the elevated temperatures from a mineral transformation and radionuclides retardation perspective was proposed. Certain long-term hydrothermal reactions generated the bentonite samples that were utilized for the investigation of their mineral transformation and radionuclide retardation characteristics. The bentonite samples are expected to be studied using in-situ synchrotron-based X-Ray Diffraction (XRD) technique to determine the smectite-to-illite transformation. Simultaneously, the 'high-temperature and high-pressure mineral alteration measurement system' based on the Diamond Anvil Cell (DAC) will control and provide the elevated temperature and pressure conditions during the measurements. The kinetic models, including the Huang and Cuadros model, are expected to predict the time and manner in which the illitization will become detrimental to the performance and safety of the repository. The sorption reactions planned for the bentonite samples to evaluate the effects on retardation will provide the information required to expand the current knowledge of repository optimization.

• Korean Journal of Environment and Ecology
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• v.33 no.5
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• pp.539-551
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• 2019

The purpose of this study is to understand the vegetation structure and ecological characteristics of the coastal forest Pinus thunbergii community in Busan Metropolitan City (BMC) and to establish reference information for the management of the coastal forest in BMC in the future. We set up 97 plots with an area of $100m^2$ each for the analysis and investigation of the vegetation characteristics. The analysis using the TWINSPAN and DCA techniques found seven community groups: Pinus thunbergii-Quercus aliena community, Pinus thunbergii-Eurya japonica(1) community, Pinus thunbergii-Eurya japonica(2) community, Pinus thunbergii-Quercus serrata community, Pinus thunbergii-Camellia japonica(1) community, Pinus thunbergii-Camellia japonica(2) community, and Pinus thunbergii-Eurya japonica-Camellia japonica community. According to the analysis of vegetation structure, Pinus thunbergii was a main dominant species at the canopy layer in all sites while Eurya japonica and Camellia japonica were dominant species at the understory layer. Pinus thunbergii-Quercus serrata community is predicted in the forest succession because of the competition between Pinus thunbergii and Quercus serrata in the canopy layer and the understory layer. As such, it is necessary to observe changes by continually monitoring this community. Tree species with strong salinity tolerance, including Pinus thunbergii, have formed community groups because of the environmental characteristics of coastal forests, strong with salinity tolerance species are forming community groups. Therefore, all community groups except for the Pinus thunbergii-Quercus serrata community will maintain the current vegetation structure unless drastic environmental changes occur.