• Proceedings of the KIPE Conference
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• 2016.11a
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• pp.13-14
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• 2016

This paper has introduces a novel Integrated On-board Charger (IOBC) to reduce the size, weight and cost of power conversion stages in Electric Vehicles (EVs). The IOBC is composed of an OBC and a low voltage dc-dc converter (LDC). The IOBC includes a bidirectional ac-dc converter and a bidirectional full-bridge converter with an active clamp circuit. The LDC converter is a hybrid topology combining an active clamped full-bridge converter and a forward converter derived from the Weinburg converter topology. Unlike conventional OBC, the proposed IOBC is compact and the LDC converter of it can achieve a higher efficiency. In addition, the LDC converter of the proposed IOBC can achieve high step-down voltage conversion ratio, no circulating current, no reverse recovery current of the rectifier diodes and small ripple current of output inductor on the auxiliary battery. A 1kW hardware of the LDC converter is implemented to verify the performances of the proposed IOBC.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.47 no.3
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• pp.240-244
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• 2019

SOQPSK-TG which consists of differential precoder and CPM modulator was adopted as telemetry standard because of its high power and bandwidth efficiency. We proposed four-state Viterbi decoder for SOQPSK-TG. Reducing the trellis state to four was possible by simplifying frequency pulse of SOQPSK-TG to square pulse of symbol length 2 and combing this with differential precoder. Compared with conventional SOQPSK-TG receivers, computer simulation result shows about 1 dB performance improvement was achieved at BER of $10^{-5}$ in AWGN channel.

• Journal of Korea Multimedia Society
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• v.24 no.5
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• pp.701-708
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• 2021

As one of the most widely used technology in the world right now, Face recognition has already received widespread attention by all the researcher and institutes. It has been used in many fields such as safety protection, surveillance system, crime control and even in our ordinary life such as home security and so on. This technology with today's technology has advantages such as high connectivity and real time transformation. But we still need to improve its recognition rate, reaction time and also reduce impact of different environmental status to the whole system. So in this paper we proposed a face recognition system model with improved CNN which combining the characteristics of flat network and residual network, integrated learning, simplify network structure and enhance portability and also improve the recognition accuracy. We also used AR and ORL database to do the experiment and result shows higher recognition rate, efficiency and robustness for different image conditions.

• Food Science and Industry
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• v.55 no.1
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• pp.74-94
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• 2022

With the discovery of metabolic mechanisms of alcohol fermentation and acetic acid fermentation in the 1800s and 1900s, the history of traditional vinegar became a turning point for changing to the history of science and technology. Since then, innovation in vinegar production has occurred, and the era of full-scale mass industrialization has opened. The most modern method, submerged fermentation, has improved the vinegar production process to produce much higher quality vinegar and provide vinegar with high productivity and quality uniformity. Innovative research for vinegar production is underway as various approaches have been developed to increase fermentation efficiency, reduce costs, and shorten fermentation time due to the trend of combining existing technologies and advanced technologies. Now that the development of the vinegar industry is currently focused on vinegar engineering, multidisciplinary approaches in various fields such as microbiology, chemistry, food technology, process engineering, and molecular biology are needed.

• Earthquakes and Structures
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• v.25 no.1
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• pp.15-26
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• 2023

It is of great importance to assess the residual displacement demand in the performance-based seismic design. In this paper, a hybrid deep learning model for predicting the residual displacement spectra under near-fault (NF) ground motions is proposed by combining the long short-term memory network (LSTM) and back-propagation (BP) network. The model is featured by its capacity of predicting the residual displacement spectrum under a given NF ground motion while considering the effects of structural parameters. To construct this model, 315 natural and artificial NF ground motions were employed to compute the residual displacement spectra through elastoplastic time history analysis considering different structural parameters. Based on the resulted dataset with a total of 9,450 samples, the proposed model was finally trained and tested. The results show that the proposed model has a satisfactory accuracy as well as a high efficiency in predicting residual displacement spectra under given NF ground motions while considering the impacts of structural parameters.

• Journal of Korea Artificial Intelligence Association
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• v.1 no.2
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• pp.21-25
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• 2023

The purpose of this study was to compare the performance using multiple regression models to predict the energy consumption of steel industry. Specific independent variables were selected in consideration of correlation among various attributes such as CO2 concentration, NSM, Week Status, Day of week, and Load Type, and preprocessing was performed to solve the multicollinearity problem. In data preprocessing, we evaluated linear and nonlinear relationships between each attribute through correlation analysis. In particular, we decided to select variables with high correlation and include appropriate variables in the final model to prevent multicollinearity problems. Among the many regression models learned, Boosted Decision Tree Regression showed the best predictive performance. Ensemble learning in this model was able to effectively learn complex patterns while preventing overfitting by combining multiple decision trees. Consequently, these predictive models are expected to provide important information for improving energy efficiency and management decision-making at steel industry. In the future, we plan to improve the performance of the model by collecting more data and extending variables, and the application of the model considering interactions with external factors will also be considered.

• Journal of the Korean institute of surface engineering
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• v.34 no.5
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• pp.403-408
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• 2001

In this work, the cyclic perfluorinated ether (c-C$_4$F$_{8}$O) with very high destructive removal efficiency (DRE) than other alternative gases, such as $C_3$F$_{8}$, c-C$_4$F$_{8}$ and NF$_3$ was used as an alternative process chemical. The plasma cleaning of silicon nitride using gas mixtures of c-C$_4$F$_{8}$O/O$_2$ and c-C$_4$F$_{8}$O/O$_2$+ $N_2$ was investigated in order to evaluate the effects of adding $N_2$ to c-C$_4$F$_{8}$O/O$_2$ on the global warming effects. Under optimum condition, the emitted net perfluorocompounds (PFCs) during cleaning of silicon nitride were quantified and then the effects of additive $N_2$ by obtaining the destructive removal efficiency (DRE) and the million metric tons of carbon equivalent (MMT-CE) were calculated. DRE and MMTCE were obtained by evaluating the volumetric emission using. Fourier transform-infrared spectroscopy (FT-IR). During the cleaning using c-C$_4$F$_{8}$O/O$_2$+$N_2$, DRE values as high as (equation omitted) 98% were obtained and MMTCE values were reduced by as high as 70% compared to the case of $C_2$F$_{6}$O$_2$. Recombination characteristics were indirectly investigated by combining the measurements of species in the chamber using optical emission spectroscopy (OES), before and after the cleaning, in order to understand any correlation between plasma and emission characteristics as well as cleaning rate of silicon nitride.silicon nitride.

• Journal of Microbiology and Biotechnology
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• v.27 no.3
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• pp.471-479
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• 2017

White spot syndrome virus (WSSV) is a major threat to the shrimp farming industry and so far there is no effective therapy for it, and thus early diagnostic of WSSV is of great importance. However, at the early stage of infection, the extremely low-abundance of WSSV DNA challenges the detection sensitivity and accuracy of PCR. To effectively detect low-abundance WSSV, here we developed a pre-amplification PCR (pre-amp PCR) method to amplify trace amounts of WSSV DNA from massive background genomic DNA. Combining with normal specific PCR, 10 copies of target WSSV genes were detected from ${\sim}10^{10}$ magnitude of backgrounds. In particular, multiple target genes were able to be balanced amplified with similar efficiency due to the usage of the universal primer. The efficiency of the pre-amp PCR was validated by nested-PCR and quantitative PCR, and pre-amp PCR showed higher efficiency than nested-PCR when multiple targets were detected. The developed method is particularly suitable for the super early diagnosis of WSSV, and has potential to be applied in other low-abundance sample detection cases.

• Journal of Electrical Engineering and Technology
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• v.13 no.1
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• pp.143-151
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• 2018

In this paper, a novel hybrid configuration combining a phase-shift full-bridge (PSFB) and a half-bridge resonant LLC converter is proposed for the On-Board Charger of Electric Vehicles (EVs). In the proposed converter, the PSFB converter shares the lagging-leg switches with half-bridge resonant converter to achieve the wide ZVS range for the switches and to improve the efficiency. The output voltage is modulated by the effective-duty-cycle of the PSFB converter. The proposed converter employs an active reset circuit composed of an active switch and a diode for the transformer which makes it possible to achieve zero circulating current and the soft switching characteristic of the primary switches and rectifier diodes regardless of the load, thereby making the converter highly efficient and eliminating the reverse recovery problem of the diodes. In addition an optimal power sharing strategy is proposed to meet the specification of the charger and to optimize the efficiency of the converter. The operation principle the proposed converter and design considerations for high efficiency are presented. A 6.6 kW prototype converter is fabricated and tested to evaluate its performance at different conditions. The peak efficiency achieved with the proposed converter is 97.7%.

• Journal of Microbiology and Biotechnology
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• v.29 no.1
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• pp.127-140
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• 2019

Since 1990, many nucleic acid expression platforms consisting of DNA or RNA have been developed. However, although RNA expression platforms have been relatively neglected, several such platforms capped at the 5' end of RNA by an anti-reverse cap analog have now been developed. At the same time, the capping reaction is a bottleneck in the production of such platforms, with high cost and low efficiency. Here, we investigated several viral and eukaryotic internal ribosome entry sites (IRESs) to develop an optimal RNA expression platform, because IRES-dependent translation does not require a capping step. RNA expression platforms constructed with IRESs from the 5' untranslated regions of the encephalomyocarditis virus (EMCV) and the intergenic region of the cricket paralysis virus (CrPV) showed sufficient expression efficiency compared with cap-dependent RNA expression platforms. However, eukaryotic IRESs exhibited a lower viral IRES expression efficiency. Interestingly, the addition of a poly(A) sequence to the 5' end of the coxsackievirus B3 (CVB3) IRES (pMA-CVB3) increased the expression level compared with the CVB3 IRES without poly(A) (pCVB3). Therefore, we developed two multiexpression platforms (termed pMA-CVB3-EMCV and pCrPV-EMCV) by combining the IRESs of CVB3, CrPV, and EMCV in a single-RNA backbone. The pMA-CVB3-EMCV-derived RNA platform showed the highest expression level. Moreover, it clearly exhibited expression in mouse muscles in vivo. These RNA expression platforms prepared using viral IRESs will be useful in developing potential RNA-based prophylactic or therapeutic vaccines, because they have better expression efficiency and do not need a capping step.