• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2003.07a
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• pp.212-215
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• 2003

In this paper, a model pole transformer was designed to improve the reliability of pole transformers and its short circuit withstand strength was tested. The failure causes of the pole transformers which had been operated in the field were analyzed and several patterns of the causes were determined. A novel countermeasure was devised to prevent the failures of the pole transformers in advance. A model pole transformer was designed and made in accordance with the given specifications to strengthen the short circuit withstand capability and its characteristic was tested. As a result, the advanced performance of the model pole transformer was confirmed and novel techniques in manufacturing process was suggested. It is considered that all the methods employed in the developing process will be helpful to design and manufacture the pole transformers thus the reliability of pole transformers in distribution lines will be improved.

• Proceedings of the Korean Vacuum Society Conference
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• 2012.02a
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• pp.557-557
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• 2012

Silicatein-${\alpha}$, the enzyme extracted from silica spicules in glass sponges, has been studied extensively in the way of chemistry from 1999, in which the pioneering work by Morse, D. E. - the discovery of the enzymatic hydrolysis in Silicatein-${\alpha}$ - was published. Since its reaction conditions are physiologically favored, synthesis of various materials, such as gallium oxide, zirconium oxide, and silicon oxide, was achieved without any hazardous wastes. Although some groups synthesized oxide films and particles, they have not achieved yet controlled morphogenesis in the reaction conditions mentioned above. With the knowledge of catalytic triad involved in hydrolysis of silicone alkoxide and oligomerization of silicic acid, we designed the novel peptide amphiphiles to not only form self-assembled structure, but also display similar activities to silicatein-${\alpha}$. Designed templates were able to self-assemble into left-handed helices for the peptide amphiphiles with L-form amino acid, catalyzing polycondensation of silicic acids onto the surface of them. It led to the formation of silica helices with 30-50 nm diameters. These results were characterized by various techniques, including SEM, TEM, and STEM. Given the situation that nano-bio-technology, the bio-applicable technology in nanometer scale, has been attracting considerable attention; this result could be applied to the latest applications in biotechnology, such as biosensors, lab-on-a-chip, biocompatible nanodevices.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.8
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• pp.3820-3841
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• 2018

Most of the accidents occur due to drowsiness while driving, avoiding road signs and due to driver's distraction. Driver's distraction depends on various factors which include talking with passengers while driving, mood disorder, nervousness, anger, over-excitement, anxiety, loud music, illness, fatigue and different driver's head rotations due to change in yaw, pitch and roll angle. The contribution of this paper is two-fold. Firstly, a data set is generated for conducting different experiments on driver's distraction. Secondly, novel approaches are presented that use features based on facial points; especially the features computed using motion vectors and interpolation to detect a special type of driver's distraction, i.e., driver's head rotation due to change in yaw angle. These facial points are detected by Active Shape Model (ASM) and Boosted Regression with Markov Networks (BoRMaN). Various types of classifiers are trained and tested on different frames to decide about a driver's distraction. These approaches are also scale invariant. The results show that the approach that uses the novel ideas of motion vectors and interpolation outperforms other approaches in detection of driver's head rotation. We are able to achieve a percentage accuracy of 98.45 using Neural Network.

• Proceedings of the KIPE Conference
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• 2019.11a
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• pp.70-72
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• 2019

For the safe and reliable operation of Lithium-ion batteries in Electric Vehicles (EVs) or Energy Storage Systems (ESSs), it is essential to have accurate information of the battery such as State of Charge (SOC). Many kinds of different techniques to estimate the SOC of the batteries have been developed so far such as the Kalman Filter. However, when it is applied to the multiple number of batteries it is difficult to maintain the accuracy of the estimation over all cells due to the difference in parameter value of each cell. Moreover the difference in the parameter of each cell may become larger as the operation time accumulates due to aging. In this paper a novel Deep Neural Network (DNN) based SOC estimation method for multi cell application is proposed. In the proposed method DNN is implemented to learn non-linear relationship of the voltage and current of the lithium-ion battery at different SOCs and different temperatures. In the training the voltage and current data of the Lithium battery at charge and discharge cycles obtained at different temperatures are used. After the comprehensive training with the data obtained with a cell resulting estimation algorithm is applied to the other cells. The experimental results show that the Mean Absolute Error (MAE) of the estimation is 0.56% at 25℃, and 3.16% at 60℃ with the proposed SOC estimation algorithm.

• Bulletin of the Korean Chemical Society
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• v.34 no.1
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• pp.143-148
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• 2013

Novel titanium containing solid core mesoporous shell silica has been synthesized by using octadecyltrichloro silane and triethylamine. The synthesized material was characterized by various physicochemical techniques. The mesoporous character of the material has been revealed from PXRD studies. The presence of octadecyltrichloro silane and triethylamine in the sample has been confirmed from EDAX studies. TG/DTA analysis reveals the thermal characteristics of the synthesized material. The presence of titanium in the frame work and its coordination state has been studies by UV-vis DR studies and XPS analysis. Chemical environment of Si in the framework of the material has been studied by $^{29}SiMASNMR$ studies. The surface area of the material is found to be around $550\;m^2g^{-1}$ and pore radius is of nano range from BET analysis. The spherical morphology and particle size of the core as well as shell has been found to be 300 nm and 50 nm respectively from TEM analysis. The catalytic application of this material towards the synthesis of caprolactam from cyclohexanone in presence of hydrogen peroxide through ammoxidation reaction has been investigated. The optimum conditions for the reaction have been established. The plausible mechanism for the formation of core silica and conversion of cyclohexanone has been proposed.

• Journal of Communications and Networks
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• v.18 no.1
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• pp.123-131
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• 2016

The high-availability seamless redundancy (HSR) protocol is one of the most important redundancy IEC standards that has garnered a great deal of attention because it offers a redundancy with zero recovery time, which is a feature that is required by most of the modern substation, smart grid, and industrial field applications. However, the HSR protocol consumes a lot of network bandwidth compared to the Ethernet standard. This is due to the duplication process for every sent frame in the HSR networks. In this paper, a novel algorithm known as the reducing multicast traffic (RMT) is presented to reduce the unnecessary redundant multicast traffic in HSR networks by limiting the spreading of the multicast traffic to only the rings that have members associated with that traffic instead of spreading the traffic into all the network parts, as occurs in the standard HSR protocol. The mathematical and the simulation analyses show that the RMT algorithm offers a traffic reduction percentage with a range of about 60-87% compared to the standard HSR protocol. Consequently, the RMT algorithm will increase the network performance by freeing more bandwidth so as to reduce HSR network congestion and also to minimize any intervention from the network administrator that would be required when using traditional traffic filtering techniques.

• The Transactions of the Korean Institute of Power Electronics
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• v.10 no.4
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• pp.331-338
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• 2005

In this paper the novel pulsewidth modulation(PWM) technique for the two-leg and four-leg two-phase inverter is proposed. The conventional space vector PWM technique for two-phase inverter was complex. The proposed PWM for two-leg inverter, which is used by sinusoidal PWM method, is simpler than the conventional SVPWU technique. Also, a simple PWM technique for four-leg two-phase inverter is proposed. Such PWM technique is based on PWM technique for two-leg inverter. Practical verification of theoretical predictions is presented to confirm the capabilities of the new techniques.

• Journal of Power Electronics
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• v.10 no.2
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• pp.132-137
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• 2010

Interleaving techniques are widely used to reduce input/output ripples and to increase the power capacity of boost converters operating in critical conduction mode. Two types of phase-shift control schemes are studied in this paper, the turn-on time shifting method and the turn-off time shifting method. It is found that although the turn-off time shifting method exhibits better performance, it suffers from sub-harmonic oscillations at high input voltages. To solve this problem, an intensive quantitative analysis of the sub-harmonic oscillation phenomenon is made in this paper. Based upon that, a novel modified turn off time shifting control scheme for interleaved boost converters operating in critical conduction mode is proposed. An important advantage of this scheme is that both the master phase and the slave phase can operate stably in critical conduction mode without any oscillations in the full input voltage range. This method is implemented with a FPGA based digital PWM control platform, and tests were carried out on a two-phase interleaved boost PFC converter prototype. Experimental results demonstrated the feasibility and performance of the proposed phase-shift control scheme.

• Journal of Information Science Theory and Practice
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• v.2 no.1
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• pp.6-21
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• 2014

This paper proposes a novel knowledge extraction system, TAKES (Two-step Approach for Knowledge Extraction System), which integrates advanced techniques from Information Retrieval (IR), Information Extraction (IE), and Natural Language Processing (NLP). In particular, TAKES adopts a novel keyphrase extraction-based query expansion technique to collect promising documents. It also uses a Conditional Random Field-based machine learning technique to extract important biological entities and relations. TAKES is applied to biological knowledge extraction, particularly retrieving promising documents that contain Protein-Protein Interaction (PPI) and extracting PPI pairs. TAKES consists of two major components: DocSpotter, which is used to query and retrieve promising documents for extraction, and a Conditional Random Field (CRF)-based entity extraction component known as FCRF. The present paper investigated research problems addressing the issues with a knowledge extraction system and conducted a series of experiments to test our hypotheses. The findings from the experiments are as follows: First, the author verified, using three different test collections to measure the performance of our query expansion technique, that DocSpotter is robust and highly accurate when compared to Okapi BM25 and SLIPPER. Second, the author verified that our relation extraction algorithm, FCRF, is highly accurate in terms of F-Measure compared to four other competitive extraction algorithms: Support Vector Machine, Maximum Entropy, Single POS HMM, and Rapier.

• Pediatric Gastroenterology, Hepatology & Nutrition
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• v.22 no.6
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• pp.581-587
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• 2019

Arthrogryposis-renal dysfunction-cholestasis (ARC) syndrome is a rare autosomal recessive multisystemic disease that is associated with the liver, kidney, skin, and central nervous and musculoskeletal systems. ARC occurs as a result of mutations in the VPS33B (Vacuolar protein sorting 33 homolog B) or VIPAR (VPS33B interacting protein, apical-basolateral polarity regulator) genes. A female infant presented with neonatal cholestasis with a severe clinical outcome. She was diagnosed with ARC syndrome using targeted exome sequencing (TES). Exome sequencing revealed compound heterozygous mutations, c.707A>T and c.239+5G>A, in VPS33B, where c.707A>T was a novel variant; the resultant functional protein defects were predicted via in silico analysis. c.239+5G>A, a pathogenic mutation that affects splicing, is found in less than 0.1% of the general population. Invasive techniques, such as liver biopsies, did not contribute to a differential diagnosis of ARC syndrome; thus, early TES together with clinical presentations constituted an apparently accurate diagnostic procedure.