• Journal of the Optical Society of Korea
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• v.10 no.1
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• pp.1-10
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• 2006

Optical transparency and high diffraction efficiency are two essential factors for high performance of the photopolymer. Optical transparency mainly depends on the miscibility between polymer binder and photopolymerized polymer, while diffraction efficiency depends on the refractive index modulation between polymer binder and photopolymerized polymer. For most of organic materials, the large refractive index difference between two polymers accompanies large structural difference that leads to the poor miscibility and thus poor optical quality via light scattering. Therefore, it is difficult to design a high-performance photopolymer satisfying both requirements. In this work, first, we prepared a new phase-stable photopolymer (PMMA) with large refractive index modulation and investigated the optical properties. Our photopolymer is based on modified poly (methyl methacrylate) as a polymer binder, acryl amide as a photopolymerizable monomer, triethanolamine as initiator, and yellow eosin as a photosensitizer at 532 nm. Diffraction efficiency over 85% and optical transmittance over 90% were obtained for the photopolymer. Second, Organic-inorganic nanocomposite films were prepared by dispersing an aromatic methacrylic monomer and a photo- initiator in organic-inorganic hybrid sol-gel matrices. The film properties could be controlled by optimizing the content of an organically modified silica precursor (TSPEG) in the sol-gel matrices. The photopolymer film modified with the organic chain (TSPEG) showed high diffraction efficiency (> 90%) under an optimized condition. High diffraction efficiency could be ascribed to the fast diffusion and efficient polymerization of monomers under interference light to generate refractive index modulation. The TSPEG modified photopolymer film could be successfully used for holographic memory.

• Applied Science and Convergence Technology
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• v.23 no.2
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• pp.72-82
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• 2014

Lithium-ion batteries (LIBs) have become popular electrochemical devices. Due to the unique advantages of LIBs in terms of high operating voltage, high energy density, low self-discharge, and absence of memory effects, their application range, which was primarily restricted to portable electronic devices, is now being extended to high-power applications, such as electric vehicles (EVs) and hybrid electrical vehicles (HEVs). Among various anode materials, $Li_4Ti_5O_{12}$ (LTO) is believed to be a promising anode material for high-power LIBs due to its advantages of high working potential and outstanding cyclic stability. However, the rate performance of LTO is limited by its intrinsically low electronic conductivity and poor $Li^+$ ion diffusion coefficient. This review highlights the recent progress in improving the rate performance of LTO through doping, compositing, and nanostructuring strategies.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.16 no.4
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• pp.139-146
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• 2006

A Signcryption proposed by Yuliang Zheng in 1997 is a hybrid public key primitive that combines a digital signature and a encryption. It provides more efficient method than a straightforward composition of an signature scheme with a encryption scheme. In a mobile communication environment, the authenticated key agreement protocol should be designed to have lower computational complexity and memory requirements. The password-based authenticated key exchange protocol is to authenticate a client and a server using an easily memorable password. This paper proposes an secure Authenticated Key Exchange protocol using Signcryption scheme. In Addition we also show that it is secure and a more efficient that other exiting authenticated key exchange protocol.

• Asia pacific journal of information systems
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• v.30 no.4
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• pp.719-740
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• 2020

The stock market changes continuously as new information emerges, affecting the judgments of investors. Online news articles are valued as a traditional window to inform investors about various information that affects the stock market. This paper proposed new ways to utilize online news articles with technical indicators. The suggested hybrid model consists of three models. First, a self-attention-based convolutional neural network (CNN) model, considered to be better in interpreting the semantics of long texts, uses news content as inputs. Second, a self-attention-based, bi-long short-term memory (bi-LSTM) neural network model for short texts utilizes news titles as inputs. Third, a bi-LSTM model, considered to be better in analyzing context information and time-series models, uses 19 technical indicators as inputs. We used news articles from the previous day and technical indicators from the past seven days to predict the share price of the next day. An experiment was performed with Korean stock market data and news articles from 33 top companies over three years. Through this experiment, our proposed model showed better performance than previous approaches, which have mainly focused on news titles. This paper demonstrated that news titles and content should be treated in different ways for superior stock price prediction.

• Journal of Life Science
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• v.19 no.8
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• pp.1055-1061
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• 2009

${\alpha}$-amino-3-hydroxy-5-methyl-4-isoxazole propionate (AMPA) receptors are widespread throughout the central nervous system and appear to serve as synaptic receptors for fast excitatory synaptic transmission mediated by glutamate. Their modulation is believed to affect learning and memory. To identify the interaction proteins for the AMPA receptor subunit glutamate receptor-interacting protein 1 (GRIPl), GRIP1 interactions with armadillo family protein p0071/plakophilin-4 were investigated. GRIP1 protein bound to the tail region of p0071/plakophilin-4 but not to other armadillo family protein members in a yeast two-hybrid assay. The "S-X-V" motif at the carboxyl (C)-terminal end of p0071/plakophilin-4 is essential for interaction with GRIP1. p0071/plakophilin-4 interacted with the Postsynaptic density-95/Discs large/Zona occludens-1 (PDZ) domains of GRIPI in the yeast two-hybrid assay, as is indicated also by Glutathione S-transferase (GST) pull-down, and co-immunoprecipitated with GRIP1 antibody in brain fraction. The findings of this study provide evidence that p0071/plakophilin-4 is an interactor of GRIP1.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2003.08a
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• pp.98-102
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• 2003

$Ba_2NaNb_5O_{15}$, hereafter BNN, thin films are attractive candidates for nonvolatile memory and electro-optic devices. In the present work, thin films that have different contents of Ba, Na and Nb have been prepared by H-MOD technique on silicon and Pt substrates. XRD and SEM were used to investigate the phase evolution behavior and the microstructure of the films. It was found that the films of about 450nm thick were crack-free and uniform in microstructure. Nb content strongly influenced the phase formation of the films, where low temperature phase was always formed at the stoichiometric BNN composition. However, the amount of low temperature phase decreased with the increase of excess Nb content, and the single phase (orthorhombic tungsten bronze structure) BNN thin film was obtained at the temperature as low as $750^{\circ}C$ for samples with excess niobium. From this study, the sub-solidus phase diagram below $850^{\circ}C$ for $BaO-Na_2O-Nb_2O_5$ ternary system is proposed.

• Journal of Internet Computing and Services
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• v.22 no.3
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• pp.9-16
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• 2021

This study aims to develop a human activity recognition (HAR) system as a Deep-Learning (DL) classification model, distinguishing various human activities. We solely rely on the signals from a wristband accelerometer worn by a person for the user's convenience. 3-axis sequential acceleration signal data are gathered within a predefined time-window-slice, and they are used as input to the classification system. We are particularly interested in developing a Deep-Learning model that can outperform conventional machine learning classification performance. A total of 13 activities based on the laboratory experiments' data are used for the initial performance comparison. We have improved classification performance using the Convolutional Neural Network (CNN) combined with an auto-encoder feature reduction and parameter tuning. With various publically available HAR datasets, we could also achieve significant improvement in HAR classification. Our CNN model is also compared against Recurrent-Neural-Network(RNN) with Long Short-Term Memory(LSTM) to demonstrate its superiority. Noticeably, our model could distinguish both general activities and near-identical activities such as sitting down on the chair and floor, with almost perfect classification accuracy.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.9
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• pp.1747-1754
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• 2016

This paper presents a high accuracy and fast hybrid on-chip temperature sensor. The proposed temperature sensor combines a SAR type temperature sensor with a ${\Sigma}{\Delta}$ type temperature sensor. The SAR type temperature sensor has fast temperature searching time but it has more error than the ${\Sigma}{\Delta}$ type temperature sensor. The ${\Sigma}{\Delta}$ type temperature sensor is accurate but it is slower than the SAR type temperature sensor. The proposed temperature sensor uses both the SAR and ${\Sigma}{\Delta}$ type temperature sensors, so that the proposed temperature sensor has high accuracy and fast temperature searching. Also, the proposed temperature sensor includes a temperature error compensating circuit by storing the temperature errors in a memory circuit after chip fabrication. The proposed temperature sensor was fabricated in 3.3V CMOS $0.35{\mu}m$ process. Its temperature resolution, power consumption, and area are $0.15^{\circ}C$, $540{\mu}W$, and $1.2mm^2$, respectively.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.2
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• pp.723-743
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• 2016

Indoor positioning is considered an enabler for a variety of applications, the demand for an indoor positioning service has also been accelerated. That is because that people spend most of their time indoor environment. Meanwhile, the smartphone integrated powerful camera is an efficient platform for navigation and positioning. However, for high accuracy indoor positioning by using a smartphone, there are two constraints that includes: (1) limited computational and memory resources of smartphone; (2) users' moving in large buildings. To address those issues, this paper uses the TC-OFDM for calculating the coarse positioning information includes horizontal and altitude information for assisting smartphone camera-based positioning. Moreover, a unified representation model of image features under variety of scenarios whose name is FAST-SURF is established for computing the fine location. Finally, an optimization marginalized particle filter is proposed for fusing the positioning information from TC-OFDM and images. The experimental result shows that the wide location detection accuracy is 0.823 m (1σ) at horizontal and 0.5 m at vertical. Comparing to the WiFi-based and ibeacon-based positioning methods, our method is powerful while being easy to be deployed and optimized.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.10a
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• pp.401-404
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• 2015

This paper proposes a high-performance in-loop filter in HEVC(High Efficiency Video Coding) encoder for Ultra HD video processing in real time. HEVC uses in-loop filter consisting of deblocking filter and SAO(Sample Adaptive Offset) to solve the problems of quantization error which causes image degradation. In the proposed in-loop filter encoder hardware architecture, the deblocking filter and SAO has a 2-level hybrid pipeline structure based on the $32{\times}32CTU$ to reduce the execution time. The deblocking filter is performed by 6-stage pipeline structure, and it supports minimization of memory access and simplification of reference memory structure using proposed efficient filtering order. Also The SAO is implemented by 2-statge pipeline for pixel classification and applying SAO parameters and it uses two three-layered parallel buffers to simplify pixel processing and reduce operation cycle. The proposed in-loop filter encoder architecture is designed by Verilog HDL, and implemented by 205K logic gates in TSMC 0.13um process. At 110MHz, the proposed in-loop filter encoder can support 4K Ultra HD video encoding at 30fps in realtime.