• MALSORI
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• no.53
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• pp.171-183
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• 2005

Call Control eXtensible Markup (CCXML) is a standard language that supports a call control of voice dialog systems such as VoiceXML based systems. CCXML allows developers to handle telephony calls in an easy way without deep knowledge about telephony networks and their switching systems.We design and implement a call control markup interpreter. At the implementation, we use a Dialogic JCT-LS board, but, by designing a wrapping class for CTI (computer telephony board) features, the interpreter can easily adopt other CTI boards. We also design and implement event-based interaction scheme between the interpreter and voice dialog systems. For verifying the interaction scheme, we implement a simple voice dialog system.

• International journal of advanced smart convergence
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• v.5 no.3
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• pp.1-7
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• 2016

In existing Convolutional Neural Network (CNNs) for object recognition task, there are only few efforts known to reduce the noises from the images. Both convolution and pooling layers perform the features extraction without considering the noises of the input image, treating all pixels equally important. In computer vision field, there has been a study to weight a pixel importance. Seam carving resizes an image by sacrificing the least important pixels, leaving only the most important ones. We propose a new way to combine seam carving approach with current existing CNN model for object recognition task. We attempt to remove the noises or the "unimportant" pixels in the image before doing convolution and pooling, in order to get better feature representatives. Our model shows promising result with CIFAR-10 dataset.

• Journal of the Korean Society for Precision Engineering
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• v.23 no.4 s.181
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• pp.162-167
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• 2006

Hot embossing lithography(HEL) has the production advantage of comparatively few process step, simple operation, a relatively low cost for embossing tools(Si), and high replication accuracy for small features. In this paper, we considered the nano-molding characteristic according to molding parameters(temperature, pressure, times, etc) and induced a optimal molding condition using HEL. High precision nano-patter master with various shapes were designed and manufactured using the DRIE(Deep Reactive ion Etching), LPCVD(Low Pressure Chemical Vapor Deposition) and thermal oxidation process, and we investigated the molding characteristic of DVD and Blu-ray nickel stamp. We induced flow behaviors of polymer, rheology by shapes and sizes of the pattern through various molding experiments. Finally, with achieving nano-structure molding with high aspect ratio, we will secure a basic technology about the molding of large-area nano-pattern media.

• Transactions of Materials Processing
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• v.21 no.6
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• pp.372-377
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• 2012

In this study, the plastic flow behaviors of extra deep drawing quality (EDDQ) steel subjected to non-proportional strain paths were investigated. Two-step uniaxial tension tests, in which the first step was performed in the rolling direction (RD) and the subsequent test in different directions in $15^{\circ}$ increments from the RD, were conducted. The experiments clearly showed that stress overshooting and strain hardening stagnation were the dominant features, which were captured reasonably well using a recently proposed distortional hardening model.

• The Bulletin of The Korean Astronomical Society
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• v.42 no.1
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• pp.30.1-30.1
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• 2017

In the hope to detect low-surface brightness features (${\mu}_{r^{\prime}}{\sim}27\;mag\;arcsec^{-2}$), we carried out KASI-Yonsei Deep Imaging Survey for Clusters (KYDISC) targeting 14 local clusters at 0.016 < z < 0.145 using Magellan/IMACS telescope and CFHT/MegaCam. Out of 1450 cluster galaxies, 18% of galaxies show the signatures of galaxy mergers. We explore merger-driven changes from various point-of-view. We first examine color-magnitude relations, and find that galaxies related to recent mergers are populated more on blue color than their counterparts. Besides, we find the extremely low frequency of mergers on low-mass red-sequence galaxies, suggesting a migration of red galaxies into the green-valley region through merger-driven star-formation. We also study the mass-size relation of our sample, finding a larger galaxy size in galaxies related to recent mergers. Our results suggest that mergers can simultaneously change properties of galaxies, making outliers on galactic scaling relations.

• The Bulletin of The Korean Astronomical Society
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• v.43 no.1
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• pp.39.2-39.2
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• 2018

GW170817/GRB170817A establishes a double neutron star merger as the progenitor of a short gamma-ray burst, starting 1.7 s post-coalescence. GRB170817A represents prompt or continuous emission from a newly formed hyper-massive neutron star or black hole. We report on a deep search for broadband extended gravitational-wave emission in spectrograms up to 700 Hz of LIGO O2 data covering this event produced by butterfly filtering comprising a bank of templates of 0.5 s. A detailed discussion is given of signal-to-noise ratios in image analysis of spectrograms and confidence levels of candidate features. This new pipeline is realized by heterogeneous computing with modern graphics processor units (GPUs). (Based on van Putten, M.H.PM., 2017, PTEP, 093F01.)

• JSTS:Journal of Semiconductor Technology and Science
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• v.15 no.2
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• pp.223-231
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• 2015

As smartphones support a variety of applications and their memory demand keeps increasing, the design of an efficient memory management policy is becoming increasingly important. Meanwhile, as nonvolatile memory (NVM) technologies such as PCM and STT-MRAM have emerged as new memory media of smartphones, characterizing memory references for NVM-based smartphone memory systems is needed. For the deep understanding of memory access features in smartphones, this paper performs comprehensive analysis of memory references for various smartphone applications. We first analyze the temporal locality and frequency of memory reference behaviors to quantify the effects of the two properties with respect to the re-reference likelihood of pages. We also analyze the skewed popularity of memory references and model it as a Zipf-like distribution. We expect that the result of this study will be a good guidance to design an efficient memory management policy for future smartphones.

• Computers and Concrete
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• v.12 no.1
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• pp.19-36
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• 2013

In the finite element analysis of reinforced concrete structures, discrete representation of the steel reinforcing bars is considered advantageous over smeared representation because of the more realistic modelling of their bond-slip behaviour. However, there is up to now limited research on how to simulate the dowel action of discrete reinforcing bars, which is an important component of shear transfer in cracked concrete structures. Herein, a numerical model for the dowel action of discrete reinforcing bars is developed. It features derivation of the dowel stiffness based on the beam-on-elastic-foundation theory and direct assemblage of the dowel stiffness matrix into the stiffness matrices of adjoining concrete elements. The dowel action model is incorporated in a nonlinear finite element program based on secant stiffness formulation and application to deep beams tested by others demonstrates that the incorporation of dowel action can improve the accuracy of the finite element analysis.

• Annals of Clinical Neurophysiology
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• v.8 no.2
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• pp.193-195
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• 2006

Acute paraplegia attributable to disc herniation is known to occur most frequently at the thoracic level. A 50-year-old male presented with progressive limb weakness and hypoactive deep tendon reflexes. On the basis of clinical features and neurological findings, the diagnosis of Guillain-Barre syndrome was suspected. Spinal MRI showed cervical disc herniation. He underwent emergency surgery consisting of removal of herniated disc and anterior fusion. We emphasize that there is a possibility of acute progression of paralysis secondary to nontraumatic enlargement of cervical disc herniation.

• Journal of Korea Multimedia Society
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• v.20 no.2
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• pp.170-178
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• 2017

Biometric recognition is one of the major challenging topics which needs high performance of recognition accuracy. Most of existing methods rely on a single source of biometric to achieve recognition. The recognition accuracy in biometrics is affected by the variability of effects, including illumination and appearance variations. In this paper, we propose a new multimodal biometrics recognition using convolutional neural network. We focus on multimodal biometrics from face and periocular regions. Through experiments, we have demonstrated that facial multimodal biometrics features deep learning framework is helpful for achieving high recognition performance.