• Journal of computational fluids engineering
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• v.14 no.4
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• pp.101-108
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• 2009

We present a new finite-element scheme for direct numerical simulation of particle suspensions in simple shear flow of a viscoelastic fluid in 3D. The sliding tri-periodic representative cell concept has been combined with DEVSS/DG finite element scheme by introducing constraint equations along the domain boundary. Rigid body motion of the freely suspended particle is described by the rigid-shell description and implemented by Lagrangian multipliers on particle boundaries. We present the bulk rheology of suspensions through the numerical examples of single-, two- and many-particle problems, which represent a large number of such systems in simple shear flow. We report the steady bulk viscosity and the first normal stress coefficient, which show shear-thickening behavior for both properties.

• Interaction and multiscale mechanics
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• v.6 no.2
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• pp.107-125
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• 2013

A strain smoothing meshfree formulation with stabilized conforming nodal integration is presented for modeling the consolidation process in saturated porous media. In the present method, nodal strain smoothing is consistently introduced into the meshfree approximation of strain and pore pressure gradient variables associated with the saturated porous media. Meanwhile, in order to achieve a consistent numerical implementation, a smoothing approximation of the meshfree shape function within a nodal representative domain is also proposed in the stiffness construction. The resulting discrete system of equations is all expressed in smoothed nodal measures that are very efficient for numerical evaluation. Subsequently the space-time fully discrete equations are further established by the generalized trapezoidal rule for time integration. The effectiveness of the proposed meshfree consolidation analysis method is systematically illustrated by several benchmark problems.

• Proceedings of the KIEE Conference
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• 2003.11c
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• pp.689-692
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• 2003

In this paper, we propose an adaptive beamforming algorithm for array antenna. The proposed beamforming algorithm, based on Block LMS (Block - Least Mean Squares) algorithm, has a variable step size from coefficient update. This method shows some advantages that the convergence speed is fast and the calculation time can reduced using a block LMS algorithm from frequency domain. As the adaptive parameter approaches a stationary state, it could reduce the number of filter coefficient update with the help of various step size. In this paper we compared the efficiency of the proposed algorithm with a standard LMS algorithm which is a representative method of adaptive beamforming.

• Coupled systems mechanics
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• v.12 no.5
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• pp.461-479
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• 2023

The paper deals with the finite element modelling of the free vibration and structural behavior of a particular four-floor reinforced concrete structure subjected to static equivalent seismic loads and supported by a shallow foundation system called SNSF (Spider Net System Footing). The two FE models are a simple 2D Matlab model and a detailed 3D model based on solid elastic elements using Altairworks (Hypermesh and Optistruct). Both models can simulate the soil structure interaction. We concentrate on the behavior of a representative cell involving two columns on five levels. The influence of the boundary conditions on the external vertical planes of the domain are duly studied. The Matlab model appears relevant for a primary estimation of frequencies and stiffness of the whole structure under vertical and lateral loads.

• The KIPS Transactions:PartB
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• v.11B no.6
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• pp.723-734
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• 2004

In this paper, we present an automated Web page classification system based upon ontology. As a first step, to identify the representative terms given a set of classes, we compute the product of term frequency and document frequency. Secondly, the information gain of each term prioritizes it based on the possibility of classification. We compile a pair of the terms selected and a web page classification into rules using machine learning algorithms. The compiled rules classify any Web page into categories defined on a domain ontology. In the experiments, 78 terms out of 240 terms were identified as representative features given a set of Web pages. The resulting accuracy of the classification was, on the average, 83.52%.

• Journal of Sensor Science and Technology
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• v.21 no.1
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• pp.59-67
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• 2012

It was reported that the latest sensor technology allow an 65536 conductive polymer sensor array to be made with broad but overlapping selectivity to different families of chemicals emulating the characteristics found in biological olfaction. However, the supernumerary redundancy always accompanies great error and risk as well as an inordinate amount of computation time and local minima in signal processing, e.g. neural networks. In this paper, we propose a new method to reduce the number of sensor for analysis by reducing redundancy between sensors and by removing unstable sensors using the cosine similarity method and to decide on representative sensor using FCM(Fuzzy C-Means) algorithm. The representative sensors can be just used in analyzing. And, we introduce DWT(Discrete Wavelet Transform) for data compression in the time domain as preprocessing. Throughout experimental trials, we have done a comparative analysis between gas sensor data with and without reduced redundancy. The possibility and superiority of the proposed methods are confirmed through experiments.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.12
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• pp.1846-1852
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• 2021

In modern society, various digital devices are being distributed in a wide range of fields due to the fourth industrial revolution and the development of IoT technology. However, noise is generated in the process of acquiring or transmitting an image, and not only damages the information, but also affects the system, causing errors and incorrect operation. AWGN is a representative noise among image noise. As a method for removing noise, prior research has been conducted, and among them, AF, A-TMF, and MF are the representative methods. Existing filters have a disadvantage that smoothing occurs in areas with high frequency components because it is difficult to consider the characteristics of images. Therefore, the proposed algorithm calculates the standard deviation distribution to effectively eliminate noise even in the high frequency domain, and then calculates the final output by applying the probability density function weight of the Laplace distribution using the curve fitting method.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.4
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• pp.169-178
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• 2022

Morphemes are most primitive units in a language that lose their original meaning when segmented into smaller parts. In Korean, a sentence is a sequence of eojeols (words) separated by spaces. Each eojeol comprises one or more morphemes. Korean morphological analysis (KMA) is to divide eojeols in a given Korean sentence into morpheme units. It also includes assigning appropriate part-of-speech(POS) tags to the resulting morphemes. KMA is one of the most important tasks in Korean natural language processing (NLP). Improving the performance of KMA is closely related to increasing performance of Korean NLP tasks. Recent research on KMA has begun to adopt the approach of machine translation (MT) models. MT is to convert a sequence (sentence) of units of one domain into a sequence (sentence) of units of another domain. Neural machine translation (NMT) stands for the approaches of MT that exploit neural network models. From a perspective of MT, KMA is to transform an input sequence of units belonging to the eojeol domain into a sequence of units in the morpheme domain. In this paper, we propose a deep learning model for KMA. The backbone of our model is based on the BERT-fused model which was shown to achieve high performance on NMT. The BERT-fused model utilizes Transformer, a representative model employed by NMT, and BERT which is a language representation model that has enabled a significant advance in NLP. The experimental results show that our model achieves 98.24 F1-Score.

• Korean Journal of Remote Sensing
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• v.38 no.5_1
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• pp.587-596
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• 2022

Sea levels are rising as a result of climate change, and low-lying areas along the coast are at risk of flooding. Therefore, we tried to investigate the relationship between sea level change and climate indices using satellite altimeter data (Topex/Poseidon, Jason-1/2/3) and southern oscillation index (SOI) and the Pacific decadal oscillation (PDO) data. If time domain data were converted to frequency domain, the original data can be analyzed in terms of the periodic components. Fourier transform and Wavelet transform are representative periodic analysis methods. Fourier transform can provide only the periodic signals, whereas wavelet transform can obtain both the periodic signals and their corresponding time location. The cross-wavelet transformation and the wavelet coherence are ideal for analyzing the common periods, correlation and phase difference for two time domain datasets. Our cross-wavelet transform analysis shows that two climate indices (SOI, PDO) and sea level height was a significant in 1-year period. PDO and sea level height were anti-phase. Also, our wavelet coherence analysis reveals when sea level height and climate indices were correlated in short (less than one year) and long periods, which did not appear in the cross wavelet transform. The two wavelet analyses provide the frequency domains of two different time domain datasets but also characterize the periodic components and relative phase difference. Therefore, our research results demonstrates that the wavelet analyses are useful to analyze the periodic component of climatic data and monitor the various oceanic phenomena that are difficult to find in time series analysis.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.22 no.10
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• pp.1005-1011
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• 2011

In this paper, we present a marching-on-in-degree(MOD) finite difference method(FDM) based on the Helmholtz wave equation for analyzing transient electromagnetic responses in a general dispersive media. The two issues related to the finite difference approximation of the time derivatives and the time consuming convolution operations are handled analytically using the properties of the Laguerre functions. The basic idea here is that we fit the transient nature of the fields, the flux densities, the permittivity with a finite sum of orthogonal Laguerre functions. Through this novel approach, not only the time variable can be decoupled analytically from the temporal variations but also the final computational form of the equations is transformed from finite difference time-domain(FDTD) to a finite difference formulation through a Galerkin testing. Representative numerical examples are presented for transient wave propagation in general Debye, Drude, and Lorentz dispersive medium.