• The Journal of the Acoustical Society of Korea
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• v.10 no.4
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• pp.38-47
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• 1991

The frequency variation among speakers is one of problems in the speech recognition. This paper applies fuzzy theory to solve the variation problem of frequency features. Reference patterns are expressed by fuzzified patterns which are produced by the peak frequency and the peak energy extracted from codebooks which are generated from training words uttered by several speakers, as they should include common features of speech signals. Words are recognized by fuzzy inference which uses the certainty factor between the reference patterns and the test fuzzified patterns which are produced by the peak frequency and the peak energy extracted from the power spectrum of input speech signals. Practically, in computing the certainty factor, to reduce memory capacity and computation requirements we propose a new equation which calculates the improved certainty factor using only the difference between two fuzzy values. As a result of experiments to test this word recognition method by fuzzy interence with Korean digits, it is shown that this word recognition method using the new equation presented in this paper, can solve the variation problem of frequency features and that the memory capacity and computation requirements are reduced.

• The Korean Journal of Applied Statistics
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• v.33 no.5
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• pp.627-637
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• 2020

In this paper, the 1.24 million elderly patient medical data (HIRA-APS-2014-0053) provided by the Health Insurance Review and Assessment Service and weather data are analyzed with generalized estimating equation (GEE) model and long short term memory (LSTM) based recurrent neural network (RNN) model to predict the number of disease occurrence. To this end, we estimate the patient's residence as the area of the served medical institution, and the local weather data and medical data were merged. The status of disease occurrence is divided into three categories(occurrence of disease of interest, occurrence of other disease, no occurrence) during a week. The probabilities of categories are estimated by the GEE model and the RNN model. The number of cases of categories are predicted by adding the probabilities of categories. The comparison result shows that predictions of RNN model are more accurate than that of GEE model.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.10C
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• pp.1023-1032
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• 2003

Object-based coding, such as MPEG-4, enables various content-based functionalities for multimedia applications. In order to support such functionalities, as well as to improve coding efficiency, each frame of video sequences should be segmented into video objects. In this paper. we propose an effective video object segmentation method using nonlinear multiscale filtering and spatio-temporal information. Proposed method performs a spatial segmentation using a nonlinear multiscale filtering based on the stabilized inverse diffusion equation(SIDE). And, the segmented regions are merged using region adjacency graph(RAG). In this paper, we use a statistical significance test and a time-variant memory as temporal segmentation methods. By combining of extracted spatial and temporal segmentations, we can segment the video objects effectively. Proposed method is more robust to noise than the existing watershed algorithm. Experimental result shows that the proposed method improves a boundary accuracy ratio by 43% on "Akiyo" and by 29% on "Claire" than A. Neri's Method does.

• Journal of Information Technology Services
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• v.12 no.1
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• pp.173-187
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• 2013

The advent of Web2.0 has believed to be the solution against many barriers in information sharing, especially wiki. Information sharing and collaboration are realized voluntarily and unselfishly with wiki. The purpose of this paper is to analyze the benefits and challenges of using wiki as a project management method in an IT/IS project. Wiki-based project management could provide project managers and members with expert knowledge collaboration for better project results. In the research model, we used TMS(Transactive Memory System) theory to define the relation of collaboration and performance of project members. Based on a survey among project members, the interactions between wiki characteristics and performance are examined in an IS project environment. Using Smart PLS 2.0, the data was analyzed to define the interactions by the structural equation modeling. From the empirical data, the mediated effect of expert knowledge collaboration is supported. We also derive the implications of wiki-based method. It is expected to bring new possibilities of Project management performance.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.38 no.2
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• pp.129-134
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• 2010

The influence of the strain-rate on the thermomechanical characteristics of shape memory alloys (SMAs) is numerically investigated. The three-dimensional SMA constitutive equations of strain-rate effect is developed. The strain-rate effect is taken into account by introducing a coupling equation between the production rate of martensite and the temperature change. For the numerical results, the SMA algorithm is implemented into the ABAQUS finite element program. Numerical simulation shows that the pseudoelasticity of SMA may significantly be changed by considering the strain-rate due to the temperature change.

• Smart Structures and Systems
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• v.20 no.5
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• pp.595-605
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• 2017

The present article reported the thermal buckling strength of the sandwich shell panel structure and subsequent improvement of the same by embedding shape memory alloy (SMA) fibre via a general higher-order mathematical model in conjunction with finite element method. The geometrical distortion of the panel structure due to the temperature is included using Green-Lagrange strain-displacement relations. In addition, the material nonlinearity of SMA fibre due to the elevated thermal environment also incorporated in the current analysis through the marching technique. The final form of the equilibrium equation is obtained by minimising the total potential energy functional and solved computationally with the help of an original MATLAB code. The convergence and the accuracy of the developed model are demonstrated by solving similar kind of published numerical examples including the necessary input parameter. After the necessary establishment of the newly developed numerical solution, the model is extended further to examine the effect of the different structural parameters (side-to-thickness ratios, curvature ratios, core-to-face thickness ratios, volume fractions of SMA fibre and end conditions) on the buckling strength of the SMA embedded sandwich composite shell panel including the different geometrical configurations.

• Nuclear Engineering and Technology
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• v.55 no.7
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• pp.2516-2533
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• 2023

Several practical methods for accelerating the depletion calculation in a GPU-based Monte Carlo (MC) code PRAGMA are presented including the multilevel spectral collapse method and the vectorized Chebyshev rational approximation method (CRAM). Since the generation of microscopic reaction rates for each nuclide needed for the construction of the depletion matrix of the Bateman equation requires either enormous memory access or tremendous physical memory, both of which are quite burdensome on GPUs, a new method called multilevel spectral collapse is proposed which combines two types of spectra to generate microscopic reaction rates: an ultrafine spectrum for an entire fuel pin and coarser spectra for each depletion region. Errors in reaction rates introduced by this method are mitigated by a hybrid usage of direct online reaction rate tallies for several important fissile nuclides. The linear system to appear in the solution process adopting the CRAM is solved by the Gauss-Seidel method which can be easily vectorized on GPUs. With the accelerated depletion methods, only about 10% of MC calculation time is consumed for depletion, so an accurate full core cycle depletion calculation for a commercial power reactor (BEAVRS) can be done in 16 h with 24 consumer-grade GPUs.

• Journal of the Korean Institute of Telematics and Electronics D
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• v.36D no.11
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• pp.45-55
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• 1999

The small signal analyzer for the stationary drift-diffusion equation is developed. The slotboom variables of the potential, electron and hole concentrations for the response of applied small signal are defined and the stationary drift-diffusion equation is linearlized on DC operation point by $S^3A$ method. Frontal solver, which is used to solve the global matrix, progresses the accuracy of the solution in high frequency and minimizes the requirement of the memory. The simulations are executed on the structure of 3 dimensional N'P junction diode and 2 dimensional n-MOSFET to verify the proposed algorithm. The average relative errors of the conductance and the capacitance compared with MEDICI are about 26% and 0.67 for N'P junction diode and 7.75% and 2.24% for n-MOSFET. The simulation by the proposed algorithm can analyze the stationary drift-diffusion equation for applied small signal in high frequency region about 100GHz.

• The Journal of the Korea Contents Association
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• v.15 no.4
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• pp.545-555
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• 2015

We investigated the influence of negative emotion such as state-trait anxiety and depression and working memory (WM) on Foreign Language Vocabulary Learning (FLVL) of South Korean university students. Also, its implications for developing contents for FLVL were discerned. To do so, state-trait anxiety and depression inventories as well as four kinds of WM test were performed for 132 undergraduate students. Participants also had two semantic learning sessions for Swahili words. The mean scores of negative emotions were normal level. The results of structural equation modeling (SEM) showed that there was no effect of negative emotion on FLVL, while direct effects of the negative emotion on WM and the WM on FLVL were significant. Such results suggested that FLVL would be weakened, with the result that WM had been impaired by negative emotions. These outcomes suggested that when developing FLVL content for university students, it is necessary to consider the negative emotions of foreign language learners and to develop the contents for FLVL in the light of WM load.

• Journal of Korea Society of Industrial Information Systems
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• v.18 no.1
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• pp.59-70
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• 2013

The purpose of this study was to identify the antecedents of organizational innovativeness, which in turn influence firm performance that is composed of new product development performance and overall firm performance. We collected responses from C-level executives, and conducted a structural equation model analysis. Results revealed that organizational memory and market orientation influence organizational innovativeness, which in turn influence new product development performance and overall firm performance. However, interestingly, new product development performance was not found to affect overall firm performance. Based on these results, we have confirmed the importance of market orientation and organizational memory for organizational innovativeness. Practical implications related to the results are provided.