• Phonetics and Speech Sciences
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• v.7 no.1
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• pp.3-10
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• 2015

In this paper, different frequency scales in cepstral feature extraction are evaluated for the text-independent speaker recognition. To this end, mel-frequency cepstral coefficients (MFCCs), linear frequency cepstral coefficients (LFCCs), and bilinear warped frequency cepstral coefficients (BWFCCs) are applied to the speaker recognition experiment. In addition, the spectro-temporal features extracted by the cepstral-time matrix (CTM) are examined as an alternative to the delta and delta-delta features. Experiments on the NIST speaker recognition evaluation (SRE) 2004 task are carried out using the Gaussian mixture model-universal background model (GMM-UBM) method and the joint factor analysis (JFA) method, both based on the ALIZE 3.0 toolkit. Experimental results using both the methods show that BWFCC with appropriate warping factor yields better performance than MFCC and LFCC. It is also shown that the feature set including the spectro-temporal information based on the CTM outperforms the conventional feature set including the delta and delta-delta features.

• Transactions of the Korean Society of Mechanical Engineers
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• v.19 no.2
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• pp.475-485
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• 1995

In this study, statistical analysis of fatigue data which had obtained from respective 24 fatigue crack, was examined for SiC whisker reinforced aluminium 6061 composite alloy (SiC$_{w}$/A16061) and aluminium 6061 alloy. SiC volume fraction in composite alloy is 25%. The analysis results stress intensity factor range and 0.1 mm fatigue crack initiation life for SiC$_{w}$/A16061 composite & A16061 matrix are the log-normal distribution. And regression analysis by linear model, exponential model and multiplicative model were performed to find out the relationship between fatigue crack growth rate(da/dN) and stress intensity for find out the relationship between fatigue crack growth rate(da/dN) and stress intensity factor range(.DELTA.K) in the SiC$_{w}$/A16061 composite and examine the applicability of Paris' equation to SiC$_{w}$A16061 composite. Also computer simulation was performed for fatigue life prediction of SiC$_{w}$/A16061 composite using the statistical results of this study.udy.

• Journal of computational fluids engineering
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• v.19 no.1
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• pp.47-56
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• 2014

Since a typical plate heat exchanger is made up of a huge number of unitary cells, it may be impossible to predict the aero-thermal performance of the full scale heat exchanger through three-dimensional numerical simulation due to the enormous amount of computing resources and time required. In the present study, a simple flow-network model using the friction factor correlation and a thermal-network model based on the effectiveness-number of transfer units (${\varepsilon}$-NTU) method has been developed. The complicated flow pattern inside the cross-corrugated heat exchanger has been modeled into flow and thermal networks. Using this model, the heat transfer between neighboring streams can be considered, and the pressure drop and the heat transfer rate of full-scale heat exchanger matrix are calculated. In the calculation, the aero-thermal performance of each unitary cell of the heat exchanger matrix was evaluated using correlations of the Fanning friction factor f and the Nusselt number Nu, which were calculated by unitary-cell CFD model.

• Journal of Korean Tunnelling and Underground Space Association
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• v.9 no.1
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• pp.63-74
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• 2007

Unexpected ground conditions have always been a major problem for the construction of tunnel. Therefore, it is necessary to evaluate the risk capacity before and/or during construction of new tunnel. This paper presents the simplified risk assessment system using modified stability number (N), namely Underground Risk Index (URI) system, to evaluate the tunnel risk possibility in the design stage. URI is a scoring system for risk possibility by rating the each appraisal elements. The modified stability number (N) which is one of risk factor in the Interaction Matrix parameters such as RQD, UCS, weathering, overburden, stability number, ground water-table, RMR, permeability and so on, is used in the system. In addition, the case study is performed in order to verify the applicability of URI-system in practice.

• Bulletin of the Korean Mathematical Society
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• v.47 no.5
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• pp.997-1000
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• 2010

We prove that the reduced free product of $k\;{\times}\;k$ matrix algebras over abelian $C^*$-algebras is not the minimal tensor product of reduced free products of $k\;{\times}\;k$ matrix algebras over abelian $C^*$-algebras. It is shown that the reduced group $C^*$-algebra associated with a group having the property T of Kazhdan is not isomorphic to a reduced free product of abelian $C^*$-algebras or the minimal tensor product of such reduced free products. The infinite tensor product of reduced free products of abelian $C^*$-algebras is not isomorphic to the tensor product of a nuclear $C^*$-algebra and a reduced free product of abelian $C^*$-algebra. We discuss the freeness of free product $II_1$-factors and solidity of free product $II_1$-factors weaker than that of Ozawa. We show that the freeness in a free product is related to the existence of Cartan subalgebras in free product $II_1$-factors. Finally, we give a free product factor which is not solid in the weak sense.

• Structural Engineering and Mechanics
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• v.22 no.4
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• pp.401-418
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• 2006

Solutions to the problems of structural parameter estimation from modal response using leastsquares minimization of force or displacement residuals are generally sensitive to noise in the response measurements. The sensitivity of the parameter estimates is governed by the physical characteristics of the structure and certain features of the noisy measurements. It has been shown that the regularization method can be used to reduce effects of the measurement noise on the estimation error through adding a regularization function to the parameter estimation objective function. In this paper, we adopt the regularization function as the Euclidean norm of the difference between the values of the currently estimated parameters and the a priori parameter estimates. The effect of the regularization function on the outcome of parameter estimation is determined by a regularization factor. Based on a singular value decomposition of the sensitivity matrix of the structural response, it is shown that the optimal regularization factor is obtained by using the maximum singular value of the sensitivity matrix. This selection exhibits the condition where the effect of the a priori estimates on the solutions to the parameter estimation problem is minimal. The performance of the proposed algorithm is investigated in comparison with certain algorithms selected from the literature by using a numerical example.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.29 no.10 s.241
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• pp.1315-1320
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• 2005

TiNi alloy fiber was used to recover the original shape of materials using its shape memory effect. The shape memory alloy plays an important role within the metal matrix composite. The shape memory alloy can control the crack propagation in metal matrix composite, and improve the tensile strength of the composite. In this study, TiNi/A16061 shape memory alloy(SMA) composite was fabricated by hot press method, and pressed by a roller for its strength improvement. The four kinds of specimens were fabricated with $0\%,\;3.2\%,\;5.2\%\;and\;7\%$ and volume fraction of TiNi alloy fiber, respectively. A fatigue test has performed to evaluate the crack initiation and propagation for the TiNi/A16061 SMA composite fabricated by かis method. In order to study the shape memory effect of the TiNi alloy fiber, the test has also done under both conditions of the room temperature and high temperature. The relationship between the crack growth rate and the stress intensity factor was clarified for the composite, and the cold rolling effect was also studied.

• Smart Structures and Systems
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• v.19 no.1
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• pp.57-66
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• 2017

Nanocomposites reinforced with carbon nanotube fibers exhibit greater stiffness, strength and damping properties in comparison to conventional composites reinforced with carbon/glass fibers. Consequently, most of the nanocomposite research is focused in understanding the dynamic characteristics, which are highly useful in applications such as vibration control and energy harvesting. It has been observed that those nanocomposites show better stiffness when the geometry of nanotubes is straight as compared to curvilinear although nanotube agglomeration may exist. In this work the damping behavior of the nanocomposite is characterized in terms of loss factor under the presence of nanotube agglomerations. A micro stick-slip damping model is used to compute the damping properties of the nanocomposites with multiwall carbon nanotubes. The present formulation considers the slippage between the interface of the matrix and the nanotubes as well as the slippage between the interlayers in the nanotubes. The nanotube agglomerations model is also presented. Results are computed based on the loss factor expressed in terms of strain amplitude and nanotube agglomerations. The results show that although-among the various factors such as the material properties (moduli of nanotubes and polymer matrix) and the geometric properties (number of nanotubes, volume fraction of nanotubes, and critical interfacial shear stresses), the agglomeration of nanotubes significantly influences the damping properties of the nanocomposites. Therefore the full potential of nanocomposites to be used for damping applications needs to be analyzed under the influence of nanotube agglomerations.

• Clinical and Experimental Reproductive Medicine
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• v.48 no.4
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• pp.303-310
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• 2021

Decorin (DCN) is a proteoglycan belonging to the small leucine-rich proteoglycan family. It is composed of a protein core containing leucine repeats with a glycosaminoglycan chain consisting of either chondroitin sulfate or dermatan sulfate. DCN is a structural component of connective tissues that can bind to type I collagen. It plays a role in the assembly of the extracellular matrix (ECM), and it is related to fibrillogenesis. It can interact with fibronectin, thrombospondin, complement component C1, transforming growth factor (TGF), and epidermal growth factor receptor. Normal DCN expression regulates a wide range of cellular processes, including proliferation, migration, apoptosis, and autophagy, through interactions with various molecules. However, its aberrant expression is associated with oocyte maturation, oocyte quality, and poor extravillous trophoblast invasion of the uterus, which underlies the occurrence of preeclampsia and intrauterine growth restriction. Spatiotemporal hormonal control of successful pregnancy should regulate the concentration and activity of specific proteins such as proteoglycan participating in the ECM remodeling of trophoblastic and uterine cells in fetal membranes and uterus. At the human feto-maternal interface, TGF-β and DCN play crucial roles in the regulation of trophoblast invasion of the uterus. This review summarizes the role of the proteoglycan DCN as an important and multifunctional molecule in the physiological regulation of oocyte maturation and trophoblast migration. This review also shows that recombinant DCN proteins might be useful for substantiating diverse functions in both animal and in vitro models of oogenesis and implantation.

• Journal of Korea Society of Digital Industry and Information Management
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• v.19 no.3
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• pp.221-232
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• 2023

In this paper, we propose a recommendation system based on the latent factor model using matrix factorization, which is one of the most commonly used collaborative filtering algorithms for recommendation systems. In particular, by introducing the concept of creating a list of recommended content and a list of non-preferred recommended content, and removing the non-preferred recommended content from the list of recommended content, we propose a method to ultimately increase the satisfaction. The experiment confirmed that using a separate list of non-preferred content to find non-preferred content increased precision by 135%, accuracy by 149%, and F1 score by 72% compared to using the existing recommendation list. In addition, assuming that users do not view non-preferred content through the proposed algorithm, the average evaluation score of a specific user used in the experiment increased by about 35%, from 2.55 to 3.44, thereby increasing user satisfaction. It has been confirmed that this algorithm is more effective than the algorithms used in existing recommendation systems.