• Journal of the Korea Institute of Information Security & Cryptology
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• v.18 no.6A
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• pp.17-25
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• 2008

The differential power attack (DPA)[8] is a very powerful side-channel attack tool against various cryptosystems and the masking method[10] is known to be one of its algorithmic countermeasures. But it is non-trivial to apply the masking method to non-linear functions, especially, to arithmetic adders. This paper proposes simple and efficient masking methods applicable to arithmetic adders. For this purpose, we use the fact that every combinational logic circuit (including the adders) can be decomposed into basic logic gates (AND, OR, NAND, NOR, XOR, XNOR, NOT) and try to devise efficient masking circuits for these basic gates. The resulting circuits are then applied to the arithmetic adders to get their masking algorithm. As applications, we applied the proposed masking methods to SEED and SHA-1 in hardware.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.16 no.6
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• pp.37-46
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• 2006

It is known to be hard to apply cryptographic one-way functions to the recognition system using bio-information directly. As one of the solutions about that problem there is a permutation transformation scheme. However, they did not show my algorithmic behavior or any performance analysis of the transformation by experiment. In this paper, by showing the recognition ratio of the transformed scheme by experiment, we prove that that scheme is sound. Also, we adopt their transformation to LDA(Linear Discriminant Analysis) to show the experimental results. In the negative side, we introduce a new type of attack against the permutation transformation schemes. finally, we briefly mention a generalization of the permutation transformation for countermeasure of the attack at the end of this paper.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.1
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• pp.183-190
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• 2021

This study is a study on the implementation and operation of smart air cleaning system to improve indoor air quality. Recently, the problem of indoor air quality is getting serious due to various environmental factors. In this study, to improve the problems of indoor air quality, we implement an air cleaning system using IoT sensor. In particular, we proposed a system that can measure air pollution in real time and change different air flow paths according to pollution level. Through this, we examined efficient air quality improvement, extension of filter life, and system energy reduction. In addition, the main functions of the indoor air quality improvement system were constructed and prototypes were manufactured to confirm the operability. Finally, the utility of fine dust resolution through the implementation of the indoor air quality improvement system was examined.

• The Korean Journal of Applied Statistics
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• v.34 no.3
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• pp.411-425
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• 2021

Accelerated failure time (AFT) model represents a linear relationship between the log-survival time and covariates. We are interested in the inference of covariate's effect affecting the variation of survival times in the AFT model. Thus, we need to model the variance as well as the mean of survival times. We call the resulting model mean and variance AFT (MV-AFT) model. In this paper, we propose a variable selection procedure of regression parameters of mean and variance in MV-AFT model using penalized likelihood function. For the variable selection, we study four penalty functions, i.e. least absolute shrinkage and selection operator (LASSO), adaptive lasso (ALASSO), smoothly clipped absolute deviation (SCAD) and hierarchical likelihood (HL). With this procedure we can select important covariates and estimate the regression parameters at the same time. The performance of the proposed method is evaluated using simulation studies. The proposed method is illustrated with a clinical example dataset.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.34 no.6
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• pp.347-353
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• 2021

In this study, we presented a novel size optimization framework to control the linear buckling temperature and several buckling modes of plates, by optimizing thickness values of composite structures for practical engineering applications. Predicting the buckling temperature and mode shape of structures is a vital research topic in engineering to achieve structural stability. However, optimizing designs of engineering structures through engineering intuition is challenging. To address this limitation, we proposed a method that combines finite element simulation and size optimization. Based on the idea that the structural buckling temperature and mode shape of a plate are affected by the thickness of the structure, the thickness values of the nodes of the target structure were set as the design variables in this optimization method; and the buckling temperature values, and buckling mode shapes were set as the objective functions. This size optimization method enabled the determination of optimal thickness distributions, to induce the desired buckling temperature values and mode shapes. The validity of the proposed method was verified in terms of their buckling temperature values and buckling mode shapes, using several numerical examples of rectangular composite structures.

• Nuclear Engineering and Technology
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• v.54 no.1
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• pp.36-48
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• 2022

As a valid numerical method to obtain a high-resolution result of a flow field, computational fluid dynamics (CFD) have been widely used to study coolant flow and heat transfer characteristics in fuel rod bundles. However, the time-consuming, iterative calculation of Navier-Stokes equations makes CFD unsuitable for the scenarios that require efficient simulation such as sensitivity analysis and uncertainty quantification. To solve this problem, a reduced-order model (ROM) based on proper orthogonal decomposition (POD) and machine learning (ML) is proposed to simulate the flow field efficiently. Firstly, a validated CFD model to output the flow field data set of the rod bundle is established. Secondly, based on the POD method, the modes and corresponding coefficients of the flow field were extracted. Then, an deep feed-forward neural network, due to its efficiency in approximating arbitrary functions and its ability to handle high-dimensional and strong nonlinear problems, is selected to build a model that maps the non-linear relationship between the mode coefficients and the boundary conditions. A trained surrogate model for modes coefficients prediction is obtained after a certain number of training iterations. Finally, the flow field is reconstructed by combining the product of the POD basis and coefficients. Based on the test dataset, an evaluation of the ROM is carried out. The evaluation results show that the proposed POD-ROM accurately describe the flow status of the fluid field in rod bundles with high resolution in only a few milliseconds.

• Journal of Audiology & Otology
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• v.25 no.3
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• pp.146-151
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• 2021

Background and Objectives: The relationship between hearing aid (HA) use and improvement in cognitive function is not fully known. This study aimed to determine whether HAs could recover temporal resolution or hearing in noise functions. Materials and Methods: We designed a prospective study with two groups: HA users and controls. Patients older than 45 years, with a pure tone average threshold of worse than 40 dB and a speech discrimination score better than 60% in both ears were eligible. Central auditory processing tests and hearing in noise tests (HINTs) were evaluated at the beginning of the study and 1, 3, 6, and 12 months after the use of a monaural HA in the HA group compared to the control group. The changes in the evaluation parameters were statistically analyzed using the linear mixed model. Results: A total of 26 participants (13 in the HA and 13 in the control group) were included in this study. The frequency (p<0.01) and duration test (p=0.02) scores showed significant improvements in the HA group after 1 year, while the HINT scores showed no significant change. Conclusions: After using an HA for one year, patients performed better on temporal resolution tests. No improvement was documented with regard to hearing in noise.

• Korean Journal of Audiology
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• v.25 no.3
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• pp.146-151
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• 2021

Background and Objectives: The relationship between hearing aid (HA) use and improvement in cognitive function is not fully known. This study aimed to determine whether HAs could recover temporal resolution or hearing in noise functions. Materials and Methods: We designed a prospective study with two groups: HA users and controls. Patients older than 45 years, with a pure tone average threshold of worse than 40 dB and a speech discrimination score better than 60% in both ears were eligible. Central auditory processing tests and hearing in noise tests (HINTs) were evaluated at the beginning of the study and 1, 3, 6, and 12 months after the use of a monaural HA in the HA group compared to the control group. The changes in the evaluation parameters were statistically analyzed using the linear mixed model. Results: A total of 26 participants (13 in the HA and 13 in the control group) were included in this study. The frequency (p<0.01) and duration test (p=0.02) scores showed significant improvements in the HA group after 1 year, while the HINT scores showed no significant change. Conclusions: After using an HA for one year, patients performed better on temporal resolution tests. No improvement was documented with regard to hearing in noise.

• Steel and Composite Structures
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• v.41 no.6
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• pp.899-910
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• 2021

A 4-unknown shear deformation theory is applied to investigate the vibration of functionally graded plates under thermal environment. The plate is fabricated from a functionally graded material mixed of ceramic and metal with continuously varying material properties through the plate thickness. Three types of thermal loadings, uniform, linear and nonlinear temperature rises along the plate thickness are taken into account. The present theory contains four unknown functions as against five or more in other higher order shear deformation theories. The through-the-thickness distributions of transverse shear stresses of the plate are considered to vary parabolically and vanish at upper and lower surfaces. The present model does not require any problem dependent shear correction factor. Analytical solutions for the free vibration analysis are derived based on Fourier series that satisfy the boundary conditions (Navier's method). Benchmark solutions are firstly considered to evaluate the accuracy of the proposed model. Comparisons with the solutions available in literature revealed the good capabilities of the present model for the simulations of vibration responses of FG plates. Some parametric studies are carried out for the frequency analysis by varying the volume fraction profile and the temperature distribution across the plate thickness.

• Journal of the Korean Society of Propulsion Engineers
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• v.25 no.6
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• pp.1-11
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• 2021

To develop an efficient procedure related to the flamelet library, the machine learning process based on artificial neural network(ANN) is applied for the gaseous hydrogen/liquid oxygen combustor under a supercritical pressure condition. For hidden layers, 25 combinations based on Rectified Linear Unit(ReLU) and hyperbolic tangent are adopted to find an optimum architecture in terms of the computational efficiency and the training performance. For activation functions, the hyperbolic tangent is proper to get the high learning performance for accurate properties. A transformation learning data is proposed to improve the training performance. When the optimal node is arranged for the 4 hidden layers, it is found to be the most efficient in terms of training performance and computational cost. Compared to the interpolation procedure, the ANN procedure reduces computational time and system memory by 37% and 99.98%, respectively.