• The Journal of Korea Institute of Information, Electronics, and Communication Technology
• /
• v.16 no.6
• /
• pp.378-384
• /
• 2023

In this study, we aim to derive the descriptor vector conditions that can simultaneously achieve the efficiency and accuracy of artificial Neural Network Potentials (NNP). The material system selected is silicon, a highly applicable material in various industries. Atomic structure-dependent energy data for training artificial neural networks were generated through density functional theory calculations. Behler-Parrinello type atomic-centered symmetric functions were employed as descriptors, and various length vector NNPs were generated. These NNPs were applied to reproduce the structure and mechanical properties of silicon materials in molecular dynamics simulations. In our findings, the minimum vector length for achieving both learning and computational efficiency while maintaining property reproducibility is approximately 50. It was also observed that, for the same conditions, incorporating more angle-dependent symmetric functions into the descriptor vector, could enhance the accuracy of NNP. Our results can provide guidelines for optimizing the conditions of descriptor vectors to achieve both efficiency and accuracy of NNP, simultaneously.

• Journal of the Korea Society for Simulation
• /
• v.18 no.1
• /
• pp.17-25
• /
• 2009

This paper suggests fuzzy-based Segment-Boost method and an effective method for face recognition using the fuzzy-based Segment-Boost. Fuzzy-based Segment-Boost eliminates the limitations of Segment-Boost, and it guarantees improved learning performance and the stability of the performance. By using the fuzzy theory, fuzzy-based Segment-Boost optimizes the selection number of sub-vectors, and leads the optimized learning performance. The fuzzy controller designed in this paper measures learning performance of the fuzzy-based Segment-Boost, and it controls the selection number of sub-vectors by inferring the optimized selection number. The simulation results show that the fuzzy controller inferred the selection number which is very approximate to the true optimized value. As a result, fuzzy-based Segment-Boost showed higher face recognition rate than compared boosting methods and it preserves the velocity of feature selection as fast as that of Segment-Boost. From the experimental results, it was proved that fuzzy-based Segment-Boost has improved and stable performances of learning, feature selection and face recognition.

• Proceedings of the Korean Operations and Management Science Society Conference
• /
• 2000.04a
• /
• pp.53-56
• /
• 2000

The problem ( Ρ ) of optimizing a linear function d$\^$T/x over the set of efficient set for a multiple objective linear program ( Μ ) is difficult because the efficient set is nonconvex. There some interesting properties between the objective linear vector ｄ and the matrix of multiple objectives C and those properties lead us to establish criteria to solve ( Ρ ) with a linear program. In this paper we investigate a system of the linear equations C$\^$T/${\alpha}$=d and construct two linearly independent positive vectors ${\mu}$, ν such that ${\alpha}$=${\mu}$-ν. From those vectors ${\mu}$, ν, solving an weighted sum linear program for finding an efficient extreme point for the ( Μ ) is a way to get an optimal solution ( Ρ ). Therefore our theory gives an easy way of solving nonconvex program ( Ρ ) with a weighted sum linear program.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.26 no.12
• /
• pp.2636-2646
• /
• 2002

This research presents an analytical model to investigate vibration due to ball bearing waviness in a rotating system supported by two or more ball bearings, taking account of the centrifugal force and gyroscopic moment of the ball. The waviness of rolling elements is modeled by the sinusoidal function, and it is incorporated into the position vectors of the race curvature center. The Hertzian con tact theory is applied to calculate the elastic deflection and nonlinear contact force while the rotor has translational and angular motions. Both the centrifugal force and gyroscopic moment of the ball and the waviness of the rolling elements are included in the kinematic constraints and force equilibrium equations of a ball to derive the nonlinear governing equations of the rotor, which are solved by using the Runge-Kutta-Fehlberg algorithm to determine the new position of the rotor. The proposed model is validated by the comparison of the results of the prior researchers. This research shows that the centrifugal force and gyroscopic moment of the ball plays the important role in determining the bearing frequencies, i.e. the principal frequencies, their harmonics and the sideband frequencies resulting from the waviness of the rolling elements of ball bearing. It also shows that the bearing vibration frequencies are generated by the waviness interaction not only between the rolling elements of one ball bearing but also between those of two or more ball bearings constrained by the rotor.

• Journal of KIISE:Computer Systems and Theory
• /
• v.29 no.8
• /
• pp.440-444
• /
• 2002

This paper presents an efficient and robust algorithm to compute the isophote of a surface of revolution. A surface of revolution can be decomposed to a set of cross-sectional circles. The surface normals along each cross-sectional circle form a cone. Using the characteristics of the normal vectors and the symmetric property of the surface of revolution, we propose a method to find the connected components of an isophote, which requires intersecting a planar curve(and its reflection) with two rays. Moreover, we propose a closed-form representation of an isophote as a parametric curve.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.31 no.9C
• /
• pp.846-852
• /
• 2006

The ${\kappa}$-error linear complexity is a ky measure of the stability of the sequences used in the areas of communication systems, stream ciphers in cryptology and so on. This paper introduces an efficient algorithm to determine the ${\kappa}$-error linear complexity and the corresponding error vectors of $p^m$-periodic binary sequences, where : is a prime and 2 is a primitive root modulo $p^2$. We also give a new sense about the ${\kappa}$-error linear complexity in viewpoint of coding theory instead of cryptographic results. We present an efficient algorithm for decoding binary cyclic codes of length $p^m$ and derive key properties of the minimum distance of these codes.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.21 no.8
• /
• pp.1276-1290
• /
• 1997

The previous elastic stiffness formulas of leaf type holddown spring assemblies(HDSs) have been corrected and extended to be able to consider the point of taper runout for the TT-HDS and all the strain energies for both the TT-HDS and the TW-HDS based on Euler beam theory and Castigliano'stheorem. The elastic stiffness sensitivity of the leaf type holddown spring assemblies was analyzed using the derived elastic stiffness formulas and their gradient vectors obtained from the mid-point formula. As a result of the sensitivity analysis, the elastic stiffness sensitivity at each design variable is quantified and design variables having remarkable sensitivity are identified. Among the design variables, leaf thickness is identified as that of having the most remarkable sensitivity of the elastic stiffness. In addition, it was found that the sensitivity of the leaf type HDS's elastic stiffness is exponentially correlated to the leaf thickness.

• Journal of the Korea Society of Computer and Information
• /
• v.9 no.4 s.32
• /
• pp.85-91
• /
• 2004

The use of gestures provides an attractive alternate to cumbersome interface devices for human-computer interaction. This has motivated a very active research area concerned with computer vision-based analysis and interpretation of hand gestures The most important issues in gesture recognition are the simplification of algorithm and the reduction of processing time. The mathematical morphology based on geometrical set theory is best used to perform the processing. The key idea of proposed algorithm is to track a trajectory of center points in primitive elements extracted by morphological shape decomposition. The trajectory of morphological center points includes the information on shape orientation. Based on this characteristic we proposed the morphological gesture sequence recognition algorithm using feature vectors calculated to the trajectory of morphological center points. Through the experiment, we demonstrated the efficiency of proposed algorithm.

• Journal of the Korea Convergence Society
• /
• v.9 no.2
• /
• pp.13-18
• /
• 2018

This paper is based on a simple approach that the most efficient learning of a multi-layered network is the process of finding the optimal set of weight vectors. To overcome the disadvantages of general learning problems, the proposed model uses a combination of features of EBP and OVSSA. In other words, the proposed method can construct a single model by taking advantage of each algorithm so that it can escape to the probability theory of OVSSA in order to reinforce the property that EBP falls into local minimum value. In the proposed algorithm, methods for reducing errors in EBP are used as energy functions and the energy is minimized to OVSSA. A simple experimental result confirms that two algorithms with different properties can be combined.

• Nuclear Engineering and Technology
• /
• v.54 no.6
• /
• pp.2011-2022
• /
• 2022

According to the defense-in-depth concept, not only a preventive strategy but also an integrated cyberattack response strategy for NPPs should be established. However, there are limitations in terms of responding to penetrations, and the existing EOPs are insufficient for responding to intentional disruptions. In this study, we focus on manipulative attacks on process data. Based on an analysis of the related attack vectors and possible attack scenarios, we adopt the Kalman filter to detect process anomalies that can be caused by manipulations of process data. To compensate for these manipulations and secure MCR operators' situational awareness, we modify the Kalman filter such that it can filter out the effects of the manipulations adaptively. A case study was conducted using a hardware-in-the-loop system. The results indicated that the developed method can be used to verify whether the displayed safety-related state data are reliable and to implement the required safety response actions.