• Steel and Composite Structures
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• v.25 no.1
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• pp.45-55
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• 2017

Stainless steel exhibits high ductility and strain hardening capacity in comparison with carbon steel widely used in constructions. To analyze the particular behaviour of stainless steel cover-plate joints, an experimental study was conducted. It showed large ductility and complex failure modes of the joints. A non-linear finite element model was developed to predict the main parameters influencing the behaviour of these joints. The results of this deterministic model allow us to built a meta-model by using the quadratic response surface method, in order to allow for efficient reliability analysis. This analysis is then applied to the assessment of design formulae in the currently used codes of practice. The reliability analysis has shown that the stainless steel joint design according to Eurocodes leads to much lower failure probabilities than the Eurocodes target reliability for carbon steel, which incites revising the resisting model evaluation and consequently reducing stainless steel joint costs. This approach can be used as a basis to evaluate a wide range of steel joints involving complex failure modes, particularly bearing failure.

• Journal of information and communication convergence engineering
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• v.1 no.1
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• pp.53-57
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• 2003

Chaos theory is a study researching the irregular, unpredictable behavior of deterministic and non-linear dynamical system. The interpretation using Chaos makes us evaluate characteristic existing in status space of system by tine series, so that the extraction of Chaos characteristic understanding and those characteristics enables us to do high precision interpretation. Therefore, This paper propose the new method which is adopted in extracting character features and recognizing characters using the Chaos Theory. Firstly, it gets features of mesh feature, projection feature and cross distance feature from input character images. And their feature is converted into time series data. Then using the modified Henon system suggested in this paper, it gets last features of character image after calculating Box-counting dimension, Natural Measure, information bit and information dimension which are meant fractal dimension. Finally, character recognition is performed by statistically finding out the each information bit showing the minimum difference against the normalized pattern database. An experimental result shows 99% character classification rates for 2,350 Korean characters (Hangul) using proposed method in this paper.

• Proceedings of the KOSOMBE Conference
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• v.1996 no.05
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• pp.27-30
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• 1996

PR interval variability has been proposed as a noninvasive tool for in-vestigating the autonomic nervous system as welt as heart rate variability. The goal of this paper is to determine whether PR interval variability is generated from deterministic nonlinear dynamics. The data used in this study is a 24-hour bolter ECGs of 20 healthy adults. We developed an automatic PR interval measurement algorithm, and tested it using MIT ECG Databases. The general discriminants of nonlinear dynamics, such as, correlation dimension and phase space reconstruction are used. Surrogate data is generated from simpler linear models to have similar statistical characteristics with the original data. Nonlinear discriminants are applied to both data, and compared for any significant results. It was concluded that PR interval variability shows non-linear characteristics.

• Communications of the Korean Mathematical Society
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• v.9 no.4
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• pp.961-973
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• 1994

A stochastics process $X = {X(t) : t \in T}$, with an index set T, is said to be infinitely divisible (ID) if its finite dimensional distributions are all ID. An ID process X is said to be a stochastic integral process if $X = {X(t) : t \in T} =^D {\int f_td\Lambda : t \in T}$ where $f : T \times S \to R$ is a deterministic function and $\Lambda$ is an ID random measure on a $\delta$-ring S of subsets of an arbitrary non-empty set S with the property; there exists an increasing sequence ${S_n}$ of sets in S with $U_n S_n = S$. Here $=^D$ denotes equality in all finite dimensional distributions.

• Proceedings of the KIEE Conference
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• 1993.07b
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• pp.932-934
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• 1993

Optimum pole shape is designed to increase the levitation and propulsion force of magnetic levitation systems. Evolution Strategy is introduced as optimization method. Evolution Strategy is random based non-deterministic method, developed by combining Genetic Algorithm with Simulated Annealing. Trasnsrapid-06, which was developed in Germany, is referenced model to be analyze. Design variables are nodes which determine fields pole shape of a linear synchronous motor, and the model analyzed by F.E.M.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.3
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• pp.1659-1673
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• 2019

Android platform provides In-app Billing service for purchasing valuable items inside mobile applications. However, it has become a major target for attackers to achieve valuable items without actual payment. Especially, application developers suffer from automated attacks targeting all the applications in the device, not a specific application. In this paper, we propose a novel scheme detecting automated attacks with probabilistic tests. The scheme tests the signature verification method in a non-deterministic way, and if the method was replaced by the automated attack, the scheme detects it with very high probability. Both the analysis and the experiment result show that the developers can prevent their applications from automated attacks securely and efficiently by using of the proposed scheme.

• Earthquakes and Structures
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• v.22 no.4
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• pp.421-430
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• 2022

This paper addresses the stochastic control problem of robots within the framework of parameter uncertainty and uncertain noise covariance. First of all, an open circle deterministic trajectory optimization issue is explained without knowing the unequivocal type of the dynamical framework. Then, a Linear Quadratic Gaussian (LQG) controller is intended for the ostensible trajectory-dependent linearized framework, to such an extent that robust hereditary NN robotic controller made out of the Kalman filter and the fuzzy controller is blended to ensure the asymptotic stability of the non-continuous controlled frameworks. Applicability and performance of the proposed algorithm shown through simulation results in the complex systems which are demonstrate the feasible to improve the performance by the proposed approach.

• Nuclear Engineering and Technology
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• v.55 no.1
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• pp.324-329
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• 2023

Different types of deterministic solution methods were used to solve neutron transport equations corresponding to half-space and slab albedo problems. In these types of solution methods, in addition to the error of the numerical solutions, the obtained results contain truncation and discretization errors. In the present work, a non-analog Monte Carlo method is provided to simulate the half-space and slab albedo problems with Inönü and Anlı-Güngör strongly anisotropic scattering functions. For each scattering function, the sampling method of the direction of the scattered neutrons is presented. The effects of different beams with different angular dependencies and the effects of different scattering parameters on the reflection probability are investigated using the developed Monte Carlo method. The validity of the Monte Carlo method is also confirmed through the comparison with the published data.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.545-546
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• 2021

In this paper, we consider the morphism of inheritance in SR DEVS. The property of determination occurring in the inheritance can be non-deterministic. In this case the process can be implemented for the inheritnace determination through the morphism. The final determination of morphism might be changed as the environments. To the morphsim, it is not the appearance of new element, but the selection is processed in current elements.

• Journal of Industrial Technology
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• v.43 no.1
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• pp.57-62
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• 2023

In this review, we introduce the non-parametric Bayesian filtering algorithm known as the point-mass filter (PMF) and discuss recent studies related to it. PMF realizes Bayesian filtering by placing a deterministic grid on the state space and calculating the probability density at each grid point. PMF is known for its robustness and high accuracy compared to other nonparametric Bayesian filtering algorithms due to its uniform sampling. However, a drawback of PMF is its inherently high computational complexity in the prediction phase. In this review, we aim to understand the principles of the PMF algorithm and the reasons for the high computational complexity, and summarize recent research efforts to overcome this challenge. We hope that this review contributes to encouraging the consideration of PMF applications for various systems.