• Proceedings of the Computational Structural Engineering Institute Conference
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• 2002.10a
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• pp.583-590
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• 2002

Point collocation method based on the fast derivatives approximation of meshfree shape function is applied to solid mechanics in this study. Enhanced meshfree approximation with approximated derivative of shape function is reviewed, and formulation of linear elastic solid mechanics by point collocation method is presented. It implies that governing equation of solid mechanics with strong form is directly formulated without no numerical integration cells or grid. The regularity of weight function is not required due to a use of approximated derivative, so we propose the exponential type weight function that is discontinuous in first derivative. The convergence and stability of the proposed method is verified by passing the generalized patch test. Also, the efficiency and applicability of the proposed method in solid mechanics is verified by solving types of solid problems. Numerical results show that not only a use of proposed weight function leads lower error and higher convergence rate than that of the conventional weight functions, but also the improved collocation method with derivative approximation enables to compute the derivatives of shape function very fast and accurately enough to replace the classical direct derivative calculation.

• Korean Journal of Artificial Intelligence
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• v.11 no.2
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• pp.19-27
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• 2023

In recent times, an exponential increase in Internet traffic has been observed as a result of advancing development of the Internet of Things, mobile networks with sensors, and communication functions within various devices. Further, the COVID-19 pandemic has inevitably led to an explosion of social network traffic. Within this context, considerable attention has been drawn to research on network traffic analysis based on machine learning. In this paper, we design and develop a new machine learning framework for network traffic analysis whereby normal and abnormal traffic is distinguished from one another. To achieve this, we combine together well-known machine learning algorithms and network traffic analysis techniques. Using one of the most widely used datasets KDD CUP'99 in the Weka and Apache Spark environments, we compare and investigate results obtained from time series type analysis of various aspects including malicious codes, feature extraction, data formalization, network traffic measurement tool implementation. Experimental analysis showed that while both the logistic regression and the support vector machine algorithm were excellent for performance evaluation, among these, the logistic regression algorithm performs better. The quantitative analysis results of our proposed machine learning framework show that this approach is reliable and practical, and the performance of the proposed system and another paper is compared and analyzed. In addition, we determined that the framework developed in the Apache Spark environment exhibits a much faster processing speed in the Spark environment than in Weka as there are more datasets used to create and classify machine learning models.

• Journal of the Korean Operations Research and Management Science Society
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• v.22 no.1
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• pp.101-121
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• 1997

Consider a Jackson type closed queueing network in which each queue has a single exponential server. Assume that N customers are moving among .kappa. queues. We propose a candidata procedure which yields a lower bound of the network throughput which is sharper than those which are currently available : Let (.rho.$_{1}$, ... .rho.$_{\kappa}$) be the loading vector, let x be a real number with 0 .leq. x .leq. N, and let y(x) denote that y is a function of x and be the unique positive solution of the equation. .sum.$_{i = 1}$$^{\kappa}$y(x) .rho.$_{i}$ (N - y(x) x $p_{i}$ ) = 1 Whitt [17] has shown that y(N) is a lower bound for the throughput. In this paper, we present evidence that y(N -1) is also a lower bound. In dosing so, we are led to formulate a rather general conjecture on 'quot;Migrating Critical Points'quot; (MCP). The .MCP. conjecture asserts that zeros of successive derivatives of certain rational functions migrate at an accelerating rate. We provide a proof of MCP in the polynomial case and some other special cases, including that in which the rational function has exactly two real poles and fewer than three real zeros.tion has exactly two real poles and fewer than three real zeros.

• Kyungpook Mathematical Journal
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• v.28 no.2
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• pp.185-196
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• 1988

We study existence of polynomial integrating factors and solutions F(x, y)=c of first order nonlinear differential equations. We characterize the homogeneous case, and give algorithms for finding existence of and a basis for polynomial solutions of linear difference and differential equations and rational solutions or linear differential equations with polynomial coefficients. We relate singularities to nature of the solution. Solution of differential equations in closed form to some degree might be called more an art than a science: The investigator can try a number of methods and for a number of classes of equations these methods always work. In particular integrating factors are tricky to find. An analogous but simpler situation exists for integrating inclosed form, where for instance there exists a criterion for when an exponential integral can be found in closed form. In this paper we make a beginning in several directions on these problems, for 2 variable ordinary differential equations. The case of exact differentials reduces immediately to quadrature. The next step is perhaps that of a polynomial integrating factor, our main study. Here we are able to provide necessary conditions based on related homogeneous equations which probably suffice to decide existence in most cases. As part of our investigations we provide complete algorithms for existence of and finding a basis for polynomial solutions of linear differential and difference equations with polynomial coefficients, also rational solutions for such differential equations. Our goal would be a method for decidability of whether any differential equation Mdx+Mdy=0 with polynomial M, N has algebraic solutions(or an undecidability proof). We reduce the question of all solutions algebraic to singularities but have not yet found a definite procedure to find their type. We begin with general results on the set of all polynomial solutions and integrating factors. Consider a differential equation Mdx+Ndy where M, N are nonreal polynomials in x, y with no common factor. When does there exist an integrating factor u which is (i) polynomial (ii) rational? In case (i) the solution F(x, y)=c will be a polynomial. We assume all functions here are complex analytic polynomial in some open set.

• Journal of Korea Water Resources Association
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• v.35 no.3
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• pp.295-306
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• 2002

The modified TOPMODEL of two storage systems has been integrated to the generalized assumptions of decreasing hydraulic conductivity to vertical direction. Three different recharge functions were introduced to explore the impact of the macropore flow to vortical direction, the storage at the surface zone and the relative storage deficit of the soil matrix. Combinations of these approaches provide 30 type of the model structure for the hillslope hydrology. Developed models have been applied to several hydrologic events at the Sulmachun watershed. The performance evaluation with the Monte carlo simulation suggests that the exponential function of transmissivity reduction should be appropriate form for the physically -based hydrologic simulation on the Sulmachun watershed. It has been shown that the recharge function of macropore flow contributes to improve the predictability of the generalized version of modified TOPMODEL.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.12 no.1
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• pp.92-98
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• 2001

When analyzing the scatting problem of multi-layered planar structures using closed-form Green's function, one of the main difficulties is that the numerical integrations for the evaluation of diagonal matrix elements converge slowly and are not so stable. Accordingly, even when the integration fur the singularity of type $e^{-jkr}/{\gamma}$, corresponding to the source dipole itself, is performed using such a method, this difficulty persists in the integration corresponding to the finite number of complex images. In order to resolve this difficulty, a new technique based upon the Gaussian quadrature in polar coordinates for the evaluation of the two-dimensional generalized exponential integral is presented. Stability of the algorithm and convergence is discussed. Performance is demonstrated for the example of a microstrip patch antenna.

• Korean Journal of Agricultural and Forest Meteorology
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• v.8 no.3
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• pp.190-198
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• 2006

Radiation use efficiency (RUE), the amount of biomass produced per unit intercepted photosynthetically active radiation (PAR), constitutes a main part of crop growth simulation models. The objective of the present study was to evaluate the variation of RUE of rice plants under various nitrogen nutritive conditions. from 1998 to 2000, shoot dry weight (DW), intercepted PAR of rice canopies, and nitrogen nutritive status were measured in various nitrogen fertilization regimes using japonica and Tongil-type varieties. These data were used for estimating the average RUEs before heading and the relationship between RUE and the nitrogen nutritive status. The canopy extinction coefficient (K) increased with the growth of rice until maximum tillering stage and maintained constant at about 0.4 from maximum tillering to heading stage, rapidly increasing again after heading stage. The DW growth revealed significant linear correlation with the cumulative PAR interception of the canopy, enabling the estimation of the average RUE before heading with the slopes of the regression lines. Average RUE tended to increase with the increased level of nitrogen fertilization. RUE increased approaching maximum as the nitrogen nutrition index (NNI) calculated by the ratio of actual shoot N concentration to the critical N concentration for the maximum growth at any growth stage and the specific leaf nitrogen $(SLN;\;g/m^2\;leaf\;area)$ increased. This relationship between RUE (g/MJ of PAR) and N nutritive status was expressed well by the following exponential functions: $$RUE=3.13\{1-exp(-4.33NNNI+1.26)\}$$ $$RUE=3.17\{1-exp(-1.33SLN+0.04)\}$$ The above equations explained, respectively, about 80% and 75% of the average RUE variation due to varying nitrogen nutritive status of rice plants. However, these equations would have some limitations if incorporated as a component model to simulate the rice growth as they are based on relationships averaged over the entire growth period before heading.