• Bulletin of the Korean Mathematical Society
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• v.60 no.1
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• pp.75-81
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• 2023

If a multiplicative function f is commutable with a quadratic form x² + xy + y², i.e., f(x² + xy + y²) = f(x)² + f(x) f(y) + f(y)², then f is the identity function. In other hand, if f is commutable with a quadratic form x² - xy + y², then f is one of three kinds of functions: the identity function, the constant function, and an indicator function for ℕ ＼ pℕ with a prime p.

• The Pure and Applied Mathematics
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• v.23 no.3
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• pp.205-221
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• 2016

We formulate the additive entropy of a natural number in terms of the additive partition function, and show that its multiplicative entropy is directly related to the multiplicative partition function. We give a practical formula for the multiplicative entropy of natural numbers with two prime factors. We use this formula to analyze the comparative density of additive and multiplicative entropy, prove that this density converges to zero as the number tends to infinity, and empirically observe this asymptotic behavior.

• Bulletin of the Korean Mathematical Society
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• v.58 no.2
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• pp.515-526
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• 2021

Denote by ��+ the set of probability measures supported on ℝ+. Suppose V�� is the variance function of the Cauchy-Stieltjes Kernel (CSK) family ��-(��) generated by a non degenerate probability measure �� ∈ ��+. We determine the formula for variance function under boolean multiplicative convolution power. This formula is used to identify the relation between variance functions under the map ${\nu}{\mapsto}{\mathbb{M}}_t({\nu})=({\nu}^{{\boxtimes}(t+1)})^{{\uplus}{\frac{1}{t+1}}}$ from ��+ onto itself.

• Bulletin of the Korean Mathematical Society
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• v.58 no.3
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• pp.603-608
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• 2021

Fix k ≥ 3. If a multiplicative function f satisfies f(x₁ + x₂ + ⋯ + x_k) = f(x₁) + f(x₂) + ⋯ + f(x_k) for arbitrary positive triangular numbers x₁, x₂, …, x_k, then f is the identity function. This extends Chung and Phong's work for k = 2.

• Journal of Korean Society for Quality Management
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• v.33 no.1
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• pp.64-72
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• 2005

The ever increasing demand for enhanced competitiveness of engineered products requires "designing-in-quality" strategies that can effectively and efficiently incorporate concepts of uncertainty and quality into design. Multi-attribute utility function is commonly used to represent the decision-maker's preference on multiple design attributes under conditions of uncertainty and risk. One of the major issues in implementing this approach concerns the generation of appropriate utility function, especially in a complex engineering design environment. Typically, the decision maker's preference is revealed through lottery questions rather than being structured on the deductive reasoning to reflect the nonlinear tradeoffs among the attributes. The use of such intuitive procedures can lead to inexact preference information that may result in inaccuracy and rank reversal problems. This paper presents an alternative procedure based on the pair-wise comparisons between design alternatives towards a consistent preference presentation in assessing multiplicative utility function. The effectiveness of the overall procedures is tested with the aid of an injection-molding process design for a capacitor can and the results are discussed.

• Journal of the Korean Operations Research and Management Science Society
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• v.31 no.3
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• pp.97-105
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• 2006

Brand Pricing is the most important issue for the brand manager in the dynamic market. in the typical dynamic pricing model, a linear function has been used based on the assumption that the non-Price Influences and the price influences were independent. However, to incorporate the characteristics of the dynamic market, it is natural to consider the multiplicative relationship. We are going to try the multiplicative linkage between the non-price Influences and the price influences and suggest a new dynamic pricing model with e multiplicative functional form. An empirical study of 19 brands in the Korean cigarette market shows the feasibility of the suggested model.

• Communications of the Korean Mathematical Society
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• v.35 no.3
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• pp.711-722
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• 2020

Given a semigroup S generated by its squares equipped with an involutive automorphism 𝝈 and a multiplicative function 𝜇 : S → ℂ such that 𝜇(x𝜎(x)) = 1 for all x ∈ S, we determine the complex-valued solutions of the following functional equations f(xy) + 𝜇(y)f(𝜎(y)x) = 2f(x)g(y), x, y ∈ S and f(xy) + 𝜇(y)f(𝜎(y)x) = 2f(y)g(x), x, y ∈ S.

• Communications of the Korean Mathematical Society
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• v.38 no.4
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• pp.1063-1074
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• 2023

Let S be a semigroup. We determine the complex-valued solutions of the following functional equation f(xy) + 𝜇(y)f(𝜎(y)x) = 2f(x)g(y), x, y ∈ S, where 𝜎 : S → S is an automorphism, and 𝜇 : S → ℂ is a multiplicative function such that 𝜇(x𝜎(x)) = 1 for all x ∈ S.

• Wind and Structures
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• v.27 no.3
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• pp.149-161
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• 2018

A reliability analysis method is proposed in this paper based on the maximum entropy (MaxEnt) principle in which constraints are specified in terms of the fractional moments instead of integer moments. Then a multiplicative dimensional reduction method (M-DRM) is introduced to compute the fractional moments. The method is applicable for both explicit and implicit limit state functions of complex structures. After two examples illustrate the accuracy and efficiency of this method in comparison to the Monte Carlo simulation (MCS), the method is used to analyze the flutter reliability of suspension bridge. The results show that the empirical formula method in which the limit state function is explicitly represented as a function of variables is only a too conservative estimate for flutter reliability analysis but is not accurate adequately. So it is not suitable for reliability analysis of bridge flutter. The actual flutter reliability analysis should be conducted based on a finite element method in which limit state function is implicitly represented as a function of variables. The proposed M-DRM provide an alternate and efficient way to analyze a much more complicated flutter reliability of long span suspension bridge.

• Journal of Environmental Science International
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• v.8 no.3
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• pp.349-354
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• 1999

The transfer function was introduced to establish the prediction method for the DO concentration at the intaking point of Kongju Water Works System. In the mose cases we analyze a single time series without explicitly using information contained in the related time series. In many forecasting situations, other events will systematically influence the series to be forecasted(the dependent variables), and therefore, there is need to go beyond a univariate forecasting model. Thus, we must bulid a forecasting model that incorporates more than one time series and introduces explicitly the dynamic characteristics of the system. Such a model is called a multiple time series model or transfer function model. The purpose of this study is to develop the stochastic stream water quality model for the intaking station of Kongju city waterworks in Keum river system. The performance of the multiplicative ARIMA model and the transfer function noise model were examined through comparisons between the historical and generated monthly dissolved oxygen series. The result reveal that the transfer function noise model lead to the improved accuracy.