• The Pure and Applied Mathematics
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• v.16 no.4
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• pp.383-404
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• 2009

The notions of P-I-open (closed) mappings, P-I-continuous mappings, P-I-neighborhoods, P-I-irresolute mappings and I-irresolute mappings are introduced. Relations between P-I-open (closed) mappings and I-open (closed) mappings are given. Characterizations of P-I-open (closed) mappings are provided. Relations between a P-I-continuous mapping and an I-continuous mapping are discussed, and characterizations of a P-I-continuous mapping are considered. Conditions for a mapping to be an I-irresolute mapping (resp. P-I-irresolute mapping) are provided.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.14 no.4
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• pp.243-250
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• 2014

In this paper, I devise a balance-swap optimization (BSO) algorithm to solve economic load dispatch with a quadratic fuel cost function. This algorithm firstly sets initial values to $P_i{\leftarrow}P_i^{max}$, (${\Sigma}P_i^{max}$ > $P_d$) and subsequently entails two major processes: a balance process whereby a generator's power i of $_{max}\{F(P_i)-F(P_i-{\alpha})\}$, ${\alpha}=_{min}(P_i-P_i^{min})$ is balanced by $P_i{\leftarrow}P_i-{\alpha}$ until ${\Sigma}P_i=P_d$; and a swap process whereby $_{max}\{F(P_i)-F(P_i-{\beta})\}$ > $_{min}\{F(P_i+{{\beta})-F(P_j)\}$, $i{\neq}j$, ${\beta}$ = 1.0, 0.1, 0.1, 0.01, 0.001 is set at $P_i{\leftarrow}P_i-{\beta}$, $P_j{\leftarrow}P_j+{\beta}$. When applied to 15, 20, and 38-generators benchmark data, this simple algorithm has proven to consistently yield the best possible results. Moreover, this algorithm has dramatically reduced the costs for a centralized operation of 73-generators - a sum of the three benchmark cases - which could otherwise have been impossible for independent operations.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.16 no.1
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• pp.253-262
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• 2016

This paper proposes a balance-swap method for the dynamic economic load dispatch problem. Based on the premise that all generators shall be operated at valve-points, the proposed algorithm initially sets the maximum generation power at $P_i{\leftarrow}P_i^{max}$. As for generator i with $_{max}c_i$, which is the maximum operating cost $c_i=\frac{F(P_i)-F(P_{iv_k})}{(P_i-P_{iv_k})}$ produced when the generation power of each generator is reduced to the valve-point $v_k$, the algorithm reduces i's generation power down to $P_{iv_k}$, the valve-point operating cost. When ${\Sigma}P_i-P_d$ > 0, it reduces the generation power of a generator with $_{max}c_i$ of $c_i=F(P_i)-F(P_i-1)$ to $P_i{\leftarrow}P_i-1$ so as to restore the equilibrium ${\Sigma}P_i=P_d$. The algorithm subsequently optimizes by employing an adult-step method in which power in the range of $_{min}\{_{max}(P_i-P_i^{min}),\;_{max}(P_i^{max}-P_i)\}$>${\alpha}{\geq}10$ is reduced by 10; a baby step method in which power in the range of 10>${\alpha}{\geq}1$ is reduced by 1; and a swap method for $_{max}[F(P_i)-F(P_i-{\alpha})]$>$_{min}[F(P_j+{\alpha})-F(P_j)]$, $i{\neq}j$ of $P_i=P_i{\pm}{\alpha}$, in which power is swapped to $P_i=P_i-{\alpha}$, $P_j=P_j+{\alpha}$. It finally executes minute swap process for ${\alpha}=\text{0.1, 0.01, 0.001, 0.0001}$. When applied to various experimental cases of the dynamic economic load dispatch problems, the proposed algorithm has proved to maximize economic benefits by significantly reducing the optimal operating cost of the extant Heuristic algorithm.

• Journal of the Korea Society of Computer and Information
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• v.17 no.11
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• pp.189-196
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• 2012

This paper proposes Swap algorithm for solving Dynamic Economic Dispatch (DED) problem. The proposed algorithm initially balances total load demand $P_d$ with total generation ${\Sigma}P_i$ by deactivating a generator with the highest unit generation cost $C_i^{max}/P_i^{max}$. It then swaps generation level $P_i=P_i{\pm}{\Delta}$, (${\Delta}$=1.0, 0.1, 0.01, 0.001) for $P_i=P_i-{\Delta}$, $P_j=P_j+{\Delta}$ provided that $_{max}[F(P_i)-F(P_i-{\Delta})]$ > $_{min}[F(P_j+{\Delta})-F(P_j)]$, $i{\neq}j$. This new algorithm is applied and tested to the experimental data of Dynamic Economic Dispatch problem, demonstrating a considerable reduction in the prevalent heuristic algorithm's optimal generation cost and in the maximization of economic profit.

• Journal of Navigation and Port Research
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• v.35 no.10
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• pp.855-861
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• 2011

With the rapid growth and development of the Korean Shipping Industry both in external quantum and internal complexity, the marine insurance industry has accordingly expanded with it. This empirical study analyzes the quality factors of the Insurance and P&I Services using 5 factors of quality measures with 22 questions regarding the effect on customer satisfaction by the services offered by the P&I Clubs. The Study is expected to provide P&I Clubs with management tactics for customer satisfaction and the subsequent continued patronage supported by their members through the enhancement of the service quality. This study also provides direction for ship-owners and the members of the P&I Clubs in finding the most efficient service provider as well as in proposing competitive prices of the P&I insurance premium as their management tactic.

• The Korean Journal of Mycology
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• v.21 no.4
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• pp.301-309
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• 1993

An alkalophilic Cephalosporium sp. RYM-202 capable of producing cellulase components was isolated from soil. This organism grew best at an initial pH 9.0 and produced cellulase maximal at an initial pH 9.5-10.0. Three carboxymethyl cellulases(CMCases), P-I-I, P-I-II and P-II-I, were partially purified by DEAE-Sephadex A-50 ion exchange column followed by Sephadex G-150 gel filtration. The optimum pH values for activity were 7.5 for P-I-I, 8.0-9.5 for P-I-II and 7.5-10.0 for P-II-I. All CMCases were stable between pH 4.5 and 12.0. Temperature optima for activity ranged between 40 and $60^{\circ}C$ and more than 50% of the maximum activity was observed at $20^{\circ}C$ for both of P-I-I and P-II-I. The activity of CMCases was significantly stable in the presence of various laundry components, such as, surfactants, chelating agents and alkaline proteinases.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.5
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• pp.155-162
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• 2015

This paper proposes a deterministic optimization algorithm to solve economic load dispatch problem with quadratic convex fuel cost function. The proposed algorithm primarily partitions a generator with prohibited zones into multiple generators so as to place them afield the prohibited zone. It then sets initial values to $P_i{\leftarrow}P_i^{max}$ and reduces power generation costs of those incurring the maximum unit power cost. It finally employs a swap optimization process of $P_i{\leftarrow}P_i-{\beta}$, $P_j{\leftarrow}P_j+{\beta}$ where $_{max}\{F(P_i)-F(P_i-{\beta})\}$ > $_{min}\{F(P_j+{\beta})-F(P_j)\}$, $i{\neq}j$, ${\beta}=1.0,0.1,0.01,0.001$. When applied to 3 different 15-generator cases, the proposed algorithm has consistently yielded optimized results compared to those of heuristic algorithms.

• Proceedings of the Korean Vacuum Society Conference
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• 2003.02a
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• pp.70-70
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• 2003

• Journal of the Korean Statistical Society
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• v.7 no.1
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• pp.3-10
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• 1978

Let $X_i,...,X_n$ be a random sample from a distribution with cumulants $K_1, K_2,...$. The statistic $t = \frac{\sqrt{x}(\bar{X}-K_1)}{S}$ has the well-known 'student' distribution with $\nu = n-1$ degrees of freedom if the $X_i$ are normally distributed (i.e., $K_i = 0$ for $i \geq 3$). An Edgeworth series expansion for the distribution of t when the $X_i$ are not normally distributed is obtained. The form of this expansion is Prob $(t

• Journal of the Korean Statistical Society
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• v.33 no.3
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• pp.313-321
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• 2004

We consider the problem of testing cell probabilities in sparse multinomial data. Aerts et al. (2000) presented T=${{\Sigma}_{i=1}}^{k}{[{p_i}^{*}-E{(p_{i}}^{*})]^2$ as a test statistic with the local least square polynomial estimator ${{p}_{i}}^{*}$, and derived its asymptotic distribution. The local least square estimator may produce negative estimates for cell probabilities. The local maximum likelihood polynomial estimator ${{\hat{p}}_{i}}$, however, guarantees positive estimates for cell probabilities and has the same asymptotic performance as the local least square estimator (Baek and Park, 2003). When there are cell probabilities with relatively much different sizes, the same contribution of the difference between the estimator and the hypothetical probability at each cell in their test statistic would not be proper to measure the total goodness-of-fit. We consider a Pearson type of goodness-of-fit test statistic, $T_1={{\Sigma}_{i=1}}^{k}{[{p_i}^{*}-E{(p_{i}}^{*})]^2/p_{i}$ instead, and show it follows an asymptotic normal distribution. Also we investigate the asymptotic normality of $T_2={{\Sigma}_{i=1}}^{k}{[{p_i}^{*}-E{(p_{i}}^{*})]^2/p_{i}$ where the minimum expected cell frequency is very small.