• Communications of the Korean Mathematical Society
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• v.13 no.4
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• pp.913-931
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• 1998

Using invariant theory, new invariant cubature formulas over a unit cube are given by imposing a group structure on the formulas. Cools and Haegemans [Computing 40, 139-146 (1988)] constructed invariant cubature formulas over a unit square. Since there exists a problem in directly extending their ideas over the unit square which were obtained by using a concept of good integrity basis to some constructions of invariant cubature formulas over the unit cube, a Reynold operator will be used to obtain new invariant cubature formulas over the unit cube. In order to practically find integration nodes and weights for the cubature formulas, it is required to solve a system of nonlinear equations. With an IMSL subroutine DUNLSF which is used for solutions of the system of nonlinear equations, we shall give integration nodes for the new invariant cubature formulas over the unit cube depending on each degree of polynomial precision.

• Bulletin of the Korean Mathematical Society
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• v.58 no.1
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• pp.205-215
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• 2021

In [1], Beznosova proved that the bound on the norm of the dyadic paraproduct with b ∈ BMO in the weighted Lebesgue space L2(w) depends linearly on the Ad2 characteristic of the weight w and extrapolated the result to the Lp(w) case. In this paper, we provide the weighted norm estimates of the dyadic paraproduct πb with b ∈ VMO and reduce the dependence of the Ad2 characteristic to 1/2 by using the property that for b ∈ VMO its mean oscillations are vanishing in certain cases. Using this result we also reduce the quadratic bound for the commutators of the Calderón-Zygmund operator [b, T] to 3/2.

• Journal of Korea Port Economic Association
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• v.28 no.1
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• pp.159-178
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• 2012

Recently, Global network expansion strategy of GTOs(Global Terminal Operator) coupled with each country's port policy, plays huge role for the evolution of modern container port. The Chinese ports can be regarded as the major markets to the GTOs. However, there are scant of researches for finding the key success factors of GTOs' strategies when they consider to invest in overseas. In this respect, the aims of this study were to draw out the evaluation variables for successful investment strategies of GTOs, and to calculate the selected target ports. The 14 variables are selected including the variable named 'development potentiality of a port' through literature reviews. Using the Factor Analysis (FA) based on selected variables, four principal factors were extracted such as 'ability for port operating and cargo generating', 'the trade route and volume', 'the calling potentiality for large vessels' and 'the possibility of utilization of existing infrastructure'. In addition, the weights of factors and variables are evaluated through Fuzzy AHP method. As a result, 'ability for port operating and cargo generating' is chosen as the most important factor among principal factors as scored 0.343, and 'the development potentiality of a port' (0.107) is represented as the most important variable among 14 detailed variables. In overall, from the Global Terminal Operator's point of view, Shanghai is ranked as most suitable port for operating new terminal among the top 5 Chinese ports.

• Journal of Korean Society of Water and Wastewater
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• v.34 no.6
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• pp.495-502
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• 2020

The 37 indicators for performance evaluation of public sewage management agencies are divided into four major categories (agency manpower management ability, wastewater treatment plant operation and management, sludge and water reuse, service quality) in the first stage, and the necessity and score acquisition for the detailed indicators by each major category in the second stages. Priority was investigated through the Analytic Hierarchy Process (AHP) analysis technique for ease and relevance of company efforts. Also, based on the results of this analysis, integrated type weighting and relative importance were analyzed. As a result of the analysis, the weight and relative importance of the first stage classification were in the order of wastewater treatment plant operation and maintenance, operation agency manpower management ability, sludge and water reuse, and service quality. As a result of analyzing the weights and priorities of the detailed performance indicators in the second stage, it was found that operator's career years, the percentage of certification holding rate in operators, compliance with the effluent water quality standards, training times for operators, and efforts to manage hazardous chemicals were important. Some of the indicators of operation agency performance evaluation may include indicators in which the performance of the company's efforts is underestimated or overestimated. In order to improve this, it is necessary to give weights in consideration of the necessity of the indicator, the relevance of the company's efforts, and the ease of obtaining scores.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.27 no.1
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• pp.109-120
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• 2004

In large scale complex system such as a nuclear power plant, it is important to select guidelines and/or checklist to evaluate the system performance, especially human performance for visual information while the number of evaluation items of the guidelines and checklist is voluminous. This paper presents the methodology and experiment for the relative weights or priority selection of evaluation items on the advanced information display of main control room in a nuclear power plant. To summarize this, 1) many human factors guidelines of Visual Display Terminal(VDT) displays are collected, 2) the collected guidelines are integrated and unified based on some rules in a way to avoid confusion or errors about work performances of operator groups, 3) using the unified guidelines, the more important items are defined when the advanced information indexes are applied by using the Analytic Hierarchy Process(AHP). For employing the AHP, the decisions and response of many human factors evaluation specialists in this field are collected to get the priority order of the evaluation items of VDT. The result of this paper will be applied for the evaluation of the usability of next generation of nuclear power plant which is focused on the visual information display on VDT.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 1993.10a
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• pp.1254-1263
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• 1993

Representing knowledge uncertainty , aggregating evidence confidences , and propagation uncertainties are three key elements that effect the ability of a rule-based expert system to represent domains with uncertainty . Fuzzy set theory provide a good mathematical tool for representing the vagueness associated with a variable when , as the condition of a rule , it only partially corresponds to the input data. However, the aggregation of ANDed and Ored confidences is not as simple as the intersection and union operators defined for fuzzy set membership. There is, in fact, a certain degree of compensation that occurs when an expert aggregates confidences associated with compound evidence . Further, expert often consider individual evidences to be varying importance , or weight , in their support for a conclusion. This paper presents a flexible approach for evaluating evidence and conclusion confidences. Evidences may be represented as fuzzy or nonfuzzy variables with as associat d degree of certainty . different weight can also be associated degree of certainty. Different weights can also be assigned to the individual condition in determining the confidence of compound evidence . Conclusion confidence is calculated using a modified approach combining the evidence confidence and a rule strength. The techniques developed offer a flexible framework for representing knowledge and propagating uncertainties. This framework has the potention to reflect human aggregation of uncertain information more accurately than simple minimum and maximum operator do.

• Journal of the Korea Society of Computer and Information
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• v.16 no.6
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• pp.61-70
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• 2011

In this paper, it is realized an image filter for a noise elimination using a recurrent neural networks with fuzzy. The proposed fuzzy neural networks structure is to converge weights and the number of iteration for a certain value by using basically recurrent neural networks structure and is simplified computation and complexity of mathematics by applying the hybrid fuzzy membership function operator. In this paper, the proposed method, the recurrent neural networks applying fuzzy which is collected a certain value, has been proved improving average 0.38dB than the conventional method, the generalied recurrent neural networks, by using PSNR. Also, a result image of the proposed method was similar to the original image than a result image of the conventional method by comparing to visual images.

• Journal of the Semiconductor & Display Technology
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• v.13 no.2
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• pp.23-28
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• 2014

For the reconstruction of three-dimensional (3D) shape of microscopic objects through shape from focus (SFF) methods, usually a single focus measure operator is employed. However, it is difficult to compute accurate depth map using a single focus measure due to different textures, light conditions and arbitrary object surfaces. Moreover, real images with diverse types of illuminations and contrasts lead to the erroneous depth map estimation through a single focus measure. In order to get better focus measurements and depth map, we have combined focus measure operators by using genetic algorithm. The resultant focus measure is obtained by weighted sum of the output of various focus measure operators. Optimal weights are obtained using genetic algorithm. Finally, depth map is obtained from the refined focus volume. The performance of the developed method is then evaluated by using both the synthetic and real world image sequences. The experimental results show that the proposed method is more effective in computing accurate depth maps as compared to the existing SFF methods.

• Korean Journal of Construction Engineering and Management
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• v.21 no.1
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• pp.50-60
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• 2020

Estimates of project costs in the early stages of a construction project have a significant impact on the operator's decision-making in important matters, such as the site's decision or the construction period. However, it is difficult to carry out the initial stage with confidence because information such as design books and specifications is not available. In previous studies, case-based reasoning was used to predict initial construction costs, and genetic algorithms were used to calculate the weight of the inquiry phase among them. However, some say that it is difficult to perform better than the current year because existing genetic algorithms are calculated in random numbers. To overcome these limitations, correlation numbers using correlation analysis rather than random numbers are reflected in the genetic algorithm by method of local search, and weights are calculated using a hybrid genetic algorithm that combines local search and genetic algorithms. A case-based reasoning model was developed using the weights calculated and validated with the data. As a result, it was found that the hybrid GA-CBR applied with local search performed better than the existing GA-CBR.

• Journal of Internet Computing and Services
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• v.6 no.1
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• pp.105-114
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• 2005

This paper describes a new measuring technique by analysing multiple time-series patterns. This paper's goal is that extracts a really measured value having a sample pattern which is the best matched with an inputted time-series, and calculates a difference ratio with the value. Therefore, the proposed technique is not a recognition but a measurement. and not a hardware but a software. The proposed technique is consisted of three stages, initialization, learning and measurement. In the initialization stage, it decides weights of all parameters using importance given by an operator. In the learning stage, it classifies sample patterns using LBG and DTW algorithm, and then creates code sequences for all the patterns. In the measurement stage, it creates a code sequence for an inputted time-series pattern, finds samples having the same code sequence by hashing, and then selects the best matched sample. Finally it outputs the really measured value with the sample and the difference ratio. For the purpose of performance evaluation, we tested on multiple time-series patterns obtained from etching machine which is a semiconductor manufacturing.