• East Asian mathematical journal
• /
• v.33 no.1
• /
• pp.103-113
• /
• 2017

We provide quantitative two weight estimates for the commutator of the Hilbert transform under certain conditions on a pair of weights (u, v) and b in $Carl_{u,v}$. In [10] and [11], Bloom's inequality is shown in a modern setting, and the boundedness of the commutators is provided by assuming both weights u, v are $A_2$ and $b{\in}BMO_{\rho}$. In the present paper we show that the condition on b can be replaced by $Carl_{u,v}$ by using the joint $A^d_2$ condition.

• Proceedings of the Korean Operations and Management Science Society Conference
• /
• 2006.05a
• /
• pp.1788-1792
• /
• 2006

The ordered weighted averaging (OWA) operator by Yager has received more and more attention since its appearance. One key point in the OWA operator is to determine its associated weights. Among numerous methods that have appeared in the literature, we notice the maximum entropy OWA (MEOWA) weights that are determined by taking into account two appealing measures characterizing the OWA weights. Instead of maximizing the entropy in the formulation for determining the MEOWA weights, the new method in the article tries to obtain the OWA weights which are evenly spread out around equal weights as much as possible while strictly satisfying the orness value provided in the program. This consideration leads to the least squared OWA (LSOWA) weighting method in which the program tries to obtain the weights that minimize the sum of deviations from the equal weights since entropy is maximized when the weights are equal. Above all, the LSOWA weights display symmetric allocations of weights on the basis of equal weights. The positive or negative allocations of weights from the median as a basis depend on the magnitude of orness specified. Further interval LSOWA weights are constructed when a decision-maker specifies his or her value of orness in uncertain numerical bounds.

• Industrial Engineering and Management Systems
• /
• v.12 no.1
• /
• pp.9-15
• /
• 2013

An inverse minimum spanning tree problem makes the least modification on the edge weights such that a predetermined spanning tree is a minimum spanning tree with respect to the new edge weights. In this paper, the concept of uncertain ${\alpha}$-minimum spanning tree is initiated for minimum spanning tree problem with uncertain edge weights. Using different decision criteria, two uncertain programming models are presented to formulate a specific inverse minimum spanning tree problem with uncertain edge weights involving a sum-type model and a minimax-type model. By means of the operational law of independent uncertain variables, the two uncertain programming models are transformed to their equivalent deterministic models which can be solved by classic optimization methods. Finally, some numerical examples on a traffic network reconstruction problem are put forward to illustrate the effectiveness of the proposed models.

• Kyungpook Mathematical Journal
• /
• v.56 no.3
• /
• pp.899-910
• /
• 2016

It is known that a semi-cubically hyponormal weighted shift need not satisfy the flatness property, in which equality of two weights forces all or almost all weights to be equal. So it is a natural question to describe all semi-cubically hyponormal weighted shifts $W_{\alpha}$ with first two weights equal. Let ${\alpha}$ : 1, 1, ${\sqrt{x}}$(${\sqrt{u}}$, ${\sqrt{v}}$, ${\sqrt{w}}$)^ be a backward 3-step extension of a recursively generated weight sequence with 1 < x < u < v < w and let $W_{\alpha}$ be the associated weighted shift. In this paper we characterize completely the semi-cubical hyponormal $W_{\alpha}$ satisfying the additional assumption of the positive determinant coefficient property, which result is parallel to results for quadratic hyponormality.

• Korean Management Science Review
• /
• v.19 no.2
• /
• pp.139-153
• /
• 2002

The Analytic Hierarchy Process (AHP) is known as a very useful decision-making model developed for obtaining the relative weights of alternatives through pairwise comparison in the context of hierarchical structure. In this paper, we propose a method to reflect the reliability of evaluators in the process of pairwise comparison. This method is applied to the evaluation of aerospace technology alternatives. We have conducted a questionnaire survey for S company that is one of the representative aerospace companies in Korea. A questionnaire was designed for obtaining both the priority with considering the reliability of evaluators' importance weights (the modified AHP priority) and the priority with assuming equally reliable evaluators' importance weights (the AHP priority) in order to compare the priority derived by each of two methods. The result shows that there exists the difference hard to neglect between the final priorities gained by two methods.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 1998.06a
• /
• pp.404-409
• /
• 1998

In this paper, we propose a learning algorithm of fuzzy neural networks with trapezoidal fuzzy weights. This fuzzy neural networks can use fuzzy numbers as well as real numbers, and represent linguistic information better than standard neural networks. We construct trapezodal fuzzy weights by the composition of two triangles, and devise a learning algorithm using the two triangular membership functions, The results of computer simulations on numerical data show that the fuzzy neural networks have high fitting ability for target output.

• Asian-Australasian Journal of Animal Sciences
• /
• v.13 no.6
• /
• pp.729-732
• /
• 2000

Weight records from birth to calving and calving scores of 407 two-year old heifers and weights of their offspring from birth to one year of age were used to study the effects of sire birth weight on maternal traits of their female progeny. The heifers (G1) were the progeny of 81 sires (G0) and were classified into three classes based on their sires' birth weights (High, Medium and Low). The heifers were from three distinct breed-groups and were mated to bulls with medium birth weights within each breed-group to produce the second generation (G2). The data were analyzed using a covariance model. The female progeny of high birth-weight sires were heavier from birth to calving than those sired by medium and low birth-weight bulls. The effect of sire birth weight on calving difficulty scores of their female progeny was not significant. Grand progeny (G2) of low birth-weight sires were lighter at birth than those from high birth-weight sires (p<0.05) but they did not differ significantly in weaning and yearling weights with the other two Grand progeny groups. The results indicated that using low birth weight sires would not result in an increase in the incidence of dystocia among their female progeny calving at two-year of age and would not have an adverse effect on weaning and yearling weights of their grand progeny.

• East Asian mathematical journal
• /
• v.38 no.3
• /
• pp.339-346
• /
• 2022

In this paper, a comparison of two types of quantitative two weight conditions for the boundedness of the dyadic paraproduct and the commutator of the Hilbert transform is provided. In the case of the commutator [b, H], the conditions of the well-known Bloom's inequality [2] and the slightly different types of two weight inequality introduced in [1] are compared around the A₂-conditions on weights and the novel conditions on the function b.

• Bulletin of the Korean Mathematical Society
• /
• v.37 no.2
• /
• pp.347-352
• /
• 2000

In this note we answer to a question of Curto: Non-first two equal weights in the weighted shift force subnormality in the presence of quadratic hyponormality. Also it is shown that every hyponormal weighted shift with two equal weights cannot be polynomially hyponormal without being flat.

• International Journal of Control, Automation, and Systems
• /
• v.4 no.5
• /
• pp.575-591
• /
• 2006

In a previous research, we presented the Grid Method and confirmed it as a systematic and efficient problem formulation method for the task-oriented design of robot kinematics. However, our previous research was limited in two ways. First, it gave only a local optimum due to its use of a local optimization technique. Second, it used constant weights for a cost function chosen by the manual weights tuning algorithm, thereby showing low efficiency in finding an optimal solution. To overcome these two limitations, therefore, this paper presents a global optimization technique and an adaptive weights tuning algorithm to solve a formulated problem using the Grid Method. The efficiencies of the proposed algorithms have been confirmed through the kinematic design examples of various robot manipulators.