• Kyungpook Mathematical Journal
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• 제18권1호
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• pp.37-46
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• 1978

The first part of this note is concerned with a neighbourhood base characterisation of locally order-convex spaces. The notions of order*-inductive limits and order ultrabornologicity in the class of locally order-convex spaces are introduced and studied in the latter part. These are the non-convex generalisation of o-inductive limits and o-bornological spaces.

• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 2002년도 가을 학술발표회 논문집
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• pp.271-278
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• 2002

Structural optimization using improved higer-order convex approximation is proposed in this paper. The proposed method is a generalization of the convex approximation method. The order of the approximation function for each constraint is automatically adjusted in the optimization process. And also the order of each design variable is differently adjusted. This self-adjusted capability makes the approximate constraint values conservative enough to maintain the optimum design point of the approximate problem in feasible region. The efficiency of proposed algorithm, compared with conventional algorithm is successfully demonstrated in the Three-bar Truss example.

• Communications for Statistical Applications and Methods
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• 제25권1호
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• pp.79-89
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• 2018

In this paper, we study the maximal property of the volume of the convex hull of d-dimensional independent random vectors. We show that the volume of the random convex hull from a multivariate location-scale family indexed by ${\Sigma}$ is stochastically maximized in simple stochastic order when ${\Sigma}$ is diagonal. The claim can be applied to a broad class of multivariate distributions that include skewed/unskewed multivariate t-distributions. We numerically investigate the proven stochastic relationship between the dependent and independent random convex hulls with the Gaussian random convex hull. The numerical results confirm our theoretical findings and the maximal property of the volume of the independent random convex hull.

• Kyungpook Mathematical Journal
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• 제55권2호
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• pp.383-394
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• 2015

In this paper, we define two new subclass of k-uniformly starlike and convex functions of order ${\alpha}$ type ${\beta}$ with varying argument of coefficients. Further, we obtain coefficient estimates, extreme points, growth and distortion bounds, radii of starlikeness, convexity and results on modified Hadamard products.

• 대한수학회지
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• 제55권3호
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• pp.719-734
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• 2018

An image restoration problem with Poisson noise arises in many applications of medical imaging, astronomy, and microscopy. To overcome ill-posedness, Total Variation (TV) model is commonly used owing to edge preserving property. Since staircase artifacts are observed in restored smooth regions, higher-order TV regularization is introduced. However, sharpness of edges in the image is also attenuated. To compromise benefits of TV and higher-order TV, the weighted sum of the non-convex TV and non-convex higher order TV is used as a regularizer in the proposed variational model. The proposed model is non-convex and non-smooth, and so it is very challenging to solve the model. We propose an iterative reweighted algorithm with the proximal linearized alternating direction method of multipliers to solve the proposed model and study convergence properties of the algorithm.

• 대한수학회보
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• 제55권1호
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• pp.165-173
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• 2018

In this paper we obtain the bounds of the third Hankel determinants for the classes $\mathcal{S}^*({\alpha})$ of starlike functions of order ${\alpha}$ and $\mathcal{K}({\alpha}$) of convex functions of order ${\alpha}$. Moreover,we derive the sharp bounds for functions in these classes which are additionally 2-fold or 3-fold symmetric.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2007년도 춘계학술대회B
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• pp.2757-2762
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• 2007

A cyclone design concept named Convex cyclone was developed to reduce pressure losses. Contrary to conventional cylinder-on-con type cyclone, inner wall of Convex cyclone are defined with a continuous curve and it has convex shape body. The discontinuity of inner diameter variation rate of cylinder-on-con type cyclone cause additional pressure loss. Continuous wall of Convex cyclone prevent additional pressure loss. In order to verify Convex cyclone design concept, we make a comparative experiments between Stairmand HE and Convex cyclone. Experimental Convex cyclone designed based on Stairmand HE model, and inner wall are defined with circular arch. The experimental result clearly shows that Convex cyclone can achieve maximum 50% pressure loss reduction with a few percent of collection efficiency drop. In addition, the experimental results indicated the existence of optimum convexity, minimum pressure loss, of cyclone wall.

• 전기학회논문지
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• 제68권1호
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• pp.159-166
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• 2019

Due to the various engagement situations, it is very difficult to generate the optimal trajectory with several constraints. This paper investigates the sequential convex programming for the impact angle control with the additional constraint of altitude limit. Recently, the SOCP(Second-Order Cone Programming), which is one area of the convex optimization, is widely used to solve variable optimal problems because it is robust to initial values, and resolves problems quickly and reliably. The trajectory optimization problem is reconstructed as convex optimization problem using appropriate linearization and discretization. Finally, simulation results are compared with analytic result and nonlinear optimization result for verification.

• East Asian mathematical journal
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• 제17권2호
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• pp.175-183
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• 2001

The main object of this paper is to investigate several majorization problems involving two subclasses $S_{p,q}(\gamma)$ and $C_{p,q}(\gamma)$ of p-valently starlike and p-valently convex functions of complex order ${\gamma}{\neq}0$ in the open unit disk $\mathbb{u}$. Relevant connections of the results presented here with those given by earlier workers on the subject are also indicated.

• Journal of applied mathematics & informatics
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• 제28권5_6호
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• pp.1395-1408
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• 2010

In this paper, a pair of Wolfe type second-order nondifferentiable multiobjective symmetric dual program over arbitrary cones is formulated. Weak, strong and converse duality theorems are established under second-order (F, $\alpha$, $\rho$, d)-convexity assumptions. An illustration is given to show that second-order (F, $\alpha$, $\rho$, d)-convex functions are generalization of second-order F-convex functions. Several known results including many recent works are obtained as special cases.