• Journal of applied mathematics & informatics
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• v.36 no.1_2
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• pp.107-114
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• 2018

We establish some new ostrowski type inequalities for MT-convex function including first order derivative via Niemann-Trouvaille fractional integral. It is interesting to mention that our results provide new estimates on these types of integral inequalities for MT-convex functions.

• Honam Mathematical Journal
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• v.42 no.4
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• pp.781-794
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• 2020

In this article, we investigate the upper bounds on the coefficients for inverse of functions belongs to certain classes of univalent functions and in particular for the functions convex in one direction. Bounds on the Fekete-Szegö functional and third order Hankel determinant for these classes have also investigated.

• Journal of applied mathematics & informatics
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• v.41 no.5
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• pp.963-972
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• 2023

In this paper, geometrically convex and s-convex functions in third and fourth sense are merged to form (g, s)-convex function. Characterizations of (g, s)-convex function, algebraic and functional properties are presented. In addition, novel functions based on the integral of (g, s)-convex functions in the third sense are created, and inequality relations for these functions are explored and examined under particular conditions. Further, there are also some relationships between (g, s)-convex function and previously defined functions. The (g, s)-convex function and its derivatives will then be used to extend the well-known H-H and Fejer's type inequalities. In order to obtain the previously mentioned conclusions, several special cases from previous literature for extended H-H and Fejer's inequalities are also investigated. The relation between the average (mean) values and newly created H-H and Fejer's inequalities are also examined.

• Journal of Electrical Engineering and Technology
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• v.12 no.4
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• pp.1417-1426
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• 2017

Power system analysis, Non-Convex Economic Dispatch (NED) is considered as an open and demanding optimization problem. Despite the fact that realistic ED problems have non-convex cost functions with equality and inequality constraints, conventional search methods have not been able to effectively find the global answers. Considering the great potential of meta-heuristic optimization techniques, many researchers have started applying these techniques in order to solve NED problems. In this paper, a new and efficient approach is proposed based on imperialist competitive algorithm (ICA). The proposed algorithm which is named multi-operator ICA (MuICA) merges three operators with the original ICA in order to simultaneously avoid the premature convergence and achieve the global optimum answer. In this study, the proposed algorithm has been applied to different test systems and the results have been compared with other optimization methods, tending to study the performance of the MuICA. Simulation results are the confirmation of superior performance of MuICA in solving NED problems.

• Communications for Statistical Applications and Methods
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• v.13 no.2
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• pp.379-387
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• 2006

Local polynomial regression is widely used because of good properties such as such as the adaptation to various types of designs, the absence of boundary effects and minimax efficiency Choi and Hall (1998) proposed an estimator of regression function using a convex combination idea. They showed that a convex combination of three local linear estimators produces an estimator which has the same order of bias as a local cubic smoother. In this paper we suggest another estimator of regression function based on a convex combination of five local constant estimates. It turned out that this estimator has the same order of bias as a local cubic smoother.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.729-731
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• 2004

This paper deals with the design of a low order $H_{\infty}$ controller by using an iterative linear matrix inequality (LMI) method. The low order $H_{\infty}$ controller is represented in terms of LMIs with a rank condition. To solve the non-convex rank-constrained LMI problem, a linear penalty function is incorporated into the objective function so that minimizing the penalized objective function subject to LMIs amounts to a convex optimization problem. With an increasing sequence of the penalty parameter, the solution of the penalized optimization problem moves towards the feasible region of the original non-convex problem. The proposed algorithm is, therefore, convergent. Numerical experiments show the effectiveness of the proposed algorithm.

• Bulletin of the Korean Mathematical Society
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• v.51 no.3
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• pp.641-651
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• 2014

Because of difficulty of using Schauder's fixed point theorem to the polynomial-like iterative equation, a lots of work are contributed to the existence of solutions for the polynomial-like iterative equation on compact set. In this paper, by applying the Schauder-Tychonoff fixed point theorem we discuss monotone solutions and convex solutions of the polynomial-like iterative equation on an open set (possibly unbounded) in $\mathbb{R}^N$. More concretely, by considering a partial order in $\mathbb{R}^N$ defined by an order cone, we prove the existence of increasing and decreasing solutions of the polynomial-like iterative equation on an open set and further obtain the conditions under which the solutions are convex in the order.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.23 no.61
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• pp.127-135
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• 2000

This paper provides a new method of initializing neurons used in self-organizing neural networks and sequencing input nodes for applying to Euclidean traveling salesman problem. We use a general property that in any optimal solution for Euclidean traveling salesman problem, vertices located on the convex hull are visited in the order in which they appear on the convex hull boundary. We composite input nodes as number of convex hulls and initialize neurons as shape of the external convex hull. And then adapt input nodes as the convex hull unit and all convex hulls are adapted as same pattern, clockwise or counterclockwise. As a result of our experiments, we obtain l∼3 % improved solutions and these solutions can be used for initial solutions of any global search algorithms.

• Journal of Korean Academy of Oral and Maxillofacial Radiology
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• v.24 no.2
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• pp.227-236
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• 1994

The purpose of this study was to observe mandibular condyle shape in an asymptomatic population. In order to carry out this study, 96 temporomandibular joints in 48 adults(22 males, 26 females), who were asymptomatic for temporomandibular disturbances and had no history of prosthodontic or orthodontic treatments, were selected, and radiographed using the Sectograph(Denar Co., U.S.A.) for lateral and frontal individualized corrected TMJ tomograph and submentovertex radiograph. Mandibular condyles were classified morphologically, and measured medioateral and anteroposterior dimensions and condylar angulation. The obtained results were as follows. 1. In the classification of condyle shape on lateral tomographs, 94.8% were convex type and 5.2% were angled type. 2. In the classification of condyle shape on frontal tomographs, 45.3% were convex type, 32.0% were round type, 16.0% were flat type, and 6.7% were angled type. 3. In the classification of condyle shape on submentovertex radiographs, 34.5% were flat-convex type, 22.9% were flat-flat type, 20.8% were concave-convex type, 19.8% were convex-convex type, and 1.0% were concave-flat type and convex-flat type. Concave-concave type, convex-concave type, and flat-concave type were not observed. 4. The average mediolateral legth of the condyle was 19.3㎜ and the average anteroposterior length was 9.4㎜. The average angle between the long axis of condyle and the coronal plane made on submentovertex view was 19.6 degrees.

• Journal of the Korean Mathematical Society
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• v.40 no.2
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• pp.225-239
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• 2003

(G, <) is an ordered group if'<'is a total order relation on G in which f < g implies that xfy < xgy for all f, g, x, y $\in$ G. We say that (G, <) is centrally ordered if (G, <) is ordered and ［G,D］ $\subseteq$ C for every convex jump C $\prec$ D in G. Equivalently, if $f^{-1}g f{\leq} g^2$ for all f, g $\in$ G with g > 1. Every order on a torsion-free locally nilpotent group is central. We prove that if every order on every two-generator subgroup of a locally soluble orderable group G is central, then G is locally nilpotent. We also provide an example of a non-nilpotent two-generator metabelian orderable group in which all orders are central.