• Structural Engineering and Mechanics
• /
• v.20 no.2
• /
• pp.225-239
• /
• 2005

Applications of the Trefftz boundary element method (BEM) to anti-plane electroelastic problems are presented in this paper. Both direct and indirect methods with domain decomposition are discussed in details. Each crack is treated as semi-infinite thin slit defined in a subregion, for which a particular solution of the anti-plane problem, satisfying exactly the crack-face condition, is derived. The stress intensity factors defined at each crack tip can be directly computed from the coefficients of the particular solution. The performance of the proposed formulation is assessed by two examples and comparison is made with results obtained by other approaches. The Trefftz boundary element approach is demonstrated to be suitable for the analysis of the anti-plane problem of piezoelectric materials.

• Journal of the Korean Society for Precision Engineering
• /
• v.26 no.2
• /
• pp.141-147
• /
• 2009

We introduce a noble method to find a variation of the optimal path problem. The problem is to find the optimal decomposition of an original planar region such that the number of paths in the region is minimized. The paths are required to uniformly cover each subregion and the directions of the paths in each sub-region are required to be either entirely vertical or entirely horizontal. We show how we can transform the path problem into a graph s-t cut problem. We solve the transformed s-t cut problem using the Ford-Fulkerson method and show its performance. The approach can be used in zig-zag milling and layerd manufacturing.

• Journal of Korean Institute of Industrial Engineers
• /
• v.28 no.2
• /
• pp.128-138
• /
• 2002

In this paper, we address how to reduce the length of tool retraction in a zigzag pocket machining. Tool retraction, in a zigzag pocket machining, is a non-cutting operation in which the tool moves to any remaining regions for machining. We developed an algorithm of generating tool retraction length in convex or concave polygonal shapes including islands. In the algorithm, we consider concave areas of cutting direction in the polygonal shape. Considering concave areas of cutting direction, the polygonal shape is decomposed to subregions which do not need any tool retraction. Using the proposed algorithm, we calculated the shortest length of tool retraction in cutting direction. Examples are shown to verify the validity of the algorithm.

• Korean Management Science Review
• /
• v.10 no.2
• /
• pp.11-26
• /
• 1993

This paper presents a new interactive procedure for multiple objective linear programming problem (MOLP). In practical multiple objective linear programming applications, there is usually no need for the decision maker to consider solutions which are not efficient. Therefore, the interactive procedure presented here searches only among efficient solutions and terminates with a solution that is guaranteed to be efficient. It also can converge to nonextreme efficient final solutions rather than being restricted to only extreme efficient points of the feasible set. The procedure does not require sophisticated judgements or inputs from the decision maker. One of the most attractive features of the procedure however, is that the method allows the DM to examine the efficient faces it finds. As iteration goes, the DM can explore a wide variety of efficient faces rather than efficient faces confined to only certain subregion of the feasible set of problem MOLP since the efficient faces that the procedure finds need not be adjacent. This helps the DM explore the nature of the efficient set of problem MOLP and also helps the DM have confidence with a final solution. For these reasons, I feel that the procedure offer significant promise in solving multiple objective linear programs rapidly and in a satisfying manner to the DM.

• 전기의세계
• /
• v.30 no.4
• /
• pp.219-226
• /
• 1981

The magnetic field distribution in saturable iron part of electromagnetic energy conversion divices is defined by the nonlinear quasi-Poisson enquation that is described the electromagnetic field characteristics and satisfied the natural boundary condition. The solution of this equation is obtained by minimizing an energy functional by means of trial function that defined in triangular subregion of two-dimensional field region. As a result, the accuracy of the machine design is increased by use of its solution. In this respect, this study is developed the basic theory to analyze the magnetic flux distribution in saturable iron part and air gap of induction motor that its secondary part is short circuit by the variational principle, the minimized theory of energy functional, the application of F.E.M., and treatment of computer. As theoritical data compared with the practics, the validity of the theory in this study is supported by experimental findings.

• Proceedings of the KIEE Conference
• /
• 1995.07b
• /
• pp.804-806
• /
• 1995

This paper discusses Self-organized Distributed Networks(SODN) as identifier of nonlinear dynamical systems. The structure of system identification employs series-parallel model. The identification procedure is based on a discrete-time formulation. The learning with the proposed SODN is fast and precise. Such properties arc caused from the local learning mechanism. Each local networks learns only data in a subregion. Large number of memory requirements and low generalization capability for the untrained region, which are drawbacks of conventional local network learning, are overcomed in the SODN. Through extensive simulation, SODN is shown to be effective for identification of nonlinear dynamical systems.

• The Transactions of the Korean Institute of Electrical Engineers
• /
• v.45 no.4
• /
• pp.574-581
• /
• 1996

The neural network approach has been shown to be a general scheme for nonlinear dynamical system identification. Unfortunately the error surface of a Multilayer Neural Networks(MNN) that widely used is often highly complex. This is a disadvantage and potential traps may exist in the identification procedure. The objective of this paper is to identify a nonlinear dynamical systems based on Self-Organized Distributed Networks (SODN). The learning with the SODN is fast and precise. Such properties are caused from the local learning mechanism. Each local network learns only data in a subregion. This paper also discusses neural network as identifier of nonlinear dynamical systems. The structure of nonlinear system identification employs series-parallel model. The identification procedure is based on a discrete-time formulation. Through extensive simulation, SODN is shown to be effective for identification of nonlinear dynamical systems. (author). 13 refs., 7 figs., 2 tabs.

• Proceedings of the KIEE Conference
• /
• 1996.07b
• /
• pp.1182-1185
• /
• 1996

The objective of this paper is to control a nonlinear dynamical systems based on Self-Organized Distributed Networks (SODN). The learning with the SODN is fast and precise. Such properties are caused from the local learning mechanism Each local network learns only data in a subregion. Methods for indirect adaptive control of nonlinear systems using the SODN is presented. Through extensive simulation, the SODN is shown to be effective for adaptive control of nonlinear dynamic systems.

• IEMEK Journal of Embedded Systems and Applications
• /
• v.16 no.3
• /
• pp.113-117
• /
• 2021

The data gathering delay and the network lifetime are important indicators to measure the service quality of wireless sensor and actuator networks (WSANs). This study proposes a dynamically cluster head (CH) selection strategy and automatic scheduling scheme of collectors for prolonging the network lifetime and shorting data gathering delay in WSAN. First the monitoring region is equally divided into several subregions and each subregion dynamically selects a sensor node as CH. These can balance the energy consumption of sensor node thereby prolonging the network lifetime. Then a task allocation method based on genetic algorithm is proposed to uniformly assign tasks to actuators. Finally the trajectory of each actuator is optimized by ant colony optimization algorithm. Simulations are conducted to evaluate the effectiveness of the proposed method and the results show that the method performs better to extend network lifetime while also reducing data delay.

• Korean Journal of Biological Psychiatry
• /
• v.19 no.2
• /
• pp.71-76
• /
• 2012

Objectives : Novelty seeking (NS) represents a dopaminergically modulated tendency toward frequent exploratory activity. Considering the reports showing the relationship between exploratory activity and amygdalar function and structure, and the fact that amygdala is one of the key structures that constitute the dopaminergic pathway in the brain, amygdala might be closely related to NS tendencies. Amygdalar subregional analysis method, which has the enhanced sensitivity compared to the volumteric approach would be appropriate in investigating the subtle differences of amygdalar structures among healthy individuals. The aim of the current study was to examine whether amygdalar subregional morphometric characteristics are associated with the NS tendencies in healthy adults using the amygdalar subregional analysis method. Methods : Twenty-six healthy adults (12 males, 14 females ; mean age $29.8{\pm}6.2$ years) were screened for eligibility. All subjects completed the Korean version of the Temperament and Character Inventory (TCI) and underwent high-resolution brain magnetic resonance imaging. Individuals were divided into 2 groups according to NS scores of the TCI. Results : Individuals of the high NS group had significantly larger laterobasal subregions in right amygdala, after adjustment with the brain parenchymal volumes. Sensitivity analyses for each potential confounding factor such as age, education years and Hamilton Depression Rating Scale (HDRS) scores demonstrated consistent results. Conclusions : This study suggests that NS differences are associated with the laterobasal subregion of the amygdala.