• Proceedings of the Korean Operations and Management Science Society Conference
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• 1995.04a
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• pp.787-796
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• 1995

A man model is a useful design tool for the evaluation of man machine systems and products. An arm reach trajectory prediction for such a model will be specifically useful to present human activities and, consequently, could increase the accuracy and reality of the evaluation. In this study, a three-dimensional reach trajectory prediction model was developed using an inverse kinematics technique. The upper body was modeled as a four link open kinematic chain with seven degrees of freedom. The Resolved Motion Method used for the robot kinematics problem was used to predict the joint movements. The cost function of the perceived discomfort developed using the central composite design was also used as a performance function. This model predicts the posture by moving the joints to minimize the discomfort on the constraint of the end effector velocity directed to a target point. The results of the pairwise t-test showed that all the joint coordinates except the shoulder joint's showed statistically no differences at .alpha. = 0.01. The reach trajectory prediction model developed in this study was found to accurately simulate human arm reach trajectory and the model will help understand the human arm reach movement.

• Proceedings of the KIEE Conference
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• 2005.07a
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• pp.149-151
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• 2005

A new approach considering CO2 air pollution constraints in the long-term generation mix is proposed under uncertain circumstances. A characteristic feature of the presented approach in this paper is what effects give the air pollution constraints in long term best generation mix. Best generation mix problem is formulated by linear programming with fuel and construction cost minimization with load growth, reliability (reserve margin rate) and air pollutionconstraints. The proposed method accommodates the operation of pumped-storage generator. It was assumed in this study that the construction planning of the hydro power plants is given separately from the other generation plans. The effectiveness of the proposed approach is demonstrated by applying to the best generation mix problem of KEPCO-system, which contains nuclear, coal, LNG, oil and pumped-storage hydro plant multi-years.

• Journal of the Korea Society for Simulation
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• v.5 no.1
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• pp.91-106
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• 1996

Control Variate (CV) is very useful technique for variance reduction in a wide class of queueing network simulations. However, the loss in variance reduction caused by the estimation of the optimum control coefficients is an increasing function of the number of control variables. Therefore, in some situations, it is required to select an optimal set of control variables to maximize the variance reduction . In this paper, we develop the Adaptive Control Variates (ACV) method which selects an optimal set of control variates during the simulation adatively. ACV is useful to maximize the simulation efficiency when we need iterated simulations to find an optimal solution. One such an example is the Simulated Annealing (SA) because, in SA algorithm, we have to repeat in calculating the objective function values at each temperature, The ACV can also be applied to the queueing network optimization problems to find an optimal input parameters (such as service rates) to maximize the throughput rate with a certain cost constraint.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.21 no.48
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• pp.113-122
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• 1998

In this paper we consider the CSP requirements determination problem of new equipment(machine) system. For the newly procured equipment systems, mathematical analyses are made for the system which is constructed with the consumable parts to derive the associated CSP requirement determination model in mathematical expression. Based on these analyses, a mathematical model is derived for making an optimal CSP requirement determination subject to tile constraint of satisfying any given operational availability limitation. We assume that the failure of a part follows a Poisson process. Firstly, the operational availability concept in CSP is defined and the relation between the general system availability and the operational availability is established. Secondly, the problem is formulated as the cost minimization problem that should satisfy the operational availability limitation, and then, using the generalized Lagrange multipliers method, the optimal solution procedure is derived.

• 제어로봇시스템학회:학술대회논문집
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• 1994.10a
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• pp.28-33
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• 1994

An optimal controller, e.g. LQG controller, may not be realistic in the sense that the required control power may not be achieved by existing actuators, and the measured output is not satisfactory. To be realistic, the controller should meet such constraints as sensor or actuator limitation, performance limit, etc. In this paper, the lnput/Output Variance Constrained (IOVC) control problem will be considered from the viewpoint of mathematical programming. A dual version shall be developed to solve the IOVC control problem, whose objective is to find a stabilizing control law attaining a minimum value of a quadratic cost function subject to the inequality constraint on each input and output variance for a stabilizable and detectable plant. One approach to the constrained optimization problem is to use the Kuhn-Tucker necessary conditions for the optimality and to seek an optimal point by an iterative algorithm. However, since the algorithm uses only the necessary conditions, the convergent point may not be optimal solution. Our algorithm will guarantee a sufficiency.

• Journal of Magnetics
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• v.17 no.4
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• pp.291-297
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• 2012

This paper presents an efficient methodology for accurate reliability assessment of electromagnetic devices. To achieve the goal, elaborate surrogated models to approximate constraint functions of interest are generated based on the dynamic Kriging method and a hypercube local window. Then, the Monte Carlo simulation scheme is applied to the surrogate models. This leads to reducing computational cost dramatically without degrading accuracy of the reliability analysis. The validity of the proposed method is tested and examined with a mathematical example and a loudspeaker design.

• Journal of Magnetics
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• v.19 no.4
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• pp.385-392
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• 2014

Uncertainties in loads, materials and manufacturing quality must be considered during electromagnetic devices design. This paper presents an effective methodology for robust optimization design based on the variance decomposition in order to keep higher accuracy of the robustness prediction. Sobol' theory is employed to estimate the response variance under some specific tolerance in design variables. Then, an optimal design is obtained by adding a criterion of response variance upon typical optimization problems as a constraint of the optimization. The main contribution of this paper is that the proposed method applies the variance decomposition to obtain a more accurate variance of the response, as well save the computational cost. The performance and robustness of the proposed algorithms are investigated through a numerical experiment with both an analytic function and the TEAM 22 problem.

• International Journal of Reliability and Applications
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• v.17 no.1
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• pp.21-49
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• 2016

Many mechanical, electrical and electronic products have more than one performance characteristics (PCs). For example the performance degradation of rubidium discharge lamps can be characterized by the rubidium consumption or the decreasing intensity the lamp. The product may degrade due to all the PCs which may be independent or dependent. This paper deals with the design of optimal bivariate step-stress partially accelerated degradation test (PADT) with degradation paths modelled by gamma process. The dependency between PCs has been modelled through Frank copula function. In partial step-stress loading, the unit is tested at usual stress for some time, and then the stress is accelerated. This helps in preventing over-stressing of the test specimens. Failure occurs when the performance characteristic crosses the critical value the first time. Under the constraint of total experimental cost, the optimal test duration and the optimal number of inspections at each intermediate stress level are obtained using variance optimality criterion.

• Journal of Digital Contents Society
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• v.13 no.4
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• pp.525-530
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• 2012

Wireless sensor networks consist of resource constraint devices which typically send data measured by sensors attached to the end devices towards a coordinator. One of the best solution for wireless sensor networks is ZigBee, where it is wireless standard introduced for low power, low cost wireless communication with moderate data rates. In this paper, we present porting of Z-Stack and implementation of UART on the TI CC2530. We show that our implemented board works correctly in terms of transmitting and receiving data via serial port.

• Proceedings of the KIEE Conference
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• 1999.07c
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• pp.1183-1185
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• 1999

The basic purpose of economic dispatch problem is that minimize fuel cost with inequality constraint of generator output. To solve this problem it is very important to express power loss equation that have quadratic function of generator output power included B-coefficient. This Paper presents a method in determining B-coefficient by use A-matrix that is calculated by loss re-distribution algorithm (LRDA) considering voltage dependent load model (VDLM)s. The Proposed algorithm is tested with IEEE 6 bus sample system, which shows the result in each cases by the change of load component factor.