• Journal of applied mathematics & informatics
• /
• v.12 no.1_2
• /
• pp.395-408
• /
• 2003

Common Channel Signaling(CCS) networks need special controls to avoid overload of signaling networks and degradation of call process-ing rate, since they play an important role of controlling communication transfer networks. Congestion control and flow control mechanisms are well described in ITU-T recommendation on Signaling System No.7(SS7). For the practical provisions, however, we need an analysis on the relation among service objects, system requirements and implementation of congestion control algorithms. SS7 provides several options for controlling link congestion in CCS networks. In this paper we give a general queueing model of congestion control algorithm which covers both the international and national options. From the queuing model, we obtain the performance parameters such as throughput, message loss rate and mean delay for the international option. To show the performance of the algorithm, some numerical results are also given.

• 제어로봇시스템학회:학술대회논문집
• /
• 2000.10a
• /
• pp.199-199
• /
• 2000

Most of linear time-varying(LTV) systems except special cases have no general solution for the dynamic equations. Thus, it is difficult to design time-varying controllers in analytic ways, and other control design approaches such as robust control have been applied to control design for uncertain LTI systems which are the approximation of LTV systems have been generally used instead. A robust control method such as quantitative feedback theory(QFT) has an advantage of guaranteeing the stability and the performance specification against plant parameter uncertainties in frozen time sense. However, if these methods are applied to the approximated linear time-invariant(LTI) plants which have large uncertainty, the designed control will be constructed in complicated forms and usually not suitable for fast dynamic performance. In this paper, as a method to enhance the fast dynamic performance, the approximated uncertainty of time-varying parameters are reduced by the proposed QFT parameter-scheduling control design based on radial basis function (RBF) networks for LTV systems with bounded time-varying parameters.

• Journal of the Korean Society of Manufacturing Technology Engineers
• /
• v.23 no.6
• /
• pp.569-575
• /
• 2014

In this study, the effect of cutting edge geometry, such as helix and rake angles, on surface roughness in ball-end milling is investigated by using the Taguchi method. A set of experiments adopting the $L_{27}(3^{13})$ design with an orthogonal array are conducted with special WC ball-end mills having different helix and rake angles. Analysis of variance (ANOVA) is performed to analyze the effects of tool geometry and machining parameters, such as cutting speed, feed per tooth, and depth of cut, on surface roughness. The ANOVA results reveal that helix and rake angles are critical factors affecting surface roughness; the interaction of helix angle and cutting speed is also important. This research can contribute to novel cutting edge designs of ball-end mills and optimization of cutting parameters.

• Journal of the Korean Society for Precision Engineering
• /
• v.16 no.5 s.98
• /
• pp.29-39
• /
• 1999

Many industrial products can be assembled in various sequences of assembly operations. To save time and cost in assembly process and to increase the quality of products, it is very important to choose an optimal assembly sequence. In this paper, we propose a methodology that generates an optimal assembly sequence by using the knowledge of experts. First, a product is divided into several sub-assemblies. Next, the disassembly sequences of sub-assembly are generated using disassembly rules and special information can be extracted through the disassembly process. By combining every assembly sequence of sub-assemblies, we can generate all the possible assembly sequences of a product. Finally, the expert system evaluates all the possible assembly sequences and finds an optimal assembly sequence. It can be achieved under consideration of the parameters such as assembly operation, tool change, safety of part. basepart location, setup change, distance, and orientation. The developed system is applied to UBR(Unit Bath Room) example.

• Communications for Statistical Applications and Methods
• /
• v.4 no.3
• /
• pp.929-941
• /
• 1997

In this paper, we propose the minimum risk estimator (MRE) and the approximate maximum likelihood estimator (AMLE) of the location and the scale parameters of the two-parameter exponential distribution with Type-II censoring. The MRE's can be derived by minimizing the mean squared error among the class of estimators which include some estimators as special cases. We show that the MRE's are more efficient than the other estimators of the scale and the location parameter in the terms of the mean squared error.

• Journal of the Korean Society for Aviation and Aeronautics
• /
• v.16 no.2
• /
• pp.21-27
• /
• 2008

An inverse method is introduced to construct the problem for the error analysis of the numerical solution of initial value problem. These problems constructed through this method have a known exact solution, even though analytical solutions are generally not obtainable. The process leading to the exact solution makes use of an initially available approximate numerical solution. A smooth interpolation of the approximate solution is forced to exactly satisfy the differential equation by analytically deriving a small forcing function to absorb all of the errors in the interpolated approximate solution. Using this special case exact solution, it is possible to investigate the relationship between global errors of a candidate numerical solution process and the associated tuning parameters for a given problem. Under the assumption that the original differential equation is well-posed with respect to the small perturbations, we thereby obtain valuable information about the optimal choice of the tuning parameters and the achievable accuracy of the numerical solution.

• Proceedings of the KIEE Conference
• /
• 1997.07b
• /
• pp.739-742
• /
• 1997

This paper proposes the structure and parameter optimization technique of fuzzy neural networks using genetic algorithm. Fuzzy neural network has advantages of both the fuzzy inference system and neural network. The determination of the optimal parameters and structure of the fuzzy neural networks, however, requires special efforts. To solve these problems, we propose a new learning method for optimization of fuzzy neural networks using genetic algorithm. It can optimize the structure and parameters of the entire fuzzy neural network globally. Numerical example is provided to show the advantages of the proposed method.

• Journal of Korean Institute of Industrial Engineers
• /
• v.17 no.2
• /
• pp.39-50
• /
• 1991

The movement of human beings - walking, running, jumping and climbing, etc. - have long been of scientific interest. In particular, the science of human walking is called gait analysis. Various instruments have been developed to assist in the study of human gait. Recently gait analysis techniques are used in medical research to investigate the abnormalities of pathological gait. In this study, we constructed a comprehensive gait analysis system consisting of a walkway, a force platform, foot-switches and an ExpertVision motion analysis system. Time-distance gait parameters and vector diagrams can be analyzed by a special application program called Force Analysis System(FOANAS). Using quantitative discrimination of this system, the gait characteristic parameters of normal and pathological gait is facilitated.

• Smart Structures and Systems
• /
• v.25 no.6
• /
• pp.669-678
• /
• 2020

This paper focuses on the free vibration analysis of axially functionally graded (FG) Euler-Bernoulli beams. The material properties of the beams are assumed to obey the linear law distribution. The complexities in solving differential equation of transverse vibration of composite beams which limit the analytical solution to some special cases are overcome using the Differential Transformation Method (DTM). Natural frequencies and corresponding normalized mode shapes are calculated. Validation targets are experimental data or finite element results. Different parameters such as reinforcement distribution, ratio of the reinforcement Young's modulus to the matrix Young's modulus and ratio of the reinforcement density to the matrix density are taken into investigation. The delivered results prove the capability and the robustness of the applied method. The studied parameters are demonstrated to be very crucial for the normalized natural frequencies and mode shapes.

• ETRI Journal
• /
• v.31 no.2
• /
• pp.162-172
• /
• 2009

A linear-prediction-based blind equalization algorithm for single-input single-output (SISO) finite impulse response/infinite impulse response (FIR/IIR) channels is proposed. The new algorithm is based on second-order statistics, and it does not require channel order estimation. By oversampling the channel output, the SISO channel model is converted to a special single-input multiple-output (SIMO) model. Two forward linear predictors with consecutive prediction delays are applied to the subchannel outputs of the SIMO model. It is demonstrated that the partial parameters of the SIMO model can be estimated from the difference between the prediction errors when the length of the predictors is sufficiently large. The sufficient filter length for achieving the optimal prediction is also derived. Based on the estimated parameters, both batch and adaptive minimum-mean-square-error equalizers are developed. The performance of the proposed equalizers is evaluated by computer simulations and compared with existing algorithms.