• Proceedings of the IEEK Conference
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• 2000.07a
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• pp.11-14
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• 2000

In this paper, we propose a fast and practical head pose estimation scheme fur eye-head controlled human computer interface with non-constrained background. The method we propose uses complete graph matching from thresholded images and the two blocks showing the greatest similarity are selected as eyes, we also locate mouth and nostrils in turn using the eye location information and size information. The average computing time of the image(360*240) is within 0.2(sec) and we employ template matching method using angles between facial features for head pose estimation. It has been tested on several sequential facial images with different illuminating conditions and varied head poses, It returned quite a satisfactory performance in both speed and accuracy.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2000.05a
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• pp.228-231
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• 2000

A hybrid fuzzy controller by means of the genetic algorithms is presented. The control input for the system in the HFC is a convex combination of the FLC's output in transient state and PlD's output in steady state by a fuzzy variable. The HFC combined a PID controller with a fuzzy controller concurrently produces the better output performance than any other controller. A auto-tuning algorithms is presented to automatically improve the performance of hybrid fuzzy controller using genetic algorithms. The algorithms estimates automatical Iy the optimal values of scaling factors, PID parameters and membership function parameters of fuzzy control rules. Especially, in order to auto-tune scaling factors and PID parameters of HFC using GA three kinds of estimation modes are effectively utilized. The HFCs are applied to the second process with time-delay. Computer simulations are conducted at step input and the performances of systems are evaluated and also discussed in ITAE(Integral of the Time multiplied by the Absolute value of Error ) and other ways.

• Ocean Systems Engineering
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• v.5 no.2
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• pp.55-76
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• 2015

Of all the six degrees of freedom, the roll motion of a ship is the most poorly understood and displays complicated phenomena. Due to the low potential wave damping at the natural frequency, the effective analysis of ship roll dynamics comes down to the accurate estimation of the viscous roll damping. This paper provides overview of the importance of roll damping and an extensive literature review of the various viscous roll damping prediction methods applied by researchers over the years. The paper also discusses in detail the current state of the art estimation of viscous roll damping for ship shaped structures. A computer code is developed based on this method and its results are compared with experimental data to demonstrate the accuracy of the method. While some of the key references describing this method are not available in English, some others have been found to contain typographic errors. The objective of this paper is to provide a comprehensive summary of the state of the art method in one place for future reference.

• Journal of Institute of Control, Robotics and Systems
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• v.3 no.3
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• pp.244-251
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• 1997

In this paper, we propose a fault diagnosis algorithm to detect and isolate multiple faults in a system. The proposed fault diagnosis algorithm is based on a multiple fault classifier which consists of two ART2 NN(adaptive resonance theory2 neural network) modules and the algorithm is composed of three main parts - parameter estimation, fault detection and isolation. When a change in the system occurs, estimated parameters go through a transition zone in which residuals between the system output and the estimated output cross the threshold, and in this zone, estimated parameters are transferred to the multiple faults classifier for fault isolation. From the computer simulation results, it is verified that when the proposed diagnosis algorithm is performed successfully, it detects and isolates faults in the position control system of a DC motor.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.14 no.24
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• pp.199-206
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• 1991

As the development of modern technology, human works shift whose roll from physical conditions to the system monitoring tasks. In this paper, safety-presentation configuration is discussed instead of well-known fault-warning configuration. Safety-presentation configuration is verified as superior to the fault-warning configuration in hazard prevention. The estimation of system states involves the decision making environments which lack of required in formations and most of all the informations are not precise too. And the limitation of human information processing show doubtful results. So the estimation of system states is regardes as fuzzy number, and its operation produces the parameter that explain the discriminability(d), decision criterion ($\beta$) of system operator's behaviors. These two values served as performance indices. Especially the $\beta$ is a good milestone of the operator's altitude degree of caution.

• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.2
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• pp.234-239
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• 2006

In this paper, we propose an interacting multiple model (IMM) method using intelligent tracking filter with fuzzy gain to reduce tracking errors for maneuvering targets. In the proposed filter, the unknown acceleration input for each sub-model is determined by mismatches between the modelled target dynamics and the actual target dynamics. After a acceleration input is detected, the state estimates for each sub-filter are modified. To modify the accurate estimation, we propose the fuzzy gain based on the relation between the filter residual and its variation. To optimize each fuzzy system, we utilize the genetic algorithm (GA). The tracking performance of the proposed method is compared with those of the adaptive interacting multiple model(AIMM) method and input estimation (IE) method through computer simulations.

• Journal of the Korean Data and Information Science Society
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• v.25 no.6
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• pp.1581-1589
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• 2014

In this paper, we consider maximum likelihood estimators of the location and scale parameters for the half-logistic distribution when samples are multiply Type I hybrid censored. The scale parameter is estimated by approximate maximum likelihood estimation methods using two different Taylor series expansion types ($\hat{\sigma}_I$, $\hat{\sigma}_{II}$). We compare the estimators in the sense of the root mean square error (RMSE). The simulation procedure is repeated 10,000 times for the sample size n=20 and 40 and various censored schemes. The approximate MLE of the second type is better than that of the first type in the sense of the RMSE. Further an illustrative example with the real data is presented.

• Steel and Composite Structures
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• v.22 no.6
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• pp.1391-1415
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• 2016

Limit load of pressure bearing structures was reviewed in this article. By means of the finite element analysis, limit load of pressurized cylinder with nozzle was taken as an example. Stress classification method and Elastic-plastic finite element analysis combining with limit load determination methods were used to determine limit load of cylinder with nozzle. Comparison of limit load determined by different methods, the results indicated that limit load determined by linearization method was the smallest. Limit load determined by twice elastic slope criterion was the nearest than experimental results. Elastic-plastic finite element analysis had comparably computational precision, but required time consuming. And then the requirements of computer processing and storage capacity by power system became higher and higher. Most of criteria for limit load estimation included any human factors based on a certain substantive characteristics of experimental results. The reasonable criterion should be objective and operational.

• Journal of Communications and Networks
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• v.9 no.3
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• pp.236-246
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• 2007

This paper investigates the performance of the transmission control protocol (TCP) transport protocol over IEEE 802.11 infrastructure based wireless networks. A wireless link is generally characterized by high transmission errors, random interference and a varying latency. The erratic packet losses usually lead to a curbing of the flow of segments on the TCP connection and thus limit TCP's performance. This paper examines the impact of the lossy nature of IEEE 802.11 wireless networks on the TCP performance and proposes a scheme to improve the performance of TCP over wireless links. A negative acknowledgment scheme, selective negative acknowledgment (SNACK), is applied on TCP over wireless networks and a series of ns-2 simulations are performed to compare its performance against that of other TCP schemes. The simulation results confirm that SNACK and its proposed enhancement SNACK-S, which incorporates a bandwidth estimation model at the sender, outperform conventional TCP implementations in 802.11 wireless networks.

• Communications for Statistical Applications and Methods
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• v.11 no.3
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• pp.643-655
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• 2004

L$_1$-estimator in the linear regression model is widely recognized to have superior robustness in the presence of vertical outliers. While the L$_1$-estimation procedures and algorithms have been developed quite well, less progress has been made with the hypothesis test in the multiple L$_1$-regression. This article suggests computer-intensive resampling approaches, jackknife and bootstrap methods, to estimating the variance of L$_1$-estimator and the scale parameter that are required to compute the test statistics. Monte Carlo simulation studies are performed to measure the power of tests in small samples. The simulation results indicate that bootstrap estimation method is the most powerful one when it is employed to the likelihood ratio test.