• Communications for Statistical Applications and Methods
• /
• v.24 no.2
• /
• pp.173-191
• /
• 2017

This study develops a new type of latent class analysis (LCA) in order to explain the associations between one latent variable and several other categorical latent variables. Our model postulates that the prevalence of the latent variable of interest is affected by another latent variable composed of other several latent variables. For the parameter estimation, we propose deterministic annealing EM (DAEM) to deal with local maxima problem in the proposed model. We perform simulation study to demonstrate how DAEM can find the set of parameter estimates at the global maximum of the likelihood over the repeated samples. We apply the proposed LCA model in an investigation of the effect of and joint patterns for drug-using behavior to violent behavior among US high school male students using data from the Youth Risk Behavior Surveillance System 2015. Considering the age of male adolescents as a covariate influencing violent behavior, we identified three classes of violent behavior and three classes of drug-using behavior. We also discovered that the prevalence of violent behavior is affected by the type of drug used for drug-using behavior.

• Journal of Advanced Marine Engineering and Technology
• /
• v.20 no.4
• /
• pp.20-26
• /
• 1996

Recently, for the speed control of a diesel engine, some methods using the modern control theory such as LQ control technique, or $\textit{H}_{\infty}$control theory etc., have been reported. However, most of speed controlers of a diesel engine ever developed are still using the PID control algorithm. And, as another approach to the speed control of a diesel engine, the authors proposed already a new method to adjust the parameters of the PID controller by a model matching method. In the previous paper, the authors confirmed that the proposed new method is superior to Ziegler & Nichols's method through the analysis of results of the digital simulations under the assumption that the parameters of a diesel engine are known exactly. But, actually, it is very difficult to find out the value of parameters of a diesel engine accurately. And the parameters of a diesel engine are changigng according to the operating condition of a diesel engine. So, in this paper, a method to estimate the parameters of the PID controller for the speed control of a diesel engine by means of the model matching method are proposed. Also, the digital simulations are carried out in cases either with or without measurement noise. And this paper confirms that the proposed method here is superior to Ziegler & Nichols's method through the analysis of the characteristics of indicial responses.

• The Transactions of the Korean Institute of Electrical Engineers P
• /
• v.61 no.4
• /
• pp.186-191
• /
• 2012

DC Bus Electrolytic capacitors have been widely used in power conversion system because they can achieve high capacitance and voltage ratings with volumetric efficiency and low cost. This type of capacitors have been traditionally used for filtering, voltage smoothing, by-pass and other many applications in power conversion circuits requiring a cost effective and volumetric efficiency components. Unfortunately, electrolytic capacitors are some of the weakest components in power electronic converter. Many papers have proposed different methods or algorithms to determinate the ESR and/or capacitance C for fault diagnosis of the electrolytic capacitor. However, both ESR and C vary with frequency and temperature. Accurate knowledge of both values at the capacitors operating conditions is essential to achieve the best reference data of fault judgement. According to parameter analysis, the capacitance increases with temperature and the ESR decreases. Higher frequencies make the ESR and C to decrease. Analysis results show that the proposed electrolytic capacitor parameter estimation technique can be applied to reference signal of capacitor diagnosis systems successfully.

• International Journal of Korean Welding Society
• /
• v.1 no.1
• /
• pp.17-22
• /
• 2001

Because the quantitative relationships between welding parameters and welding result are not yet blown, optimal values of welding parameters for $CO_2$ robotic arc welding is a difficult task. Using the various artificial data processing methods may solve this difficulty. This research aims to develop an expert system for $CO_2$ robotic arc welding to recommend the optimal values of welding parameters. This system has three main functions. First is the recommendation of reasonable values of welding parameters. For such work, the relationships in between the welding parameters are investigated by the use of regression analysis and fuzzy system. The second is the estimation of bead shape by a neural network system. In this study the welding current voltage, speed, weaving width, and root gap are considered as the main parameters influencing a bead shape. The neural network system uses the 3-layer back-propagation model and a generalized delta rule as teaming algorithm. The last is the optimization of the parameters for the correction of undesirable weld bead. The causalities of undesirable weld bead are represented in the form of rules. The inference engine derives conclusions from these rules. The conclusions give the corrected values of the welding parameters. This expert system was developed as a PC-based system of which can be used for the automatic or semi-automatic $CO_2$ fillet welding with 1.2, 1.4, and 1.6mm diameter the solid wires or flux-cored wires.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.14 no.8
• /
• pp.1752-1758
• /
• 2010

A FM-CW radar is used for the various purposes as a remote sensing device since it has the advantages of the relatively simple implementation and the low probability of signal interception. A FM-CW radar uses the same frequency modulated continuous wave for both transmission and demodulation. Therefore, the received beat frequency represents the range and Doppler information of targets. However, using the conventional FFT method, the degree of accuracy and resolution in the spectrum estimation can be seriously degraded in the detection and tracking of fast moving targets because of the short dwell time. Therefore, in this paper, the model parameter estimation methods called as an autoregressive method is applied to overcome these problems and showed that the improved accuracy and resolution can be obtained for the target range and velocity estimation.

• Journal of Korean Institute of Industrial Engineers
• /
• v.37 no.1
• /
• pp.74-82
• /
• 2011

The Bass model is a cornerstone in diffusion theory which is used for forecasting demand of durables or new services. Three well-known estimation methods for parameters of the Bass model are Ordinary Least Square (OLS), Maximum Likelihood Estimator (MLE), Nonlinear Least Square (NLS). In this paper, a hybrid method incorporating OLS and NLS is presented and it's performance is analyzed and compared with OLS and NLS by using simulation data and empirical data. The results show that NLS has the best performance in terms of accuracy and our hybrid method has the best performance in terms of stability. Specifically, hybrid method has better performance with less data. This result means much in practical aspect because the avaliable data is little when a diffusion model is used for forecasting demand of a new product.

• Journal of Power Electronics
• /
• v.10 no.5
• /
• pp.485-490
• /
• 2010

Sensorless control methods are generally used in motor control for home-appliances because of the material cost and manufactureing standard restrictions. The current model-based control algorithm is mainly used for PMSM sensorless control in the home-appliance industry. In this control method, the rotor position is estimated by using the d-axis and q-axis current errors between the real system and a motor model of the position estimator. As a result, the accuracy of the motor model parameters are critical in this control method. A mismatch of the PMSM parameters affects the speed and torque in low speed, steadystate responses. Rotor position errors are mainly caused by a mismatch of the stator resistance. In this paper, a stator resistance compensation algorithm is proposed to improve sensorless control performance. This algorithm is easy to implement and does not require a modification of the motor model or any special interruptions of the controller. The effectiveness of the proposed algorithm is verified through experimental results.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.43 no.3 s.309
• /
• pp.34-42
• /
• 2006

In general, almost information is stored in only a few wavelet coefficients. This sparse characteristic of wavelet coefficient can be modeled by the mixture of Gaussian probability density function and point mass at zero, and denoising for this prior model is peformed by using Bayesian estimation. In this paper, we propose a method of parameter estimation for denoising using hypothesis-testing problem. Hypothesis-testing problem is applied to variance of wavelet coefficient, and $X^2$-test is used. Simulation results show our method outperforms about 0.3dB higher PSNR(peak signal-to-noise ratio) gains compared to the states-of-art denoising methods when using orthogonal wavelets.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.50 no.12
• /
• pp.3-13
• /
• 2013

This paper contains two algorithms proposed for synchronization in OFDM system. The first is having 1 symbol offset while calculating the timing metric, and the second is introduced in new parameter such as Reduction Factor(${\rho}$), Break Constant(${\beta}_k$) and Implant Depth(${\delta}_I$) in order to control the power of CP(Cyclic Prefix) area. Two proposed method are evaluated performance with conventional methode, and than the result of simulation show proposed methods is better than conventional methode while it experience into multipath fading channel.

• Transactions of the Korean Society of Mechanical Engineers B
• /
• v.22 no.12
• /
• pp.1715-1725
• /
• 1998

A two-dimensional transient inverse heat conduction problem involving the estimation of the unknown location, ($X^*$, $Y^*$), and timewise varying unknown strength, $G({\tau})$, of a line heat source embedded inside a rectangular bar with insulated boundaries has been solved simultaneously. The regular conjugate gradient method, RCGM and the modified conjugate gradient method, MCGM with adjoint equation, are used alternately to estimate the unknown strength $G({\tau})$ of the source term, while the parameter estimation approach is used to estimate the unknown location ($X^*$, $Y^*$) of the line heat source. The alternate use of the regular and the modified conjugate gradient methods alleviates the convergence difficulties encountered at the initial and final times (i.e ${\tau}=0$ and ${\tau}={\tau}_f$), hence stabilizes the computation and fastens the convergence of the solution. In order to examine the effectiveness of this approach under severe test conditions, the unknown strength $G({\tau})$ is chosen in the form of rectangular, triangular and sinusoidal functions.