• Proceedings of the Korean Statistical Society Conference
• /
• 2003.05a
• /
• pp.75-78
• /
• 2003

Those who are interested in making inferences concerning linear combination of variance components in a simple linear regression model with unbalanced nested error structure can use the confidence intervals proposed in this paper. Two approximate confidence intervals for the sum of two variance components in the model are proposed. Simulation study is peformed to compare the methods.

• The Pure and Applied Mathematics
• /
• v.10 no.1
• /
• pp.37-47
• /
• 2003

We will show that any linear perturbation of polynomials that introduces bounded perturbations into the roots of polynomial is some linear combination of the derivatives of a polynomial. And we will derive an absolute root bound functional which is in some sense better than the other known absolute root bound functionals.

• Journal of The Korean Astronomical Society
• /
• v.36 no.3
• /
• pp.75-80
• /
• 2003

When a bright astronomical object (source) is gravitationally lensed by a foreground mass (lens), its image appears to be located at different positions. The lens equation describes the relations between the locations of the lens, source, and images. The lens equation used for the description of the lensing behavior caused by a lens system composed of multiple masses has a form with a linear combination of the individual single lens equations. In this paper, we examine the validity of the linear nature of the multi-lens equation based on the general relativistic point of view.

• Journal of the Korean Society for Nondestructive Testing
• /
• v.27 no.6
• /
• pp.531-540
• /
• 2007

While determination of the solid propellant burning rates by ultrasound, it has been reported that the frequent data scatters were caused by two major factors; 1) variation in the acoustical properties, and 2) non-linear burning of a solid propellant sample under investigation. This work is carried out for the purpose of investigating the effect of non-linear burning of solid propellant samples. Specifically, we propose an ultrasonic measurement model that can predict the reflections from solid propellant surfaces with non-linear burning by the combination of two ingredients; 1) a pulse-echo ultrasonic measurement model for a planar, circular reflector imbedded in the second medium in an immersion set-up, and 2) an efficient model of non-linear burning surfaces with a number of small, planar circles. Then, we demonstrate the capability of the proposed measurement model by simulation of the surface echo signals from four different burning surfaces that have been generated by the combination of two factors; the base shape (flat or paraboloidal) and the surface roughness (perfectly smooth or randomly rough). From the simulation presented here, we can confirm the fact that the non-linear burning of the propellant can cause the waveform change of the burning surface echo and the corresponding spectrum variation.

• Journal of the Korean Society for Precision Engineering
• /
• v.19 no.7
• /
• pp.163-170
• /
• 2002

This paper presents some measures far the optimization of the thermal behavior of linear motors, which are used as a high speed feed mechanism in machine tools. Thermo-Sandwich-Construction using two cooling circuits and an insulation layer shows an effective cooling system for linear motors. Conducting sheet can be also used to reduce heat flow from linear motor to machine table. Cooling pipe is a simple and effective cooling system for the secondary part of synchronous linear motor. Through the combination of the Thermo-Sandwich-Construction, conducting sheet and cooling pipe the thermally optimized linear motor shows a well improved thermal behavior in comparison with the prototype motor.

• Journal of Information Processing Systems
• /
• v.18 no.2
• /
• pp.268-281
• /
• 2022

The development of information technology is bringing many changes to everyday life, and machine learning can be used as a technique to solve a wide range of real-world problems. Analysis and utilization of data are essential processes in applying machine learning to real-world problems. As a method of processing data in machine learning, we propose an approach based on applying multiple linear regression models by interlacing data to the task of classifying similar software. Linear regression is widely used in estimation problems to model the relationship between input and output data. In our approach, multiple linear regression models are generated by training on interlaced feature data. A combination of these multiple models is then used as the prediction model for classifying similar software. Experiments are performed to evaluate the proposed approach as compared to conventional linear regression, and the experimental results show that the proposed method classifies similar software more accurately than the conventional model. We anticipate the proposed approach to be applied to various kinds of classification problems to improve the accuracy of conventional linear regression.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
• /
• v.20 no.8
• /
• pp.54-62
• /
• 2006

Voltage unbalance will be generated by the load unbalance operation such as combination operation of single & three phase load and current unbalance will be more severe by the deteriorated voltage quality. Under the these unbalance conditions, all power electronic converters used in different types of electronic systems can increase harmonic disturbances by injecting harmonic currents directly into the feeder grid of three phase 4-wire. Harmonic current may cause torque to decrease. it may also overheat or become noisy and torque oscillation in the rotor can lead to mechanical resonance and vibration. This paper presents a scheme on the characteristics of induction motor under the combination of linear & non-linear loads at the three phase 4-wire power distribution system by the unbalance and harmonic components. It was able to confirm that the number of torque pulsation decreased and torque ripple values increased by the harmonics that reduction was difficult by five harmonics filters at additional driving time of single-phase non-linear load.

• Proceedings of the KIEE Conference
• /
• 2004.05a
• /
• pp.98-101
• /
• 2004

Linear Programming(LP) is the term used for defining a wide range of optimization problems in which the objective function to be minimized or maximized is linear in the unknown variables and the constraints are a combination of linear equalities and inequalities. LP problems occur in many real-life economic situations where profits are to be maximized or costs minimized with constraint limits on resources. While the simplex method introduced in a later reference can be used for hand solution of LP problems, computer use becomes necessary even for a small number of variables. Problems involving diet decisions, transportation, production and manufacturing, product mix, engineering limit analysis in design, airline scheduling, and so on are solved using computers. This technique is called Sequential Linear Programming (SLP). This paper describes LP's problems and solves a LP's problems using the neural networks.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.9 no.2
• /
• pp.3-12
• /
• 1999

We introduce feedback registers and definitions of complexity of a register or a sequence generated by it. In the view point of cryptography the linear complexity of an ultimately periodic sequence is important because large one gives an enemy infeasible jobs. We state some results about the linear complexity of sum and product of two LFSRs.

• Journal of information and communication convergence engineering
• /
• v.21 no.1
• /
• pp.62-67
• /
• 2023

This paper proposes an imputation method using a bidirectional k-nearest components search based local linear regression method. The bidirectional k-nearest-components search method selects components in the dynamic range from the missing points. Unlike the existing methods, which use a fixed-size window, the proposed method can flexibly select adjacent components in an imputation problem. The weight values assigned to the components around the missing points are calculated using local linear regression. The local linear regression method is free from the rank problem in a matrix of dependent variables. In addition, it can calculate the weight values that reflect the data flow in a specific environment, such as a blackout. The original missing values were estimated from a linear combination of the components and their weights. Finally, the estimated value imputes the missing values. In the experimental results, the proposed method outperformed the existing methods when the error between the original data and imputation data was measured using MAE and RMSE.