• Journal of the Korean Society for Industrial and Applied Mathematics
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• 제3권1호
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• pp.71-79
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• 1999

We consider multi-step quasi-Newton methods for unconstrained optimization. These methods were introduced by Ford and Moghrabi [1, 2], who showed how interpolating curves could be used to derive a generalization of the Secant Equation (the relation normally employed in the construction of quasi-Newton methods). One of the most successful of these multi-step methods makes use of the current approximation to the Hessian to determine the parameterization of the interpolating curve in the variable-space and, hence, the generalized updating formula. In this paper, we investigate new parameterization techniques to the approximate Hessian, in an attempt to determine a better Hessian approximation at each iteration and, thus, improve the numerical performance of such algorithms.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2002년도 춘계학술대회 논문집
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• pp.1043-1046
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• 2002

In this paper, drill tests were carried out by modifying drill geometry for burr minimization. Final objective of this study is to develop compatible drill shape for minimization of burr formation. These experimented results with modified drill are measured with laser sensor after performing drilling with variable material. Simultaneously, the cutting force and the torque of various drill geometry have been observed with same cutting condition to judge drill stability. As a result, burr was minimized in step drill with 75$^{\circ}$ step angle at every material.

• 한국철도학회:학술대회논문집
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• 한국철도학회 2005년도 춘계학술대회 논문집
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• pp.843-848
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• 2005

Currently the train traffic control system is built wholly by one package construction. It is under variable circumstance such as variation of signalling equipment and station expansion. This condition reduces system reliability and availability. And the term of system change is longer than 10 years, so it is hard to update to the latest technology and the new function. In order to do the system should be replaced to new one completely. The step by step construction of ADS(Autonomous Decentralized System) is one of the solution. So the simulation of it on the real station help to find system requirement and verify good of online expansion and online test.

• 한국정밀공학회지
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• 제27권9호
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• pp.43-51
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• 2010

Speed, accuracy and smoothness are the important properties of pan-tilt camera. In the case of a high ratio zoom lens system, low vibration characteristic is a crucial point in driving pan-tilt mechanism. In this paper, a novel micro-stepping controller with a function of reducing vibration was designed using field programmable gate arrays (FPGA) technology for high zoom ratio pan-tilt camera. The proposed variable reference current (VRC) control scheme reduces vibration decently and optimizing coil current in order to prevent the step motor from occurring missing steps. By employing VRC control scheme, the vibration in low speed could be significantly minimized. The proposed controller can also make very high speed of 378kpps micro-step driving, and increase maximum acceleration in motion profiles.

• ETRI Journal
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• 제45권1호
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• pp.119-130
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• 2023

We propose a quantized gradient search algorithm that can achieve global optimization by monotonically reducing the quantization step with respect to time when quantization is composed of integer or fixed-point fractional values applied to an optimization algorithm. According to the white noise hypothesis states, a quantization step is sufficiently small and the quantization is well defined, the round-off error caused by quantization can be regarded as a random variable with identically independent distribution. Thus, we rewrite the searching equation based on a gradient descent as a stochastic differential equation and obtain the monotonically decreasing rate of the quantization step, enabling the global optimization by stochastic analysis for deriving an objective function. Consequently, when the search equation is quantized by a monotonically decreasing quantization step, which suitably reduces the round-off error, we can derive the searching algorithm evolving from an optimization algorithm. Numerical simulations indicate that due to the property of quantization-based global optimization, the proposed algorithm shows better optimization performance on a search space to each iteration than the conventional algorithm with a higher success rate and fewer iterations.

• Bulletin of the Korean Chemical Society
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• 제33권5호
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• pp.1527-1535
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• 2012

Selection of the most informative molecular descriptors from the original data set is a key step for development of quantitative structure activity/property relationship models. Recently, mutual information (MI) has gained increasing attention in feature selection problems. This paper presents an effective mutual information-based feature selection approach, named mutual information maximization by replacing collinear variables (MIMRCV), for nonlinear quantitative structure-property relationship models. The proposed variable selection method was applied to three different QSPR datasets, soil degradation half-life of 47 organophosphorus pesticides, GC-MS retention times of 85 volatile organic compounds, and water-to-micellar cetyltrimethylammonium bromide partition coefficients of 62 organic compounds.The obtained results revealed that using MIMRCV as feature selection method improves the predictive quality of the developed models compared to conventional MI based variable selection algorithms.

• International Journal of Advanced Culture Technology
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• 제8권3호
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• pp.260-268
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• 2020

Currently, it is usually a 3D scanner processing method as a laser method. However, the laser method has a disadvantage of slow scanning speed and poor precision. Although optical scanners are used as a method to compensate for these shortcomings, optical scanners are closely related to the distance and precision of the object, and have the disadvantage of being expensive. In this paper, 3D scanner using variable focus lens-based structured light module with improved measurement precision was designed to be high performance, low price, and usable in industrial fields. To this end, designed a telecentric optical system based on a variable focus lens and connected to the telecentric mechanism of the step motor and lens to adjust the focus of the variable lens. Designed a connection structure with optimized scalability of hardware circuits that configures a stepper motor to form a system with a built-in processor. In addition, by applying an algorithm that can simultaneously acquire high-resolution texture image and depth information and apply image synthesis technology and GPU-based high-speed structured light processing technology, it is also stable for changes to external light. We will designed and implemented for further improving high measurement precision.

• 한국해양공학회지
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• 제25권4호
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• pp.18-22
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• 2011

The Ranking source panel method was used to predict the flow phenomenon of a ship with a goose-neck type bulbous bow penetrating the free surface. The non-linearity of the free surface boundary condition was fully satisfied using an iterative calculation method, and the raised panel method was adopted to obtain a more stable solution at each iteration step. The panel cutting method was applied to generate a hull calculation grid at each iteration step, including the first step. At that time, the nose of the goose-neck type bulbous bow was divided by the free surface and the free surface panel was modified at each iteration step using the variable free surface panel method. Numerical calculations were performed to investigate the validity and efficiency of the applied numerical algorithm using the 3600 TEU container carrier. The computed wave resistance coefficients were compared with the experimentally achieved residual resistance coefficients.

• 품질경영학회지
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• 제47권3호
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• pp.537-552
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• 2019

Purpose: The development of information technology makes it easy to utilize high-dimensional categorical data. In this regard, the purpose of this study is to propose a novel method to select the proper categorical variables in high-dimensional categorical data. Methods: The proposed feature selection method consists of three steps: (1) The first step defines the goodness-to-pick measure. In this paper, a categorical variable is relevant if it has relationships among other variables. According to the above definition of relevant variables, the goodness-to-pick measure calculates the normalized conditional entropy with other variables. (2) The second step finds the relevant feature subset from the original variables set. This step decides whether a variable is relevant or not. (3) The third step eliminates redundancy variables from the relevant feature subset. Results: Our experimental results showed that the proposed feature selection method generally yielded better classification performance than without feature selection in high-dimensional categorical data, especially as the number of irrelevant categorical variables increase. Besides, as the number of irrelevant categorical variables that have imbalanced categorical values is increasing, the difference in accuracy between the proposed method and the existing methods being compared increases. Conclusion: According to experimental results, we confirmed that the proposed method makes it possible to consistently produce high classification accuracy rates in high-dimensional categorical data. Therefore, the proposed method is promising to be used effectively in high-dimensional situation.

• 산업경영시스템학회지
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• 제39권1호
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• pp.123-129
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• 2016

In the manufacturing industry fields, thousands of quality characteristics are measured in a day because the systems of process have been automated through the development of computer and improvement of techniques. Also, the process has been monitored in database in real time. Particularly, the data in the design step of the process have contributed to the product that customers have required through getting useful information from the data and reflecting them to the design of product. In this study, first, characteristics and variables affecting to them in the data of the design step of the process were analyzed by decision tree to find out the relation between explanatory and target variables. Second, the tolerance of continuous variables influencing on the target variable primarily was shown by the application of algorithm of decision tree, C4.5. Finally, the target variable, loss, was calculated by a loss function of Taguchi and analyzed. In this paper, the general method that the value of continuous explanatory variables has been used intactly not to be transformed to the discrete value and new method that the value of continuous explanatory variables was divided into 3 categories were compared. As a result, first, the tolerance obtained from the new method was more effective in decreasing the target variable, loss, than general method. In addition, the tolerance levels for the continuous explanatory variables to be chosen of the major variables were calculated. In further research, a systematic method using decision tree of data mining needs to be developed in order to categorize continuous variables under various scenarios of loss function.