• Journal of Digital Convergence
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• v.12 no.6
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• pp.223-229
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• 2014

In an attempt to retrieve useful information for an efficient decision in the large knowledge system, it is generally necessary and important for a refined feature selection. Rough set has difficulty in generating optimal reducts and classifying boundary objects. In this paper, we propose quick reduction algorithm generating optimal features by rough entropy analysis for condition and decision attributes to improve these restrictions. We define a new conditional information entropy for efficient feature extraction and describe procedure of feature selection to classify the significance of features. Through the simulation of 5 datasets from UCI storage, we compare our feature selection approach based on rough set theory with the other selection theories. As the result, our modeling method is more efficient than the previous theories in classification accuracy for feature selection.

• Journal of the Korea Computer Industry Society
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• v.5 no.5
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• pp.747-754
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• 2004

In this paper, we obtain an optimal corpus that can represent its characteristics very well from the baseline corpus which consists of unique 1,566,943 names among company names in a directory assistance serve (114). Two kinds of optimal solutions ared considered to obtain the optimal corpus. The first solution is to find phonetically balanced corpus (PBC), which are the minimum set including all possible triphones in the baseline corpus. The second solution is to find the phonetically distributed corpus (PDC), which is a minimum set representing the frequency characteristics of triphones in the baseline corpus. We can obtain 8,699 words as the PBC and 16,783 words (similarity measure R = 0.92) as PDC, respectively. These corpora can be used for the development of speech recognition and speech synthesis.

• Steel and Composite Structures
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• v.7 no.1
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• pp.53-70
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• 2007

This paper presents a analysis of the problem of optimal design of the beams with two I-type cross section shapes. These types of beams are simply supported and subject to pure bending. The strength and stability conditions were formulated and analytically solved in the form of mathematical equations. Both global and selected types of local stability forms were taken into account. The optimization problem was defined as bicriteria. The cross section area of the beam is the first objective function, while the deflection of the beam is the second. The geometric parameters of cross section were selected as the design variables. The set of constraints includes global and local stability conditions, the strength condition, and technological and constructional requirements in the form of geometric relations. The optimization problem was formulated and solved with the help of the Pareto concept of optimality. During the numerical calculations a set of optimal compromise solutions was generated. The numerical procedures include discrete and continuous sets of the design variables. Results of numerical analysis are presented in the form of tables, cross section outlines and diagrams. Results are discussed at the end of the work. These results may be useful for designers in optimal designing of thin-walled beams, increasing information required in the decision-making procedure.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.4 no.4
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• pp.63-69
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• 1981

As enterprises are getting bigger and bigger and more competecious, an engineering economy for the maximization of profit based on basic theory must be considered. This thesis present dynamic computer model for the decision which controls complicated and various man- machine system optimally. This model occur in general stage can be adaptable to every kind of enterprises. So, any one who has no expert knowledge is able to get the optimal solution. And decision tree used in this paper can be applied in every kinds of academic circles as well as whole the industrial world. This paper studied optimal management of engineering project based upon basic theory of engineering economy. It introduces and functionizes the variables which generalize every possible elements, set up a model in order to find out the variable which maximize the calculated value among many other variables. And the selected values ate used as decision- marking variables for the optimal management of engineering projects. It found out some problem of this model. They are : 1. In some kinds of man-machine system it refers to Probability, but other case, it depends on only experimental probability. 2. Unless decision making process (decision tree) goes on, this model can not be applied. So these cases, this paper says, can be solved by adapting finite decision tree which is analyzed by using the same technic as those in product introduction problem. And this paper set up the computer model in order to control every procedure quickly and optimally, using Fortran IV.

• Journal of Biosystems Engineering
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• v.19 no.4
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• pp.291-300
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• 1994

It is desired to operate tractor engines at or near maximum torque much of the time in field operation to increase fuel efficiency. To do this it is necessary to reduce engine speed and to shift gears to higher ratios as frequently as possible. Because of load variations in most drawbar work and inconvenience in gear shift, however, gear-type transmission are usually set in one ratio at unnecessarily high engine speeds, and engine-torque variations are used to compensate for changes in drawbar load. As a result, the most of time the tractor is not operated efficiently in terms of fuel consumption and work output. The objective of this study was to develop an automatic control system which is able to operate a tractor equipped with gear transmission under the optimal condition in terms of fuel efficiency with automatic governor setting and gear shift. An indoor experimental test set which can be used to simulate tractor operation, control engine speed and transmission ratio was developed in the previous paper. In this paper, the performance of the optimal operation system is reported. Through a series of tests, it was found that the automatic control system for optimal operation of tractors with gear transmission had a satisfactory performance.

• Korean Journal of Veterinary Research
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• v.56 no.2
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• pp.85-89
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• 2016

We tested a set of conditions for obtaining optimal tissue quality in preparation for histology in samples of mouse brain. C57BL/6J mice were sacrificed and perfused with 4% paraformaldehyde, after which the brains were removed and dehydrated in 30% sucrose solution. The brains were then divided into four groups according to freezing temperature and usage of optimal cutting temperature (OCT) compound. Next, we stained the sectioned brain tissues with Harris hematoxylin and eosin Y and immunohistochemistry was performed for doublecortin. The best quality tissue was obtained at $-25^{\circ}C$ and by not embedding with the OCT compound. When frozen at $-25^{\circ}C$, the embedded tissue was significantly damaged by crystals, while at $-80^{\circ}C$ there were no meaningful differences between qualities of embedded- and non-embedded tissues. Overall, we identified a set of conditions to obtain quality frozen brain sections. Our developed protocol will help resolve matters associated with damage caused to sectioned brain tissue by crystal formation during freezing.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.2
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• pp.212-215
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• 2008

In this paper, we develop the optimal path planning algorithm using the improved Dijkstra algorithm and the particle swarm optimization. To get the optimal path, at first we construct the MAKLINK on the world environment and then make a graph associated with the MAKLINK. The MAKLINK is a set of edges which consist of the convex set. Some of the edges come from the edges of the obstacles. From the graph, we obtain the Dijkstra path between the starting point and the destination point. From the optimal path, we search the improved Dijkstra path using the graph. Finally, applying the particle swarm optimization to the improved Dijkstra path, we obtain the optimal path for the mobile robot. It turns out that the proposed method has better performance than the result in [1] through the experiment.

• Journal of the Society of Naval Architects of Korea
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• v.42 no.3
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• pp.284-289
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• 2005

A structural design system is developed for the optimum design of double hull tankers based on the multi-objective function method. As a multi-objective function method, Pareto optimal based random search method is adopted to find the minimum structural weight and fabrication cost. The fabrication cost model is developed by considering the welding technique, welding poses and assembly stages to manage the fabrication man-hour and process. In this study, a new structural design is investigated due to the rapidly increased material cost. Several optimum structural designs on the basis of high material cost are carried out based on the Pareto optimal set obtained by the random search method. The design results are compared with existing ship, which is designed under low material cost.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.6
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• pp.786-791
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• 2011

An optimal feature selection and extraction procedure is an important task that significantly affects the success of brain activity analysis in brain-computer interface (BCI) research area. In this paper, a novel method for extracting the optimal feature from electroencephalogram (EEG) signal is proposed. At first, a student's-t-statistic method is used to normalize and to minimize statistical error between EEG measurements. And, 2D time-frequency data set from the raw EEG signal was extracted using discrete wavelet transform (DWT) as a raw feature, standard deviations and mean of 2D time-frequency matrix were extracted as a optimal EEG feature vector along with other basis feature of sub-band signals. In the experiment, data set 1 of BCI competition IV are used and classification using SVM to prove strength of our new method.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.18 no.11
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• pp.896-905
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• 2006

An optimal control of an air-conditioning system with slab thermal storage is investigated by making use of the Maximum Principle. An optimal heat input to a plenum chamber and an air-conditioned room is determined by minimizing a criterion function which is given as integral sum of two terms. The first term is the square of the deviation in the room air temperature from the set-point value, and the second is the absolute value of the heat input. The result indicates that it tries to keep a room air temperature in set-point value by heating as much as possible at the time of a setup of a room air temperature or just before that, in order to avoid a heat loss arising at the time of the non-air conditioning. The result is compared with that of the case when the square of the heat input is used as a criterion.